From 68f5a646de869071e2f23e2463585f12a8803dfb Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 16 Dec 2025 14:33:41 -0500 Subject: [PATCH 01/19] Add shared pipeline execution logic for HTTP, MCP, and gateways --- src/dspy_cli/server/execution.py | 330 +++++++++++++++++++++++++++++++ src/dspy_cli/server/mcp.py | 122 +++--------- src/dspy_cli/server/routes.py | 319 +----------------------------- 3 files changed, 371 insertions(+), 400 deletions(-) create mode 100644 src/dspy_cli/server/execution.py diff --git a/src/dspy_cli/server/execution.py b/src/dspy_cli/server/execution.py new file mode 100644 index 0000000..ff2e33f --- /dev/null +++ b/src/dspy_cli/server/execution.py @@ -0,0 +1,330 @@ +"""Shared pipeline execution logic for HTTP, MCP, and gateways.""" + +import base64 +import logging +import time +from datetime import datetime +from pathlib import Path +from typing import Any, Dict, List + +import dspy + +from dspy_cli.discovery import DiscoveredModule +from dspy_cli.server.logging import log_inference + +logger = logging.getLogger(__name__) + + +def _extract_lm_metrics(lm: dspy.LM, history_start_idx: int) -> Dict[str, Any]: + """Extract metrics from LM history entries created during a program call. + + Args: + lm: The language model instance + history_start_idx: Index in lm.history where this call's entries start + + Returns: + Dictionary with tokens, cost_usd, and lm_calls breakdown + """ + if not hasattr(lm, 'history') or not lm.history: + return {"tokens": None, "cost_usd": None, "lm_calls": None} + + new_entries = lm.history[history_start_idx:] + if not new_entries: + return {"tokens": None, "cost_usd": None, "lm_calls": None} + + total_prompt_tokens = 0 + total_completion_tokens = 0 + total_cost = 0.0 + has_cost = False + lm_calls: List[Dict[str, Any]] = [] + + for entry in new_entries: + usage = entry.get("usage", {}) + if isinstance(usage, dict): + prompt = usage.get("prompt_tokens", 0) or 0 + completion = usage.get("completion_tokens", 0) or 0 + total_prompt_tokens += prompt + total_completion_tokens += completion + + cost = entry.get("cost") + if cost is not None: + total_cost += cost + has_cost = True + + lm_calls.append({ + "model": entry.get("model", "unknown"), + "timestamp": entry.get("timestamp"), + "prompt_tokens": usage.get("prompt_tokens") if isinstance(usage, dict) else None, + "completion_tokens": usage.get("completion_tokens") if isinstance(usage, dict) else None, + "cost_usd": cost, + }) + + tokens = { + "prompt_tokens": total_prompt_tokens, + "completion_tokens": total_completion_tokens, + "total_tokens": total_prompt_tokens + total_completion_tokens, + } + + return { + "tokens": tokens if total_prompt_tokens > 0 or total_completion_tokens > 0 else None, + "cost_usd": total_cost if has_cost else None, + "lm_calls": lm_calls if lm_calls else None, + } + + +def _convert_dspy_types(inputs: Dict[str, Any], module: DiscoveredModule) -> Dict[str, Any]: + """Convert string inputs to DSPy types based on forward type annotations. + + For fields with dspy types (Image, Audio, etc.), converts string values + (URLs or data URIs) to proper dspy objects. + + Args: + inputs: Dictionary of input values from the request + module: DiscoveredModule with forward type information + + Returns: + Dictionary with converted values + """ + if not module.is_forward_typed or not module.forward_input_fields: + return inputs + + converted = {} + for field_name, value in inputs.items(): + if field_name not in module.forward_input_fields: + converted[field_name] = value + continue + + field_info = module.forward_input_fields[field_name] + field_type = field_info.get('annotation') + + if field_type and hasattr(field_type, '__module__') and field_type.__module__.startswith('dspy'): + try: + if isinstance(value, str) or isinstance(value, dict): + converted[field_name] = field_type(value) + else: + converted[field_name] = value + except Exception as e: + logger.warning(f"Failed to convert {field_name} to {field_type.__name__}: {e}") + converted[field_name] = value + else: + converted[field_name] = value + + return converted + + +def _save_image(image_data: str, logs_dir: Path, program_name: str, field_name: str) -> str: + """Save an image to disk and return the relative path. + + Args: + image_data: Image data (data URI or URL) + logs_dir: Base logs directory + program_name: Name of the program + field_name: Name of the input/output field + + Returns: + Relative path to saved image (e.g., "img/program_timestamp_field.png") + """ + img_dir = logs_dir / "img" + img_dir.mkdir(exist_ok=True, parents=True) + + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f") + + if image_data.startswith('data:'): + try: + header, data = image_data.split(',', 1) + mime_type = header.split(':')[1].split(';')[0] + + ext_map = { + 'image/png': 'png', + 'image/jpeg': 'jpg', + 'image/jpg': 'jpg', + 'image/gif': 'gif', + 'image/webp': 'webp', + 'image/svg+xml': 'svg' + } + ext = ext_map.get(mime_type, 'png') + + if 'base64' in header: + image_bytes = base64.b64decode(data) + else: + image_bytes = data.encode('utf-8') + + filename = f"{program_name}_{timestamp}_{field_name}.{ext}" + filepath = img_dir / filename + + with open(filepath, 'wb') as f: + f.write(image_bytes) + + return f"img/{filename}" + + except Exception as e: + logger.error(f"Failed to save data URI image: {e}") + return f"data:[error saving image: {str(e)[:50]}]" + else: + return image_data + + +def _serialize_for_logging(data: Any, logs_dir: Path, program_name: str, field_prefix: str = "") -> Any: + """Recursively serialize data for JSON logging, extracting images to files. + + Args: + data: Data to serialize (can be dict, list, dspy.Image, etc.) + logs_dir: Base logs directory + program_name: Name of the program + field_prefix: Prefix for field names (for nested structures) + + Returns: + Serialized data with dspy.Image objects replaced by file paths + """ + if hasattr(data, '__class__') and data.__class__.__name__ == 'Image' and \ + hasattr(data.__class__, '__module__') and data.__class__.__module__.startswith('dspy'): + image_data = getattr(data, 'url', None) or str(data) + field_name = field_prefix or 'image' + return _save_image(image_data, logs_dir, program_name, field_name) + + elif isinstance(data, dict): + return { + key: _serialize_for_logging( + value, + logs_dir, + program_name, + field_prefix=f"{field_prefix}_{key}" if field_prefix else key + ) + for key, value in data.items() + } + + elif isinstance(data, list): + return [ + _serialize_for_logging( + item, + logs_dir, + program_name, + field_prefix=f"{field_prefix}_{i}" if field_prefix else f"item_{i}" + ) + for i, item in enumerate(data) + ] + + elif hasattr(data, '__class__') and hasattr(data.__class__, '__module__') and \ + data.__class__.__module__.startswith('dspy'): + if hasattr(data, 'toDict'): + return _serialize_for_logging(data.toDict(), logs_dir, program_name, field_prefix) + elif hasattr(data, '__dict__'): + return _serialize_for_logging(vars(data), logs_dir, program_name, field_prefix) + else: + return str(data) + + else: + return data + + +def _normalize_output(result: Any, module: DiscoveredModule) -> Dict[str, Any]: + """Normalize any DSPy result into a dict for HTTP/MCP/gateways. + + Args: + result: The result from a DSPy module execution + module: The DiscoveredModule that produced the result + + Returns: + Dictionary representation of the result + """ + if isinstance(result, dspy.Prediction): + return result.toDict() + elif hasattr(result, '__dict__'): + return vars(result) + elif isinstance(result, dict): + return result + else: + if module.is_forward_typed and module.forward_output_fields: + field_names = list(module.forward_output_fields.keys()) + if len(field_names) == 1: + return {field_names[0]: result} + return {"result": result} + + +async def execute_pipeline( + *, + module: DiscoveredModule, + instance: dspy.Module, + lm: dspy.LM, + model_name: str, + program_name: str, + inputs: Dict[str, Any], + logs_dir: Path, +) -> Dict[str, Any]: + """Run a DSPy module with its own LM copy, log metrics and I/O, and return output dict. + + This is the shared execution logic used by HTTP routes, MCP, and gateways. + + Args: + module: DiscoveredModule metadata + instance: Instantiated DSPy module + lm: Language model instance (will be copied for this request) + model_name: Model name for logging + program_name: Program name for logging + inputs: Input dictionary (already converted via _convert_dspy_types) + logs_dir: Directory for log files + + Returns: + Dictionary of output values + + Raises: + The original exception on failure after logging. + """ + start_time = time.time() + request_lm = lm.copy() + + try: + logger.info(f"Executing {program_name} with inputs: {inputs}") + + with dspy.context(lm=request_lm): + if hasattr(instance, 'aforward'): + result = await instance.acall(**inputs) + else: + result = instance(**inputs) + + output = _normalize_output(result, module) + duration_ms = (time.time() - start_time) * 1000 + metrics = _extract_lm_metrics(request_lm, 0) + + serialized_inputs = _serialize_for_logging(inputs, logs_dir, program_name) + serialized_outputs = _serialize_for_logging(output, logs_dir, program_name) + + log_inference( + logs_dir=logs_dir, + program_name=program_name, + model=model_name, + inputs=serialized_inputs, + outputs=serialized_outputs, + duration_ms=duration_ms, + tokens=metrics["tokens"], + cost_usd=metrics["cost_usd"], + lm_calls=metrics["lm_calls"], + ) + + logger.info(f"Program {program_name} completed successfully.") + return output + + except Exception as e: + duration_ms = (time.time() - start_time) * 1000 + metrics = _extract_lm_metrics(request_lm, 0) + + try: + serialized_inputs = _serialize_for_logging(inputs, logs_dir, program_name) + except Exception: + serialized_inputs = {} + + log_inference( + logs_dir=logs_dir, + program_name=program_name, + model=model_name, + inputs=serialized_inputs, + outputs={}, + duration_ms=duration_ms, + error=str(e), + tokens=metrics["tokens"], + cost_usd=metrics["cost_usd"], + lm_calls=metrics["lm_calls"], + ) + + logger.error(f"Error executing {program_name}: {e}", exc_info=True) + raise diff --git a/src/dspy_cli/server/mcp.py b/src/dspy_cli/server/mcp.py index affb033..740cc3a 100644 --- a/src/dspy_cli/server/mcp.py +++ b/src/dspy_cli/server/mcp.py @@ -1,20 +1,16 @@ """MCP (Model Context Protocol) integration for DSPy programs.""" import logging -import time from typing import Any, Dict -import dspy from fastapi import FastAPI from pydantic import BaseModel from dspy_cli.config import get_model_config, get_program_model -from dspy_cli.server.logging import log_inference +from dspy_cli.server.execution import _convert_dspy_types, execute_pipeline from dspy_cli.server.routes import ( - _convert_dspy_types, _create_request_model_from_forward, _create_response_model_from_forward, - _serialize_for_logging, ) logger = logging.getLogger(__name__) @@ -90,92 +86,36 @@ def _register_program_tool(mcp_server: "FastMCP", app: FastAPI, module): # Create tool execution logic async def execute_program(**kwargs) -> Dict[str, Any]: """Execute the DSPy program with given parameters.""" - start_time = time.time() - - try: - # Validate with request model if available - if has_types and _is_pydantic_model(RequestModel): - validated = RequestModel(**kwargs) - inputs = validated.model_dump() - else: - inputs = kwargs - - # Convert dspy types (Image, Audio, etc.) - inputs = _convert_dspy_types(inputs, module) - - # Instantiate module per call to avoid shared state across concurrent requests - instance = module.instantiate() - - # Execute with program-specific LM - logger.info(f"MCP: Executing {program_name} with inputs: {inputs}") - with dspy.context(lm=lm): - if hasattr(instance, "aforward"): - result = await instance.acall(**inputs) - else: - result = instance(**inputs) - - # Convert result to dict - if isinstance(result, dspy.Prediction): - output = result.toDict() - elif hasattr(result, "__dict__"): - output = vars(result) - elif isinstance(result, dict): - output = result - else: - # Simple value - wrap in expected field name - if module.is_forward_typed and module.forward_output_fields: - field_names = list(module.forward_output_fields.keys()) - output = {field_names[0]: result} if len(field_names) == 1 else {"result": result} - else: - output = {"result": result} - - duration_ms = (time.time() - start_time) * 1000 - - # Log inference - serialized_inputs = _serialize_for_logging(inputs, app.state.logs_dir, program_name) - serialized_outputs = _serialize_for_logging(output, app.state.logs_dir, program_name) - - log_inference( - logs_dir=app.state.logs_dir, - program_name=program_name, - model=model_name, - inputs=serialized_inputs, - outputs=serialized_outputs, - duration_ms=duration_ms, - ) - - logger.info(f"MCP: Program {program_name} completed in {duration_ms:.0f}ms") - - # Validate response if model available - if has_types and _is_pydantic_model(ResponseModel): - validated_output = ResponseModel(**output) - return validated_output.model_dump() - - return output - - except Exception as e: - duration_ms = (time.time() - start_time) * 1000 - - # Log failed inference - try: - serialized_inputs = _serialize_for_logging( - inputs if "inputs" in locals() else kwargs, app.state.logs_dir, program_name - ) - except Exception: - serialized_inputs = {} - - log_inference( - logs_dir=app.state.logs_dir, - program_name=program_name, - model=model_name, - inputs=serialized_inputs, - outputs={}, - duration_ms=duration_ms, - error=str(e), - ) - - logger.exception(f"MCP: Error executing {program_name}") - raise + # Validate with request model if available + if has_types and _is_pydantic_model(RequestModel): + validated = RequestModel(**kwargs) + inputs = validated.model_dump() + else: + inputs = kwargs + + # Convert dspy types (Image, Audio, etc.) + inputs = _convert_dspy_types(inputs, module) + + # Instantiate module per call to avoid shared state across concurrent requests + instance = module.instantiate() + + # Execute via shared pipeline executor + output = await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name=model_name, + program_name=program_name, + inputs=inputs, + logs_dir=app.state.logs_dir, + ) + + # Validate response if model available + if has_types and _is_pydantic_model(ResponseModel): + validated_output = ResponseModel(**output) + return validated_output.model_dump() + + return output # Register tool with explicit fields if typed, else generic params if has_types and _is_pydantic_model(RequestModel): diff --git a/src/dspy_cli/server/routes.py b/src/dspy_cli/server/routes.py index 740ddae..e61aa42 100644 --- a/src/dspy_cli/server/routes.py +++ b/src/dspy_cli/server/routes.py @@ -1,250 +1,18 @@ """Dynamic route generation for DSPy programs.""" -import base64 import logging -import time -from datetime import datetime -from pathlib import Path -from typing import Any, Dict, List +from typing import Any, Dict import dspy from fastapi import FastAPI, HTTPException from pydantic import BaseModel, create_model from dspy_cli.discovery import DiscoveredModule -from dspy_cli.server.logging import log_inference +from dspy_cli.server.execution import _convert_dspy_types, execute_pipeline logger = logging.getLogger(__name__) -def _extract_lm_metrics(lm: dspy.LM, history_start_idx: int) -> Dict[str, Any]: - """Extract metrics from LM history entries created during a program call. - - Args: - lm: The language model instance - history_start_idx: Index in lm.history where this call's entries start - - Returns: - Dictionary with tokens, cost_usd, and lm_calls breakdown - """ - if not hasattr(lm, 'history') or not lm.history: - return {"tokens": None, "cost_usd": None, "lm_calls": None} - - new_entries = lm.history[history_start_idx:] - if not new_entries: - return {"tokens": None, "cost_usd": None, "lm_calls": None} - - total_prompt_tokens = 0 - total_completion_tokens = 0 - total_cost = 0.0 - has_cost = False - lm_calls: List[Dict[str, Any]] = [] - - for entry in new_entries: - usage = entry.get("usage", {}) - if isinstance(usage, dict): - prompt = usage.get("prompt_tokens", 0) or 0 - completion = usage.get("completion_tokens", 0) or 0 - total_prompt_tokens += prompt - total_completion_tokens += completion - - cost = entry.get("cost") - if cost is not None: - total_cost += cost - has_cost = True - - lm_calls.append({ - "model": entry.get("model", "unknown"), - "timestamp": entry.get("timestamp"), - "prompt_tokens": usage.get("prompt_tokens") if isinstance(usage, dict) else None, - "completion_tokens": usage.get("completion_tokens") if isinstance(usage, dict) else None, - "cost_usd": cost, - }) - - tokens = { - "prompt_tokens": total_prompt_tokens, - "completion_tokens": total_completion_tokens, - "total_tokens": total_prompt_tokens + total_completion_tokens, - } - - return { - "tokens": tokens if total_prompt_tokens > 0 or total_completion_tokens > 0 else None, - "cost_usd": total_cost if has_cost else None, - "lm_calls": lm_calls if lm_calls else None, - } - - -def _convert_dspy_types(inputs: Dict[str, Any], module: DiscoveredModule) -> Dict[str, Any]: - """Convert string inputs to DSPy types based on forward type annotations. - - For fields with dspy types (Image, Audio, etc.), converts string values - (URLs or data URIs) to proper dspy objects. - - Args: - inputs: Dictionary of input values from the request - module: DiscoveredModule with forward type information - - Returns: - Dictionary with converted values - """ - if not module.is_forward_typed or not module.forward_input_fields: - return inputs - - converted = {} - for field_name, value in inputs.items(): - if field_name not in module.forward_input_fields: - # Pass through unknown fields - converted[field_name] = value - continue - - field_info = module.forward_input_fields[field_name] - field_type = field_info.get('annotation') - - # Check if field type is a dspy type (from dspy module) - if field_type and hasattr(field_type, '__module__') and field_type.__module__.startswith('dspy'): - # Convert string/dict to dspy type - try: - if isinstance(value, str) or isinstance(value, dict): - converted[field_name] = field_type(value) - else: - # Already the right type or not convertible - converted[field_name] = value - except Exception as e: - logger.warning(f"Failed to convert {field_name} to {field_type.__name__}: {e}") - # Pass through unconverted on error - converted[field_name] = value - else: - # Not a dspy type, pass through - converted[field_name] = value - - return converted - - -def _save_image(image_data: str, logs_dir: Path, program_name: str, field_name: str) -> str: - """Save an image to disk and return the relative path. - - Args: - image_data: Image data (data URI or URL) - logs_dir: Base logs directory - program_name: Name of the program - field_name: Name of the input/output field - - Returns: - Relative path to saved image (e.g., "img/program_timestamp_field.png") - """ - # Create img directory if it doesn't exist - img_dir = logs_dir / "img" - img_dir.mkdir(exist_ok=True, parents=True) - - # Generate timestamp for unique filename - timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f") - - # Determine file extension and decode data - if image_data.startswith('data:'): - # Parse data URI: data:image/png;base64,iVBORw0KG... - try: - # Extract mime type and data - header, data = image_data.split(',', 1) - mime_type = header.split(':')[1].split(';')[0] - - # Determine extension from mime type - ext_map = { - 'image/png': 'png', - 'image/jpeg': 'jpg', - 'image/jpg': 'jpg', - 'image/gif': 'gif', - 'image/webp': 'webp', - 'image/svg+xml': 'svg' - } - ext = ext_map.get(mime_type, 'png') - - # Decode base64 data - if 'base64' in header: - image_bytes = base64.b64decode(data) - else: - # Plain data URI (rare) - image_bytes = data.encode('utf-8') - - # Save to file - filename = f"{program_name}_{timestamp}_{field_name}.{ext}" - filepath = img_dir / filename - - with open(filepath, 'wb') as f: - f.write(image_bytes) - - return f"img/{filename}" - - except Exception as e: - logger.error(f"Failed to save data URI image: {e}") - # Return the original data URI truncated for logging - return f"data:[error saving image: {str(e)[:50]}]" - else: - # It's a URL - just return it as-is - # (We could optionally download and save, but URLs are already compact) - return image_data - - -def _serialize_for_logging(data: Any, logs_dir: Path, program_name: str, field_prefix: str = "") -> Any: - """Recursively serialize data for JSON logging, extracting images to files. - - Args: - data: Data to serialize (can be dict, list, dspy.Image, etc.) - logs_dir: Base logs directory - program_name: Name of the program - field_prefix: Prefix for field names (for nested structures) - - Returns: - Serialized data with dspy.Image objects replaced by file paths - """ - # Handle dspy.Image objects - if hasattr(data, '__class__') and data.__class__.__name__ == 'Image' and \ - hasattr(data.__class__, '__module__') and data.__class__.__module__.startswith('dspy'): - # Extract the image URL/data URI from the Image object - # dspy.Image stores the data in a 'url' attribute - image_data = getattr(data, 'url', None) or str(data) - field_name = field_prefix or 'image' - return _save_image(image_data, logs_dir, program_name, field_name) - - # Handle dictionaries - elif isinstance(data, dict): - return { - key: _serialize_for_logging( - value, - logs_dir, - program_name, - field_prefix=f"{field_prefix}_{key}" if field_prefix else key - ) - for key, value in data.items() - } - - # Handle lists - elif isinstance(data, list): - return [ - _serialize_for_logging( - item, - logs_dir, - program_name, - field_prefix=f"{field_prefix}_{i}" if field_prefix else f"item_{i}" - ) - for i, item in enumerate(data) - ] - - # Handle other dspy types (future-proof) - elif hasattr(data, '__class__') and hasattr(data.__class__, '__module__') and \ - data.__class__.__module__.startswith('dspy'): - # For other dspy types, try to convert to dict or string - if hasattr(data, 'toDict'): - return _serialize_for_logging(data.toDict(), logs_dir, program_name, field_prefix) - elif hasattr(data, '__dict__'): - return _serialize_for_logging(vars(data), logs_dir, program_name, field_prefix) - else: - return str(data) - - # All other types pass through (str, int, bool, etc.) - else: - return data - - def create_program_routes( app: FastAPI, module: DiscoveredModule, @@ -286,12 +54,6 @@ def create_program_routes( @app.post(f"/{program_name}", response_model=response_model) async def run_program(request: request_model): """Execute the DSPy program with given inputs.""" - start_time = time.time() - - # Create a fresh LM copy for this request to avoid race conditions - # with concurrent requests (each copy has its own empty history) - request_lm = lm.copy() - try: # Convert request to dict if it's a Pydantic model if isinstance(request, BaseModel): @@ -300,83 +62,22 @@ async def run_program(request: request_model): inputs = request # Convert dspy types (Image, Audio, etc.) from strings to objects - # Note: This only works if forward types include proper dspy type annotations inputs = _convert_dspy_types(inputs, module) - # Execute the program with the request-specific LM via context - logger.info(f"Executing {program_name} with inputs: {inputs}") - with dspy.context(lm=request_lm): - if hasattr(instance, 'aforward'): - result = await instance.acall(**inputs) - else: - result = instance(**inputs) - - # Convert result to dict - if isinstance(result, dspy.Prediction): - output = result.toDict() - elif hasattr(result, '__dict__'): - output = vars(result) - elif isinstance(result, dict): - output = result - else: - # Simple return value (str, int, list, etc.) - if module.is_forward_typed and module.forward_output_fields: - field_names = list(module.forward_output_fields.keys()) - if len(field_names) == 1: - output = {field_names[0]: result} - else: - output = {"result": result} - else: - output = {"result": result} - - duration_ms = (time.time() - start_time) * 1000 - - # Extract metrics from the request-specific LM's history (starts at 0) - metrics = _extract_lm_metrics(request_lm, 0) - - # Serialize inputs and outputs for logging (extract images to files) - serialized_inputs = _serialize_for_logging(inputs, app.state.logs_dir, program_name) - serialized_outputs = _serialize_for_logging(output, app.state.logs_dir, program_name) - - # Log the inference trace with metrics - log_inference( - logs_dir=app.state.logs_dir, + # Execute via shared pipeline executor + output = await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name=model_name, program_name=program_name, - model=model_name, - inputs=serialized_inputs, - outputs=serialized_outputs, - duration_ms=duration_ms, - tokens=metrics["tokens"], - cost_usd=metrics["cost_usd"], - lm_calls=metrics["lm_calls"], + inputs=inputs, + logs_dir=app.state.logs_dir, ) - logger.info(f"Program {program_name} completed successfully. Response: {output}") return output except Exception as e: - duration_ms = (time.time() - start_time) * 1000 - - # Extract metrics even on failure - metrics = _extract_lm_metrics(request_lm, 0) - - raw_inputs = inputs if 'inputs' in locals() else {} - serialized_inputs = _serialize_for_logging(raw_inputs, app.state.logs_dir, program_name) - - log_inference( - logs_dir=app.state.logs_dir, - program_name=program_name, - model=model_name, - inputs=serialized_inputs, - outputs={}, - duration_ms=duration_ms, - error=str(e), - tokens=metrics["tokens"], - cost_usd=metrics["cost_usd"], - lm_calls=metrics["lm_calls"], - ) - - logger.error(f"Error executing {program_name}: {e}", exc_info=True) raise HTTPException(status_code=500, detail=str(e)) From 87e9e7f49c81d0165b772f67c388db1631e2d0e2 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 16 Dec 2025 14:52:02 -0500 Subject: [PATCH 02/19] Refactor module instantiation to avoid shared state across concurrent requests and add unit tests for pipeline execution and related functions. --- src/dspy_cli/server/routes.py | 6 +- tests/test_execution.py | 372 ++++++++++++++++++++++++++++++++++ 2 files changed, 375 insertions(+), 3 deletions(-) create mode 100644 tests/test_execution.py diff --git a/src/dspy_cli/server/routes.py b/src/dspy_cli/server/routes.py index e61aa42..efe6b73 100644 --- a/src/dspy_cli/server/routes.py +++ b/src/dspy_cli/server/routes.py @@ -32,9 +32,6 @@ def create_program_routes( program_name = module.name model_name = model_config.get("model", "unknown") - # Instantiate the module once during route creation - instance = module.instantiate() - # Create request/response models based on forward types if module.is_forward_typed: try: @@ -64,6 +61,9 @@ async def run_program(request: request_model): # Convert dspy types (Image, Audio, etc.) from strings to objects inputs = _convert_dspy_types(inputs, module) + # Instantiate module per call to avoid shared state across concurrent requests + instance = module.instantiate() + # Execute via shared pipeline executor output = await execute_pipeline( module=module, diff --git a/tests/test_execution.py b/tests/test_execution.py new file mode 100644 index 0000000..98c977a --- /dev/null +++ b/tests/test_execution.py @@ -0,0 +1,372 @@ +"""Unit tests for the shared pipeline execution module.""" + +import asyncio +from dataclasses import dataclass +from unittest.mock import AsyncMock, MagicMock, patch + +import dspy +import pytest + +from dspy_cli.server.execution import ( + _convert_dspy_types, + _extract_lm_metrics, + _normalize_output, + _serialize_for_logging, + execute_pipeline, +) + + +def run_async(coro): + """Helper to run async functions in tests.""" + return asyncio.get_event_loop().run_until_complete(coro) + + +class TestNormalizeOutput: + """Tests for _normalize_output function.""" + + def test_prediction_to_dict(self): + """dspy.Prediction should be converted to dict.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + prediction = dspy.Prediction(answer="hello", confidence=0.9) + result = _normalize_output(prediction, module) + + assert isinstance(result, dict) + assert result["answer"] == "hello" + assert result["confidence"] == 0.9 + + def test_dict_passthrough(self): + """Dict should pass through unchanged.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + data = {"key": "value", "num": 42} + result = _normalize_output(data, module) + + assert result == data + + def test_simple_value_with_typed_output(self): + """Simple value with single typed output field should use field name.""" + module = MagicMock() + module.is_forward_typed = True + module.forward_output_fields = {"summary": {"type": "str", "annotation": str}} + + result = _normalize_output("This is a summary", module) + + assert result == {"summary": "This is a summary"} + + def test_simple_value_without_typed_output(self): + """Simple value without typed output should use 'result' key.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + result = _normalize_output("plain text", module) + + assert result == {"result": "plain text"} + + def test_object_with_dict(self): + """Object with __dict__ should be converted via vars().""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + @dataclass + class Result: + name: str + value: int + + obj = Result(name="test", value=123) + result = _normalize_output(obj, module) + + assert result == {"name": "test", "value": 123} + + +class TestConvertDspyTypes: + """Tests for _convert_dspy_types function.""" + + def test_passthrough_when_not_typed(self): + """Should pass through when module is not forward typed.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_input_fields = None + + inputs = {"text": "hello"} + result = _convert_dspy_types(inputs, module) + + assert result == inputs + + def test_passthrough_unknown_fields(self): + """Should pass through fields not in forward_input_fields.""" + module = MagicMock() + module.is_forward_typed = True + module.forward_input_fields = {"known": {"annotation": str}} + + inputs = {"known": "value", "unknown": "other"} + result = _convert_dspy_types(inputs, module) + + assert result["unknown"] == "other" + + def test_passthrough_non_dspy_types(self): + """Should pass through non-dspy types.""" + module = MagicMock() + module.is_forward_typed = True + module.forward_input_fields = {"text": {"annotation": str}} + + inputs = {"text": "hello"} + result = _convert_dspy_types(inputs, module) + + assert result == {"text": "hello"} + + +class TestExtractLmMetrics: + """Tests for _extract_lm_metrics function.""" + + def test_no_history(self): + """Should return None values when no history.""" + lm = MagicMock() + lm.history = [] + + result = _extract_lm_metrics(lm, 0) + + assert result == {"tokens": None, "cost_usd": None, "lm_calls": None} + + def test_no_history_attr(self): + """Should handle LM without history attribute.""" + lm = MagicMock(spec=[]) + + result = _extract_lm_metrics(lm, 0) + + assert result == {"tokens": None, "cost_usd": None, "lm_calls": None} + + def test_extracts_token_counts(self): + """Should extract token counts from history.""" + lm = MagicMock() + lm.history = [ + { + "model": "gpt-4", + "usage": {"prompt_tokens": 100, "completion_tokens": 50}, + "cost": 0.005, + }, + { + "model": "gpt-4", + "usage": {"prompt_tokens": 80, "completion_tokens": 30}, + "cost": 0.003, + }, + ] + + result = _extract_lm_metrics(lm, 0) + + assert result["tokens"]["prompt_tokens"] == 180 + assert result["tokens"]["completion_tokens"] == 80 + assert result["tokens"]["total_tokens"] == 260 + assert result["cost_usd"] == 0.008 + assert len(result["lm_calls"]) == 2 + + def test_respects_start_index(self): + """Should only count entries from start_idx onwards.""" + lm = MagicMock() + lm.history = [ + {"model": "gpt-4", "usage": {"prompt_tokens": 100, "completion_tokens": 50}}, + {"model": "gpt-4", "usage": {"prompt_tokens": 80, "completion_tokens": 30}}, + ] + + result = _extract_lm_metrics(lm, 1) + + assert result["tokens"]["prompt_tokens"] == 80 + assert result["tokens"]["completion_tokens"] == 30 + + +class TestSerializeForLogging: + """Tests for _serialize_for_logging function.""" + + def test_dict_serialization(self, tmp_path): + """Should serialize nested dicts.""" + data = {"outer": {"inner": "value"}} + result = _serialize_for_logging(data, tmp_path, "test_program") + + assert result == {"outer": {"inner": "value"}} + + def test_list_serialization(self, tmp_path): + """Should serialize lists.""" + data = ["a", "b", "c"] + result = _serialize_for_logging(data, tmp_path, "test_program") + + assert result == ["a", "b", "c"] + + def test_passthrough_primitives(self, tmp_path): + """Should pass through primitive types.""" + assert _serialize_for_logging("text", tmp_path, "prog") == "text" + assert _serialize_for_logging(42, tmp_path, "prog") == 42 + assert _serialize_for_logging(True, tmp_path, "prog") is True + + +class TestExecutePipeline: + """Tests for execute_pipeline function.""" + + def test_successful_execution(self, tmp_path): + """Should execute module and return output dict.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + # Use spec to ensure instance doesn't have aforward (sync execution path) + instance = MagicMock(spec=['__call__']) + instance.return_value = {"result": "success"} + + lm = MagicMock() + lm.copy.return_value = lm + lm.history = [] + + async def run(): + with patch("dspy_cli.server.execution.dspy.context"): + return await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name="test-model", + program_name="test_program", + inputs={"text": "hello"}, + logs_dir=tmp_path, + ) + + result = run_async(run()) + assert result == {"result": "success"} + instance.assert_called_once_with(text="hello") + + def test_async_module_execution(self, tmp_path): + """Should use acall for modules with aforward.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + instance = MagicMock(spec=['aforward', 'acall']) + instance.acall = AsyncMock(return_value={"async_result": "done"}) + + lm = MagicMock() + lm.copy.return_value = lm + lm.history = [] + + async def run(): + with patch("dspy_cli.server.execution.dspy.context"): + return await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name="test-model", + program_name="test_program", + inputs={"query": "test"}, + logs_dir=tmp_path, + ) + + result = run_async(run()) + assert result == {"async_result": "done"} + instance.acall.assert_called_once_with(query="test") + + def test_logs_on_success(self, tmp_path): + """Should log inference on successful execution.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + # Use spec to ensure instance doesn't have aforward (sync execution path) + instance = MagicMock(spec=['__call__']) + instance.return_value = {"result": "ok"} + + lm = MagicMock() + lm.copy.return_value = lm + lm.history = [] + + async def run(): + with patch("dspy_cli.server.execution.dspy.context"), \ + patch("dspy_cli.server.execution.log_inference") as mock_log: + await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name="gpt-4", + program_name="my_program", + inputs={"x": 1}, + logs_dir=tmp_path, + ) + return mock_log + + mock_log = run_async(run()) + mock_log.assert_called_once() + call_kwargs = mock_log.call_args.kwargs + assert call_kwargs["program_name"] == "my_program" + assert call_kwargs["model"] == "gpt-4" + assert "error" not in call_kwargs or call_kwargs.get("error") is None + + def test_logs_on_error(self, tmp_path): + """Should log inference with error on failure.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + # Use spec to ensure instance doesn't have aforward (sync execution path) + instance = MagicMock(spec=['__call__']) + instance.side_effect = ValueError("Something went wrong") + + lm = MagicMock() + lm.copy.return_value = lm + lm.history = [] + + mock_log_ref = MagicMock() + + async def run(): + with patch("dspy_cli.server.execution.dspy.context"), \ + patch("dspy_cli.server.execution.log_inference") as mock_log: + mock_log_ref.mock = mock_log + await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name="gpt-4", + program_name="failing_program", + inputs={"x": 1}, + logs_dir=tmp_path, + ) + + with pytest.raises(ValueError, match="Something went wrong"): + run_async(run()) + + mock_log_ref.mock.assert_called_once() + call_kwargs = mock_log_ref.mock.call_args.kwargs + assert call_kwargs["error"] == "Something went wrong" + assert call_kwargs["outputs"] == {} + + def test_copies_lm_for_isolation(self, tmp_path): + """Should copy LM to avoid concurrent request interference.""" + module = MagicMock() + module.is_forward_typed = False + module.forward_output_fields = None + + # Use spec to ensure instance doesn't have aforward (sync execution path) + instance = MagicMock(spec=['__call__']) + instance.return_value = {} + + lm = MagicMock() + copied_lm = MagicMock() + copied_lm.history = [] + lm.copy.return_value = copied_lm + + async def run(): + with patch("dspy_cli.server.execution.dspy.context") as mock_context: + await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name="test", + program_name="test", + inputs={}, + logs_dir=tmp_path, + ) + return mock_context + + mock_context = run_async(run()) + lm.copy.assert_called_once() + mock_context.assert_called_once_with(lm=copied_lm) From ee9b0e699ead547a3ec802db2cbc0672f66a483a Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 16 Dec 2025 15:23:09 -0500 Subject: [PATCH 03/19] Add gateway discovery and instantiation functionality with associated tests. Introduced Gateway base class and specific implementations (APIGateway, CronGateway, IdentityGateway) to handle HTTP and scheduled execution. Enhanced module discovery to extract gateway classes and ensure backward compatibility. --- src/dspy_cli/discovery/gateway_finder.py | 83 +++++++++ src/dspy_cli/discovery/module_finder.py | 47 ++++- src/dspy_cli/gateway/__init__.py | 18 ++ src/dspy_cli/gateway/api.py | 69 ++++++++ src/dspy_cli/gateway/base.py | 12 ++ src/dspy_cli/gateway/cron.py | 58 ++++++ tests/discovery/__init__.py | 1 + tests/discovery/test_module_finder.py | 203 +++++++++++++++++++++ tests/gateway/__init__.py | 1 + tests/gateway/test_gateway.py | 214 +++++++++++++++++++++++ tests/gateway/test_gateway_finder.py | 182 +++++++++++++++++++ 11 files changed, 885 insertions(+), 3 deletions(-) create mode 100644 src/dspy_cli/discovery/gateway_finder.py create mode 100644 src/dspy_cli/gateway/__init__.py create mode 100644 src/dspy_cli/gateway/api.py create mode 100644 src/dspy_cli/gateway/base.py create mode 100644 src/dspy_cli/gateway/cron.py create mode 100644 tests/discovery/__init__.py create mode 100644 tests/discovery/test_module_finder.py create mode 100644 tests/gateway/__init__.py create mode 100644 tests/gateway/test_gateway.py create mode 100644 tests/gateway/test_gateway_finder.py diff --git a/src/dspy_cli/discovery/gateway_finder.py b/src/dspy_cli/discovery/gateway_finder.py new file mode 100644 index 0000000..b607075 --- /dev/null +++ b/src/dspy_cli/discovery/gateway_finder.py @@ -0,0 +1,83 @@ +"""Gateway discovery for DSPy modules. + +This module provides utilities to find and instantiate gateways for DSPy modules. +Gateways can be specified in two ways: + +1. Module attribute: The DSPy module class has a `gateway` class attribute + pointing to a Gateway subclass. + + class MyModule(dspy.Module): + gateway = MyCustomGateway + +2. Default: If no gateway is specified, IdentityGateway is used for + backward compatibility (HTTP inputs == pipeline inputs). +""" + +import logging +from typing import Optional, Type, Union + +from dspy_cli.discovery import DiscoveredModule +from dspy_cli.gateway import APIGateway, CronGateway, Gateway, IdentityGateway + +logger = logging.getLogger(__name__) + + +def get_gateway_for_module(module: DiscoveredModule) -> Gateway: + """Get or create the gateway instance for a discovered module. + + Checks if the module class has a `gateway` attribute pointing to a + Gateway subclass. If so, instantiates and returns it. Otherwise, + returns an IdentityGateway instance for backward compatibility. + + Args: + module: DiscoveredModule to get gateway for + + Returns: + Gateway instance (APIGateway, CronGateway, or subclass) + """ + gateway_class = get_gateway_class(module) + + if gateway_class is None: + logger.debug(f"No gateway for {module.name}, using IdentityGateway") + return IdentityGateway() + + try: + gateway = gateway_class() + logger.info(f"Using {gateway_class.__name__} for {module.name}") + return gateway + except Exception as e: + logger.warning( + f"Failed to instantiate {gateway_class.__name__} for {module.name}: {e}. " + f"Falling back to IdentityGateway." + ) + return IdentityGateway() + + +def get_gateway_class(module: DiscoveredModule) -> Optional[Type[Gateway]]: + """Extract the gateway class from a module if specified. + + Args: + module: DiscoveredModule to check + + Returns: + Gateway subclass if specified, None otherwise + """ + return module.gateway_class + + +def _is_gateway_class(obj) -> bool: + """Check if an object is a Gateway subclass (not instance).""" + try: + return isinstance(obj, type) and issubclass(obj, Gateway) + except TypeError: + return False + + +def is_api_gateway(gateway: Gateway) -> bool: + """Check if a gateway is an APIGateway (handles HTTP requests).""" + return isinstance(gateway, APIGateway) + + +def is_cron_gateway(gateway: Gateway) -> bool: + """Check if a gateway is a CronGateway (scheduled execution).""" + return isinstance(gateway, CronGateway) diff --git a/src/dspy_cli/discovery/module_finder.py b/src/dspy_cli/discovery/module_finder.py index 2aa605c..d0cde18 100644 --- a/src/dspy_cli/discovery/module_finder.py +++ b/src/dspy_cli/discovery/module_finder.py @@ -4,13 +4,16 @@ import inspect import logging import sys -from dataclasses import dataclass +from dataclasses import dataclass, field from pathlib import Path -from typing import Any, Dict, List, Optional, Type, get_type_hints +from typing import TYPE_CHECKING, Any, Dict, List, Optional, Type, get_type_hints import dspy from pydantic import BaseModel +if TYPE_CHECKING: + from dspy_cli.gateway import Gateway + logger = logging.getLogger(__name__) @@ -25,6 +28,7 @@ class DiscoveredModule: forward_input_fields: Optional[Dict[str, Any]] = None # Input field types from forward() method forward_output_fields: Optional[Dict[str, Any]] = None # Output field types from forward() method is_forward_typed: bool = False # True if forward() has proper type annotations + gateway_class: Optional[Type["Gateway"]] = None # Gateway class if specified on module def instantiate(self, lm: dspy.LM | None = None) -> dspy.Module: """Create an instance of this module.""" @@ -120,6 +124,9 @@ def discover_modules( # Also try to extract signature (for backward compatibility and fallback) signature = _extract_signature(obj) + # Extract gateway class if specified + gateway_class = _extract_gateway_class(obj) + discovered.append( DiscoveredModule( name=name, @@ -128,7 +135,8 @@ def discover_modules( signature=signature, forward_input_fields=forward_info.get("inputs"), forward_output_fields=forward_info.get("outputs"), - is_forward_typed=forward_info.get("is_typed", False) + is_forward_typed=forward_info.get("is_typed", False), + gateway_class=gateway_class, ) ) @@ -150,6 +158,39 @@ def discover_modules( return discovered +def _extract_gateway_class(module_class: Type[dspy.Module]) -> Optional[Type["Gateway"]]: + """Extract the gateway class from a module if specified. + + Checks for a `gateway` class attribute on the module that should be + a Gateway subclass. + + Args: + module_class: The DSPy Module class + + Returns: + Gateway subclass if specified and valid, None otherwise + """ + from dspy_cli.gateway import Gateway + + gateway_attr = getattr(module_class, 'gateway', None) + + if gateway_attr is None: + return None + + try: + if isinstance(gateway_attr, type) and issubclass(gateway_attr, Gateway): + logger.debug(f"Found gateway {gateway_attr.__name__} on {module_class.__name__}") + return gateway_attr + except TypeError: + pass + + logger.warning( + f"Module {module_class.__name__} has 'gateway' attribute but it's not a Gateway subclass: " + f"{type(gateway_attr)}. Ignoring." + ) + return None + + def _extract_forward_types(module_class: Type[dspy.Module]) -> Dict[str, Any]: """Extract type information from a module's forward() method. diff --git a/src/dspy_cli/gateway/__init__.py b/src/dspy_cli/gateway/__init__.py new file mode 100644 index 0000000..a81aa5d --- /dev/null +++ b/src/dspy_cli/gateway/__init__.py @@ -0,0 +1,18 @@ +"""Gateway abstractions for HTTP and scheduled pipeline execution. + +Gateways separate HTTP endpoint concerns from DSPy pipeline logic: +- APIGateway: Transform HTTP requests to pipeline inputs and outputs +- CronGateway: Load data from external sources on a schedule +- IdentityGateway: Default pass-through (backward compatible) +""" + +from dspy_cli.gateway.api import APIGateway, IdentityGateway +from dspy_cli.gateway.base import Gateway +from dspy_cli.gateway.cron import CronGateway + +__all__ = [ + "Gateway", + "APIGateway", + "IdentityGateway", + "CronGateway", +] diff --git a/src/dspy_cli/gateway/api.py b/src/dspy_cli/gateway/api.py new file mode 100644 index 0000000..9ba0b40 --- /dev/null +++ b/src/dspy_cli/gateway/api.py @@ -0,0 +1,69 @@ +"""API Gateway for HTTP request/response transformation.""" + +from typing import Any, Dict, Optional, Type + +from pydantic import BaseModel + +from dspy_cli.gateway.base import Gateway + + +class APIGateway(Gateway): + """Gateway for HTTP request/response transformation. + + Use this when you need to: + - Transform HTTP request bodies before passing to the pipeline + - Transform pipeline outputs before returning as HTTP response + - Customize the HTTP endpoint path or method + - Add authentication requirements + + Example: + class MyGateway(APIGateway): + path = "/api/v2/analyze" + + def to_pipeline_inputs(self, request): + # Transform webhook payload to pipeline format + return {"text": request["data"]["content"]} + + def from_pipeline_output(self, output): + # Wrap output for API consumers + return {"status": "success", "result": output} + """ + + request_model: Optional[Type[BaseModel]] = None + response_model: Optional[Type[BaseModel]] = None + path: Optional[str] = None + method: str = "POST" + requires_auth: bool = False + + def to_pipeline_inputs(self, request: Any) -> Dict[str, Any]: + """Transform HTTP request to forward() kwargs. + + Args: + request: The HTTP request body (Pydantic model or dict) + + Returns: + Dictionary of kwargs to pass to the DSPy module's forward() + """ + if isinstance(request, BaseModel): + return request.model_dump() + return dict(request) if request else {} + + def from_pipeline_output(self, output: Any) -> Any: + """Transform pipeline output to HTTP response. + + Args: + output: The normalized output dict from execute_pipeline + + Returns: + The HTTP response body (will be serialized to JSON) + """ + return output + + +class IdentityGateway(APIGateway): + """Default gateway - HTTP inputs == pipeline inputs. + + This provides backward compatibility: modules without an explicit + gateway attribute use this, which passes inputs/outputs unchanged. + """ + pass diff --git a/src/dspy_cli/gateway/base.py b/src/dspy_cli/gateway/base.py new file mode 100644 index 0000000..e252da3 --- /dev/null +++ b/src/dspy_cli/gateway/base.py @@ -0,0 +1,12 @@ +"""Base Gateway class for all gateway types.""" + +from abc import ABC + + +class Gateway(ABC): + """Base class for all gateways. + + A gateway controls how data flows into and out of a DSPy pipeline. + Subclasses define specific input/output transformation patterns. + """ + pass diff --git a/src/dspy_cli/gateway/cron.py b/src/dspy_cli/gateway/cron.py new file mode 100644 index 0000000..160c74f --- /dev/null +++ b/src/dspy_cli/gateway/cron.py @@ -0,0 +1,58 @@ +"""Cron Gateway for scheduled pipeline execution.""" + +from abc import abstractmethod +from typing import Any, Dict, List + +from dspy_cli.gateway.base import Gateway + + +class CronGateway(Gateway): + """Gateway for scheduled pipeline execution. + + Use this when your pipeline needs to: + - Run on a schedule (e.g., every 5 minutes) + - Load input data from external sources (APIs, databases, queues) + - Take actions based on pipeline outputs (webhooks, API calls) + + Example: + class DiscordModerationGateway(CronGateway): + schedule = "*/5 * * * *" # Every 5 minutes + + async def get_pipeline_inputs(self) -> list[dict]: + # Fetch unmoderated messages from Discord API + messages = await fetch_recent_messages() + return [{"message": m["content"], "author": m["author"]} for m in messages] + + async def on_complete(self, inputs: dict, output) -> None: + # Take action based on moderation result + if output.action == "delete": + await delete_message(inputs["_meta"]["message_id"]) + """ + + schedule: str # Cron expression like "*/5 * * * *" + + @abstractmethod + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + """Fetch input data from external sources. + + Called on each scheduled execution. Returns a list of input dicts, + and the pipeline will be executed once for each. + + Returns: + List of input dictionaries for pipeline execution. + Each dict should contain the kwargs for forward(). + Include "_meta" key for data needed in on_complete but not by the pipeline. + """ + ... + + @abstractmethod + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + """Handle pipeline output. + + Called after each successful pipeline execution. + + Args: + inputs: The original input dict (including _meta if provided) + output: The normalized output dict from execute_pipeline + """ + ... diff --git a/tests/discovery/__init__.py b/tests/discovery/__init__.py new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/tests/discovery/__init__.py @@ -0,0 +1 @@ + diff --git a/tests/discovery/test_module_finder.py b/tests/discovery/test_module_finder.py new file mode 100644 index 0000000..da00372 --- /dev/null +++ b/tests/discovery/test_module_finder.py @@ -0,0 +1,203 @@ +"""Tests for module discovery including gateway extraction.""" + +import sys +import tempfile +from pathlib import Path + +import dspy +import pytest + +from dspy_cli.discovery.module_finder import ( + DiscoveredModule, + _extract_gateway_class, + discover_modules, +) +from dspy_cli.gateway import APIGateway, CronGateway, IdentityGateway + + +class TestExtractGatewayClass: + """Tests for _extract_gateway_class function.""" + + def test_returns_none_when_no_gateway(self): + """Should return None when module has no gateway attribute.""" + class NoGatewayModule(dspy.Module): + def forward(self, text: str) -> str: + return text + + result = _extract_gateway_class(NoGatewayModule) + + assert result is None + + def test_returns_api_gateway_class(self): + """Should return APIGateway subclass when specified.""" + class CustomGateway(APIGateway): + path = "/custom" + + class ModuleWithGateway(dspy.Module): + gateway = CustomGateway + + def forward(self, text: str) -> str: + return text + + result = _extract_gateway_class(ModuleWithGateway) + + assert result is CustomGateway + + def test_returns_identity_gateway_class(self): + """Should return IdentityGateway when explicitly specified.""" + class ModuleWithIdentity(dspy.Module): + gateway = IdentityGateway + + def forward(self, text: str) -> str: + return text + + result = _extract_gateway_class(ModuleWithIdentity) + + assert result is IdentityGateway + + def test_ignores_non_gateway_class(self): + """Should return None for non-Gateway class attributes.""" + class NotAGateway: + pass + + class ModuleWithWrongType(dspy.Module): + gateway = NotAGateway + + def forward(self, text: str) -> str: + return text + + result = _extract_gateway_class(ModuleWithWrongType) + + assert result is None + + def test_ignores_gateway_instance(self): + """Should return None when gateway is an instance, not a class.""" + class ModuleWithInstance(dspy.Module): + gateway = IdentityGateway() + + def forward(self, text: str) -> str: + return text + + result = _extract_gateway_class(ModuleWithInstance) + + assert result is None + + def test_ignores_string_gateway(self): + """Should return None when gateway is a string.""" + class ModuleWithString(dspy.Module): + gateway = "not a gateway" + + def forward(self, text: str) -> str: + return text + + result = _extract_gateway_class(ModuleWithString) + + assert result is None + + +class TestDiscoverModulesWithGateway: + """Integration tests for discover_modules with gateway extraction.""" + + def test_discovers_module_with_gateway(self, tmp_path): + """Should discover module and extract gateway class.""" + modules_dir = tmp_path / "test_pkg" / "modules" + modules_dir.mkdir(parents=True) + + (modules_dir / "__init__.py").write_text("") + (tmp_path / "test_pkg" / "__init__.py").write_text("") + + module_code = ''' +import dspy +from dspy_cli.gateway import APIGateway + +class CustomGateway(APIGateway): + path = "/api/test" + +class TestModule(dspy.Module): + gateway = CustomGateway + + def forward(self, text: str) -> str: + return text +''' + (modules_dir / "test_module.py").write_text(module_code) + + sys.path.insert(0, str(tmp_path)) + try: + discovered = discover_modules(modules_dir, "test_pkg.modules") + + assert len(discovered) == 1 + module = discovered[0] + assert module.name == "TestModule" + assert module.gateway_class is not None + assert module.gateway_class.__name__ == "CustomGateway" + assert issubclass(module.gateway_class, APIGateway) + finally: + sys.path.remove(str(tmp_path)) + for key in list(sys.modules.keys()): + if key.startswith("test_pkg"): + del sys.modules[key] + + def test_discovers_module_without_gateway(self, tmp_path): + """Should discover module with gateway_class=None when not specified.""" + modules_dir = tmp_path / "test_pkg2" / "modules" + modules_dir.mkdir(parents=True) + + (modules_dir / "__init__.py").write_text("") + (tmp_path / "test_pkg2" / "__init__.py").write_text("") + + module_code = ''' +import dspy + +class SimpleModule(dspy.Module): + def forward(self, text: str) -> str: + return text +''' + (modules_dir / "simple.py").write_text(module_code) + + sys.path.insert(0, str(tmp_path)) + try: + discovered = discover_modules(modules_dir, "test_pkg2.modules") + + assert len(discovered) == 1 + module = discovered[0] + assert module.name == "SimpleModule" + assert module.gateway_class is None + finally: + sys.path.remove(str(tmp_path)) + for key in list(sys.modules.keys()): + if key.startswith("test_pkg2"): + del sys.modules[key] + + +class TestDiscoveredModuleDataclass: + """Tests for DiscoveredModule dataclass.""" + + def test_gateway_class_defaults_to_none(self): + """gateway_class should default to None.""" + class DummyModule(dspy.Module): + pass + + module = DiscoveredModule( + name="DummyModule", + class_obj=DummyModule, + module_path="test.dummy", + ) + + assert module.gateway_class is None + + def test_gateway_class_can_be_set(self): + """gateway_class can be set to a Gateway subclass.""" + class DummyModule(dspy.Module): + pass + + class MyGateway(APIGateway): + pass + + module = DiscoveredModule( + name="DummyModule", + class_obj=DummyModule, + module_path="test.dummy", + gateway_class=MyGateway, + ) + + assert module.gateway_class is MyGateway diff --git a/tests/gateway/__init__.py b/tests/gateway/__init__.py new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/tests/gateway/__init__.py @@ -0,0 +1 @@ + diff --git a/tests/gateway/test_gateway.py b/tests/gateway/test_gateway.py new file mode 100644 index 0000000..ac952b7 --- /dev/null +++ b/tests/gateway/test_gateway.py @@ -0,0 +1,214 @@ +"""Tests for Gateway base classes.""" + +import asyncio +from typing import Any, Dict, List + +import pytest +from pydantic import BaseModel + +from dspy_cli.gateway import APIGateway, CronGateway, Gateway, IdentityGateway + + +def run_async(coro): + """Helper to run async functions in tests.""" + return asyncio.get_event_loop().run_until_complete(coro) + + +class TestIdentityGateway: + """Tests for IdentityGateway (default pass-through).""" + + def test_to_pipeline_inputs_dict_passthrough(self): + """Dict inputs should pass through unchanged.""" + gateway = IdentityGateway() + inputs = {"text": "hello", "count": 5} + + result = gateway.to_pipeline_inputs(inputs) + + assert result == {"text": "hello", "count": 5} + + def test_to_pipeline_inputs_pydantic_model(self): + """Pydantic model should be converted to dict.""" + class RequestModel(BaseModel): + text: str + count: int + + gateway = IdentityGateway() + request = RequestModel(text="hello", count=5) + + result = gateway.to_pipeline_inputs(request) + + assert result == {"text": "hello", "count": 5} + + def test_to_pipeline_inputs_empty(self): + """Empty/None inputs should return empty dict.""" + gateway = IdentityGateway() + + assert gateway.to_pipeline_inputs({}) == {} + assert gateway.to_pipeline_inputs(None) == {} + + def test_from_pipeline_output_passthrough(self): + """Output should pass through unchanged.""" + gateway = IdentityGateway() + output = {"answer": "result", "score": 0.95} + + result = gateway.from_pipeline_output(output) + + assert result == {"answer": "result", "score": 0.95} + + def test_default_attributes(self): + """Default attributes should be set correctly.""" + gateway = IdentityGateway() + + assert gateway.request_model is None + assert gateway.response_model is None + assert gateway.path is None + assert gateway.method == "POST" + assert gateway.requires_auth is False + + +class TestAPIGateway: + """Tests for custom APIGateway subclasses.""" + + def test_custom_to_pipeline_inputs(self): + """Subclass can override input transformation.""" + class WebhookGateway(APIGateway): + def to_pipeline_inputs(self, request: Any) -> Dict[str, Any]: + return {"text": request["data"]["content"]} + + gateway = WebhookGateway() + request = {"data": {"content": "hello world"}} + + result = gateway.to_pipeline_inputs(request) + + assert result == {"text": "hello world"} + + def test_custom_from_pipeline_output(self): + """Subclass can override output transformation.""" + class WrappedGateway(APIGateway): + def from_pipeline_output(self, output: Any) -> Any: + return {"status": "success", "result": output} + + gateway = WrappedGateway() + output = {"answer": "42"} + + result = gateway.from_pipeline_output(output) + + assert result == {"status": "success", "result": {"answer": "42"}} + + def test_custom_path_and_method(self): + """Subclass can set custom path and method.""" + class CustomGateway(APIGateway): + path = "/api/v2/analyze" + method = "PUT" + requires_auth = True + + gateway = CustomGateway() + + assert gateway.path == "/api/v2/analyze" + assert gateway.method == "PUT" + assert gateway.requires_auth is True + + def test_custom_request_response_models(self): + """Subclass can specify Pydantic models.""" + class MyRequest(BaseModel): + query: str + + class MyResponse(BaseModel): + answer: str + + class TypedGateway(APIGateway): + request_model = MyRequest + response_model = MyResponse + + gateway = TypedGateway() + + assert gateway.request_model is MyRequest + assert gateway.response_model is MyResponse + + +class TestCronGateway: + """Tests for CronGateway abstract class.""" + + def test_requires_schedule(self): + """CronGateway subclass must define schedule.""" + class ValidCronGateway(CronGateway): + schedule = "*/5 * * * *" + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [{"text": "test"}] + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + pass + + gateway = ValidCronGateway() + assert gateway.schedule == "*/5 * * * *" + + def test_abstract_methods_required(self): + """Cannot instantiate CronGateway without implementing abstract methods.""" + class IncompleteCronGateway(CronGateway): + schedule = "0 * * * *" + + with pytest.raises(TypeError, match="abstract"): + IncompleteCronGateway() + + def test_get_pipeline_inputs(self): + """get_pipeline_inputs should return list of input dicts.""" + class TestCronGateway(CronGateway): + schedule = "0 0 * * *" + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [ + {"id": 1, "text": "first"}, + {"id": 2, "text": "second"}, + ] + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + pass + + gateway = TestCronGateway() + inputs = run_async(gateway.get_pipeline_inputs()) + + assert len(inputs) == 2 + assert inputs[0] == {"id": 1, "text": "first"} + + def test_on_complete_receives_inputs_and_output(self): + """on_complete should receive original inputs and pipeline output.""" + received = {} + + class TrackingCronGateway(CronGateway): + schedule = "0 0 * * *" + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [{"text": "test", "_meta": {"msg_id": 123}}] + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + received["inputs"] = inputs + received["output"] = output + + gateway = TrackingCronGateway() + inputs = run_async(gateway.get_pipeline_inputs())[0] + run_async(gateway.on_complete(inputs, {"result": "done"})) + + assert received["inputs"]["_meta"]["msg_id"] == 123 + assert received["output"] == {"result": "done"} + + +class TestGatewayInheritance: + """Tests for Gateway class hierarchy.""" + + def test_identity_gateway_is_api_gateway(self): + """IdentityGateway should be a subclass of APIGateway.""" + assert issubclass(IdentityGateway, APIGateway) + assert issubclass(IdentityGateway, Gateway) + + def test_api_gateway_is_gateway(self): + """APIGateway should be a subclass of Gateway.""" + assert issubclass(APIGateway, Gateway) + + def test_cron_gateway_is_gateway(self): + """CronGateway should be a subclass of Gateway.""" + assert issubclass(CronGateway, Gateway) + + def test_cron_gateway_not_api_gateway(self): + """CronGateway should NOT be a subclass of APIGateway.""" + assert not issubclass(CronGateway, APIGateway) diff --git a/tests/gateway/test_gateway_finder.py b/tests/gateway/test_gateway_finder.py new file mode 100644 index 0000000..fc0190e --- /dev/null +++ b/tests/gateway/test_gateway_finder.py @@ -0,0 +1,182 @@ +"""Tests for gateway discovery.""" + +from unittest.mock import MagicMock + +import dspy +import pytest + +from dspy_cli.discovery import DiscoveredModule +from dspy_cli.discovery.gateway_finder import ( + get_gateway_class, + get_gateway_for_module, + is_api_gateway, + is_cron_gateway, +) +from dspy_cli.gateway import APIGateway, CronGateway, Gateway, IdentityGateway + + +class TestGetGatewayForModule: + """Tests for get_gateway_for_module function.""" + + def test_returns_identity_gateway_when_no_gateway(self): + """Should return IdentityGateway when module has no gateway attr.""" + class SimpleModule(dspy.Module): + pass + + module = DiscoveredModule( + name="SimpleModule", + class_obj=SimpleModule, + module_path="test.simple", + ) + + gateway = get_gateway_for_module(module) + + assert isinstance(gateway, IdentityGateway) + + def test_returns_custom_api_gateway(self): + """Should return custom APIGateway when specified.""" + class CustomGateway(APIGateway): + path = "/custom" + + class ModuleWithGateway(dspy.Module): + gateway = CustomGateway + + module = DiscoveredModule( + name="ModuleWithGateway", + class_obj=ModuleWithGateway, + module_path="test.with_gateway", + gateway_class=CustomGateway, + ) + + gateway = get_gateway_for_module(module) + + assert isinstance(gateway, CustomGateway) + assert gateway.path == "/custom" + + def test_returns_identity_for_invalid_gateway_attr(self): + """Should fallback to IdentityGateway for invalid gateway attr.""" + class ModuleWithBadGateway(dspy.Module): + gateway = "not a gateway class" + + module = DiscoveredModule( + name="ModuleWithBadGateway", + class_obj=ModuleWithBadGateway, + module_path="test.bad_gateway", + ) + + gateway = get_gateway_for_module(module) + + assert isinstance(gateway, IdentityGateway) + + +class TestGetGatewayClass: + """Tests for get_gateway_class function.""" + + def test_returns_none_when_no_gateway(self): + """Should return None when module has no gateway attr.""" + class NoGatewayModule(dspy.Module): + pass + + module = DiscoveredModule( + name="NoGatewayModule", + class_obj=NoGatewayModule, + module_path="test.no_gateway", + ) + + result = get_gateway_class(module) + + assert result is None + + def test_returns_gateway_class(self): + """Should return gateway class when specified.""" + class MyGateway(APIGateway): + pass + + class ModuleWithGateway(dspy.Module): + gateway = MyGateway + + module = DiscoveredModule( + name="ModuleWithGateway", + class_obj=ModuleWithGateway, + module_path="test.with_gateway", + gateway_class=MyGateway, + ) + + result = get_gateway_class(module) + + assert result is MyGateway + + def test_ignores_non_gateway_class(self): + """Should return None for non-Gateway class attributes.""" + class NotAGateway: + pass + + class ModuleWithWrongType(dspy.Module): + gateway = NotAGateway + + module = DiscoveredModule( + name="ModuleWithWrongType", + class_obj=ModuleWithWrongType, + module_path="test.wrong_type", + ) + + result = get_gateway_class(module) + + assert result is None + + def test_ignores_gateway_instance(self): + """Should return None when gateway is an instance, not a class.""" + class ModuleWithInstance(dspy.Module): + gateway = IdentityGateway() + + module = DiscoveredModule( + name="ModuleWithInstance", + class_obj=ModuleWithInstance, + module_path="test.instance", + ) + + result = get_gateway_class(module) + + assert result is None + + +class TestIsApiGateway: + """Tests for is_api_gateway type check.""" + + def test_identity_gateway_is_api(self): + """IdentityGateway should be an API gateway.""" + assert is_api_gateway(IdentityGateway()) is True + + def test_api_gateway_subclass_is_api(self): + """APIGateway subclass should be an API gateway.""" + class CustomAPI(APIGateway): + pass + + assert is_api_gateway(CustomAPI()) is True + + def test_cron_gateway_is_not_api(self): + """CronGateway should not be an API gateway.""" + class TestCron(CronGateway): + schedule = "* * * * *" + async def get_pipeline_inputs(self): return [] + async def on_complete(self, inputs, output): pass + + assert is_api_gateway(TestCron()) is False + + +class TestIsCronGateway: + """Tests for is_cron_gateway type check.""" + + def test_cron_gateway_is_cron(self): + """CronGateway should be detected.""" + class TestCron(CronGateway): + schedule = "* * * * *" + async def get_pipeline_inputs(self): return [] + async def on_complete(self, inputs, output): pass + + assert is_cron_gateway(TestCron()) is True + + def test_api_gateway_is_not_cron(self): + """APIGateway should not be a cron gateway.""" + assert is_cron_gateway(APIGateway()) is False + assert is_cron_gateway(IdentityGateway()) is False From 8d1355b53747470197f6e7f4c3902caf11e31d52 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 16 Dec 2025 15:42:52 -0500 Subject: [PATCH 04/19] Enhance authentication middleware to support dynamic open paths and integrate APIGateway for route handling. Added tests for APIGateway functionality, ensuring proper input/output transformations and backward compatibility for modules without gateways. --- src/dspy_cli/server/app.py | 8 +- src/dspy_cli/server/auth.py | 9 +- src/dspy_cli/server/routes.py | 78 +++++--- tests/gateway/test_gateway_routes.py | 288 +++++++++++++++++++++++++++ 4 files changed, 351 insertions(+), 32 deletions(-) create mode 100644 tests/gateway/test_gateway_routes.py diff --git a/src/dspy_cli/server/app.py b/src/dspy_cli/server/app.py index 81142ae..b09c911 100644 --- a/src/dspy_cli/server/app.py +++ b/src/dspy_cli/server/app.py @@ -193,6 +193,7 @@ async def program_metrics(program_name: str): # Setup authentication if enabled if enable_auth: from dspy_cli.server.auth import ( + DEFAULT_OPEN_PATHS, AuthMiddleware, create_auth_routes, generate_token, @@ -215,8 +216,13 @@ async def program_metrics(program_name: str): auth_router = create_auth_routes(token) app.include_router(auth_router) + # Combine default open paths with gateway public paths (requires_auth=False) + open_paths = set(DEFAULT_OPEN_PATHS) + if hasattr(app.state, "public_paths"): + open_paths.update(app.state.public_paths) + # Add auth middleware (must be added after routes) - app.add_middleware(AuthMiddleware, token=token) + app.add_middleware(AuthMiddleware, token=token, open_paths=open_paths) logger.info("Authentication enabled") return app diff --git a/src/dspy_cli/server/auth.py b/src/dspy_cli/server/auth.py index 88f2b9f..65f2922 100644 --- a/src/dspy_cli/server/auth.py +++ b/src/dspy_cli/server/auth.py @@ -26,8 +26,8 @@ ENV_API_TOKEN = "DSPY_API_KEY" ENV_AUTH_ENABLED = "DSPY_CLI_AUTH_ENABLED" -# Paths that don't require authentication -OPEN_PATHS = {"/login", "/health", "/favicon.ico"} +# Paths that don't require authentication (defaults) +DEFAULT_OPEN_PATHS = {"/login", "/health", "/favicon.ico"} def get_api_token() -> str | None: @@ -96,15 +96,16 @@ def check_auth(request: Request, token: str) -> bool: class AuthMiddleware(BaseHTTPMiddleware): """Middleware that enforces authentication on all routes except open paths.""" - def __init__(self, app, token: str): + def __init__(self, app, token: str, open_paths: set[str] | None = None): super().__init__(app) self.token = token + self.open_paths = open_paths if open_paths is not None else DEFAULT_OPEN_PATHS async def dispatch(self, request: Request, call_next: Callable) -> Response: path = request.url.path.rstrip("/") or "/" # Allow open paths without auth - if path in OPEN_PATHS or path == "/login": + if path in self.open_paths or path == "/login": return await call_next(request) # Allow static files diff --git a/src/dspy_cli/server/routes.py b/src/dspy_cli/server/routes.py index efe6b73..a8d5bd1 100644 --- a/src/dspy_cli/server/routes.py +++ b/src/dspy_cli/server/routes.py @@ -8,6 +8,8 @@ from pydantic import BaseModel, create_model from dspy_cli.discovery import DiscoveredModule +from dspy_cli.discovery.gateway_finder import get_gateway_for_module +from dspy_cli.gateway import APIGateway from dspy_cli.server.execution import _convert_dspy_types, execute_pipeline logger = logging.getLogger(__name__) @@ -18,7 +20,8 @@ def create_program_routes( module: DiscoveredModule, lm: dspy.LM, model_config: Dict, - config: Dict + config: Dict, + gateway: APIGateway | None = None, ): """Create API routes for a DSPy program. @@ -28,58 +31,79 @@ def create_program_routes( lm: Language model instance for this program model_config: Model configuration for this program config: Full configuration dictionary + gateway: Optional APIGateway instance (if None, will be discovered) """ program_name = module.name model_name = model_config.get("model", "unknown") - # Create request/response models based on forward types - if module.is_forward_typed: - try: - request_model = _create_request_model_from_forward(module) - response_model = _create_response_model_from_forward(module) - except Exception as e: - logger.warning(f"Could not create models from forward types for {program_name}: {e}") + if gateway is None: + gateway = get_gateway_for_module(module) + if not isinstance(gateway, APIGateway): + logger.warning(f"Module {program_name} has non-API gateway, skipping route creation") + return + + request_model = gateway.request_model + response_model = gateway.response_model + + if request_model is None: + if module.is_forward_typed: + try: + request_model = _create_request_model_from_forward(module) + except Exception as e: + logger.warning(f"Could not create request model from forward types for {program_name}: {e}") + request_model = Dict[str, Any] + else: + logger.warning(f"Module {program_name} does not have typed forward() method - API will have no validation") request_model = Dict[str, Any] + + if response_model is None: + if module.is_forward_typed: + try: + response_model = _create_response_model_from_forward(module) + except Exception as e: + logger.warning(f"Could not create response model from forward types for {program_name}: {e}") + response_model = Dict[str, Any] + else: response_model = Dict[str, Any] - else: - # No typed forward method - use generic dict models (no validation) - logger.warning(f"Module {program_name} does not have typed forward() method - API will have no validation") - request_model = Dict[str, Any] - response_model = Dict[str, Any] - - # Create POST /{program} endpoint - @app.post(f"/{program_name}", response_model=response_model) + + route_path = gateway.path if gateway.path else f"/{program_name}" + async def run_program(request: request_model): """Execute the DSPy program with given inputs.""" try: - # Convert request to dict if it's a Pydantic model - if isinstance(request, BaseModel): - inputs = request.model_dump() - else: - inputs = request + pipeline_inputs = gateway.to_pipeline_inputs(request) - # Convert dspy types (Image, Audio, etc.) from strings to objects - inputs = _convert_dspy_types(inputs, module) + pipeline_inputs = _convert_dspy_types(pipeline_inputs, module) - # Instantiate module per call to avoid shared state across concurrent requests instance = module.instantiate() - # Execute via shared pipeline executor output = await execute_pipeline( module=module, instance=instance, lm=lm, model_name=model_name, program_name=program_name, - inputs=inputs, + inputs=pipeline_inputs, logs_dir=app.state.logs_dir, ) - return output + return gateway.from_pipeline_output(output) except Exception as e: raise HTTPException(status_code=500, detail=str(e)) + app.add_api_route( + route_path, + run_program, + methods=[gateway.method], + response_model=response_model, + ) + + if not gateway.requires_auth: + if not hasattr(app.state, "public_paths"): + app.state.public_paths = set() + app.state.public_paths.add(route_path) + def _create_request_model_from_forward(module: DiscoveredModule) -> type: """Create a Pydantic model for request validation based on forward() types. diff --git a/tests/gateway/test_gateway_routes.py b/tests/gateway/test_gateway_routes.py new file mode 100644 index 0000000..e47ad03 --- /dev/null +++ b/tests/gateway/test_gateway_routes.py @@ -0,0 +1,288 @@ +"""Integration tests for APIGateway with routes.""" + +import sys + +import pytest +from fastapi.testclient import TestClient + +from dspy_cli.server.app import create_app + + +@pytest.fixture +def test_config(): + """Minimal valid config for testing.""" + return { + "models": { + "default": "test_model", + "registry": { + "test_model": { + "model": "openai/gpt-3.5-turbo", + "env": "OPENAI_API_KEY", + "max_tokens": 4000, + "temperature": 1.0, + "model_type": "chat" + } + } + } + } + + +@pytest.fixture +def gateway_project(tmp_path, monkeypatch): + """Create a project with a module that uses a custom APIGateway.""" + from click.testing import CliRunner + from dspy_cli.cli import main + + monkeypatch.chdir(tmp_path) + + runner = CliRunner() + result = runner.invoke( + main, + ["new", "gatewaypkg", "--program-name", "main", "--module-type", "Predict", + "--signature", "question -> answer", "--model", "openai/gpt-4o-mini", "--api-key", ""], + catch_exceptions=False + ) + assert result.exit_code == 0 + + project_root = tmp_path / "gatewaypkg" + + default_module = project_root / "src" / "gatewaypkg" / "modules" / "main_predict.py" + if default_module.exists(): + default_module.unlink() + + module_path = project_root / "src" / "gatewaypkg" / "modules" / "webhook_processor.py" + module_path.write_text('''"""Module with custom APIGateway for webhook processing.""" +import dspy +from dspy_cli.gateway import APIGateway + + +class WebhookGateway(APIGateway): + """Transform webhook payload to pipeline inputs.""" + path = "/webhooks/process" + + def to_pipeline_inputs(self, request): + """Extract text from nested webhook payload.""" + if isinstance(request, dict): + return {"text": request.get("data", {}).get("content", "")} + return {"text": str(request)} + + def from_pipeline_output(self, output): + """Wrap output in webhook response format.""" + return { + "status": "processed", + "result": output, + } + + +class WebhookProcessor(dspy.Module): + """Process webhook data - no LLM calls.""" + gateway = WebhookGateway + + def forward(self, text: str): + return {"processed_text": text.upper(), "length": len(text)} +''') + + config_path = project_root / "dspy.config.yaml" + config_content = """version: 1 +models: + default: test_model + registry: + test_model: + model: openai/gpt-3.5-turbo + env: OPENAI_API_KEY + max_tokens: 4000 + temperature: 1.0 + model_type: chat +""" + config_path.write_text(config_content) + + monkeypatch.chdir(project_root) + sys.path.insert(0, str(project_root / "src")) + + yield { + "root": project_root, + "modules_path": project_root / "src" / "gatewaypkg" / "modules", + "package_name": "gatewaypkg.modules", + } + + if str(project_root / "src") in sys.path: + sys.path.remove(str(project_root / "src")) + + +@pytest.fixture +def identity_gateway_project(tmp_path, monkeypatch): + """Create a project with a module that has no gateway (uses IdentityGateway).""" + from click.testing import CliRunner + from dspy_cli.cli import main + + monkeypatch.chdir(tmp_path) + + runner = CliRunner() + result = runner.invoke( + main, + ["new", "identitypkg", "--program-name", "main", "--module-type", "Predict", + "--signature", "question -> answer", "--model", "openai/gpt-4o-mini", "--api-key", ""], + catch_exceptions=False + ) + assert result.exit_code == 0 + + project_root = tmp_path / "identitypkg" + + default_module = project_root / "src" / "identitypkg" / "modules" / "main_predict.py" + if default_module.exists(): + default_module.unlink() + + module_path = project_root / "src" / "identitypkg" / "modules" / "echo.py" + module_path.write_text('''"""Simple echo module with no gateway.""" +import dspy + + +class Echo(dspy.Module): + """Echo back input - no gateway, no LLM calls.""" + + def forward(self, text: str): + return {"echo": text} +''') + + config_path = project_root / "dspy.config.yaml" + config_content = """version: 1 +models: + default: test_model + registry: + test_model: + model: openai/gpt-3.5-turbo + env: OPENAI_API_KEY + max_tokens: 4000 + temperature: 1.0 + model_type: chat +""" + config_path.write_text(config_content) + + monkeypatch.chdir(project_root) + sys.path.insert(0, str(project_root / "src")) + + yield { + "root": project_root, + "modules_path": project_root / "src" / "identitypkg" / "modules", + "package_name": "identitypkg.modules", + } + + if str(project_root / "src") in sys.path: + sys.path.remove(str(project_root / "src")) + + +class TestAPIGatewayRoutes: + """Tests for APIGateway integration with routes.""" + + def test_custom_gateway_path(self, gateway_project, test_config): + """Custom gateway path should be used instead of module name.""" + app = create_app( + config=test_config, + package_path=gateway_project["modules_path"], + package_name=gateway_project["package_name"], + logs_dir=gateway_project["root"] / "logs", + enable_ui=False + ) + + routes = [r.path for r in app.routes if hasattr(r, "path")] + assert "/webhooks/process" in routes + assert "/WebhookProcessor" not in routes + + def test_custom_gateway_input_transform(self, gateway_project, test_config): + """Gateway should transform webhook payload to pipeline inputs.""" + app = create_app( + config=test_config, + package_path=gateway_project["modules_path"], + package_name=gateway_project["package_name"], + logs_dir=gateway_project["root"] / "logs", + enable_ui=False + ) + + with TestClient(app) as client: + response = client.post( + "/webhooks/process", + json={"data": {"content": "hello world"}} + ) + assert response.status_code == 200 + result = response.json() + + assert result["status"] == "processed" + assert result["result"]["processed_text"] == "HELLO WORLD" + assert result["result"]["length"] == 11 + + def test_custom_gateway_output_transform(self, gateway_project, test_config): + """Gateway should wrap pipeline output in response format.""" + app = create_app( + config=test_config, + package_path=gateway_project["modules_path"], + package_name=gateway_project["package_name"], + logs_dir=gateway_project["root"] / "logs", + enable_ui=False + ) + + with TestClient(app) as client: + response = client.post( + "/webhooks/process", + json={"data": {"content": "test"}} + ) + assert response.status_code == 200 + result = response.json() + + assert "status" in result + assert "result" in result + assert result["status"] == "processed" + + +class TestIdentityGatewayRoutes: + """Tests for IdentityGateway (default) behavior.""" + + def test_no_gateway_uses_module_name_path(self, identity_gateway_project, test_config): + """Module without gateway should use /{module_name} path.""" + app = create_app( + config=test_config, + package_path=identity_gateway_project["modules_path"], + package_name=identity_gateway_project["package_name"], + logs_dir=identity_gateway_project["root"] / "logs", + enable_ui=False + ) + + routes = [r.path for r in app.routes if hasattr(r, "path")] + assert "/Echo" in routes + + def test_identity_gateway_passthrough(self, identity_gateway_project, test_config): + """IdentityGateway should pass inputs/outputs unchanged.""" + app = create_app( + config=test_config, + package_path=identity_gateway_project["modules_path"], + package_name=identity_gateway_project["package_name"], + logs_dir=identity_gateway_project["root"] / "logs", + enable_ui=False + ) + + with TestClient(app) as client: + response = client.post("/Echo", json={"text": "hello"}) + assert response.status_code == 200 + result = response.json() + + assert result == {"echo": "hello"} + + def test_backward_compatibility(self, identity_gateway_project, test_config): + """Existing modules without gateways should work unchanged.""" + app = create_app( + config=test_config, + package_path=identity_gateway_project["modules_path"], + package_name=identity_gateway_project["package_name"], + logs_dir=identity_gateway_project["root"] / "logs", + enable_ui=False + ) + + with TestClient(app) as client: + response = client.get("/programs") + assert response.status_code == 200 + programs = response.json()["programs"] + assert len(programs) == 1 + assert programs[0]["name"] == "Echo" + + response = client.post("/Echo", json={"text": "test input"}) + assert response.status_code == 200 + assert response.json()["echo"] == "test input" From 30cfcb57aa9d6e609907b8485317edaf29011ae6 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 16 Dec 2025 16:19:27 -0500 Subject: [PATCH 05/19] WIP gateway working --- docs/gateways.md | 215 ++++++++++++++++++ mkdocs.yml | 1 + pyproject.toml | 1 + src/dspy_cli/commands/generate.py | 173 ++++++++++++++ src/dspy_cli/gateway/api.py | 2 +- src/dspy_cli/server/app.py | 37 ++- src/dspy_cli/server/scheduler.py | 90 ++++++++ .../code_templates/gateway_api.py.template | 51 +++++ .../code_templates/gateway_cron.py.template | 50 ++++ tests/gateway/test_gateway.py | 2 +- tests/server/test_scheduler.py | 140 ++++++++++++ uv.lock | 35 +++ 12 files changed, 792 insertions(+), 5 deletions(-) create mode 100644 docs/gateways.md create mode 100644 src/dspy_cli/server/scheduler.py create mode 100644 src/dspy_cli/templates/code_templates/gateway_api.py.template create mode 100644 src/dspy_cli/templates/code_templates/gateway_cron.py.template create mode 100644 tests/server/test_scheduler.py diff --git a/docs/gateways.md b/docs/gateways.md new file mode 100644 index 0000000..f1b1399 --- /dev/null +++ b/docs/gateways.md @@ -0,0 +1,215 @@ +# Gateways + +Gateways separate HTTP endpoint concerns from DSPy pipeline logic. They let you transform webhook payloads, customize API paths, and schedule background jobs—all without changing your module's `forward()` method. + +**Principle:** Pipelines should transform data, not load it. + +## Quick Example + +```python +from dspy_cli.gateway import APIGateway + +class WebhookGateway(APIGateway): + path = "/webhooks/slack" + + def to_pipeline_inputs(self, request): + # Transform Slack webhook payload to pipeline format + return {"text": request["event"]["text"]} + + def from_pipeline_output(self, output): + # Wrap output for Slack API + return {"response_type": "in_channel", "text": output["reply"]} + +class SlackResponder(dspy.Module): + gateway = WebhookGateway # <-- Gateway registration + + def forward(self, text: str) -> dspy.Prediction: + # Pure LLM logic - no Slack API knowledge + return self.predict(text=text) +``` + +Without gateways, this module would be tightly coupled to Slack's payload format. With gateways, the module stays focused on the LLM task. + +## Gateway Types + +### APIGateway + +Transform HTTP requests and responses. Use when you need to: + +- Accept webhook payloads with nested data structures +- Customize the HTTP endpoint path or method +- Wrap outputs in API-specific response formats +- Add or remove authentication requirements + +```python +from dspy_cli.gateway import APIGateway + +class MyGateway(APIGateway): + path = "/api/v2/analyze" # Custom path (default: /{ModuleName}) + method = "POST" # HTTP method (default: POST) + requires_auth = True # Require authentication (default: True) + request_model = MyRequestModel # Optional: Pydantic model for validation + response_model = MyResponseModel # Optional: Pydantic model for response + + def to_pipeline_inputs(self, request): + """Transform HTTP request to forward() kwargs.""" + return {"text": request["data"]["content"]} + + def from_pipeline_output(self, output): + """Transform pipeline output to HTTP response.""" + return {"status": "success", "result": output} +``` + +### IdentityGateway + +The default gateway when none is specified. Passes inputs and outputs unchanged for backward compatibility. + +```python +# These are equivalent: +class MyModule(dspy.Module): + def forward(self, text: str): ... + +class MyModule(dspy.Module): + gateway = IdentityGateway + def forward(self, text: str): ... +``` + +### CronGateway + +Schedule background pipeline execution. Use when you need to: + +- Poll external APIs on a schedule +- Process queued items periodically +- Run batch jobs at specific times + +```python +from dspy_cli.gateway import CronGateway + +class DiscordModerationGateway(CronGateway): + schedule = "*/5 * * * *" # Every 5 minutes + + async def get_pipeline_inputs(self) -> list[dict]: + """Fetch data from external source.""" + messages = await fetch_discord_messages() + return [{"message": m["content"], "author": m["author"]} for m in messages] + + async def on_complete(self, inputs: dict, output) -> None: + """Handle pipeline output.""" + if output["action"] == "delete": + await delete_discord_message(inputs["_meta"]["message_id"]) + +class ModerateMessage(dspy.Module): + gateway = DiscordModerationGateway + + def forward(self, message: str, author: str) -> dspy.Prediction: + return self.classifier(message=message, author=author) +``` + +## Common Patterns + +### Webhook Integration + +Accept webhooks from external services (Slack, Discord, GitHub, etc.): + +```python +class GitHubWebhookGateway(APIGateway): + path = "/webhooks/github" + requires_auth = False # GitHub uses signature verification + + def to_pipeline_inputs(self, request): + return { + "action": request["action"], + "issue_title": request["issue"]["title"], + "issue_body": request["issue"]["body"], + } + + def from_pipeline_output(self, output): + return {"processed": True, "label": output["suggested_label"]} +``` + +### API Versioning + +Expose the same module at multiple API versions: + +```python +class V1Gateway(APIGateway): + path = "/api/v1/summarize" + +class V2Gateway(APIGateway): + path = "/api/v2/summarize" + + def from_pipeline_output(self, output): + # V2 adds metadata + return {"summary": output["summary"], "version": "2.0"} +``` + +### Response Wrapping + +Wrap all responses in a consistent envelope: + +```python +class EnvelopeGateway(APIGateway): + def from_pipeline_output(self, output): + return { + "success": True, + "data": output, + "timestamp": datetime.now().isoformat(), + } +``` + +### Public Endpoints + +Create endpoints that don't require authentication: + +```python +class PublicGateway(APIGateway): + path = "/public/health-check" + requires_auth = False +``` + +## Gateway Discovery + +Gateways are discovered automatically when you add a `gateway` class attribute to your module: + +```python +class MyModule(dspy.Module): + gateway = MyCustomGateway # Must be a Gateway subclass, not an instance +``` + +If no gateway is specified, `IdentityGateway` is used automatically. + +## Cron Schedule Format + +CronGateway uses standard cron expressions: + +| Expression | Description | +|------------|-------------| +| `* * * * *` | Every minute | +| `*/5 * * * *` | Every 5 minutes | +| `0 * * * *` | Every hour | +| `0 0 * * *` | Daily at midnight | +| `0 9 * * 1-5` | Weekdays at 9 AM | +| `0 0 1 * *` | First day of each month | + +Format: `minute hour day-of-month month day-of-week` + +## Best Practices + +1. **Keep modules pure** — Modules should contain LLM logic only. Put API-specific transformations in gateways. + +2. **Use descriptive paths** — `/webhooks/slack` is clearer than `/slack`. + +3. **Default to requiring auth** — Set `requires_auth = False` only for public endpoints like webhooks with their own verification. + +4. **Handle errors in on_complete** — CronGateway's `on_complete` should handle failures gracefully since there's no HTTP response to report errors. + +5. **Pass metadata through** — Use `_meta` keys in inputs to carry IDs or context needed in `on_complete`: + + ```python + async def get_pipeline_inputs(self): + return [{"text": m["content"], "_meta": {"msg_id": m["id"]}}] + + async def on_complete(self, inputs, output): + msg_id = inputs["_meta"]["msg_id"] + await update_message(msg_id, output) + ``` diff --git a/mkdocs.yml b/mkdocs.yml index 69a3f08..546d799 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -99,6 +99,7 @@ nav: - new: commands/new.md - serve: commands/serve.md - generate: commands/generate.md + - Gateways: gateways.md - Deployment: deployment.md - Configuration: configuration.md - Use Cases: diff --git a/pyproject.toml b/pyproject.toml index 4c10514..425ea23 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -30,6 +30,7 @@ dependencies = [ "requests>=2.28", "fastmcp>=2.0.0", "asgi-lifespan>=2.0.0", + "apscheduler>=3.10.0", ] [project.optional-dependencies] diff --git a/src/dspy_cli/commands/generate.py b/src/dspy_cli/commands/generate.py index 7d4379d..11c3d0c 100644 --- a/src/dspy_cli/commands/generate.py +++ b/src/dspy_cli/commands/generate.py @@ -8,6 +8,19 @@ from dspy_cli.utils.signature_utils import parse_signature_string, to_class_name, build_forward_components from dspy_cli.utils.constants import MODULE_TYPES +GATEWAY_TYPES = { + "api": { + "template": "gateway_api.py.template", + "suffix": "gateway", + "description": "HTTP request/response transformation", + }, + "cron": { + "template": "gateway_cron.py.template", + "suffix": "cron_gateway", + "description": "Scheduled background execution", + }, +} + @click.group(name="generate") def generate(): @@ -283,6 +296,166 @@ def module(program_name, module): raise click.Abort() +@generate.command() +@click.argument("name") +@click.option( + "--type", + "-t", + "gateway_type", + default="api", + help=f"Gateway type. Available: {', '.join(GATEWAY_TYPES.keys())} (default: api)", +) +@click.option( + "--path", + "-p", + default=None, + help="Custom HTTP path for API gateway (default: /{Name})", +) +@click.option( + "--schedule", + "-s", + default="0 * * * *", + help="Cron schedule for cron gateway (default: hourly)", +) +@click.option( + "--public/--private", + default=False, + help="Whether the endpoint requires authentication (default: private/requires auth)", +) +def gateway(name, gateway_type, path, schedule, public): + """Generate a new gateway file. + + Creates a gateway file in src//gateways/ for transforming + HTTP requests/responses or scheduling background jobs. + + Examples: + # Create API gateway with default settings + dspy-cli g gateway webhook + + # Create API gateway with custom path + dspy-cli g gateway slack -p /webhooks/slack + + # Create public API gateway (no auth required) + dspy-cli g gateway health --public + + # Create cron gateway for scheduled execution + dspy-cli g gateway moderator -t cron -s "*/5 * * * *" + """ + click.echo(f"Generating gateway: {name}") + click.echo() + + # Validate we're in a DSPy project + if not validate_project_structure(): + click.echo(click.style("Error: Not in a valid DSPy project directory", fg="red")) + click.echo() + click.echo("Make sure you're in a directory created with 'dspy-cli new'") + click.echo("Required files: dspy.config.yaml, src/") + raise click.Abort() + + # Validate gateway type + if gateway_type not in GATEWAY_TYPES: + click.echo(click.style(f"Error: Unknown gateway type '{gateway_type}'", fg="red")) + click.echo() + click.echo(f"Available gateway types: {', '.join(GATEWAY_TYPES.keys())}") + raise click.Abort() + + # Find package directory + package_dir = find_package_directory() + if not package_dir: + click.echo(click.style("Error: Could not find package in src/", fg="red")) + raise click.Abort() + + package_name = package_dir.name + + # Convert dashes to underscores for valid Python identifier + original_name = name + name = name.replace("-", "_") + + if original_name != name: + click.echo(f" Note: Converted '{original_name}' to '{name}' for Python compatibility") + + # Validate name is valid Python identifier + if not name.replace("_", "").isalnum() or name[0].isdigit(): + click.echo(click.style(f"Error: Gateway name '{name}' is not a valid Python identifier", fg="red")) + raise click.Abort() + + gateway_info = GATEWAY_TYPES[gateway_type] + click.echo(f" Type: {gateway_type} ({gateway_info['description']})") + click.echo(f" Package: {package_name}") + + if gateway_type == "api": + effective_path = path if path else f"/{to_class_name(name)}" + click.echo(f" Path: {effective_path}") + click.echo(f" Auth required: {not public}") + else: + click.echo(f" Schedule: {schedule}") + + click.echo() + + try: + _create_gateway_file(package_dir, name, gateway_type, path, schedule, public) + + click.echo(click.style("✓ Gateway created successfully!", fg="green")) + click.echo() + file_name = f"{name.lower()}_{gateway_info['suffix']}.py" + click.echo(f"File created: gateways/{file_name}") + click.echo() + click.echo("Next steps:") + click.echo(" 1. Edit the gateway file to implement your transformation logic") + click.echo(" 2. Add 'gateway = YourGateway' to your module class") + + except Exception as e: + click.echo(click.style(f"Error creating gateway: {e}", fg="red")) + raise click.Abort() + + +def _create_gateway_file(package_dir, name, gateway_type, path, schedule, public): + """Create a gateway file.""" + from dspy_cli.templates import code_templates + + templates_dir = Path(code_templates.__file__).parent + gateway_info = GATEWAY_TYPES[gateway_type] + + # Ensure gateways directory exists + gateways_dir = package_dir / "gateways" + gateways_dir.mkdir(exist_ok=True) + + # Create __init__.py if it doesn't exist + init_file = gateways_dir / "__init__.py" + if not init_file.exists(): + init_file.write_text('"""Gateway definitions."""\n') + + # Generate file path + file_name = f"{name.lower()}_{gateway_info['suffix']}.py" + gateway_file_path = gateways_dir / file_name + + # Check if file already exists + if gateway_file_path.exists(): + click.echo(click.style(f"Warning: Gateway file already exists: {gateway_file_path}", fg="yellow")) + if not click.confirm("Overwrite?"): + raise click.Abort() + + # Generate class name + class_name = to_class_name(name) + "Gateway" + module_name = to_class_name(name) + + # Default path if not specified + effective_path = path if path else f"/{module_name}" + + # Load and format template + template = (templates_dir / gateway_info["template"]).read_text() + content = template.format( + module_name=module_name, + class_name=class_name, + path=effective_path, + schedule=schedule, + requires_auth=str(not public), + ) + + gateway_file_path.write_text(content) + click.echo(f" Created: gateways/{file_name}") + + def _create_signature_file(package_dir, program_name, signature_str, signature_fields): """Create a signature file for the program.""" from dspy_cli.templates import code_templates diff --git a/src/dspy_cli/gateway/api.py b/src/dspy_cli/gateway/api.py index 9ba0b40..dd35e5d 100644 --- a/src/dspy_cli/gateway/api.py +++ b/src/dspy_cli/gateway/api.py @@ -33,7 +33,7 @@ def from_pipeline_output(self, output): response_model: Optional[Type[BaseModel]] = None path: Optional[str] = None method: str = "POST" - requires_auth: bool = False + requires_auth: bool = True def to_pipeline_inputs(self, request: Any) -> Dict[str, Any]: """Transform HTTP request to forward() kwargs. diff --git a/src/dspy_cli/server/app.py b/src/dspy_cli/server/app.py index b09c911..2af88c9 100644 --- a/src/dspy_cli/server/app.py +++ b/src/dspy_cli/server/app.py @@ -9,9 +9,12 @@ from dspy_cli.config import get_model_config, get_program_model from dspy_cli.discovery import discover_modules +from dspy_cli.discovery.gateway_finder import get_gateway_for_module, is_cron_gateway +from dspy_cli.gateway import APIGateway, CronGateway from dspy_cli.server.logging import setup_logging from dspy_cli.server.metrics import get_all_metrics, get_program_metrics_cached from dspy_cli.server.routes import create_program_routes +from dspy_cli.server.scheduler import GatewayScheduler from dspy_cli.utils.openapi import enhance_openapi_metadata, create_openapi_extensions logger = logging.getLogger(__name__) @@ -89,6 +92,10 @@ def create_app( logger.info(f"Created LM for program: {module.name} (model: {model_alias})") + # Initialize scheduler for cron gateways + scheduler = GatewayScheduler(logs_dir) + app.state.scheduler = scheduler + # Create routes for each discovered module for module in modules: # Get the LM instance for this program @@ -96,9 +103,23 @@ def create_app( model_alias = get_program_model(config, module.name) model_config = get_model_config(config, model_alias) - create_program_routes(app, module, lm, model_config, config) - - logger.info(f"Registered program: {module.name} (model: {model_alias})") + # Get gateway and route by type + gateway = get_gateway_for_module(module) + + if is_cron_gateway(gateway): + # Register with scheduler instead of creating HTTP route + scheduler.register_cron_gateway( + module=module, + gateway=gateway, + lm=lm, + model_name=model_config.get("model", "unknown"), + ) + logger.info(f"Registered cron program: {module.name} (schedule: {gateway.schedule})") + elif isinstance(gateway, APIGateway): + create_program_routes(app, module, lm, model_config, config, gateway=gateway) + logger.info(f"Registered program: {module.name} (model: {model_alias})") + else: + logger.warning(f"Unknown gateway type for {module.name}: {type(gateway)}") # Add programs list endpoint @app.get("/programs") @@ -225,6 +246,16 @@ async def program_metrics(program_name: str): app.add_middleware(AuthMiddleware, token=token, open_paths=open_paths) logger.info("Authentication enabled") + # Add scheduler lifecycle events if any cron jobs registered + if scheduler.job_count > 0: + @app.on_event("startup") + async def _start_scheduler(): + scheduler.start() + + @app.on_event("shutdown") + async def _stop_scheduler(): + scheduler.shutdown() + return app diff --git a/src/dspy_cli/server/scheduler.py b/src/dspy_cli/server/scheduler.py new file mode 100644 index 0000000..38ea75a --- /dev/null +++ b/src/dspy_cli/server/scheduler.py @@ -0,0 +1,90 @@ +"""Scheduler for cron-based gateway execution.""" + +import logging +from pathlib import Path +from typing import Dict + +import dspy +from apscheduler.schedulers.asyncio import AsyncIOScheduler +from apscheduler.triggers.cron import CronTrigger + +from dspy_cli.discovery import DiscoveredModule +from dspy_cli.gateway import CronGateway +from dspy_cli.server.execution import _convert_dspy_types, execute_pipeline + +logger = logging.getLogger(__name__) + + +class GatewayScheduler: + """Manages cron-based gateway execution.""" + + def __init__(self, logs_dir: Path): + self.logs_dir = logs_dir + self.scheduler = AsyncIOScheduler() + self._jobs: Dict[str, str] = {} + + def register_cron_gateway( + self, + module: DiscoveredModule, + gateway: CronGateway, + lm: dspy.LM, + model_name: str, + ): + """Register a CronGateway for scheduled execution. + + Args: + module: DiscoveredModule metadata + gateway: CronGateway instance with schedule and callbacks + lm: Language model instance for this program + model_name: Model name for logging + """ + program_name = module.name + + async def execute_job(): + logger.info(f"CronGateway: executing {program_name}") + instance = module.instantiate() + + try: + inputs_list = await gateway.get_pipeline_inputs() + except Exception as e: + logger.error(f"CronGateway error fetching inputs for {program_name}: {e}", exc_info=True) + return + + for raw_inputs in inputs_list: + inputs = _convert_dspy_types(raw_inputs, module) + try: + output = await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name=model_name, + program_name=program_name, + inputs=inputs, + logs_dir=self.logs_dir, + ) + await gateway.on_complete(raw_inputs, output) + except Exception as e: + logger.error(f"CronGateway error for {program_name}: {e}", exc_info=True) + + trigger = CronTrigger.from_crontab(gateway.schedule) + job_id = f"cron_{program_name}" + self.scheduler.add_job(execute_job, trigger, id=job_id) + self._jobs[program_name] = job_id + logger.info(f"Registered cron gateway: {program_name} schedule={gateway.schedule}") + + def start(self): + """Start the scheduler.""" + if not self.scheduler.running: + self.scheduler.start() + logger.info("GatewayScheduler started") + + def shutdown(self): + """Shutdown the scheduler.""" + if self.scheduler.running: + self.scheduler.shutdown(wait=False) + logger.info("GatewayScheduler shutdown") + + @property + def job_count(self) -> int: + """Number of registered cron jobs.""" + return len(self._jobs) diff --git a/src/dspy_cli/templates/code_templates/gateway_api.py.template b/src/dspy_cli/templates/code_templates/gateway_api.py.template new file mode 100644 index 0000000..8ab7890 --- /dev/null +++ b/src/dspy_cli/templates/code_templates/gateway_api.py.template @@ -0,0 +1,51 @@ +"""API Gateway for {module_name}.""" + +from typing import Any, Dict + +from dspy_cli.gateway import APIGateway + + +class {class_name}(APIGateway): + """Transform HTTP requests/responses for {module_name}. + + Customize this gateway to: + - Transform incoming webhook payloads to pipeline inputs + - Wrap pipeline outputs in API-specific response formats + - Set custom paths, methods, or authentication requirements + """ + + path = "{path}" + method = "POST" + requires_auth = {requires_auth} + + def to_pipeline_inputs(self, request: Any) -> Dict[str, Any]: + """Transform HTTP request to forward() kwargs. + + Args: + request: The HTTP request body (dict or Pydantic model) + + Returns: + Dictionary of kwargs to pass to the module's forward() + """ + # Example: Extract from nested payload + # return {{"text": request["data"]["content"]}} + + # Default: pass through unchanged + if hasattr(request, "model_dump"): + return request.model_dump() + return dict(request) if request else {{}} + + def from_pipeline_output(self, output: Any) -> Any: + """Transform pipeline output to HTTP response. + + Args: + output: The normalized output dict from the pipeline + + Returns: + The HTTP response body (will be serialized to JSON) + """ + # Example: Wrap in response envelope + # return {{"status": "success", "result": output}} + + # Default: pass through unchanged + return output diff --git a/src/dspy_cli/templates/code_templates/gateway_cron.py.template b/src/dspy_cli/templates/code_templates/gateway_cron.py.template new file mode 100644 index 0000000..0e011b5 --- /dev/null +++ b/src/dspy_cli/templates/code_templates/gateway_cron.py.template @@ -0,0 +1,50 @@ +"""Cron Gateway for {module_name}.""" + +from typing import Any, Dict, List + +from dspy_cli.gateway import CronGateway + + +class {class_name}(CronGateway): + """Schedule periodic execution of {module_name}. + + This gateway fetches data from external sources on a schedule + and processes it through the pipeline. + """ + + schedule = "{schedule}" # Cron expression: minute hour day-of-month month day-of-week + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + """Fetch data to process from external source. + + Called on each scheduled execution. Returns a list of input + dictionaries, each processed separately through the pipeline. + + Returns: + List of input dicts, each passed to the module's forward() + """ + # Example: Fetch from an API + # messages = await fetch_pending_messages() + # return [ + # {{"text": m["content"], "_meta": {{"id": m["id"]}}}} + # for m in messages + # ] + + # Placeholder implementation + return [] + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + """Handle pipeline output after processing. + + Called once per input after successful pipeline execution. + Use this to update external systems, send notifications, etc. + + Args: + inputs: The original input dict (including any _meta keys) + output: The pipeline output dict + """ + # Example: Update external system based on output + # if output.get("action") == "flag": + # await flag_message(inputs["_meta"]["id"]) + + pass diff --git a/tests/gateway/test_gateway.py b/tests/gateway/test_gateway.py index ac952b7..2255c56 100644 --- a/tests/gateway/test_gateway.py +++ b/tests/gateway/test_gateway.py @@ -63,7 +63,7 @@ def test_default_attributes(self): assert gateway.response_model is None assert gateway.path is None assert gateway.method == "POST" - assert gateway.requires_auth is False + assert gateway.requires_auth is True class TestAPIGateway: diff --git a/tests/server/test_scheduler.py b/tests/server/test_scheduler.py new file mode 100644 index 0000000..03b1889 --- /dev/null +++ b/tests/server/test_scheduler.py @@ -0,0 +1,140 @@ +"""Tests for GatewayScheduler.""" + +import asyncio +from pathlib import Path +from typing import Any, Dict, List +from unittest.mock import MagicMock, AsyncMock, patch + +import dspy +import pytest + +from dspy_cli.discovery import DiscoveredModule +from dspy_cli.gateway import CronGateway +from dspy_cli.server.scheduler import GatewayScheduler + + +class MockCronGateway(CronGateway): + """Test CronGateway implementation.""" + + schedule = "*/5 * * * *" + + def __init__(self): + self.inputs_to_return: List[Dict[str, Any]] = [] + self.completed_calls: List[tuple] = [] + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return self.inputs_to_return + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + self.completed_calls.append((inputs, output)) + + +@pytest.fixture +def mock_module(): + """Create a mock DiscoveredModule.""" + module = MagicMock(spec=DiscoveredModule) + module.name = "TestModule" + module.is_forward_typed = False + module.forward_input_fields = None + + mock_instance = MagicMock() + mock_instance.return_value = {"result": "test_output"} + module.instantiate.return_value = mock_instance + + return module + + +@pytest.fixture +def mock_lm(): + """Create a mock LM.""" + lm = MagicMock(spec=dspy.LM) + lm.copy.return_value = lm + lm.history = [] + return lm + + +class TestGatewayScheduler: + """Tests for GatewayScheduler.""" + + def test_init(self, tmp_path): + """Scheduler initializes with empty jobs.""" + scheduler = GatewayScheduler(logs_dir=tmp_path) + + assert scheduler.job_count == 0 + assert scheduler.logs_dir == tmp_path + + def test_register_cron_gateway(self, tmp_path, mock_module, mock_lm): + """Registering a cron gateway adds a job.""" + scheduler = GatewayScheduler(logs_dir=tmp_path) + gateway = MockCronGateway() + + scheduler.register_cron_gateway( + module=mock_module, + gateway=gateway, + lm=mock_lm, + model_name="test-model", + ) + + assert scheduler.job_count == 1 + assert "TestModule" in scheduler._jobs + + def test_multiple_registrations(self, tmp_path, mock_lm): + """Multiple gateways can be registered.""" + scheduler = GatewayScheduler(logs_dir=tmp_path) + + for i in range(3): + module = MagicMock(spec=DiscoveredModule) + module.name = f"Module{i}" + module.is_forward_typed = False + module.forward_input_fields = None + module.instantiate.return_value = MagicMock(return_value={"result": "ok"}) + + gateway = MockCronGateway() + scheduler.register_cron_gateway( + module=module, + gateway=gateway, + lm=mock_lm, + model_name="test-model", + ) + + assert scheduler.job_count == 3 + + def test_shutdown_when_not_running(self, tmp_path): + """Shutdown is safe when scheduler not running.""" + scheduler = GatewayScheduler(logs_dir=tmp_path) + scheduler.shutdown() + + +class TestCronJobExecution: + """Tests for cron job execution flow.""" + + def test_job_is_registered(self, tmp_path, mock_module, mock_lm): + """Job should be registered with correct ID.""" + scheduler = GatewayScheduler(logs_dir=tmp_path) + gateway = MockCronGateway() + gateway.inputs_to_return = [{"text": "test"}] + + scheduler.register_cron_gateway( + module=mock_module, + gateway=gateway, + lm=mock_lm, + model_name="test-model", + ) + + job = scheduler.scheduler.get_job("cron_TestModule") + assert job is not None + + def test_job_handles_empty_inputs(self, tmp_path, mock_module, mock_lm): + """Job should handle empty input list gracefully.""" + scheduler = GatewayScheduler(logs_dir=tmp_path) + gateway = MockCronGateway() + gateway.inputs_to_return = [] + + scheduler.register_cron_gateway( + module=mock_module, + gateway=gateway, + lm=mock_lm, + model_name="test-model", + ) + + assert scheduler.job_count == 1 diff --git a/uv.lock b/uv.lock index f093ae5..d3852cd 100644 --- a/uv.lock +++ b/uv.lock @@ -163,6 +163,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/15/b3/9b1a8074496371342ec1e796a96f99c82c945a339cd81a8e73de28b4cf9e/anyio-4.11.0-py3-none-any.whl", hash = "sha256:0287e96f4d26d4149305414d4e3bc32f0dcd0862365a4bddea19d7a1ec38c4fc", size = 109097, upload-time = "2025-09-23T09:19:10.601Z" }, ] +[[package]] +name = "apscheduler" +version = "3.11.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "tzlocal" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/d0/81/192db4f8471de5bc1f0d098783decffb1e6e69c4f8b4bc6711094691950b/apscheduler-3.11.1.tar.gz", hash = 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[PATCH 06/19] initial discord bot example --- examples/discord-mod/.dockerignore | 7 + examples/discord-mod/.gitignore | 47 + examples/discord-mod/.python-version | 1 + examples/discord-mod/Dockerfile | 15 + examples/discord-mod/README.md | 140 + examples/discord-mod/dspy.config.yaml | 20 + examples/discord-mod/pyproject.toml | 31 + .../scripts/test_discord_integration.py | 108 + examples/discord-mod/scripts/test_dry_run.py | 78 + examples/discord-mod/scripts/test_with_llm.py | 101 + .../discord-mod/src/discord_mod/__init__.py | 1 + .../src/discord_mod/gateways/__init__.py | 5 + .../gateways/job_posting_gateway.py | 197 ++ .../src/discord_mod/metrics/__init__.py | 0 .../src/discord_mod/modules/__init__.py | 0 .../modules/classify_job_posting.py | 61 + .../src/discord_mod/optimizers/__init__.py | 0 .../src/discord_mod/signatures/__init__.py | 0 .../src/discord_mod/utils/__init__.py | 0 .../src/discord_mod/utils/discord_client.py | 136 + examples/discord-mod/uv.lock | 2685 +++++++++++++++++ 21 files changed, 3633 insertions(+) create mode 100644 examples/discord-mod/.dockerignore create mode 100644 examples/discord-mod/.gitignore create mode 100644 examples/discord-mod/.python-version create mode 100644 examples/discord-mod/Dockerfile create mode 100644 examples/discord-mod/README.md create mode 100644 examples/discord-mod/dspy.config.yaml create mode 100644 examples/discord-mod/pyproject.toml create mode 100644 examples/discord-mod/scripts/test_discord_integration.py create mode 100755 examples/discord-mod/scripts/test_dry_run.py create mode 100644 examples/discord-mod/scripts/test_with_llm.py create mode 100644 examples/discord-mod/src/discord_mod/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/gateways/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py create mode 100644 examples/discord-mod/src/discord_mod/metrics/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/modules/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/modules/classify_job_posting.py create mode 100644 examples/discord-mod/src/discord_mod/optimizers/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/signatures/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/utils/__init__.py create mode 100644 examples/discord-mod/src/discord_mod/utils/discord_client.py create mode 100644 examples/discord-mod/uv.lock diff --git a/examples/discord-mod/.dockerignore b/examples/discord-mod/.dockerignore new file mode 100644 index 0000000..9ca07ae --- /dev/null +++ b/examples/discord-mod/.dockerignore @@ -0,0 +1,7 @@ +.git +.env +__pycache__ +*.pyc +.vscode +.mypy_cache +logs/ \ No newline at end of file diff --git a/examples/discord-mod/.gitignore b/examples/discord-mod/.gitignore new file mode 100644 index 0000000..e46029a --- /dev/null +++ b/examples/discord-mod/.gitignore @@ -0,0 +1,47 @@ +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg + +# Virtual environments +venv/ +env/ +ENV/ +.venv + +# Environment variables +.env +.env.local + +# IDE +.vscode/ +.idea/ +*.swp +*.swo +*~ + +# DSPy +logs/ +*.log +data/cache/ + +# OS +.DS_Store +Thumbs.db diff --git a/examples/discord-mod/.python-version b/examples/discord-mod/.python-version new file mode 100644 index 0000000..24ee5b1 --- /dev/null +++ b/examples/discord-mod/.python-version @@ -0,0 +1 @@ +3.13 diff --git a/examples/discord-mod/Dockerfile b/examples/discord-mod/Dockerfile new file mode 100644 index 0000000..be079d0 --- /dev/null +++ b/examples/discord-mod/Dockerfile @@ -0,0 +1,15 @@ +FROM python:3.11-slim + +ENV PYTHONDONTWRITEBYTECODE=1 +ENV PYTHONUNBUFFERED=1 +ENV XDG_CACHE_HOME=/tmp/.cache + +COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv + +COPY . . +RUN uv sync --no-dev + +EXPOSE 8000 + +CMD ["uv", "run", "dspy-cli", "serve", "--host", "0.0.0.0", "--port", "8000", "--auth", "--no-reload"] + diff --git a/examples/discord-mod/README.md b/examples/discord-mod/README.md new file mode 100644 index 0000000..8578243 --- /dev/null +++ b/examples/discord-mod/README.md @@ -0,0 +1,140 @@ +# Discord Moderation Bot + +A DSPy project that demonstrates the **Gateway pattern** for separating Discord API concerns from LLM pipeline logic. + +## Overview + +This bot monitors Discord channels for job postings and automatically: +- **Classifies** messages as job postings, job-seeking, or general chat +- **Moves** job posts to a dedicated jobs channel +- **Flags** suspicious content for manual review +- **Deletes** spam or rule violations + +### The Gateway Pattern + +The key insight is that **pipelines should transform data, not load it**: + +``` +┌─────────────────────────────────────────────────────────────────┐ +│ JobPostingGateway │ +│ ┌──────────────────┐ ┌──────────────────────────┐ │ +│ │ get_pipeline_ │ │ on_complete() │ │ +│ │ inputs() │ │ │ │ +│ │ │ │ • Move to jobs channel │ │ +│ │ • Fetch msgs │ │ • Send DM to author │ │ +│ │ • Filter bots │ │ • Add reaction flag │ │ +│ │ • Extract data │ │ • Delete spam │ │ +│ └────────┬─────────┘ └──────────▲───────────────┘ │ +└───────────│────────────────────────────────────│────────────────┘ + │ │ + ▼ │ +┌─────────────────────────────────────────────────────────────────┐ +│ ClassifyJobPosting │ +│ │ +│ Pure LLM logic - no Discord API knowledge │ +│ │ +│ Input: message, author, channel_name │ +│ Output: intent, action, reason │ +└─────────────────────────────────────────────────────────────────┘ +``` + +## Project Structure + +``` +src/discord_mod/ +├── modules/ +│ └── classify_job_posting.py # Pure LLM classification logic +├── gateways/ +│ └── job_posting_gateway.py # Discord API interactions (CronGateway) +└── utils/ + └── discord_client.py # Discord REST API client +``` + +## Setup + +1. **Create a Discord bot** at https://discord.com/developers/applications + +2. **Configure environment variables** in `.env`: + ```bash + # Discord bot token + DISCORD_BOT_TOKEN=your-bot-token + + # Channels to monitor (comma-separated) + DISCORD_CHANNEL_IDS=123456789,987654321 + + # Channel to move job posts to + DISCORD_JOBS_CHANNEL_ID=111222333 + + # LLM API key + OPENAI_API_KEY=your-openai-key + ``` + +3. **Install dependencies**: + ```bash + uv sync + ``` + +## Running + +Start the server with cron scheduling enabled: + +```bash +dspy-cli serve +``` + +The `ClassifyJobPosting` module uses a `CronGateway` with `schedule = "*/5 * * * *"`, so it will: +1. Poll the configured channels every 5 minutes +2. Classify each new message +3. Take the appropriate moderation action + +## How It Works + +### The Module (Pure LLM Logic) + +```python +class ClassifyJobPosting(dspy.Module): + gateway = JobPostingGateway # <-- Gateway registration + + def forward(self, message: str, author: str, channel_name: str): + # Only LLM classification logic here + return self.classifier(message=message, author=author, channel_name=channel_name) +``` + +### The Gateway (Discord API Concerns) + +```python +class JobPostingGateway(CronGateway): + schedule = "*/5 * * * *" + + async def get_pipeline_inputs(self): + # Fetch from Discord API, transform to pipeline inputs + messages = await self.client.get_recent_messages(channel_id) + return [{"message": m["content"], "_meta": {"message_id": m["id"]}} ...] + + async def on_complete(self, inputs, output): + # Take action based on classification + if output["action"] == "move": + await self.client.send_message(jobs_channel, inputs["message"]) + await self.client.delete_message(inputs["_meta"]["message_id"]) +``` + +## Classification Actions + +| Action | Description | +|--------|-------------| +| `allow` | Message is appropriate for the channel | +| `move` | Job posting should be in the jobs channel | +| `flag` | Add ⚠️ reaction for manual review | +| `delete` | Remove spam or rule violations, DM the author | + +## Testing + +Run tests: +```bash +pytest +``` + +## Learn More + +- [Gateway Documentation](https://dspy-cli.readthedocs.io/gateways/) +- [DSPy Documentation](https://dspy.ai) diff --git a/examples/discord-mod/dspy.config.yaml b/examples/discord-mod/dspy.config.yaml new file mode 100644 index 0000000..e53c0b5 --- /dev/null +++ b/examples/discord-mod/dspy.config.yaml @@ -0,0 +1,20 @@ +# DSPy Configuration +# Define your language models and their settings here + +app_id: discord-mod +models: + # The default model to use if no per-program override is specified + default: openai:gpt-5-mini + + # Model registry - define all available models here + registry: + openai:gpt-5-mini: + model: openai/gpt-5-mini + model_type: chat + max_tokens: 16000 + temperature: 1.0 + env: OPENAI_API_KEY + +# Optional: Override the model for specific programs +# program_models: +# MySpecialProgram: openai:gpt-5-mini diff --git a/examples/discord-mod/pyproject.toml b/examples/discord-mod/pyproject.toml new file mode 100644 index 0000000..22eff64 --- /dev/null +++ b/examples/discord-mod/pyproject.toml @@ -0,0 +1,31 @@ +[build-system] +requires = ["setuptools>=61.0", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "discord-mod" +version = "0.1.0" +description = "A DSPy project" +readme = "README.md" +requires-python = ">=3.13" +dependencies = [ + "audioop-lts", + "dspy-ai>=3.0.3", + "dspy-cli", + "httpx>=0.27.0", + "py-cord[voice]>=2.6.1", + "python-dotenv>=1.2.1", +] + +[project.optional-dependencies] +dev = [ + "pytest>=7.0", + "pytest-asyncio>=0.21", +] + +# Use local editable install of dspy-cli for development +[tool.uv.sources] +dspy-cli = { path = "../..", editable = true } + +[tool.setuptools.packages.find] +where = ["src"] diff --git a/examples/discord-mod/scripts/test_discord_integration.py b/examples/discord-mod/scripts/test_discord_integration.py new file mode 100644 index 0000000..90ee807 --- /dev/null +++ b/examples/discord-mod/scripts/test_discord_integration.py @@ -0,0 +1,108 @@ +#!/usr/bin/env python +"""Test Discord API integration with mocked LLM responses. + +Tests the gateway's Discord interactions (fetch + actions) without LLM calls. + +Usage: + # Dry run with sample data (no Discord API calls) + DRY_RUN=true python scripts/test_discord_integration.py + + # Test real Discord fetch, dry run actions + DISCORD_BOT_TOKEN=... DISCORD_CHANNEL_IDS=123,456 DRY_RUN=true python scripts/test_discord_integration.py + + # Test real Discord fetch AND actions (careful!) + DISCORD_BOT_TOKEN=... DISCORD_CHANNEL_IDS=123,456 python scripts/test_discord_integration.py +""" + +import asyncio +import json +import logging +import os +from datetime import datetime + +from dotenv import load_dotenv + +load_dotenv() + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", +) +logger = logging.getLogger(__name__) + +# Mocked LLM responses - maps message content patterns to outputs +MOCK_CLASSIFICATIONS = { + "hiring": {"intent": "post_job", "action": "move", "reason": "Job posting in general channel"}, + "looking for work": {"intent": "seek_job", "action": "move", "reason": "Job seeking in general channel"}, + "MAKE $": {"intent": "other", "action": "delete", "reason": "Spam detected"}, + "_default": {"intent": "other", "action": "allow", "reason": "Normal conversation"}, +} + + +def mock_classify(message: str) -> dict: + """Return mocked classification based on message content.""" + message_lower = message.lower() + for pattern, result in MOCK_CLASSIFICATIONS.items(): + if pattern.lower() in message_lower: + return result + return MOCK_CLASSIFICATIONS["_default"] + + +async def main(): + dry_run = os.environ.get("DRY_RUN", "").lower() == "true" + has_token = bool(os.environ.get("DISCORD_BOT_TOKEN")) + + logger.info("=" * 60) + logger.info("Discord Integration Test") + logger.info(f" DRY_RUN: {dry_run}") + logger.info(f" Has Discord token: {has_token}") + logger.info("=" * 60) + + # Import gateway + from discord_mod.gateways.job_posting_gateway import JobPostingGateway + + gateway = JobPostingGateway() + + # Test 1: Fetch messages + logger.info("\n[TEST 1] Fetching messages...") + inputs_list = await gateway.get_pipeline_inputs() + logger.info(f"Fetched {len(inputs_list)} messages") + + # Export to JSON for inspection + output_file = f"fetched_messages_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json" + with open(output_file, "w", encoding="utf-8") as f: + json.dump(inputs_list, f, indent=2, ensure_ascii=False) + logger.info(f"Exported messages to {output_file}") + + if not inputs_list: + logger.warning("No messages to process. Check DISCORD_CHANNEL_IDS or use DRY_RUN=true for samples.") + return + + # Test 2: Process each message with mocked LLM + logger.info("\n[TEST 2] Processing messages with mocked classifier...") + for i, inputs in enumerate(inputs_list, 1): + logger.info(f"\n--- Message {i}/{len(inputs_list)} ---") + logger.info(f"Author: {inputs['author']}") + logger.info(f"Channel: {inputs['channel_name']}") + logger.info(f"Message: {inputs['message'][:80]}...") + + # Mock the LLM classification + output = mock_classify(inputs["message"]) + logger.info(f"[MOCKED] Intent: {output['intent']}, Action: {output['action']}") + logger.info(f"[MOCKED] Reason: {output['reason']}") + + # Test 3: Execute action (respects DRY_RUN) + await gateway.on_complete(inputs, output) + + # Test 4: Summary + logger.info("\n" + "=" * 60) + logger.info("Integration test complete") + if dry_run: + logger.info("DRY_RUN was enabled - no Discord actions were executed") + else: + logger.info("⚠️ LIVE MODE - actions were executed on Discord!") + logger.info("=" * 60) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/discord-mod/scripts/test_dry_run.py b/examples/discord-mod/scripts/test_dry_run.py new file mode 100755 index 0000000..c8f5c8e --- /dev/null +++ b/examples/discord-mod/scripts/test_dry_run.py @@ -0,0 +1,78 @@ +#!/usr/bin/env python +"""Test the job posting classifier in dry run mode. + +Usage: + DRY_RUN=true python scripts/test_dry_run.py +""" + +import asyncio +import logging +import os +import sys + +# Ensure DRY_RUN is set before any imports +os.environ.setdefault("DRY_RUN", "true") + +import dspy +from dotenv import load_dotenv + +load_dotenv() + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", +) +logger = logging.getLogger(__name__) + + +async def main(): + # Configure the LM + lm = dspy.LM( + model="openai/gpt-4o-mini", + api_key=os.environ.get("OPENAI_API_KEY"), + ) + dspy.configure(lm=lm) + + # Import after dspy is configured + from discord_mod.gateways.job_posting_gateway import JobPostingGateway + from discord_mod.modules.classify_job_posting import ClassifyJobPosting + + # Create instances + gateway = JobPostingGateway() + classifier = ClassifyJobPosting() + + logger.info("=" * 60) + logger.info("Running job posting classifier in DRY RUN mode") + logger.info("=" * 60) + + # Get sample inputs (dry run mode returns test data) + inputs_list = await gateway.get_pipeline_inputs() + + for i, inputs in enumerate(inputs_list, 1): + logger.info(f"\n--- Message {i}/{len(inputs_list)} ---") + logger.info(f"Author: {inputs['author']}") + logger.info(f"Channel: {inputs['channel_name']}") + logger.info(f"Message: {inputs['message'][:100]}...") + + # Run classification + result = classifier( + message=inputs["message"], + author=inputs["author"], + channel_name=inputs["channel_name"], + ) + + output = result.toDict() + logger.info(f"Intent: {output.get('intent')}") + logger.info(f"Action: {output.get('action')}") + logger.info(f"Reason: {output.get('reason')}") + + # Log what would happen (dry run) + await gateway.on_complete(inputs, output) + + logger.info("\n" + "=" * 60) + logger.info("Dry run complete - no Discord actions were taken") + logger.info("=" * 60) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/discord-mod/scripts/test_with_llm.py b/examples/discord-mod/scripts/test_with_llm.py new file mode 100644 index 0000000..186509b --- /dev/null +++ b/examples/discord-mod/scripts/test_with_llm.py @@ -0,0 +1,101 @@ +#!/usr/bin/env python +"""Test Discord integration with real LLM classification. + +Usage: + DRY_RUN=true python scripts/test_with_llm.py +""" + +import asyncio +import json +import logging +import os +from datetime import datetime + +from dotenv import load_dotenv + +load_dotenv() + +logging.basicConfig( + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", +) +logger = logging.getLogger(__name__) + + +async def main(): + import dspy + + # Configure LM + lm = dspy.LM( + model="openai/gpt-4o-mini", + api_key=os.environ.get("OPENAI_API_KEY"), + ) + dspy.configure(lm=lm) + + from discord_mod.gateways.job_posting_gateway import JobPostingGateway + from discord_mod.modules.classify_job_posting import ClassifyJobPosting + + dry_run = os.environ.get("DRY_RUN", "").lower() == "true" + + logger.info("=" * 60) + logger.info("Discord + LLM Integration Test") + logger.info(f" DRY_RUN: {dry_run}") + logger.info("=" * 60) + + gateway = JobPostingGateway() + classifier = ClassifyJobPosting() + + # Fetch messages + logger.info("\n[FETCH] Getting messages...") + inputs_list = await gateway.get_pipeline_inputs() + logger.info(f"Fetched {len(inputs_list)} messages") + + # Export + output_file = f"classified_messages_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json" + results = [] + + for i, inputs in enumerate(inputs_list, 1): + logger.info(f"\n--- Message {i}/{len(inputs_list)} ---") + logger.info(f"Author: {inputs['author']}") + logger.info(f"Message: {inputs['message'][:100]}...") + + # Real LLM classification + result = classifier( + message=inputs["message"], + author=inputs["author"], + channel_name=inputs["channel_name"], + ) + output = result.toDict() + + logger.info(f"[LLM] Intent: {output.get('intent')}") + logger.info(f"[LLM] Action: {output.get('action')}") + logger.info(f"[LLM] Reason: {output.get('reason')}") + + results.append({ + **inputs, + "classification": output, + }) + + # Execute action (respects DRY_RUN) + await gateway.on_complete(inputs, output) + + # Save results + with open(output_file, "w", encoding="utf-8") as f: + json.dump(results, f, indent=2, ensure_ascii=False) + logger.info(f"\nExported results to {output_file}") + + # Summary + actions = {} + for r in results: + action = r["classification"].get("action", "unknown") + actions[action] = actions.get(action, 0) + 1 + + logger.info("\n" + "=" * 60) + logger.info("Summary:") + for action, count in sorted(actions.items()): + logger.info(f" {action}: {count}") + logger.info("=" * 60) + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/examples/discord-mod/src/discord_mod/__init__.py b/examples/discord-mod/src/discord_mod/__init__.py new file mode 100644 index 0000000..126dac0 --- /dev/null +++ b/examples/discord-mod/src/discord_mod/__init__.py @@ -0,0 +1 @@ +"""DSPy project: discord_mod.""" diff --git a/examples/discord-mod/src/discord_mod/gateways/__init__.py b/examples/discord-mod/src/discord_mod/gateways/__init__.py new file mode 100644 index 0000000..bc4c9e1 --- /dev/null +++ b/examples/discord-mod/src/discord_mod/gateways/__init__.py @@ -0,0 +1,5 @@ +"""Discord moderation gateways.""" + +from discord_mod.gateways.job_posting_gateway import JobPostingGateway + +__all__ = ["JobPostingGateway"] diff --git a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py new file mode 100644 index 0000000..55fc57a --- /dev/null +++ b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py @@ -0,0 +1,197 @@ +"""CronGateway for Discord job posting moderation. + +This gateway handles all Discord API interactions: +- Fetching new messages from monitored channels +- Taking moderation actions based on classification results + +The pipeline module (ClassifyJobPosting) stays pure - it only knows about +message content, not Discord API details. +""" + +import logging +import os +from typing import Any, Dict, List + +from dspy_cli.gateway import CronGateway + +from discord_mod.utils.discord_client import DiscordClient + +logger = logging.getLogger(__name__) + + +class JobPostingGateway(CronGateway): + """Poll Discord channels and moderate job postings. + + Configuration via environment variables: + DISCORD_BOT_TOKEN: Bot authentication token + DISCORD_CHANNEL_IDS: Comma-separated channel IDs to monitor + DISCORD_JOBS_CHANNEL_ID: Channel ID to move job posts to + DRY_RUN: Set to "true" to log actions without executing them + """ + + schedule = "*/5 * * * *" # Every 5 minutes + + def __init__(self): + self.dry_run = os.environ.get("DRY_RUN", "").lower() == "true" + self.client = DiscordClient( + token=os.environ.get("DISCORD_BOT_TOKEN", ""), + ) + self.channel_ids = os.environ.get("DISCORD_CHANNEL_IDS", "").split(",") + self.jobs_channel_id = os.environ.get("DISCORD_JOBS_CHANNEL_ID") + + if self.dry_run: + logger.info("DRY_RUN mode enabled - no actions will be executed") + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + """Fetch recent unprocessed messages from monitored channels.""" + if self.dry_run: + return self._get_sample_inputs() + + inputs = [] + + for channel_id in self.channel_ids: + if not channel_id.strip(): + continue + + messages = await self.client.get_recent_messages( + channel_id=channel_id.strip(), + limit=50, + ) + + for msg in messages: + if msg.get("author", {}).get("bot", False): + continue + + inputs.append({ + "message": msg["content"], + "author": msg["author"]["username"], + "channel_name": msg.get("channel_name", "unknown"), + "_meta": { + "message_id": msg["id"], + "channel_id": channel_id.strip(), + "author_id": msg["author"]["id"], + }, + }) + + logger.info(f"Fetched {len(inputs)} messages to classify") + return inputs + + def _get_sample_inputs(self) -> List[Dict[str, Any]]: + """Return sample messages for dry run testing.""" + samples = [ + { + "message": "Hey everyone, we're hiring a senior Python developer! Remote OK, competitive salary. DM me for details.", + "author": "recruiter_jane", + "channel_name": "general", + "_meta": {"message_id": "sample_1", "channel_id": "123", "author_id": "u1"}, + }, + { + "message": "Anyone know a good coffee shop near downtown?", + "author": "coffee_lover", + "channel_name": "general", + "_meta": {"message_id": "sample_2", "channel_id": "123", "author_id": "u2"}, + }, + { + "message": "Looking for work! 5 years of React experience, open to contract or full-time.", + "author": "dev_looking", + "channel_name": "general", + "_meta": {"message_id": "sample_3", "channel_id": "123", "author_id": "u3"}, + }, + { + "message": "🚀🚀🚀 MAKE $10K/WEEK FROM HOME!!! Click here: spam.link 🚀🚀🚀", + "author": "totally_not_spam", + "channel_name": "general", + "_meta": {"message_id": "sample_4", "channel_id": "123", "author_id": "u4"}, + }, + ] + logger.info(f"[DRY RUN] Using {len(samples)} sample messages") + return samples + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + """Take moderation action based on classification result.""" + meta = inputs.get("_meta", {}) + message_id = meta.get("message_id") + channel_id = meta.get("channel_id") + author = inputs.get("author", "unknown") + + action = output.get("action", "allow") + intent = output.get("intent", "other") + reason = output.get("reason", "") + + logger.info( + f"Message {message_id} from {author}: " + f"intent={intent}, action={action}, reason={reason}" + ) + + if action == "allow": + return + + if self.dry_run: + await self._log_dry_run_action(action, inputs, output) + return + + if action == "move" and self.jobs_channel_id: + original_content = inputs["message"] + await self.client.send_message( + channel_id=self.jobs_channel_id, + content=f"**Moved from <#{channel_id}>**\n" + f"*Originally posted by {author}:*\n\n{original_content}", + ) + await self.client.delete_message( + channel_id=channel_id, + message_id=message_id, + ) + await self.client.send_dm( + user_id=meta["author_id"], + content=f"Your job posting was moved to <#{self.jobs_channel_id}>. " + f"Please post job-related content there in the future.", + ) + logger.info(f"Moved message {message_id} to jobs channel") + + elif action == "flag": + await self.client.add_reaction( + channel_id=channel_id, + message_id=message_id, + emoji="⚠️", + ) + logger.info(f"Flagged message {message_id} for review") + + elif action == "delete": + await self.client.delete_message( + channel_id=channel_id, + message_id=message_id, + ) + await self.client.send_dm( + user_id=meta["author_id"], + content=f"Your message was removed: {reason}", + ) + logger.info(f"Deleted message {message_id}") + + async def _log_dry_run_action( + self, action: str, inputs: Dict[str, Any], output: Any + ) -> None: + """Log what would happen without executing.""" + meta = inputs.get("_meta", {}) + message_id = meta.get("message_id") + channel_id = meta.get("channel_id") + author = inputs.get("author", "unknown") + reason = output.get("reason", "") + + if action == "move": + logger.info( + f"[DRY RUN] WOULD move message {message_id} from {author} " + f"to jobs channel {self.jobs_channel_id}" + ) + logger.info(f"[DRY RUN] WOULD delete original from #{channel_id}") + logger.info(f"[DRY RUN] WOULD DM {meta.get('author_id')} about the move") + + elif action == "flag": + logger.info( + f"[DRY RUN] WOULD add ⚠️ reaction to message {message_id}" + ) + + elif action == "delete": + logger.info( + f"[DRY RUN] WOULD delete message {message_id}: {reason}" + ) + logger.info(f"[DRY RUN] WOULD DM {meta.get('author_id')}: {reason}") diff --git a/examples/discord-mod/src/discord_mod/metrics/__init__.py b/examples/discord-mod/src/discord_mod/metrics/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/examples/discord-mod/src/discord_mod/modules/__init__.py b/examples/discord-mod/src/discord_mod/modules/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py new file mode 100644 index 0000000..55ba636 --- /dev/null +++ b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py @@ -0,0 +1,61 @@ +"""Job posting classifier module - pure LLM logic, no Discord API knowledge.""" + +from typing import Literal + +import dspy + +from discord_mod.gateways.job_posting_gateway import JobPostingGateway + + +class ClassifyJobPosting(dspy.Module): + """Classify Discord messages as job postings, job-seeking, or general chat. + + This module contains only the LLM classification logic. + The gateway handles Discord API interactions (fetching messages, taking actions). + """ + + gateway = JobPostingGateway + + def __init__(self): + super().__init__() + self.classifier = dspy.ChainOfThought(JobPostingSignature) + + def forward( + self, + message: str, + author: str, + channel_name: str, + ) -> dspy.Prediction: + """Classify a message and determine the appropriate action. + + Args: + message: The Discord message content + author: The message author's username + channel_name: The channel where the message was posted + + Returns: + Prediction with intent, action, and reason fields + """ + return self.classifier( + message=message, + author=author, + channel_name=channel_name, + ) + + +class JobPostingSignature(dspy.Signature): + """Classify a Discord message and determine moderation action.""" + + message: str = dspy.InputField(desc="The Discord message content") + author: str = dspy.InputField(desc="The message author's username") + channel_name: str = dspy.InputField(desc="The channel where the message was posted") + + intent: Literal["post_job", "seek_job", "other"] = dspy.OutputField( + desc="The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion" + ) + action: Literal["allow", "move", "flag", "delete"] = dspy.OutputField( + desc="Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation" + ) + reason: str = dspy.OutputField( + desc="Brief explanation of the classification and recommended action" + ) diff --git a/examples/discord-mod/src/discord_mod/optimizers/__init__.py b/examples/discord-mod/src/discord_mod/optimizers/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/examples/discord-mod/src/discord_mod/signatures/__init__.py b/examples/discord-mod/src/discord_mod/signatures/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/examples/discord-mod/src/discord_mod/utils/__init__.py b/examples/discord-mod/src/discord_mod/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/examples/discord-mod/src/discord_mod/utils/discord_client.py b/examples/discord-mod/src/discord_mod/utils/discord_client.py new file mode 100644 index 0000000..1974f4c --- /dev/null +++ b/examples/discord-mod/src/discord_mod/utils/discord_client.py @@ -0,0 +1,136 @@ +"""Discord API client for gateway interactions. + +This is a simple async client that wraps the Discord REST API. +For production use, consider using discord.py or similar libraries. +""" + +import logging +from typing import Any, Dict, List, Optional + +import httpx + +logger = logging.getLogger(__name__) + +DISCORD_API_BASE = "https://discord.com/api/v10" + + +class DiscordClient: + """Async Discord API client for moderation actions.""" + + def __init__(self, token: str): + self.token = token + self.headers = { + "Authorization": f"Bot {token}", + "Content-Type": "application/json", + } + + async def _request( + self, + method: str, + endpoint: str, + json: Optional[Dict] = None, + ) -> Any: + """Make an authenticated request to the Discord API.""" + url = f"{DISCORD_API_BASE}{endpoint}" + async with httpx.AsyncClient() as client: + response = await client.request( + method=method, + url=url, + headers=self.headers, + json=json, + ) + if response.status_code == 204: + return None + response.raise_for_status() + return response.json() + + async def get_recent_messages( + self, + channel_id: str, + limit: int = 50, + after: Optional[str] = None, + ) -> List[Dict[str, Any]]: + """Fetch recent messages from a channel. + + Args: + channel_id: The channel to fetch from + limit: Max messages to return (1-100) + after: Only get messages after this message ID + + Returns: + List of message objects from Discord API + """ + endpoint = f"/channels/{channel_id}/messages?limit={limit}" + if after: + endpoint += f"&after={after}" + + try: + messages = await self._request("GET", endpoint) + channel = await self.get_channel(channel_id) + for msg in messages: + msg["channel_name"] = channel.get("name", "unknown") + return messages + except httpx.HTTPStatusError as e: + logger.error(f"Failed to fetch messages from {channel_id}: {e}") + return [] + + async def get_channel(self, channel_id: str) -> Dict[str, Any]: + """Get channel information.""" + try: + return await self._request("GET", f"/channels/{channel_id}") + except httpx.HTTPStatusError: + return {} + + async def send_message( + self, + channel_id: str, + content: str, + ) -> Dict[str, Any]: + """Send a message to a channel.""" + return await self._request( + "POST", + f"/channels/{channel_id}/messages", + json={"content": content}, + ) + + async def delete_message( + self, + channel_id: str, + message_id: str, + ) -> None: + """Delete a message.""" + await self._request( + "DELETE", + f"/channels/{channel_id}/messages/{message_id}", + ) + + async def add_reaction( + self, + channel_id: str, + message_id: str, + emoji: str, + ) -> None: + """Add a reaction to a message.""" + import urllib.parse + encoded_emoji = urllib.parse.quote(emoji) + await self._request( + "PUT", + f"/channels/{channel_id}/messages/{message_id}/reactions/{encoded_emoji}/@me", + ) + + async def send_dm( + self, + user_id: str, + content: str, + ) -> Optional[Dict[str, Any]]: + """Send a direct message to a user.""" + 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environment variables. --- examples/discord-mod/README.md | 30 +- examples/discord-mod/dspy.config.yaml | 6 +- examples/discord-mod/openapi.json | 345 ++++++++++++++++++ .../gateways/job_posting_gateway.py | 74 +++- .../modules/classify_job_posting.py | 6 +- src/dspy_cli/server/scheduler.py | 15 +- 6 files changed, 456 insertions(+), 20 deletions(-) create mode 100644 examples/discord-mod/openapi.json diff --git a/examples/discord-mod/README.md b/examples/discord-mod/README.md index 8578243..87c27ed 100644 --- a/examples/discord-mod/README.md +++ b/examples/discord-mod/README.md @@ -56,17 +56,17 @@ src/discord_mod/ 2. **Configure environment variables** in `.env`: ```bash - # Discord bot token - DISCORD_BOT_TOKEN=your-bot-token + # Required + DISCORD_BOT_TOKEN=your-bot-token # Bot authentication token + DISCORD_CHANNEL_IDS=123456789,987654321 # Channels to monitor (comma-separated) + DISCORD_JOBS_CHANNEL_ID=111222333 # Channel to move job posts to + OPENAI_API_KEY=your-openai-key # LLM API key - # Channels to monitor (comma-separated) - DISCORD_CHANNEL_IDS=123456789,987654321 + DISCORD_AUDIT_CHANNEL_ID=444555666 # Channel for moderation audit logs - # Channel to move job posts to - DISCORD_JOBS_CHANNEL_ID=111222333 - - # LLM API key - OPENAI_API_KEY=your-openai-key + # Optional + DRY_RUN=true # Log actions without executing (default: true) + USE_SAMPLE_DATA=true # Use sample messages instead of Discord API ``` 3. **Install dependencies**: @@ -74,6 +74,18 @@ src/discord_mod/ uv sync ``` +## Environment Variables + +| Variable | Required | Description | +|----------|----------|-------------| +| `DISCORD_BOT_TOKEN` | ✅ | Bot authentication token from Discord Developer Portal | +| `DISCORD_CHANNEL_IDS` | ✅ | Comma-separated channel IDs to monitor | +| `DISCORD_JOBS_CHANNEL_ID` | ✅ | Channel ID where job posts are moved to | +| `OPENAI_API_KEY` | ✅ | OpenAI API key for LLM classification | +| `DISCORD_AUDIT_CHANNEL_ID` | ✅ | Channel for audit logs (move/flag/delete actions) | +| `DRY_RUN` | ❌ | Set to `false` to execute real actions (default: `true`) | +| `USE_SAMPLE_DATA` | ❌ | Set to `true` to use sample messages for testing | + ## Running Start the server with cron scheduling enabled: diff --git a/examples/discord-mod/dspy.config.yaml b/examples/discord-mod/dspy.config.yaml index e53c0b5..2530a88 100644 --- a/examples/discord-mod/dspy.config.yaml +++ b/examples/discord-mod/dspy.config.yaml @@ -4,12 +4,12 @@ app_id: discord-mod models: # The default model to use if no per-program override is specified - default: openai:gpt-5-mini + default: openai:gpt-5-nano # Model registry - define all available models here registry: - openai:gpt-5-mini: - model: openai/gpt-5-mini + openai:gpt-5-nano: + model: openai/gpt-5-nano model_type: chat max_tokens: 16000 temperature: 1.0 diff --git a/examples/discord-mod/openapi.json b/examples/discord-mod/openapi.json new file mode 100644 index 0000000..88b5a7a --- /dev/null +++ b/examples/discord-mod/openapi.json @@ -0,0 +1,345 @@ +{ + "openapi": "3.1.0", + "info": { + "title": "discord-mod", + "description": "Automatically generated API for DSPy programs", + "version": "0.1.0", + "x-dspy-config": { + "default_model": null, + "programs_count": 2 + }, + "x-dspy-programs": [ + { + "name": "MyProgramPredict", + "module_path": "discord_mod.modules.my_program_predict", + "is_forward_typed": true + }, + { + "name": "ClassifyJobPosting", + "module_path": "discord_mod.modules.classify_job_posting", + "is_forward_typed": true + } + ], + "x-dspy-program-models": { + "MyProgramPredict": "openai:gpt-5-mini", + "ClassifyJobPosting": "openai:gpt-5-mini" + } + }, + "paths": { + "/MyProgramPredict": { + "post": { + "summary": "Run Program", + "description": "Execute the DSPy program with given inputs.", + "operationId": "run_program_MyProgramPredict_post", + "requestBody": { + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/MyProgramPredictRequest" + } + } + }, + "required": true + }, + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": { + "additionalProperties": true, + "type": "object", + "title": "Response Run Program Myprogrampredict Post" + } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, + "/programs": { + "get": { + "summary": "List Programs", + "description": "List all discovered programs and their schemas.", + "operationId": "list_programs_programs_get", + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": {} + } + } + } + } + } + }, + "/api/metrics": { + "get": { + "summary": "List Metrics", + "description": "Get aggregated metrics for all programs.\n\nArgs:\n sort_by: Sort key (name, calls, latency, cost, tokens, last_call)\n order: Sort order (asc, desc)", + "operationId": "list_metrics_api_metrics_get", + "parameters": [ + { + "name": "sort_by", + "in": "query", + "required": false, + "schema": { + "type": "string", + "default": "calls", + "title": "Sort By" + } + }, + { + "name": "order", + "in": "query", + "required": false, + "schema": { + "type": "string", + "default": "desc", + "title": "Order" + } + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": {} + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, + "/api/metrics/{program_name}": { + "get": { + "summary": "Program Metrics", + "description": "Get detailed metrics for a specific program.", + "operationId": "program_metrics_api_metrics__program_name__get", + "parameters": [ + { + "name": "program_name", + "in": "path", + "required": true, + "schema": { + "type": "string", + "title": "Program Name" + } + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": {} + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, + "/": { + "get": { + "summary": "Index", + "description": "Render the index page with a list of all programs.", + "operationId": "index__get", + "responses": { + "200": { + "description": "Successful Response", + "content": { + "text/html": { + "schema": { + "type": "string" + } + } + } + } + } + } + }, + "/ui/{program_name}": { + "get": { + "summary": "Program Page", + "description": "Render the program detail page.", + "operationId": "program_page_ui__program_name__get", + "parameters": [ + { + "name": "program_name", + "in": "path", + "required": true, + "schema": { + "type": "string", + "title": "Program Name" + } + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "text/html": { + "schema": { + "type": "string" + } + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + }, + "/api/logs/{program_name}": { + "get": { + "summary": "Get Logs", + "description": "Get recent logs for a program.", + "operationId": "get_logs_api_logs__program_name__get", + "parameters": [ + { + "name": "program_name", + "in": "path", + "required": true, + "schema": { + "type": "string", + "title": "Program Name" + } + }, + { + "name": "limit", + "in": "query", + "required": false, + "schema": { + "type": "integer", + "default": 50, + "title": "Limit" + } + } + ], + "responses": { + "200": { + "description": "Successful Response", + "content": { + "application/json": { + "schema": {} + } + } + }, + "422": { + "description": "Validation Error", + "content": { + "application/json": { + "schema": { + "$ref": "#/components/schemas/HTTPValidationError" + } + } + } + } + } + } + } + }, + "components": { + "schemas": { + "HTTPValidationError": { + "properties": { + "detail": { + "items": { + "$ref": "#/components/schemas/ValidationError" + }, + "type": "array", + "title": "Detail" + } + }, + "type": "object", + "title": "HTTPValidationError" + }, + "MyProgramPredictRequest": { + "properties": { + "comment": { + "type": "string", + "title": "Comment" + } + }, + "type": "object", + "required": [ + "comment" + ], + "title": "MyProgramPredictRequest" + }, + "ValidationError": { + "properties": { + "loc": { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "type": "integer" + } + ] + }, + "type": "array", + "title": "Location" + }, + "msg": { + "type": "string", + "title": "Message" + }, + "type": { + "type": "string", + "title": "Error Type" + } + }, + "type": "object", + "required": [ + "loc", + "msg", + "type" + ], + "title": "ValidationError" + } + } + } +} \ No newline at end of file diff --git a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py index 55fc57a..a81ffb3 100644 --- a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py +++ b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py @@ -29,22 +29,45 @@ class JobPostingGateway(CronGateway): DRY_RUN: Set to "true" to log actions without executing them """ - schedule = "*/5 * * * *" # Every 5 minutes + schedule = "* * * * *" # Every minute (testing) def __init__(self): - self.dry_run = os.environ.get("DRY_RUN", "").lower() == "true" + # Validate required environment variables + missing = [] + if not os.environ.get("DISCORD_BOT_TOKEN"): + missing.append("DISCORD_BOT_TOKEN") + if not os.environ.get("DISCORD_CHANNEL_IDS"): + missing.append("DISCORD_CHANNEL_IDS") + if not os.environ.get("DISCORD_JOBS_CHANNEL_ID"): + missing.append("DISCORD_JOBS_CHANNEL_ID") + if not os.environ.get("DISCORD_AUDIT_CHANNEL_ID"): + missing.append("DISCORD_AUDIT_CHANNEL_ID") + + if missing and not os.environ.get("USE_SAMPLE_DATA", "").lower() == "true": + logger.error(f"Missing required environment variables: {', '.join(missing)}") + logger.error("Set these variables or use USE_SAMPLE_DATA=true for testing") + raise SystemExit(1) + + # USE_SAMPLE_DATA: Use sample messages instead of fetching from Discord + self.use_sample_data = os.environ.get("USE_SAMPLE_DATA", "").lower() == "true" + # DRY_RUN: Log actions instead of executing them + self.dry_run = os.environ.get("DRY_RUN", "true").lower() == "true" + self.client = DiscordClient( token=os.environ.get("DISCORD_BOT_TOKEN", ""), ) self.channel_ids = os.environ.get("DISCORD_CHANNEL_IDS", "").split(",") self.jobs_channel_id = os.environ.get("DISCORD_JOBS_CHANNEL_ID") + self.audit_channel_id = os.environ.get("DISCORD_AUDIT_CHANNEL_ID") + if self.use_sample_data: + logger.info("USE_SAMPLE_DATA mode - using sample messages") if self.dry_run: - logger.info("DRY_RUN mode enabled - no actions will be executed") + logger.info("DRY_RUN mode - actions will be logged, not executed") async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: """Fetch recent unprocessed messages from monitored channels.""" - if self.dry_run: + if self.use_sample_data: return self._get_sample_inputs() inputs = [] @@ -55,7 +78,7 @@ async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: messages = await self.client.get_recent_messages( channel_id=channel_id.strip(), - limit=50, + limit=20, ) for msg in messages: @@ -128,6 +151,7 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: if self.dry_run: await self._log_dry_run_action(action, inputs, output) + await self._send_audit_log(action, inputs, output, dry_run=True) return if action == "move" and self.jobs_channel_id: @@ -147,6 +171,7 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: f"Please post job-related content there in the future.", ) logger.info(f"Moved message {message_id} to jobs channel") + await self._send_audit_log(action, inputs, output, dry_run=False) elif action == "flag": await self.client.add_reaction( @@ -155,6 +180,7 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: emoji="⚠️", ) logger.info(f"Flagged message {message_id} for review") + await self._send_audit_log(action, inputs, output, dry_run=False) elif action == "delete": await self.client.delete_message( @@ -166,6 +192,44 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: content=f"Your message was removed: {reason}", ) logger.info(f"Deleted message {message_id}") + await self._send_audit_log(action, inputs, output, dry_run=False) + + async def _send_audit_log( + self, action: str, inputs: Dict[str, Any], output: Any, dry_run: bool + ) -> None: + """Send audit log to moderator channel.""" + if not self.audit_channel_id: + return + + meta = inputs.get("_meta", {}) + message_id = meta.get("message_id", "unknown") + channel_id = meta.get("channel_id", "unknown") + author = inputs.get("author", "unknown") + intent = output.get("intent", "unknown") + reason = output.get("reason", "") + message_preview = inputs.get("message", "")[:100] + + dry_run_prefix = "🔍 **[DRY RUN]** " if dry_run else "" + + action_emoji = {"move": "📦", "flag": "⚠️", "delete": "🗑️"}.get(action, "❓") + + audit_message = ( + f"{dry_run_prefix}{action_emoji} **Action: {action.upper()}**\n" + f"**Author:** {author}\n" + f"**Channel:** <#{channel_id}>\n" + f"**Intent:** {intent}\n" + f"**Reason:** {reason}\n" + f"**Message:** `{message_preview}{'...' if len(inputs.get('message', '')) > 100 else ''}`\n" + f"**Message ID:** {message_id}" + ) + + try: + await self.client.send_message( + channel_id=self.audit_channel_id, + content=audit_message, + ) + except Exception as e: + logger.warning(f"Failed to send audit log: {e}") async def _log_dry_run_action( self, action: str, inputs: Dict[str, Any], output: Any diff --git a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py index 55ba636..0a6f6b3 100644 --- a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py +++ b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py @@ -44,7 +44,11 @@ def forward( class JobPostingSignature(dspy.Signature): - """Classify a Discord message and determine moderation action.""" + """Classify a Discord message and determine moderation action. + + A Job posting or job seeking message will explicitly state: + 1. A user's resume/openness to work + 2. A user's availability to hire (e.g. "I'm looking for a software engineer to hire immediately")""" message: str = dspy.InputField(desc="The Discord message content") author: str = dspy.InputField(desc="The message author's username") diff --git a/src/dspy_cli/server/scheduler.py b/src/dspy_cli/server/scheduler.py index 38ea75a..2052138 100644 --- a/src/dspy_cli/server/scheduler.py +++ b/src/dspy_cli/server/scheduler.py @@ -51,7 +51,10 @@ async def execute_job(): return for raw_inputs in inputs_list: - inputs = _convert_dspy_types(raw_inputs, module) + # Strip _meta from inputs before passing to pipeline + # _meta is used by gateway.on_complete() but not by forward() + pipeline_inputs = {k: v for k, v in raw_inputs.items() if not k.startswith("_")} + inputs = _convert_dspy_types(pipeline_inputs, module) try: output = await execute_pipeline( module=module, @@ -68,7 +71,15 @@ async def execute_job(): trigger = CronTrigger.from_crontab(gateway.schedule) job_id = f"cron_{program_name}" - self.scheduler.add_job(execute_job, trigger, id=job_id) + # max_instances=1: Don't start a new run if previous is still running + # coalesce=True: If multiple runs were missed, only run once + self.scheduler.add_job( + execute_job, + trigger, + id=job_id, + max_instances=1, + coalesce=True, + ) self._jobs[program_name] = job_id logger.info(f"Registered cron gateway: {program_name} schedule={gateway.schedule}") From 791775c96dd2f3bafd526910eb687c0e916eaa2b Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Wed, 17 Dec 2025 14:37:44 -0500 Subject: [PATCH 08/19] remove sample inputs --- examples/discord-mod/README.md | 14 ++++++ .../gateways/job_posting_gateway.py | 47 ++----------------- 2 files changed, 19 insertions(+), 42 deletions(-) diff --git a/examples/discord-mod/README.md b/examples/discord-mod/README.md index 87c27ed..ea69496 100644 --- a/examples/discord-mod/README.md +++ b/examples/discord-mod/README.md @@ -99,6 +99,20 @@ The `ClassifyJobPosting` module uses a `CronGateway` with `schedule = "*/5 * * * 2. Classify each new message 3. Take the appropriate moderation action + +## Deployment: +fly scale count 1 +fly deploy --ha=false + +fly secrets set \ + DISCORD_BOT_TOKEN="" \ + DISCORD_CHANNEL_IDS="<>" \ + DISCORD_JOBS_CHANNEL_ID="<>" \ + DISCORD_AUDIT_CHANNEL_ID="" \ + OPENAI_API_KEY="" \ + DRY_RUN="false" + + ## How It Works ### The Module (Pure LLM Logic) diff --git a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py index a81ffb3..61c0d52 100644 --- a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py +++ b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py @@ -29,7 +29,7 @@ class JobPostingGateway(CronGateway): DRY_RUN: Set to "true" to log actions without executing them """ - schedule = "* * * * *" # Every minute (testing) + schedule = "*/5 * * * *" # Every 5 minutes def __init__(self): # Validate required environment variables @@ -43,13 +43,11 @@ def __init__(self): if not os.environ.get("DISCORD_AUDIT_CHANNEL_ID"): missing.append("DISCORD_AUDIT_CHANNEL_ID") - if missing and not os.environ.get("USE_SAMPLE_DATA", "").lower() == "true": + if missing: logger.error(f"Missing required environment variables: {', '.join(missing)}") - logger.error("Set these variables or use USE_SAMPLE_DATA=true for testing") + logger.error("Set these variables") raise SystemExit(1) - # USE_SAMPLE_DATA: Use sample messages instead of fetching from Discord - self.use_sample_data = os.environ.get("USE_SAMPLE_DATA", "").lower() == "true" # DRY_RUN: Log actions instead of executing them self.dry_run = os.environ.get("DRY_RUN", "true").lower() == "true" @@ -60,16 +58,11 @@ def __init__(self): self.jobs_channel_id = os.environ.get("DISCORD_JOBS_CHANNEL_ID") self.audit_channel_id = os.environ.get("DISCORD_AUDIT_CHANNEL_ID") - if self.use_sample_data: - logger.info("USE_SAMPLE_DATA mode - using sample messages") if self.dry_run: logger.info("DRY_RUN mode - actions will be logged, not executed") async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: """Fetch recent unprocessed messages from monitored channels.""" - if self.use_sample_data: - return self._get_sample_inputs() - inputs = [] for channel_id in self.channel_ids: @@ -99,37 +92,6 @@ async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: logger.info(f"Fetched {len(inputs)} messages to classify") return inputs - def _get_sample_inputs(self) -> List[Dict[str, Any]]: - """Return sample messages for dry run testing.""" - samples = [ - { - "message": "Hey everyone, we're hiring a senior Python developer! Remote OK, competitive salary. DM me for details.", - "author": "recruiter_jane", - "channel_name": "general", - "_meta": {"message_id": "sample_1", "channel_id": "123", "author_id": "u1"}, - }, - { - "message": "Anyone know a good coffee shop near downtown?", - "author": "coffee_lover", - "channel_name": "general", - "_meta": {"message_id": "sample_2", "channel_id": "123", "author_id": "u2"}, - }, - { - "message": "Looking for work! 5 years of React experience, open to contract or full-time.", - "author": "dev_looking", - "channel_name": "general", - "_meta": {"message_id": "sample_3", "channel_id": "123", "author_id": "u3"}, - }, - { - "message": "🚀🚀🚀 MAKE $10K/WEEK FROM HOME!!! Click here: spam.link 🚀🚀🚀", - "author": "totally_not_spam", - "channel_name": "general", - "_meta": {"message_id": "sample_4", "channel_id": "123", "author_id": "u4"}, - }, - ] - logger.info(f"[DRY RUN] Using {len(samples)} sample messages") - return samples - async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: """Take moderation action based on classification result.""" meta = inputs.get("_meta", {}) @@ -189,7 +151,8 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: ) await self.client.send_dm( user_id=meta["author_id"], - content=f"Your message was removed: {reason}", + content=f"Your message was removed: {reason}\n\n" + f"If you believe this was a false positive, please let us know.", ) logger.info(f"Deleted message {message_id}") await self._send_audit_log(action, inputs, output, dry_run=False) From 9876ffe14968e7cc99848e12e2153c94b8313e6e Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 23 Dec 2025 09:43:50 -0500 Subject: [PATCH 09/19] Enhance gateway functionality with lifecycle hooks and batch processing support. Added setup and shutdown methods to Gateway base class, allowing for resource management. Implemented batch execution in CronGateway, enabling parallel processing of inputs. Updated APIGateway and CronGateway to utilize PipelineInputs and PipelineOutput types for better type safety. Added tests for lifecycle hooks and batch configuration. --- src/dspy_cli/gateway/__init__.py | 3 + src/dspy_cli/gateway/api.py | 35 ++++++- src/dspy_cli/gateway/base.py | 23 ++++- src/dspy_cli/gateway/cron.py | 40 +++++++- src/dspy_cli/gateway/types.py | 17 ++++ src/dspy_cli/server/app.py | 33 +++++-- src/dspy_cli/server/execution.py | 157 ++++++++++++++++++++++++++++++- src/dspy_cli/server/routes.py | 16 +++- src/dspy_cli/server/scheduler.py | 141 ++++++++++++++++++++++----- tests/gateway/test_gateway.py | 125 ++++++++++++++++++++++++ tests/server/test_scheduler.py | 57 ++++++++++- 11 files changed, 605 insertions(+), 42 deletions(-) create mode 100644 src/dspy_cli/gateway/types.py diff --git a/src/dspy_cli/gateway/__init__.py b/src/dspy_cli/gateway/__init__.py index a81aa5d..f26fde4 100644 --- a/src/dspy_cli/gateway/__init__.py +++ b/src/dspy_cli/gateway/__init__.py @@ -9,10 +9,13 @@ from dspy_cli.gateway.api import APIGateway, IdentityGateway from dspy_cli.gateway.base import Gateway from dspy_cli.gateway.cron import CronGateway +from dspy_cli.gateway.types import PipelineInputs, PipelineOutput __all__ = [ "Gateway", "APIGateway", "IdentityGateway", "CronGateway", + "PipelineOutput", + "PipelineInputs", ] diff --git a/src/dspy_cli/gateway/api.py b/src/dspy_cli/gateway/api.py index dd35e5d..ca1e77b 100644 --- a/src/dspy_cli/gateway/api.py +++ b/src/dspy_cli/gateway/api.py @@ -1,10 +1,16 @@ """API Gateway for HTTP request/response transformation.""" -from typing import Any, Dict, Optional, Type +from __future__ import annotations + +from typing import TYPE_CHECKING, Any, Callable, Dict, Optional, Type from pydantic import BaseModel from dspy_cli.gateway.base import Gateway +from dspy_cli.gateway.types import PipelineOutput + +if TYPE_CHECKING: + from fastapi import FastAPI class APIGateway(Gateway): @@ -48,7 +54,7 @@ def to_pipeline_inputs(self, request: Any) -> Dict[str, Any]: return request.model_dump() return dict(request) if request else {} - def from_pipeline_output(self, output: Any) -> Any: + def from_pipeline_output(self, output: PipelineOutput) -> Any: """Transform pipeline output to HTTP response. Args: @@ -59,6 +65,31 @@ def from_pipeline_output(self, output: Any) -> Any: """ return output + def configure_route( + self, + app: FastAPI, + route_path: str, + endpoint: Callable[..., Any], + response_model: Optional[Type[Any]] = None, + ) -> None: + """Configure the FastAPI route for this gateway. + + Override to customize route registration, add dependencies, + custom responses, tags, rate limiting, etc. + + Args: + app: The FastAPI application instance + route_path: The URL path for this endpoint + endpoint: The async function to handle requests + response_model: Optional Pydantic model for response validation + """ + app.add_api_route( + route_path, + endpoint, + methods=[self.method], + response_model=response_model, + ) + class IdentityGateway(APIGateway): """Default gateway - HTTP inputs == pipeline inputs. diff --git a/src/dspy_cli/gateway/base.py b/src/dspy_cli/gateway/base.py index e252da3..a88d00c 100644 --- a/src/dspy_cli/gateway/base.py +++ b/src/dspy_cli/gateway/base.py @@ -9,4 +9,25 @@ class Gateway(ABC): A gateway controls how data flows into and out of a DSPy pipeline. Subclasses define specific input/output transformation patterns. """ - pass + + def setup(self) -> None: + """Optional initialization hook. + + Called once when the gateway is registered. Use for: + - Validating configuration + - Creating clients + - Reading environment variables + + Raise an exception to indicate setup failure. + """ + pass + + def shutdown(self) -> None: + """Optional cleanup hook. + + Called when the server is shutting down. Use for: + - Closing connections + - Flushing buffers + - Releasing resources + """ + pass diff --git a/src/dspy_cli/gateway/cron.py b/src/dspy_cli/gateway/cron.py index 160c74f..5d27fa5 100644 --- a/src/dspy_cli/gateway/cron.py +++ b/src/dspy_cli/gateway/cron.py @@ -4,6 +4,7 @@ from typing import Any, Dict, List from dspy_cli.gateway.base import Gateway +from dspy_cli.gateway.types import PipelineOutput class CronGateway(Gateway): @@ -14,9 +15,15 @@ class CronGateway(Gateway): - Load input data from external sources (APIs, databases, queues) - Take actions based on pipeline outputs (webhooks, API calls) + Batch Mode: + Set `use_batch = True` to process all inputs in parallel using DSPy's + module.batch() method. Configure `num_threads` to control parallelism. + Example: class DiscordModerationGateway(CronGateway): schedule = "*/5 * * * *" # Every 5 minutes + use_batch = True # Enable parallel processing + num_threads = 4 # Use 4 threads (default: None = DSPy default) async def get_pipeline_inputs(self) -> list[dict]: # Fetch unmoderated messages from Discord API @@ -30,6 +37,9 @@ async def on_complete(self, inputs: dict, output) -> None: """ schedule: str # Cron expression like "*/5 * * * *" + use_batch: bool = False # Enable batch processing with module.batch() + num_threads: int | None = None # Number of threads for batch (None = DSPy default) + max_errors: int | None = None # Max errors before stopping batch (None = no limit) @abstractmethod async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: @@ -46,7 +56,7 @@ async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: ... @abstractmethod - async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + async def on_complete(self, inputs: Dict[str, Any], output: PipelineOutput) -> None: """Handle pipeline output. Called after each successful pipeline execution. @@ -56,3 +66,31 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: output: The normalized output dict from execute_pipeline """ ... + + async def on_error(self, inputs: Dict[str, Any], error: Exception) -> None: + """Handle pipeline execution error. + + Called when pipeline execution fails for an input. Override to implement + custom error handling (e.g., logging, alerting, retry logic). + + Default implementation does nothing - errors are still logged by the scheduler. + + Args: + inputs: The original input dict (including _meta if provided) + error: The exception that occurred during execution + """ + pass + + @staticmethod + def extract_pipeline_kwargs(inputs: Dict[str, Any]) -> Dict[str, Any]: + """Extract pipeline kwargs from raw inputs, stripping _-prefixed keys. + + Use this to separate pipeline inputs from metadata like _meta. + + Args: + inputs: Raw input dict that may contain _-prefixed keys + + Returns: + Dict with only non-_-prefixed keys (suitable for forward()) + """ + return {k: v for k, v in inputs.items() if not k.startswith("_")} diff --git a/src/dspy_cli/gateway/types.py b/src/dspy_cli/gateway/types.py new file mode 100644 index 0000000..7cea491 --- /dev/null +++ b/src/dspy_cli/gateway/types.py @@ -0,0 +1,17 @@ +"""Type definitions for gateways.""" + +from typing import Any, Dict + +PipelineOutput = Dict[str, Any] +"""Output from a DSPy pipeline after normalization via _normalize_output. + +This is always a dictionary mapping field names to their values, +regardless of the original return type from the DSPy module. +""" + +PipelineInputs = Dict[str, Any] +"""Input kwargs for a DSPy pipeline's forward() method. + +Should not contain _-prefixed keys like _meta; those are stripped +before passing to the pipeline. +""" diff --git a/src/dspy_cli/server/app.py b/src/dspy_cli/server/app.py index 2af88c9..88bc103 100644 --- a/src/dspy_cli/server/app.py +++ b/src/dspy_cli/server/app.py @@ -1,6 +1,7 @@ """FastAPI application factory.""" import logging +from contextlib import asynccontextmanager from pathlib import Path from typing import Dict @@ -48,7 +49,8 @@ def create_app( app = FastAPI( title="DSPy API", description="Automatically generated API for DSPy programs", - version="0.1.0" + version="0.1.0", + lifespan=lifespan, ) # Store logs directory and metrics cache in app state @@ -246,17 +248,28 @@ async def program_metrics(program_name: str): app.add_middleware(AuthMiddleware, token=token, open_paths=open_paths) logger.info("Authentication enabled") - # Add scheduler lifecycle events if any cron jobs registered - if scheduler.job_count > 0: - @app.on_event("startup") - async def _start_scheduler(): - scheduler.start() + return app - @app.on_event("shutdown") - async def _stop_scheduler(): - scheduler.shutdown() - return app +@asynccontextmanager +async def lifespan(app: FastAPI): + """Lifespan context manager for startup/shutdown events.""" + # Startup + scheduler = getattr(app.state, "scheduler", None) + if scheduler and scheduler.job_count > 0: + scheduler.start() + + yield + + # Shutdown + if scheduler and scheduler.job_count > 0: + scheduler.shutdown() + + for shutdown_fn in getattr(app.state, "_gateway_shutdowns", []): + try: + shutdown_fn() + except Exception as e: + logger.warning(f"Gateway shutdown error: {e}") def _create_lm_instance(model_config: Dict) -> dspy.LM: diff --git a/src/dspy_cli/server/execution.py b/src/dspy_cli/server/execution.py index ff2e33f..8279392 100644 --- a/src/dspy_cli/server/execution.py +++ b/src/dspy_cli/server/execution.py @@ -5,7 +5,7 @@ import time from datetime import datetime from pathlib import Path -from typing import Any, Dict, List +from typing import Any, Dict, List, Optional, Tuple import dspy @@ -328,3 +328,158 @@ async def execute_pipeline( logger.error(f"Error executing {program_name}: {e}", exc_info=True) raise + + +async def execute_pipeline_batch( + *, + module: DiscoveredModule, + instance: dspy.Module, + lm: dspy.LM, + model_name: str, + program_name: str, + inputs_list: List[Dict[str, Any]], + logs_dir: Path, + num_threads: Optional[int] = None, + max_errors: Optional[int] = None, +) -> List[Tuple[Dict[str, Any], Optional[Dict[str, Any]], Optional[Exception]]]: + """Run a DSPy module in batch mode using module.batch(). + + This processes multiple inputs in parallel using DSPy's built-in + batch processing with thread pooling. + + Args: + module: DiscoveredModule metadata + instance: Instantiated DSPy module + lm: Language model instance + model_name: Model name for logging + program_name: Program name for logging + inputs_list: List of raw input dictionaries (may contain _meta) + logs_dir: Directory for log files + num_threads: Number of threads for batch (None = DSPy default) + max_errors: Maximum errors before stopping (None = no limit) + + Returns: + List of tuples: (raw_inputs, output_dict or None, error or None) + """ + start_time = time.time() + request_lm = lm.copy() + + prepared_inputs = [] + for raw_inputs in inputs_list: + pipeline_inputs = {k: v for k, v in raw_inputs.items() if not k.startswith("_")} + converted = _convert_dspy_types(pipeline_inputs, module) + prepared_inputs.append((raw_inputs, converted)) + + examples = [ + dspy.Example(**converted).with_inputs(*converted.keys()) + for _, converted in prepared_inputs + ] + + logger.info( + f"Batch executing {program_name} with {len(examples)} inputs " + f"(threads={num_threads or 'default'})" + ) + + results: List[Tuple[Dict[str, Any], Optional[Dict[str, Any]], Optional[Exception]]] = [] + + try: + with dspy.context(lm=request_lm): + batch_kwargs = { + "return_failed_examples": True, + "provide_traceback": True, + } + if num_threads is not None: + batch_kwargs["num_threads"] = num_threads + if max_errors is not None: + batch_kwargs["max_errors"] = max_errors + + batch_result = instance.batch(examples, **batch_kwargs) + + if isinstance(batch_result, tuple) and len(batch_result) == 3: + successful, failed_examples, exceptions = batch_result + else: + successful = batch_result + failed_examples = [] + exceptions = [] + + duration_ms = (time.time() - start_time) * 1000 + + failed_map = {} + used_indices: set[int] = set() + for i, (failed_ex, exc) in enumerate(zip(failed_examples, exceptions)): + for j, (raw_inputs, converted) in enumerate(prepared_inputs): + if j not in used_indices and _examples_match(failed_ex, converted): + failed_map[j] = exc + used_indices.add(j) + break + + success_idx = 0 + for i, (raw_inputs, converted) in enumerate(prepared_inputs): + if i in failed_map: + results.append((raw_inputs, None, failed_map[i])) + + try: + serialized_inputs = _serialize_for_logging(converted, logs_dir, program_name) + except Exception: + serialized_inputs = {} + + log_inference( + logs_dir=logs_dir, + program_name=program_name, + model=model_name, + inputs=serialized_inputs, + outputs={}, + duration_ms=0, + error=str(failed_map[i]), + tokens=None, + cost_usd=None, + lm_calls=None, + ) + else: + if success_idx < len(successful): + result = successful[success_idx] + output = _normalize_output(result, module) + results.append((raw_inputs, output, None)) + + try: + serialized_inputs = _serialize_for_logging(converted, logs_dir, program_name) + serialized_outputs = _serialize_for_logging(output, logs_dir, program_name) + except Exception: + serialized_inputs = {} + serialized_outputs = {} + + log_inference( + logs_dir=logs_dir, + program_name=program_name, + model=model_name, + inputs=serialized_inputs, + outputs=serialized_outputs, + duration_ms=duration_ms / len(inputs_list), + tokens=None, + cost_usd=None, + lm_calls=None, + ) + success_idx += 1 + + logger.info( + f"Batch {program_name} completed: {len(successful)} succeeded, " + f"{len(failed_examples)} failed in {duration_ms:.0f}ms" + ) + + except Exception as e: + logger.error(f"Batch execution error for {program_name}: {e}", exc_info=True) + for raw_inputs, _ in prepared_inputs: + results.append((raw_inputs, None, e)) + + return results + + +def _examples_match(example: dspy.Example, inputs: Dict[str, Any]) -> bool: + """Check if a DSPy Example matches the given inputs dict.""" + try: + for key, value in inputs.items(): + if getattr(example, key, None) != value: + return False + return True + except Exception: + return False diff --git a/src/dspy_cli/server/routes.py b/src/dspy_cli/server/routes.py index a8d5bd1..1b5e08b 100644 --- a/src/dspy_cli/server/routes.py +++ b/src/dspy_cli/server/routes.py @@ -92,10 +92,18 @@ async def run_program(request: request_model): except Exception as e: raise HTTPException(status_code=500, detail=str(e)) - app.add_api_route( - route_path, - run_program, - methods=[gateway.method], + # Initialize gateway lifecycle + gateway.setup() + + # Register shutdown hook with FastAPI + if not hasattr(app.state, "_gateway_shutdowns"): + app.state._gateway_shutdowns = [] + app.state._gateway_shutdowns.append(gateway.shutdown) + + gateway.configure_route( + app=app, + route_path=route_path, + endpoint=run_program, response_model=response_model, ) diff --git a/src/dspy_cli/server/scheduler.py b/src/dspy_cli/server/scheduler.py index 2052138..c3ef394 100644 --- a/src/dspy_cli/server/scheduler.py +++ b/src/dspy_cli/server/scheduler.py @@ -2,7 +2,7 @@ import logging from pathlib import Path -from typing import Dict +from typing import Any, Dict, List, Tuple import dspy from apscheduler.schedulers.asyncio import AsyncIOScheduler @@ -10,7 +10,11 @@ from dspy_cli.discovery import DiscoveredModule from dspy_cli.gateway import CronGateway -from dspy_cli.server.execution import _convert_dspy_types, execute_pipeline +from dspy_cli.server.execution import ( + _convert_dspy_types, + execute_pipeline, + execute_pipeline_batch, +) logger = logging.getLogger(__name__) @@ -22,6 +26,7 @@ def __init__(self, logs_dir: Path): self.logs_dir = logs_dir self.scheduler = AsyncIOScheduler() self._jobs: Dict[str, str] = {} + self._gateways: List[CronGateway] = [] def register_cron_gateway( self, @@ -40,6 +45,8 @@ def register_cron_gateway( """ program_name = module.name + gateway.setup() + async def execute_job(): logger.info(f"CronGateway: executing {program_name}") instance = module.instantiate() @@ -50,24 +57,30 @@ async def execute_job(): logger.error(f"CronGateway error fetching inputs for {program_name}: {e}", exc_info=True) return - for raw_inputs in inputs_list: - # Strip _meta from inputs before passing to pipeline - # _meta is used by gateway.on_complete() but not by forward() - pipeline_inputs = {k: v for k, v in raw_inputs.items() if not k.startswith("_")} - inputs = _convert_dspy_types(pipeline_inputs, module) - try: - output = await execute_pipeline( - module=module, - instance=instance, - lm=lm, - model_name=model_name, - program_name=program_name, - inputs=inputs, - logs_dir=self.logs_dir, - ) - await gateway.on_complete(raw_inputs, output) - except Exception as e: - logger.error(f"CronGateway error for {program_name}: {e}", exc_info=True) + if not inputs_list: + logger.debug(f"CronGateway: no inputs for {program_name}") + return + + if gateway.use_batch: + await self._execute_batch( + module=module, + instance=instance, + gateway=gateway, + lm=lm, + model_name=model_name, + program_name=program_name, + inputs_list=inputs_list, + ) + else: + await self._execute_sequential( + module=module, + instance=instance, + gateway=gateway, + lm=lm, + model_name=model_name, + program_name=program_name, + inputs_list=inputs_list, + ) trigger = CronTrigger.from_crontab(gateway.schedule) job_id = f"cron_{program_name}" @@ -81,7 +94,85 @@ async def execute_job(): coalesce=True, ) self._jobs[program_name] = job_id - logger.info(f"Registered cron gateway: {program_name} schedule={gateway.schedule}") + self._gateways.append(gateway) + batch_info = f" batch={gateway.use_batch}" if gateway.use_batch else "" + threads_info = f" threads={gateway.num_threads}" if gateway.use_batch and gateway.num_threads else "" + logger.info(f"Registered cron gateway: {program_name} schedule={gateway.schedule}{batch_info}{threads_info}") + + async def _execute_sequential( + self, + *, + module: DiscoveredModule, + instance: dspy.Module, + gateway: CronGateway, + lm: dspy.LM, + model_name: str, + program_name: str, + inputs_list: List[Dict[str, Any]], + ): + """Execute pipeline sequentially for each input.""" + for raw_inputs in inputs_list: + pipeline_inputs = gateway.extract_pipeline_kwargs(raw_inputs) + inputs = _convert_dspy_types(pipeline_inputs, module) + try: + output = await execute_pipeline( + module=module, + instance=instance, + lm=lm, + model_name=model_name, + program_name=program_name, + inputs=inputs, + logs_dir=self.logs_dir, + ) + await gateway.on_complete(raw_inputs, output) + except Exception as e: + logger.error(f"CronGateway error for {program_name}: {e}", exc_info=True) + try: + await gateway.on_error(raw_inputs, e) + except Exception as hook_err: + logger.error(f"CronGateway on_error hook failed for {program_name}: {hook_err}", exc_info=True) + + async def _execute_batch( + self, + *, + module: DiscoveredModule, + instance: dspy.Module, + gateway: CronGateway, + lm: dspy.LM, + model_name: str, + program_name: str, + inputs_list: List[Dict[str, Any]], + ): + """Execute pipeline in batch mode using DSPy's module.batch().""" + logger.info( + f"CronGateway: batch processing {len(inputs_list)} inputs " + f"for {program_name} (threads={gateway.num_threads or 'default'})" + ) + + results = await execute_pipeline_batch( + module=module, + instance=instance, + lm=lm, + model_name=model_name, + program_name=program_name, + inputs_list=inputs_list, + logs_dir=self.logs_dir, + num_threads=gateway.num_threads, + max_errors=gateway.max_errors, + ) + + for raw_inputs, output, error in results: + if error: + logger.error(f"CronGateway batch error for {program_name}: {error}", exc_info=False) + try: + await gateway.on_error(raw_inputs, error) + except Exception as hook_err: + logger.error(f"CronGateway on_error hook failed for {program_name}: {hook_err}", exc_info=True) + continue + try: + await gateway.on_complete(raw_inputs, output) + except Exception as e: + logger.error(f"CronGateway on_complete error for {program_name}: {e}", exc_info=True) def start(self): """Start the scheduler.""" @@ -90,7 +181,13 @@ def start(self): logger.info("GatewayScheduler started") def shutdown(self): - """Shutdown the scheduler.""" + """Shutdown the scheduler and all gateways.""" + for gateway in self._gateways: + try: + gateway.shutdown() + except Exception as e: + logger.error(f"Gateway shutdown error: {e}", exc_info=True) + if self.scheduler.running: self.scheduler.shutdown(wait=False) logger.info("GatewayScheduler shutdown") diff --git a/tests/gateway/test_gateway.py b/tests/gateway/test_gateway.py index 2255c56..55fc31e 100644 --- a/tests/gateway/test_gateway.py +++ b/tests/gateway/test_gateway.py @@ -143,6 +143,66 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: gateway = ValidCronGateway() assert gateway.schedule == "*/5 * * * *" + def test_extract_pipeline_kwargs(self): + """extract_pipeline_kwargs should strip _-prefixed keys.""" + class TestGateway(CronGateway): + schedule = "0 * * * *" + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [] + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + pass + + gateway = TestGateway() + raw_inputs = { + "text": "hello", + "count": 5, + "_meta": {"id": 123}, + "_internal": "data", + } + + result = gateway.extract_pipeline_kwargs(raw_inputs) + + assert result == {"text": "hello", "count": 5} + assert "_meta" not in result + assert "_internal" not in result + + def test_on_error_default_noop(self): + """Default on_error should be a no-op.""" + class TestGateway(CronGateway): + schedule = "0 * * * *" + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [] + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + pass + + gateway = TestGateway() + error = RuntimeError("test error") + + # Should not raise + run_async(gateway.on_error({"text": "test"}, error)) + + def test_on_error_can_be_overridden(self): + """Subclass can override on_error to handle failures.""" + errors_received = [] + + class ErrorTrackingGateway(CronGateway): + schedule = "0 * * * *" + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [] + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + pass + async def on_error(self, inputs: Dict[str, Any], error: Exception) -> None: + errors_received.append((inputs, error)) + + gateway = ErrorTrackingGateway() + error = ValueError("something failed") + + run_async(gateway.on_error({"id": 42}, error)) + + assert len(errors_received) == 1 + assert errors_received[0][0] == {"id": 42} + assert isinstance(errors_received[0][1], ValueError) + def test_abstract_methods_required(self): """Cannot instantiate CronGateway without implementing abstract methods.""" class IncompleteCronGateway(CronGateway): @@ -193,6 +253,71 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: assert received["output"] == {"result": "done"} +class TestGatewayLifecycle: + """Tests for Gateway lifecycle hooks (setup/shutdown).""" + + def test_setup_default_noop(self): + """Default setup() should be a no-op.""" + gateway = IdentityGateway() + # Should not raise + gateway.setup() + + def test_shutdown_default_noop(self): + """Default shutdown() should be a no-op.""" + gateway = IdentityGateway() + # Should not raise + gateway.shutdown() + + def test_setup_can_be_overridden(self): + """Subclass can override setup for initialization.""" + setup_called = [] + + class SetupGateway(APIGateway): + def setup(self) -> None: + setup_called.append(True) + + gateway = SetupGateway() + gateway.setup() + + assert len(setup_called) == 1 + + def test_setup_can_raise_to_indicate_failure(self): + """setup() can raise to indicate configuration error.""" + class FailingGateway(APIGateway): + def setup(self) -> None: + raise RuntimeError("Missing required config") + + gateway = FailingGateway() + + with pytest.raises(RuntimeError, match="Missing required config"): + gateway.setup() + + def test_cron_gateway_lifecycle(self): + """CronGateway can use lifecycle hooks for resource management.""" + events = [] + + class ResourceGateway(CronGateway): + schedule = "0 * * * *" + + def setup(self) -> None: + events.append("setup") + + def shutdown(self) -> None: + events.append("shutdown") + + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: + return [] + + async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + pass + + gateway = ResourceGateway() + gateway.setup() + gateway.shutdown() + + assert events == ["setup", "shutdown"] + + class TestGatewayInheritance: """Tests for Gateway class hierarchy.""" diff --git a/tests/server/test_scheduler.py b/tests/server/test_scheduler.py index 03b1889..f0e3930 100644 --- a/tests/server/test_scheduler.py +++ b/tests/server/test_scheduler.py @@ -18,9 +18,11 @@ class MockCronGateway(CronGateway): schedule = "*/5 * * * *" - def __init__(self): + def __init__(self, use_batch: bool = False, num_threads: int | None = None): self.inputs_to_return: List[Dict[str, Any]] = [] self.completed_calls: List[tuple] = [] + self.use_batch = use_batch + self.num_threads = num_threads async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: return self.inputs_to_return @@ -138,3 +140,56 @@ def test_job_handles_empty_inputs(self, tmp_path, mock_module, mock_lm): ) assert scheduler.job_count == 1 + + +class TestCronGatewayBatchConfig: + """Tests for CronGateway batch mode configuration.""" + + def test_default_batch_settings(self): + """CronGateway has batch disabled by default.""" + gateway = MockCronGateway() + assert gateway.use_batch is False + assert gateway.num_threads is None + + def test_batch_enabled(self): + """CronGateway can enable batch mode.""" + gateway = MockCronGateway(use_batch=True, num_threads=4) + assert gateway.use_batch is True + assert gateway.num_threads == 4 + + def test_register_batch_gateway_logs_batch_info(self, tmp_path, mock_module, mock_lm, caplog): + """Registering a batch gateway logs batch info.""" + import logging + caplog.set_level(logging.INFO) + + scheduler = GatewayScheduler(logs_dir=tmp_path) + gateway = MockCronGateway(use_batch=True, num_threads=8) + gateway.inputs_to_return = [] + + scheduler.register_cron_gateway( + module=mock_module, + gateway=gateway, + lm=mock_lm, + model_name="test-model", + ) + + assert "batch=True" in caplog.text + assert "threads=8" in caplog.text + + def test_register_sequential_gateway_no_batch_in_log(self, tmp_path, mock_module, mock_lm, caplog): + """Registering a sequential gateway doesn't mention batch.""" + import logging + caplog.set_level(logging.INFO) + + scheduler = GatewayScheduler(logs_dir=tmp_path) + gateway = MockCronGateway(use_batch=False) + gateway.inputs_to_return = [] + + scheduler.register_cron_gateway( + module=mock_module, + gateway=gateway, + lm=mock_lm, + model_name="test-model", + ) + + assert "batch=" not in caplog.text From ae3659141df0635149bf98dc954a125a01262a71 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Wed, 24 Dec 2025 16:20:23 -0500 Subject: [PATCH 10/19] Add Discord moderation bot documentation and enhance JobPostingGateway with improved error handling and dry run functionality. Updated ClassifyJobPosting module to clarify its purpose and streamlined comments for better readability. --- .../gateways/job_posting_gateway.py | 27 +- .../modules/classify_job_posting.py | 22 +- .../discord-mod/src/discord_mod/readme.md | 355 ++++++++++++++++++ 3 files changed, 373 insertions(+), 31 deletions(-) create mode 100644 examples/discord-mod/src/discord_mod/readme.md diff --git a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py index 61c0d52..10bae4a 100644 --- a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py +++ b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py @@ -12,7 +12,7 @@ import os from typing import Any, Dict, List -from dspy_cli.gateway import CronGateway +from dspy_cli.gateway import CronGateway, PipelineOutput from discord_mod.utils.discord_client import DiscordClient @@ -32,7 +32,14 @@ class JobPostingGateway(CronGateway): schedule = "*/5 * * * *" # Every 5 minutes def __init__(self): - # Validate required environment variables + self.dry_run = os.environ.get("DRY_RUN", "true").lower() == "true" + self.client: DiscordClient | None = None + self.channel_ids: List[str] = [] + self.jobs_channel_id: str | None = None + self.audit_channel_id: str | None = None + + def setup(self) -> None: + """Validate configuration and create Discord client.""" missing = [] if not os.environ.get("DISCORD_BOT_TOKEN"): missing.append("DISCORD_BOT_TOKEN") @@ -44,13 +51,10 @@ def __init__(self): missing.append("DISCORD_AUDIT_CHANNEL_ID") if missing: - logger.error(f"Missing required environment variables: {', '.join(missing)}") - logger.error("Set these variables") - raise SystemExit(1) + msg = f"Missing required environment variables: {', '.join(missing)}" + logger.error(msg) + raise RuntimeError(msg) - # DRY_RUN: Log actions instead of executing them - self.dry_run = os.environ.get("DRY_RUN", "true").lower() == "true" - self.client = DiscordClient( token=os.environ.get("DISCORD_BOT_TOKEN", ""), ) @@ -63,6 +67,7 @@ def __init__(self): async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: """Fetch recent unprocessed messages from monitored channels.""" + assert self.client is not None, "setup() must be called before get_pipeline_inputs()" inputs = [] for channel_id in self.channel_ids: @@ -92,7 +97,7 @@ async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: logger.info(f"Fetched {len(inputs)} messages to classify") return inputs - async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: + async def on_complete(self, inputs: Dict[str, Any], output: PipelineOutput) -> None: """Take moderation action based on classification result.""" meta = inputs.get("_meta", {}) message_id = meta.get("message_id") @@ -158,7 +163,7 @@ async def on_complete(self, inputs: Dict[str, Any], output: Any) -> None: await self._send_audit_log(action, inputs, output, dry_run=False) async def _send_audit_log( - self, action: str, inputs: Dict[str, Any], output: Any, dry_run: bool + self, action: str, inputs: Dict[str, Any], output: PipelineOutput, dry_run: bool ) -> None: """Send audit log to moderator channel.""" if not self.audit_channel_id: @@ -195,7 +200,7 @@ async def _send_audit_log( logger.warning(f"Failed to send audit log: {e}") async def _log_dry_run_action( - self, action: str, inputs: Dict[str, Any], output: Any + self, action: str, inputs: Dict[str, Any], output: PipelineOutput ) -> None: """Log what would happen without executing.""" meta = inputs.get("_meta", {}) diff --git a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py index 0a6f6b3..f0b0a06 100644 --- a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py +++ b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py @@ -1,5 +1,3 @@ -"""Job posting classifier module - pure LLM logic, no Discord API knowledge.""" - from typing import Literal import dspy @@ -8,11 +6,7 @@ class ClassifyJobPosting(dspy.Module): - """Classify Discord messages as job postings, job-seeking, or general chat. - - This module contains only the LLM classification logic. - The gateway handles Discord API interactions (fetching messages, taking actions). - """ + """Classify Discord messages as job postings, job-seeking, or general chat.""" gateway = JobPostingGateway @@ -26,16 +20,6 @@ def forward( author: str, channel_name: str, ) -> dspy.Prediction: - """Classify a message and determine the appropriate action. - - Args: - message: The Discord message content - author: The message author's username - channel_name: The channel where the message was posted - - Returns: - Prediction with intent, action, and reason fields - """ return self.classifier( message=message, author=author, @@ -46,9 +30,7 @@ def forward( class JobPostingSignature(dspy.Signature): """Classify a Discord message and determine moderation action. - A Job posting or job seeking message will explicitly state: - 1. A user's resume/openness to work - 2. A user's availability to hire (e.g. "I'm looking for a software engineer to hire immediately")""" + A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" message: str = dspy.InputField(desc="The Discord message content") author: str = dspy.InputField(desc="The message author's username") diff --git a/examples/discord-mod/src/discord_mod/readme.md b/examples/discord-mod/src/discord_mod/readme.md new file mode 100644 index 0000000..927d2e0 --- /dev/null +++ b/examples/discord-mod/src/discord_mod/readme.md @@ -0,0 +1,355 @@ +## TODO + +- [ ] Finish `on_complete` explanation in Gateway section (line ~154) +- [ ] Remove leftover outline bullets in Production section (lines ~161-165) +- [ ] Make sure that the thing is still running +- [ ] Paste signature and prompt examples in Appendix +- [ ] Delete notes at top once draft is final + +--- + +# Building a Discord moderation bot with DSPy + +## The Problem + +I am one of the mods for the DSPy community discord. One of the most common things that happens is that people end up posting jobs in the #general channel. We want people to post jobs! But we do not want the main channel to be cluttered with intros or people advertising. + +It doesn't take long to delete the message and send a dm asking them to move it, but it certainly gets annoying. + +Classifying whether or not something is a job posting is pretty easy. We can expect most modern LLMs to do a good job at this. + +Like a REALLY good job. So i expect any errors to come from mostly underspecification rather than from LLM errors. + +For instance: +> Oh yeah I see why GEPA is cool. In my last job, I used MIPRO to improve our LLM-as-a-judge for insurance document relevance inside a chat by 20%, and my manager + our customers were very happy. Ultimately, I’m now looking for the next challenge and I’m excited about applying GEPA to whatever my next problem is (P.S. pls DM if you’d like to chat about hiring me!). + +The primary of the intent of the message is to say that GEPA is cool and validate that they have done it at a company + share the project that they worked on, and secondarily is to get hired. As a team we talked about this, and its about the primary intent, rather than the presence of anything hiring related. + +The other design consideration is that while it would be annoying for people to get messages false positives for a case I haven't considered, its not the end of the world. Certainly I can notice a new error case, and just adjust the bot and redeploy in a relatively timely manner. Any change does not need to be thoroughly tested, because the stakes are quite low so long as it doesn't delete the whole discord server. + +## Designing the LLM pipeline + +The most common case that this is trying to solve for is people posting job descriptions or looking for work posts inside of the general channel. + +This isn't meant to ban users. If it happens to catch and delete a stray non-job spam message, thats upside, but really the usecase is about moving job postings into the correct channel. + +So what do we want this system to do? We want it to detect the intent of a message, and suggest an action. We also want to be notified as mods if there is an action taken, so that we can be aware if things start to break. + +Our pipeline starts to look something like: + +`message, metadata -> (model_reasoning), intent, action, action_reason` + +Let's start to put that into a DSPy signature: + +```python +class JobPostingSignature(dspy.Signature): + """Classify a Discord message and determine moderation action. + + A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" + + message: str = dspy.InputField(desc="The Discord message content") + author: str = dspy.InputField(desc="The message author's username") + channel_name: str = dspy.InputField(desc="The channel where the message was posted") + + intent: Literal["post_job", "seek_job", "other"] = dspy.OutputField( + desc="The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion" + ) + action: Literal["allow", "move", "flag", "delete"] = dspy.OutputField( + desc="Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation" + ) + reason: str = dspy.OutputField( + desc="Brief explanation of the classification and recommended action" + ) +``` + +We pass in the message, author, and the channel it was posted in. All of these could provide relevant information. If a user named `dm_me_for_free_crypto` sends a sketchy message, the LLM should take the username into account. Same with channel. + +In #help-channel, if someone is struggling with a problem that requires a lot of extra help. its totally fine for them to ask for help and offer compensation. It's just the explicit usage of only posting in `#help-channel` that you're looking for an AI engineer that we want to target. + +It's because of this contextual nuance that things look a little fuzzy, rather than the purer classification of `message -> job_posting: bool` pipeline. + +Note that there are two reasoning fields. This is important. The first model reasoning happens when we call the signature with `dspy.ChainOfThought(JobPostingSignature)`. This is to give the model time to deliberate. We are using gpt-5 nano with no reasoning built in, so this will explicitly give the model a chance to discuss the message if there is any nuance. The second reasoning field is meant to be user/moderator facing. After the model has committed to a course of action, we want to show the user "why did you get banned" which is different reasoning than the model's debate about what the intent of the message is. + +### Why use DSPy instead of just writing the prompts myself + +Part of why using DSPy is just because everything is built in already. Structured outputs, retries, plumbling between different LLMs and providers if I ever want to update, are all for free. + +My code can be incredibly simple. + +The module which takes in the signature above looks like: + +```python +class ClassifyJobPosting(dspy.Module): + """Classify Discord messages as job postings, job-seeking, or general chat.""" + + gateway = JobPostingGateway + + def __init__(self): + super().__init__() + self.classifier = dspy.ChainOfThought(JobPostingSignature) + + def forward(self, message: str, author: str, channel_name: str) -> dspy.Prediction: + return self.classifier(message=message, author=author, channel_name=channel_name,) +``` + +Then the only thing that I need around this is the discord network code. + +Its like 8 real lines of code for an LLM pipeline, plumbing included, wrapping around the structured inputs and outputs. + +## Building the gateway + +The LLM logic is pretty simple. The most complex part is designing the system with discord. + +There are two main ways that we can build this bot: +1. Realtime streaming +2. Running on a cronjob + +We opt for (2) the cron approach. Mostly because the realtime streaming requires us to maintain a websocket connection. If the dspy server was so popular that we had a large volume of messages, I might take on the higher complexity of building that. The dspy server averages less than 20 messages every 5 minutes. If we instead just build something that will check the last 20 messages every 5 minutes, its totally fine. If a job posting is live on the server for 5 minutes, noone cares. This constraint would be different for different servers, but these are the constraints of the problem we are trying to solve without overengineering. + +We need to set up a discord bot token with access to read messages, send messages, and delete messages. + +You can see the discord tutorial for how to do that (here)[https://discord.com/developers/docs/quick-start/getting-started]. + +The actual behavior of this will be as follows: +Every 5 minutes: +1. Gather the last 20 messages +2. Skip any that have already been processed +3. Classify as "move", "flag", "delete", or "allow" +4. Take the relevant action for "move", "flag", "delete", and send an audit message into the moderator only channel +- Move moves the message into the #jobs channel, "flag" adds an emoji reaction and sends an audit message for the mods to review, "delete", well, deletes, and "allow" does nothing. + +The routing logic is simplified by using `dspy-cli`. + +There are a few different kinds of entry points you may want for any DSPy application. The two that `dspy-cli` currently supports are **api-based** and **cron-based**. + +You might just want to have your modules as named endpoints so you can send a POST request to `/{ModuleName}`. In this case, your post requests would directly have the inputs that you want for your `Module.forward` method. You might also want to have a webhook setup, where your endpoint takes in some webhook payload, say from GitHub, extracts some data from it, such as fetching the code of the PR that triggered the webhook, and then passes that code into your module. Your real code might look like: `dspy.ReAct("files: Dict[str, str] -> review", tools=[file_search, web_search, run_code, ...])` You need to get all of the files and put them into whatever format makes sense. For this, you want a layer to sit in between the api and your LLM logic. Here `APIGateway` makes sense as your middleware for your LLM logic, + +For this discord case, we want to gather a bunch of inputs every so often, and run batch inference over them. + +### JobPostingGateway + +JobPostingGateway subclasses CronGateway. This is how you specify your specific data loading behavior. In our case, it will load the data, and take actions after. + +CronGateway is an ABC with two core methods: + +1. **`get_pipeline_inputs`**: Fetches your data and returns a list of input dictionaries for the pipeline to process. Each dict contains the kwargs for your module's `forward()` method. You can also include a `_meta` key for data needed in `on_complete` but not by the pipeline itself (like message IDs or channel IDs). + +2. **`on_complete`**: Runs after each successful pipeline execution. This is where you take action based on the LLM's output. It receives both the original inputs (including `_meta`) and the pipeline output. + +There's also an optional `on_error` method for handling failures. + +Here's a simplified version of our gateway: + +```python +class JobPostingGateway(CronGateway): + schedule = "*/5 * * * *" # Every 5 minutes + + def setup(self) -> None: + """Validate config and create Discord client.""" + self.client = DiscordClient(token=os.environ["DISCORD_BOT_TOKEN"]) + self.channel_ids = os.environ["DISCORD_CHANNEL_IDS"].split(",") + + async def get_pipeline_inputs(self) -> list[dict]: + """Fetch recent messages from monitored channels.""" + inputs = [] + for channel_id in self.channel_ids: + messages = await self.client.get_recent_messages(channel_id, limit=20) + for msg in messages: + if msg["author"].get("bot"): + continue + inputs.append({ + "message": msg["content"], + "author": msg["author"]["username"], + "channel_name": msg.get("channel_name", "unknown"), + "_meta": { + "message_id": msg["id"], + "channel_id": channel_id, + "author_id": msg["author"]["id"], + }, + }) + return inputs + + async def on_complete(self, inputs: dict, output: PipelineOutput) -> None: + """Take moderation action based on classification result.""" + meta = inputs["_meta"] + action = output.get("action", "allow") + + if action == "allow": + return + + if action == "move": + # Repost in jobs channel, delete original, DM user + await self.client.send_message( + self.jobs_channel_id, + f"**Moved from <#{meta['channel_id']}>**\n{inputs['message']}", + ) + await self.client.delete_message(meta["channel_id"], meta["message_id"]) + await self.client.send_dm( + meta["author_id"], + "Your job posting was moved to the jobs channel.", + ) + + elif action == "flag": + await self.client.add_reaction(meta["channel_id"], meta["message_id"], "⚠️") + + elif action == "delete": + await self.client.delete_message(meta["channel_id"], meta["message_id"]) + await self.client.send_dm(meta["author_id"], output.get("reason", "")) +``` + +### Batch Processing + +For higher throughput, CronGateway supports batch mode which processes all inputs in parallel using DSPy's `module.batch()`: + +```python +class JobPostingGateway(CronGateway): + schedule = "*/5 * * * *" + use_batch = True # Enable parallel processing + num_threads = 4 # Number of concurrent threads (optional) + max_errors = 10 # Stop batch if this many errors occur (optional) +``` + +With batch mode enabled, the scheduler will call your module's `batch()` method instead of running `forward()` sequentially. This is useful when you have many inputs and want to parallelize LLM calls. The `on_complete` callback still runs once per input after all batch results return + +## Production considerations + +"production" is a loose word here because of the small scale, but this is deployed live. + + +5. Production Considerations (2-3 min) + - Dry-run mode + - Audit logging + - DM notifications to users + - Fly.io deployment + +Because this is such a small project, there wasn't a great dev environment nor was it worth it to set up one. I sent messages into #general to test this. Before I enabled any actions that would actually remove messages, I set up a dry run mode that would analyze messages and send a dry run audit message into #moderator-only. I saw that it was correctly flagging the examples that I put in, and that was enough to turn off dry run mode. + +We also want to notify users after they have a message moved. This is a simple DM, but important from a UX perspective. + +### Deployment + +We deploy this onto Fly.io. We want this to be a permananelty running machine that will trigger itself with the python process every 5 minutes. + +# TODO: Make sure that it is still running + +Fly automatically scales your workload to 2 machines, and will pause if there is not enough external traffic. For this deployment, there will definitionally be 0 traffic, so we need to get around the auto-scaling. We also don't want 2 machines. (1) I don't want to pay for that and (2) We havent built in any persistence or deduplication mechanisms. If there are two machines running, they might both pick up the same messages. + +We need to set some environment variables in order to tell which channels to look at. + + +## Results and Lessons + +After I made this bot, there were uh no job postings that it flagged because I think people are not active on discord this week. It was launched right before the holidays. I hope to see some more job postings to move in the next few weeks. + +OR they got so scared by my bot that noone dared try anything. + +We will see if its useful when things pick back up in the new year. + +Notes: +Is this the most robust setup? Nah this is a discord bot without a ton of traffic. +Could someone prompt inject this? Like very potentially! Does it matter? No not at all. The bot has no tool access, and its not like the prompt is secret. There are no tools to access other messages, etc + +## Appendix + +If you are curious about how the dspy signature gets turned into a prompt, it looks like the following. + +The signature is: +```python +class JobPostingSignature(dspy.Signature): + """Classify a Discord message and determine moderation action. + + A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" + + message: str = dspy.InputField(desc="The Discord message content") + author: str = dspy.InputField(desc="The message author's username") + channel_name: str = dspy.InputField(desc="The channel where the message was posted") + + intent: Literal["post_job", "seek_job", "other"] = dspy.OutputField( + desc="The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion" + ) + action: Literal["allow", "move", "flag", "delete"] = dspy.OutputField( + desc="Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation" + ) + reason: str = dspy.OutputField( + desc="Brief explanation of the classification and recommended action" + ) +``` + +DSPy has a concept of an "adapter" which is a class that determines how a signature gets turned into a prompt, and also how the answers get extracted on the other end. + +The rough outline for the adapters is: +```python +System prompt: +1. Inputs +2. Outputs +3. Task + +User prompt: +Field name: value for field, value in inputs +``` + +The exact prompt that gets sent to the LLM is: +``` +System message: + +Your input fields are: +1. `message` (str): The Discord message content +2. `author` (str): The message author's username +3. `channel_name` (str): The channel where the message was posted +Your output fields are: +1. `intent` (Literal['post_job', 'seek_job', 'other']): The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion +2. `action` (Literal['allow', 'move', 'flag', 'delete']): Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation +3. `reason` (str): Brief explanation of the classification and recommended action +All interactions will be structured in the following way, with the appropriate values filled in. + +[[ ## message ## ]] +{message} + +[[ ## author ## ]] +{author} + +[[ ## channel_name ## ]] +{channel_name} + +[[ ## intent ## ]] +{intent} # note: the value you produce must exactly match (no extra characters) one of: post_job; seek_job; other + +[[ ## action ## ]] +{action} # note: the value you produce must exactly match (no extra characters) one of: allow; move; flag; delete + +[[ ## reason ## ]] +{reason} + +[[ ## completed ## ]] +In adhering to this structure, your objective is: + Classify a Discord message and determine moderation action. + + A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others + +User message: + +[[ ## message ## ]] +Hey everyone! I'm a senior Python developer with 5 years of experience looking for new opportunities. Open to remote work! + +[[ ## author ## ]] +job_seeker_123 + +[[ ## channel_name ## ]] +general-chat + +Respond with the corresponding output fields, starting with the field `[[ ## intent ## ]]` (must be formatted as a valid Python Literal['post_job', 'seek_job', 'other']), then `[[ ## action ## ]]` (must be formatted as a valid Python Literal['allow', 'move', 'flag', 'delete']), then `[[ ## reason ## ]]`, and then ending with the marker for `[[ ## completed ## ]]`. +``` + +And the LM responds with: +``` +[[ ## intent ## ]] +seek_job + +[[ ## action ## ]] +move + +[[ ## reason ## ]] +The message expresses the user's intent to seek job opportunities, which is more appropriate for a jobs channel rather than a general chat. + +[[ ## completed ## ]] +``` \ No newline at end of file From 447be22ae8a8de0b680ac130c50a8e53f1851ed9 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Wed, 24 Dec 2025 16:35:22 -0500 Subject: [PATCH 11/19] bump uv lock --- examples/discord-mod/uv.lock | 36 ++---------------------------------- 1 file changed, 2 insertions(+), 34 deletions(-) diff --git a/examples/discord-mod/uv.lock b/examples/discord-mod/uv.lock index 5ed6409..91fbef7 100644 --- a/examples/discord-mod/uv.lock +++ b/examples/discord-mod/uv.lock @@ -506,7 +506,7 @@ dev = [ requires-dist = [ { name = "audioop-lts" }, { name = "dspy-ai", specifier = ">=3.0.3" }, - { name = "dspy-cli", editable = "../../" }, + { name = "dspy-cli", git = "https://github.com/cmpnd-ai/dspy-cli.git?rev=isaac%2Fgateways" }, { name = "httpx", specifier = ">=0.27.0" }, { name = "py-cord", extras = ["voice"], specifier = ">=2.6.1" }, { name = "pytest", marker = "extra == 'dev'", specifier = ">=7.0" }, @@ -609,7 +609,7 @@ wheels = [ [[package]] name = "dspy-cli" version = "0.1.9" -source = { editable = "../../" } +source = { git = "https://github.com/cmpnd-ai/dspy-cli.git?rev=isaac%2Fgateways#ae3659141df0635149bf98dc954a125a01262a71" } dependencies = [ { name = "apscheduler" }, { name = "asgi-lifespan" }, @@ -624,38 +624,6 @@ dependencies = [ { name = "uvicorn", extra = ["standard"] }, ] -[package.metadata] -requires-dist = [ - { name = "apscheduler", specifier = ">=3.10.0" }, - { name = "asgi-lifespan", specifier = ">=2.0.0" }, - { name = "black", marker = "extra == 'dev'", specifier = ">=23.0" }, - { name = "click", specifier = ">=8.0" }, - { name = "dspy-ai", specifier = ">=3.0.3" }, - { name = "fastapi", specifier = ">=0.100" }, - { name = "fastmcp", specifier = ">=2.0.0" }, - { name = "httpx", marker = "extra == 'dev'", specifier = ">=0.24" }, - { name = "mkdocs", marker = "extra == 'docs'", specifier = ">=1.6.0" }, - { name = "mkdocs-material", marker = "extra == 'docs'", specifier = ">=9.5.0" }, - { name = "mkdocstrings", extras = ["python"], marker = "extra == 'docs'", specifier = ">=0.24.0" }, - { name = "pydantic", specifier = ">=2.0" }, - { name = "pymdown-extensions", marker = "extra == 'docs'", specifier = ">=10.7.0" }, - { name = "pytest", marker = "extra == 'dev'", specifier = ">=7.0" }, - { name = "pytest-asyncio", marker = "extra == 'dev'", specifier = ">=0.21" }, - { name = "python-dotenv", specifier = ">=1.0" }, - { name = "pyyaml", specifier = ">=6.0" }, - { name = "requests", specifier = ">=2.28" }, - { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.1.0" }, - { name = "uvicorn", extras = ["standard"], specifier = ">=0.20" }, -] -provides-extras = ["dev", "docs"] - -[package.metadata.requires-dev] -dev = [ - { name = "docker", specifier = ">=7.1.0" }, - { name = "pytest", specifier = ">=7.4.0" }, - { name = "python-multipart", specifier = ">=0.0.20" }, -] - [[package]] name = "email-validator" version = "2.3.0" From 4c24c9a3f58e3265e2309285113e35dcd8fded5c Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Fri, 26 Dec 2025 09:35:29 -0500 Subject: [PATCH 12/19] Add a store to process messages --- .../gateways/job_posting_gateway.py | 14 ++ .../src/discord_mod/utils/processed_store.py | 126 ++++++++++++++++++ 2 files changed, 140 insertions(+) create mode 100644 examples/discord-mod/src/discord_mod/utils/processed_store.py diff --git a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py index 10bae4a..f2d48d1 100644 --- a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py +++ b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py @@ -15,6 +15,7 @@ from dspy_cli.gateway import CronGateway, PipelineOutput from discord_mod.utils.discord_client import DiscordClient +from discord_mod.utils.processed_store import ProcessedMessageStore logger = logging.getLogger(__name__) @@ -37,6 +38,7 @@ def __init__(self): self.channel_ids: List[str] = [] self.jobs_channel_id: str | None = None self.audit_channel_id: str | None = None + self.processed_store: ProcessedMessageStore | None = None def setup(self) -> None: """Validate configuration and create Discord client.""" @@ -61,10 +63,16 @@ def setup(self) -> None: self.channel_ids = os.environ.get("DISCORD_CHANNEL_IDS", "").split(",") self.jobs_channel_id = os.environ.get("DISCORD_JOBS_CHANNEL_ID") self.audit_channel_id = os.environ.get("DISCORD_AUDIT_CHANNEL_ID") + self.processed_store = ProcessedMessageStore() if self.dry_run: logger.info("DRY_RUN mode - actions will be logged, not executed") + def shutdown(self) -> None: + """Flush processed messages to disk on shutdown.""" + if self.processed_store: + self.processed_store.flush() + async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: """Fetch recent unprocessed messages from monitored channels.""" assert self.client is not None, "setup() must be called before get_pipeline_inputs()" @@ -82,6 +90,9 @@ async def get_pipeline_inputs(self) -> List[Dict[str, Any]]: for msg in messages: if msg.get("author", {}).get("bot", False): continue + + if self.processed_store.is_processed(msg["id"]): + continue inputs.append({ "message": msg["content"], @@ -113,6 +124,9 @@ async def on_complete(self, inputs: Dict[str, Any], output: PipelineOutput) -> N f"intent={intent}, action={action}, reason={reason}" ) + if message_id: + self.processed_store.mark_processed(message_id) + if action == "allow": return diff --git a/examples/discord-mod/src/discord_mod/utils/processed_store.py b/examples/discord-mod/src/discord_mod/utils/processed_store.py new file mode 100644 index 0000000..33d8ee2 --- /dev/null +++ b/examples/discord-mod/src/discord_mod/utils/processed_store.py @@ -0,0 +1,126 @@ +"""Simple file-based store for tracking processed message IDs. + +Prevents reprocessing the same messages across restarts. +Uses a JSON file that can be persisted on a Fly.io volume. +""" + +import json +import logging +import os +import time +from pathlib import Path +from typing import Set + +logger = logging.getLogger(__name__) + +DEFAULT_TTL_DAYS = 7 + + +def _get_default_path() -> str: + """Get default path, preferring /data (Fly.io volume) if available.""" + fly_path = Path("/data") + if fly_path.exists() and fly_path.is_dir(): + return "/data/processed_messages.json" + return "processed_messages.json" + + +class ProcessedMessageStore: + """Track processed message IDs with automatic cleanup of old entries. + + Uses debounced saving to avoid excessive disk writes when processing + many messages in sequence. + """ + + def __init__( + self, + path: str | None = None, + ttl_days: int = DEFAULT_TTL_DAYS, + save_interval: float = 5.0, + cleanup_interval: float = 3600.0, # 1 hour + ): + self.path = Path(path or os.environ.get("PROCESSED_MESSAGES_PATH") or _get_default_path()) + self.ttl_seconds = ttl_days * 24 * 60 * 60 + self.save_interval = save_interval + self.cleanup_interval = cleanup_interval + self._data: dict[str, float] = {} # message_id -> timestamp + self._dirty = False + self._last_save: float = 0 + self._last_cleanup: float = time.time() + self._load() + + def _load(self) -> None: + """Load existing data from file.""" + if self.path.exists(): + try: + with open(self.path) as f: + self._data = json.load(f) + logger.info(f"Loaded {len(self._data)} processed message IDs from {self.path}") + except (json.JSONDecodeError, IOError) as e: + logger.warning(f"Failed to load processed messages: {e}") + self._data = {} + else: + logger.info(f"No existing processed messages file at {self.path}") + + def _save(self, force: bool = False) -> None: + """Save data to file if dirty and interval elapsed (or forced).""" + if not self._dirty: + return + + now = time.time() + if not force and (now - self._last_save) < self.save_interval: + return + + try: + self.path.parent.mkdir(parents=True, exist_ok=True) + tmp_path = self.path.with_suffix(".tmp") + with open(tmp_path, "w") as f: + json.dump(self._data, f) + os.replace(tmp_path, self.path) + self._dirty = False + self._last_save = now + except IOError as e: + logger.error(f"Failed to save processed messages: {e}") + + def _cleanup_old(self, force: bool = False) -> None: + """Remove entries older than TTL (debounced unless forced).""" + now = time.time() + if not force and (now - self._last_cleanup) < self.cleanup_interval: + return + + cutoff = now - self.ttl_seconds + old_count = len(self._data) + self._data = {k: v for k, v in self._data.items() if v > cutoff} + removed = old_count - len(self._data) + self._last_cleanup = now + if removed > 0: + self._dirty = True + logger.info(f"Cleaned up {removed} old processed message IDs") + + def is_processed(self, message_id: str) -> bool: + """Check if a message has already been processed.""" + return message_id in self._data + + def mark_processed(self, message_id: str) -> None: + """Mark a message as processed (debounced save and cleanup).""" + self._data[message_id] = time.time() + self._dirty = True + self._cleanup_old() + self._save() + + def mark_batch_processed(self, message_ids: Set[str]) -> None: + """Mark multiple messages as processed (immediate save).""" + now = time.time() + for mid in message_ids: + self._data[mid] = now + self._dirty = True + self._cleanup_old(force=True) + self._save(force=True) + + def flush(self) -> None: + """Force save any pending changes and cleanup old entries.""" + self._cleanup_old(force=True) + self._save(force=True) + + def get_unprocessed(self, message_ids: Set[str]) -> Set[str]: + """Filter to only unprocessed message IDs.""" + return message_ids - set(self._data.keys()) From c515b166aad4454fa1919c02ece0ad0ea3e8fd32 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Mon, 29 Dec 2025 09:56:49 -0500 Subject: [PATCH 13/19] update sig string to call out cryptoi --- .../discord-mod/src/discord_mod/modules/classify_job_posting.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py index f0b0a06..624ff13 100644 --- a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py +++ b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py @@ -29,6 +29,8 @@ def forward( class JobPostingSignature(dspy.Signature): """Classify a Discord message and determine moderation action. + + The subject of the Discord server is DSPy, the framework for building and optimizing LLM applications. The server has nothing to do with blockchain, crypto, or NFTs, and these are generally spam. A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" From 36161accf7eb0ac3a92c3a0b66bc6b113be66c9f Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Mon, 29 Dec 2025 09:57:04 -0500 Subject: [PATCH 14/19] add fly.toml --- examples/discord-mod/fly.toml | 27 +++++++++++++++++++++++++++ 1 file changed, 27 insertions(+) create mode 100644 examples/discord-mod/fly.toml diff --git a/examples/discord-mod/fly.toml b/examples/discord-mod/fly.toml new file mode 100644 index 0000000..24251ec --- /dev/null +++ b/examples/discord-mod/fly.toml @@ -0,0 +1,27 @@ +# fly.toml app configuration file generated for discord-mod on 2025-12-16T18:08:46-05:00 +# +# See https://fly.io/docs/reference/configuration/ for information about how to use this file. +# + +app = 'discord-mod' +primary_region = 'ewr' + +[build] + +[http_service] + internal_port = 8000 + force_https = true + auto_stop_machines = false + auto_start_machines = true + min_machines_running = 1 + processes = ['app'] + +[[vm]] + memory = '1gb' + cpu_kind = 'shared' + cpus = 1 + memory_mb = 1024 + +[mounts] + source = "processed_data" + destination = "/data" \ No newline at end of file From baf0d3f4000f29fa512c2ff3a358d9db94702338 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Mon, 29 Dec 2025 09:58:20 -0500 Subject: [PATCH 15/19] Update dspy-cli dependency to use specific GitHub branch in pyproject.toml and remove local editable install configuration. --- examples/discord-mod/pyproject.toml | 4 ---- 1 file changed, 4 deletions(-) diff --git a/examples/discord-mod/pyproject.toml b/examples/discord-mod/pyproject.toml index 22eff64..53b68f0 100644 --- a/examples/discord-mod/pyproject.toml +++ b/examples/discord-mod/pyproject.toml @@ -23,9 +23,5 @@ dev = [ "pytest-asyncio>=0.21", ] -# Use local editable install of dspy-cli for development -[tool.uv.sources] -dspy-cli = { path = "../..", editable = true } - [tool.setuptools.packages.find] where = ["src"] From f236ba79e33ff83450b779ffd2f894025c0364d3 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Mon, 29 Dec 2025 20:08:19 -0500 Subject: [PATCH 16/19] blog draft v1 --- examples/discord-mod/README.md | 5 +- .../gateways/job_posting_gateway.py | 2 +- .../discord-mod/src/discord_mod/readme.md | 268 +++++++++++++----- 3 files changed, 200 insertions(+), 75 deletions(-) diff --git a/examples/discord-mod/README.md b/examples/discord-mod/README.md index ea69496..73295c9 100644 --- a/examples/discord-mod/README.md +++ b/examples/discord-mod/README.md @@ -65,7 +65,7 @@ src/discord_mod/ DISCORD_AUDIT_CHANNEL_ID=444555666 # Channel for moderation audit logs # Optional - DRY_RUN=true # Log actions without executing (default: true) + DRY_RUN=true # Log actions without executing (default: false) USE_SAMPLE_DATA=true # Use sample messages instead of Discord API ``` @@ -83,7 +83,7 @@ src/discord_mod/ | `DISCORD_JOBS_CHANNEL_ID` | ✅ | Channel ID where job posts are moved to | | `OPENAI_API_KEY` | ✅ | OpenAI API key for LLM classification | | `DISCORD_AUDIT_CHANNEL_ID` | ✅ | Channel for audit logs (move/flag/delete actions) | -| `DRY_RUN` | ❌ | Set to `false` to execute real actions (default: `true`) | +| `DRY_RUN` | ❌ | Set to `true` to log actions without executing (default: `false`) | | `USE_SAMPLE_DATA` | ❌ | Set to `true` to use sample messages for testing | ## Running @@ -101,6 +101,7 @@ The `ClassifyJobPosting` module uses a `CronGateway` with `schedule = "*/5 * * * ## Deployment: +fly volumes create processed_data --size 1 fly scale count 1 fly deploy --ha=false diff --git a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py index f2d48d1..f3a6f32 100644 --- a/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py +++ b/examples/discord-mod/src/discord_mod/gateways/job_posting_gateway.py @@ -33,7 +33,7 @@ class JobPostingGateway(CronGateway): schedule = "*/5 * * * *" # Every 5 minutes def __init__(self): - self.dry_run = os.environ.get("DRY_RUN", "true").lower() == "true" + self.dry_run = os.environ.get("DRY_RUN", "false").lower() == "true" self.client: DiscordClient | None = None self.channel_ids: List[str] = [] self.jobs_channel_id: str | None = None diff --git a/examples/discord-mod/src/discord_mod/readme.md b/examples/discord-mod/src/discord_mod/readme.md index 927d2e0..f34d69a 100644 --- a/examples/discord-mod/src/discord_mod/readme.md +++ b/examples/discord-mod/src/discord_mod/readme.md @@ -1,10 +1,5 @@ ## TODO - -- [ ] Finish `on_complete` explanation in Gateway section (line ~154) -- [ ] Remove leftover outline bullets in Production section (lines ~161-165) -- [ ] Make sure that the thing is still running -- [ ] Paste signature and prompt examples in Appendix -- [ ] Delete notes at top once draft is final +- [ ] Proofread and adjust for structure. --- @@ -14,30 +9,40 @@ I am one of the mods for the DSPy community discord. One of the most common things that happens is that people end up posting jobs in the #general channel. We want people to post jobs! But we do not want the main channel to be cluttered with intros or people advertising. -It doesn't take long to delete the message and send a dm asking them to move it, but it certainly gets annoying. +It doesn't take long to delete the message and send a DM asking them to move it, but it certainly gets annoying. -Classifying whether or not something is a job posting is pretty easy. We can expect most modern LLMs to do a good job at this. +The good news is that classifying whether something is a job posting is pretty easy. We can expect most modern LLMs to do a good job at this. -Like a REALLY good job. So i expect any errors to come from mostly underspecification rather than from LLM errors. +Like a REALLY good job. So I expect any errors to come from underspecification rather than LLM errors. For instance: > Oh yeah I see why GEPA is cool. In my last job, I used MIPRO to improve our LLM-as-a-judge for insurance document relevance inside a chat by 20%, and my manager + our customers were very happy. Ultimately, I’m now looking for the next challenge and I’m excited about applying GEPA to whatever my next problem is (P.S. pls DM if you’d like to chat about hiring me!). -The primary of the intent of the message is to say that GEPA is cool and validate that they have done it at a company + share the project that they worked on, and secondarily is to get hired. As a team we talked about this, and its about the primary intent, rather than the presence of anything hiring related. - -The other design consideration is that while it would be annoying for people to get messages false positives for a case I haven't considered, its not the end of the world. Certainly I can notice a new error case, and just adjust the bot and redeploy in a relatively timely manner. Any change does not need to be thoroughly tested, because the stakes are quite low so long as it doesn't delete the whole discord server. +The primary intent of the message is to say that GEPA is cool, validate that they've used it at a company, and share the project they worked on. Getting hired is secondary. As a team we talked about this, and it's about the primary intent, rather than the presence of anything hiring-related. ## Designing the LLM pipeline -The most common case that this is trying to solve for is people posting job descriptions or looking for work posts inside of the general channel. +This bot isn't meant to ban users or be a catch-all spam detector. If it happens to catch and delete a stray non-job spam message, that's upside, but really the use case is about moving job postings into the correct channel. -This isn't meant to ban users. If it happens to catch and delete a stray non-job spam message, thats upside, but really the usecase is about moving job postings into the correct channel. +### Sketching out the shape -So what do we want this system to do? We want it to detect the intent of a message, and suggest an action. We also want to be notified as mods if there is an action taken, so that we can be aware if things start to break. +So what do we want this system to do? We want it to detect if the primary intent of a message is job-related or not, and suggest an action. We also want to be notified as mods if there is an action taken, so that we can be aware if things start to break. Our pipeline starts to look something like: -`message, metadata -> (model_reasoning), intent, action, action_reason` +``` +INPUTS: +- message: str +- metadata + +OUTPUTS: +- internal_model_reasoning: str +- intent: POST, SEEK or NEITHER +- action: MOVE, FLAG, DELETE, ALLOW +- action_reason: str +``` + +### Convert to DSPy Let's start to put that into a DSPy signature: @@ -64,15 +69,19 @@ class JobPostingSignature(dspy.Signature): We pass in the message, author, and the channel it was posted in. All of these could provide relevant information. If a user named `dm_me_for_free_crypto` sends a sketchy message, the LLM should take the username into account. Same with channel. -In #help-channel, if someone is struggling with a problem that requires a lot of extra help. its totally fine for them to ask for help and offer compensation. It's just the explicit usage of only posting in `#help-channel` that you're looking for an AI engineer that we want to target. +In `#help-channel`, if someone is struggling with a problem that requires a lot of extra help, it's totally fine for them to ask for help and offer compensation. It's only when someone posts exclusively in `#help-channel` saying they're looking for an AI engineer that we want to flag it. It's because of this contextual nuance that things look a little fuzzy, rather than the purer classification of `message -> job_posting: bool` pipeline. -Note that there are two reasoning fields. This is important. The first model reasoning happens when we call the signature with `dspy.ChainOfThought(JobPostingSignature)`. This is to give the model time to deliberate. We are using gpt-5 nano with no reasoning built in, so this will explicitly give the model a chance to discuss the message if there is any nuance. The second reasoning field is meant to be user/moderator facing. After the model has committed to a course of action, we want to show the user "why did you get banned" which is different reasoning than the model's debate about what the intent of the message is. +Note that there are two reasoning fields. This is a design choice. -### Why use DSPy instead of just writing the prompts myself +The first model reasoning happens when we call the signature with `dspy.ChainOfThought(JobPostingSignature)`. This is to give the model time to deliberate. We are using `gpt-5-nano` with no reasoning built in, so this will explicitly give the model a chance to discuss the message if there is any nuance. This is similar to setting the model thinking parameter. -Part of why using DSPy is just because everything is built in already. Structured outputs, retries, plumbling between different LLMs and providers if I ever want to update, are all for free. +The second reasoning field is meant to be user/moderator facing. After the model has committed to a course of action, we want to show the user and us as the mods, "why did you get banned" which is different reasoning than the model's internal debate about what the intent of the message is. + +#### Why use DSPy instead of just writing the prompts myself + +Part of why I use DSPy is that everything is built in already. Structured outputs, retries, plumbing between different LLMs and providers if I ever want to update, are all for free. My code can be incredibly simple. @@ -80,8 +89,6 @@ The module which takes in the signature above looks like: ```python class ClassifyJobPosting(dspy.Module): - """Classify Discord messages as job postings, job-seeking, or general chat.""" - gateway = JobPostingGateway def __init__(self): @@ -92,45 +99,63 @@ class ClassifyJobPosting(dspy.Module): return self.classifier(message=message, author=author, channel_name=channel_name,) ``` -Then the only thing that I need around this is the discord network code. - -Its like 8 real lines of code for an LLM pipeline, plumbing included, wrapping around the structured inputs and outputs. +Then the only thing I need around this is the Discord network code. It's like 8 real lines of code for an LLM pipeline, plumbing included. The LLM logic is simple—to actually wire it up to Discord, I need a gateway. ## Building the gateway -The LLM logic is pretty simple. The most complex part is designing the system with discord. +The most complex part is integrating with Discord. There are two main ways that we can build this bot: 1. Realtime streaming 2. Running on a cronjob -We opt for (2) the cron approach. Mostly because the realtime streaming requires us to maintain a websocket connection. If the dspy server was so popular that we had a large volume of messages, I might take on the higher complexity of building that. The dspy server averages less than 20 messages every 5 minutes. If we instead just build something that will check the last 20 messages every 5 minutes, its totally fine. If a job posting is live on the server for 5 minutes, noone cares. This constraint would be different for different servers, but these are the constraints of the problem we are trying to solve without overengineering. +We opt for (2) the cron approach. Mostly because the realtime streaming requires us to maintain a websocket connection. If the dspy server was so popular that we had a large volume of messages, I might take on the higher complexity of building that. The dspy server averages way less than 20 messages every 5 minutes. -We need to set up a discord bot token with access to read messages, send messages, and delete messages. +If we instead just build something that checks the last 20 messages every 5 minutes, it's totally fine. If a job posting is live on the server for 5 minutes, no one cares. This constraint would be different for different servers, but these are the constraints of the problem I'm solving without overengineering. -You can see the discord tutorial for how to do that (here)[https://discord.com/developers/docs/quick-start/getting-started]. - -The actual behavior of this will be as follows: +The behavior will be as follows: Every 5 minutes: 1. Gather the last 20 messages 2. Skip any that have already been processed 3. Classify as "move", "flag", "delete", or "allow" 4. Take the relevant action for "move", "flag", "delete", and send an audit message into the moderator only channel -- Move moves the message into the #jobs channel, "flag" adds an emoji reaction and sends an audit message for the mods to review, "delete", well, deletes, and "allow" does nothing. +- "move" moves the message into the #jobs channel, +- "flag" adds an emoji reaction and sends an audit message for the mods to review, +- "delete", well, deletes the message +- "allow" does nothing + +To implement this, I use `dspy-cli` to handle the routing and scheduling. + +### dspy-cli explanation + +[`dspy-cli`](https://github.com/cmpnd-ai/dspy-cli) is a command line tool to help you create, scaffold, and deploy dspy applications. You can serve a `dspy-cli` created project by running `dspy-cli serve`, and it will bring up a local endpoint for you that you can test against. It is also what created our initial project directory structure. + +The default serve endpoint has your modules as named endpoints so you can send a POST request to `/{ModuleName}`. In this case, your post requests would directly have the inputs that you want for your `Module.forward` method. + +There are a few different kinds of alternative entry points you may want for any DSPy application. The two that `dspy-cli` currently supports are **API-based** and **cron-based**. + +**API-based** + +For some cases, you want a layer to sit in between the calling api and your LLM logic. `APIGateway` makes sense here for your LLM logic. + +If you were to create a PR review bot, you might want a webhook setup. Your endpoint takes in a webhook payload from GitHub, extracts some data from it, uses that to fetch the code of the PR that triggered the webhook, and passes that code into your module. -The routing logic is simplified by using `dspy-cli`. +Your DSPy code might look like: `dspy.ReAct("files: Dict[str, str] -> review", tools=[file_search, web_search, run_code, ...])` -There are a few different kinds of entry points you may want for any DSPy application. The two that `dspy-cli` currently supports are **api-based** and **cron-based**. +In order to call this, you need a loading step to get all of the files and put them into whatever format makes sense. -You might just want to have your modules as named endpoints so you can send a POST request to `/{ModuleName}`. In this case, your post requests would directly have the inputs that you want for your `Module.forward` method. You might also want to have a webhook setup, where your endpoint takes in some webhook payload, say from GitHub, extracts some data from it, such as fetching the code of the PR that triggered the webhook, and then passes that code into your module. Your real code might look like: `dspy.ReAct("files: Dict[str, str] -> review", tools=[file_search, web_search, run_code, ...])` You need to get all of the files and put them into whatever format makes sense. For this, you want a layer to sit in between the api and your LLM logic. Here `APIGateway` makes sense as your middleware for your LLM logic, -For this discord case, we want to gather a bunch of inputs every so often, and run batch inference over them. +**cron-based** + +`CronGateway` is what you use when your trigger is periodic rather than based on a call. + +For this discord case, we want to gather a bunch of inputs every so often, and run batch inference over them, so `CronGateway` makes more sense. We will subclass it to implement the loading logic. ### JobPostingGateway -JobPostingGateway subclasses CronGateway. This is how you specify your specific data loading behavior. In our case, it will load the data, and take actions after. +`JobPostingGateway` subclasses `CronGateway`. This is how you specify your data loading behavior. In our case, it loads the data and takes actions afterward. -CronGateway is an ABC with two core methods: +`CronGateway` is an ABC with two core methods: 1. **`get_pipeline_inputs`**: Fetches your data and returns a list of input dictionaries for the pipeline to process. Each dict contains the kwargs for your module's `forward()` method. You can also include a `_meta` key for data needed in `on_complete` but not by the pipeline itself (like message IDs or channel IDs). @@ -197,60 +222,117 @@ class JobPostingGateway(CronGateway): await self.client.send_dm(meta["author_id"], output.get("reason", "")) ``` -### Batch Processing +## Production considerations -For higher throughput, CronGateway supports batch mode which processes all inputs in parallel using DSPy's `module.batch()`: +"production" is a loose word here because of the small scale, but this is deployed live, and actively affecting DSPy discord users. -```python -class JobPostingGateway(CronGateway): - schedule = "*/5 * * * *" - use_batch = True # Enable parallel processing - num_threads = 4 # Number of concurrent threads (optional) - max_errors = 10 # Stop batch if this many errors occur (optional) -``` +Because this is such a small project, there wasn't a great dev environment nor was it worth it to set up one. I sent messages into `#general` to test this. Before I enabled any actions that would actually remove messages, I set up a dry run mode that would analyze messages and send a dry run audit message into `#moderator-only`. I saw that it was correctly flagging the examples that I put in, and that was enough to turn off dry run mode. -With batch mode enabled, the scheduler will call your module's `batch()` method instead of running `forward()` sequentially. This is useful when you have many inputs and want to parallelize LLM calls. The `on_complete` callback still runs once per input after all batch results return +One other consideration: while it would be annoying for people to get messages falsely moved for a case that isn't specified, it's not the end of the world. A fine developer workflow is to notice a new error case, adjust the bot, and redeploy. Any change does not need to be thoroughly tested, because the stakes are quite low so long as it doesn't delete the whole Discord server. -## Production considerations +We also notify users via DM after their message is moved—a small thing, but important from a UX perspective. + +## Fly.io -"production" is a loose word here because of the small scale, but this is deployed live. +### Persistence +We create a file to store all of the IDs that we have processed. Losing this isn't a big deal—at most you're redoing 20 calls—but if you were to expand this system, you'd certainly want to change it. -5. Production Considerations (2-3 min) - - Dry-run mode - - Audit logging - - DM notifications to users - - Fly.io deployment +`fly volumes create dspy_discord_data --size 1` -Because this is such a small project, there wasn't a great dev environment nor was it worth it to set up one. I sent messages into #general to test this. Before I enabled any actions that would actually remove messages, I set up a dry run mode that would analyze messages and send a dry run audit message into #moderator-only. I saw that it was correctly flagging the examples that I put in, and that was enough to turn off dry run mode. +Then inside `fly.toml` we add: +```toml +[mounts] + source = "dspy_discord_data" + destination = "/data" +``` + +### Secrets -We also want to notify users after they have a message moved. This is a simple DM, but important from a UX perspective. +Then we need to set the secrets. + +You'll need a Discord bot token with access to read messages, send messages, and delete messages. You can get the bot token from [this tutorial](https://discord.com/developers/docs/quick-start/getting-started). To get the Channel ID, make sure your Discord client is in developer mode, then right click on the channel and select `Copy Channel ID`. + +```bash +fly secrets set \ + DISCORD_BOT_TOKEN="" \ + DISCORD_CHANNEL_IDS=", " \ + DISCORD_JOBS_CHANNEL_ID="" \ + DISCORD_AUDIT_CHANNEL_ID="" \ + OPENAI_API_KEY="" +``` + +You can set the `DRY_RUN` environment variable to `true` if you want to only send audit logs without taking actions, to verify it's working properly. ### Deployment -We deploy this onto Fly.io. We want this to be a permananelty running machine that will trigger itself with the python process every 5 minutes. +We deploy this onto Fly.io. We want a single permanently running machine that triggers itself every 5 minutes via the Python process. -# TODO: Make sure that it is still running +You can trigger the first deploy using `fly launch`. -Fly automatically scales your workload to 2 machines, and will pause if there is not enough external traffic. For this deployment, there will definitionally be 0 traffic, so we need to get around the auto-scaling. We also don't want 2 machines. (1) I don't want to pay for that and (2) We havent built in any persistence or deduplication mechanisms. If there are two machines running, they might both pick up the same messages. +Fly automatically scales your workload to 2 machines and will pause if there is not enough external traffic. For this deployment, there will by definition be 0 API-based traffic, so we need to turn off auto-scaling while keeping a minimum of one machine running. -We need to set some environment variables in order to tell which channels to look at. +#### Setting the minimum +You can add a line to your `fly.toml` to get the pausing behavior we want: -## Results and Lessons +```toml +auto_stop_machines = false +auto_start_machines = true +min_machines_running = 1 +``` + +If our one machine goes down, we do want it to start another one. We don't want it to stop a machine because of no activity, so we turn off `auto_stop_machines`. -After I made this bot, there were uh no job postings that it flagged because I think people are not active on discord this week. It was launched right before the holidays. I hope to see some more job postings to move in the next few weeks. +#### Setting the maximum -OR they got so scared by my bot that noone dared try anything. +We also don't want more than one machine: (1) I don't want to pay for that, and (2) we haven't built in any deduplication mechanisms. If there are two machines running, they might both pick up the same messages. -We will see if its useful when things pick back up in the new year. +You can set the number of machines to one and turn off `ha` (horizontal autoscaling). +```bash +fly scale count 1 +fly deploy --ha=false +``` + +`fly scale` should remove one of the two default machines if you already ran `fly launch`. This was a bit finicky when I was setting it up, so you may also need to run `fly machine kill` to manually remove one. + +## Results and Lessons -Notes: -Is this the most robust setup? Nah this is a discord bot without a ton of traffic. -Could someone prompt inject this? Like very potentially! Does it matter? No not at all. The bot has no tool access, and its not like the prompt is secret. There are no tools to access other messages, etc +After I made this bot, there were some messages it missed. For instance, it thought some scammy crypto job postings were actually people introducing themselves. As some people in the Discord pointed out (thanks @prashanth and @mchonedev), it's pretty obvious that anyone using the word "blockchain" in their post is not a legitimate user. DSPy is obviously not a crypto server, and any real dev would hopefully know their audience. + +### FAQ: +- Is this the most robust setup? + + Nope, this is a discord bot without a ton of traffic. + +- Could someone prompt inject this? + + In practice? Not in a way that matters. + + The bot has no tool access, and it's not like the signature prompt is secret. There are no tools to access other messages, or perform destructive actions towards other users. + + Notably, I do not allow for any other messages in the thread context to be seen by the model. Showing full conversations would open up a lot of weird prompt injection avenues that I don't want to deal with. + +- What if someone sends a spam message into many channels? + + Processing a single message at a time means that we miss people who send a job posting in multiple channels. + + Often what these bots do is drop a message into every channel in the server. Because each message is processed individually, we currently would take all of these and (without deduping) move them into #jobs. + + I will add some very simple dedup behavior in a future update, but for now I am just going to leave it. The goal of this bot for now is to catch the 80% of the simple cases. + +- How much does it cost? + + This is shockingly cheap to run! The LLM inference is not expensive (using gpt-5-nano), and the server costs <$1 per month (thank you Firecracker VMs + Fly.io). I'm happy to eat this cost to keep the server healthier and save myself the work I would have done otherwise. + +--- + +If you want to join the DSPy Discord and see the bot in action, here's the invite: [https://discord.gg/f5DJ778ZnK](https://discord.gg/f5DJ778ZnK) ## Appendix +### DSPy Signature to prompt example + If you are curious about how the dspy signature gets turned into a prompt, it looks like the following. The signature is: @@ -278,17 +360,18 @@ class JobPostingSignature(dspy.Signature): DSPy has a concept of an "adapter" which is a class that determines how a signature gets turned into a prompt, and also how the answers get extracted on the other end. The rough outline for the adapters is: -```python +``` System prompt: 1. Inputs 2. Outputs 3. Task User prompt: -Field name: value for field, value in inputs +1. Field name: value for field, value in inputs +2. Desired assistant output list ``` -The exact prompt that gets sent to the LLM is: +The exact prompt that gets sent to the LLM for our signature above is: ``` System message: @@ -335,7 +418,7 @@ Hey everyone! I'm a senior Python developer with 5 years of experience looking f job_seeker_123 [[ ## channel_name ## ]] -general-chat +general Respond with the corresponding output fields, starting with the field `[[ ## intent ## ]]` (must be formatted as a valid Python Literal['post_job', 'seek_job', 'other']), then `[[ ## action ## ]]` (must be formatted as a valid Python Literal['allow', 'move', 'flag', 'delete']), then `[[ ## reason ## ]]`, and then ending with the marker for `[[ ## completed ## ]]`. ``` @@ -352,4 +435,45 @@ move The message expresses the user's intent to seek job opportunities, which is more appropriate for a jobs channel rather than a general chat. [[ ## completed ## ]] +``` + +### Batch Processing + +For higher throughput, `CronGateway` supports batch mode which processes all inputs in parallel using DSPy's `module.batch()`: + +```python +class JobPostingGateway(CronGateway): + schedule = "*/5 * * * *" + use_batch = True # Enable parallel processing + num_threads = 4 # Number of concurrent threads (optional) + max_errors = 10 # Stop batch if this many errors occur (optional) +``` + +With batch mode enabled, the scheduler will call your module's `batch()` method instead of running `forward()` sequentially. This is useful when you have many inputs and want to parallelize LLM calls. The `on_complete` callback still runs once per input after all batch results return. + +### Full fly.toml + +```toml +app = 'discord-mod' +primary_region = 'ewr' + +[build] + +[http_service] + internal_port = 8000 + force_https = true + auto_stop_machines = false + auto_start_machines = true + min_machines_running = 1 + processes = ['app'] + +[[vm]] + memory = '1gb' + cpu_kind = 'shared' + cpus = 1 + memory_mb = 1024 + +[mounts] + source = "processed_data" + destination = "/data" ``` \ No newline at end of file From ece4608e75e9e331e95c7fb4a3ecbffc5213e36f Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Mon, 29 Dec 2025 20:08:27 -0500 Subject: [PATCH 17/19] add task message --- examples/discord-mod/src/discord_mod/readme.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/examples/discord-mod/src/discord_mod/readme.md b/examples/discord-mod/src/discord_mod/readme.md index f34d69a..e47a021 100644 --- a/examples/discord-mod/src/discord_mod/readme.md +++ b/examples/discord-mod/src/discord_mod/readme.md @@ -31,6 +31,9 @@ So what do we want this system to do? We want it to detect if the primary intent Our pipeline starts to look something like: ``` +TASK: +Determine if a discord message is either a job posting, looking for a job, or neither. If it is in the wrong channel, move it. + INPUTS: - message: str - metadata From 7a2beb729df573dca535fd46207a53a4757a07a0 Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Tue, 30 Dec 2025 17:43:12 -0500 Subject: [PATCH 18/19] update blog --- .../discord-mod/src/discord_mod/readme.md | 207 +++++++++--------- 1 file changed, 107 insertions(+), 100 deletions(-) diff --git a/examples/discord-mod/src/discord_mod/readme.md b/examples/discord-mod/src/discord_mod/readme.md index e47a021..05af2ba 100644 --- a/examples/discord-mod/src/discord_mod/readme.md +++ b/examples/discord-mod/src/discord_mod/readme.md @@ -1,38 +1,49 @@ -## TODO -- [ ] Proofread and adjust for structure. +# Moderating Discord with DSPy ---- +There is a common annoyance among every Discord moderator: people posting in the wrong channels. + +In the DSPy community Discord, this happens most frequently with job related postings: people looking to hire and people looking to be hired. To be clear: we like job posts! We just don't want listings and resumes cluttering the main channel. -# Building a Discord moderation bot with DSPy +It doesn't take long to delete the message and send a DM asking them to move it, but it certainly gets annoying. -## The Problem +The good news is that getting AI to detect and take the action is pretty easy. -I am one of the mods for the DSPy community discord. One of the most common things that happens is that people end up posting jobs in the #general channel. We want people to post jobs! But we do not want the main channel to be cluttered with intros or people advertising. +## Specifying our task -It doesn't take long to delete the message and send a DM asking them to move it, but it certainly gets annoying. +We expect most modern LLMs to do a good job at this. Like a REALLY good job. So I expect any errors to come from underspecification rather than LLM errors. -The good news is that classifying whether something is a job posting is pretty easy. We can expect most modern LLMs to do a good job at this. +This bot isn't meant to ban users or be a catch-all spam detector. If it happens to catch and delete a stray non-job spam message, that's upside, but really the use case is about moving job postings into the correct channel. + +### Sketching out the shape -Like a REALLY good job. So I expect any errors to come from underspecification rather than LLM errors. +The main goal of this system is to **detect the primary intent of a message**. The intent can be job posting, job seeking, or neither. We also want the system to suggest an action, between deleting, moving, flagging, or allowing, depending on context. -For instance: +We also want to be notified as mods if there is an action taken, so that we can be aware if things start to break. + +#### Where There's Nuance + +Primary intent is a fuzzy line to draw. There are messages that have self-promotion in them, but the primary intent is not to promote. This line was chosen by talking to the team during the creation of this project. + +For example: > Oh yeah I see why GEPA is cool. In my last job, I used MIPRO to improve our LLM-as-a-judge for insurance document relevance inside a chat by 20%, and my manager + our customers were very happy. Ultimately, I’m now looking for the next challenge and I’m excited about applying GEPA to whatever my next problem is (P.S. pls DM if you’d like to chat about hiring me!). -The primary intent of the message is to say that GEPA is cool, validate that they've used it at a company, and share the project they worked on. Getting hired is secondary. As a team we talked about this, and it's about the primary intent, rather than the presence of anything hiring-related. +In this case, The primary intent of the message is to validate that they've used GEPA at a company, and share the project they worked on. Getting hired is secondary. As a team we talked about this, and it's about the primary intent, rather than the presence of anything hiring-related. -## Designing the LLM pipeline +We will want to use in the message, author, and the channel it was posted in. All of these could provide relevant information. If a user named `dm_me_for_free_crypto` sends a sketchy message, the LLM should take the username into account. Same with channel. -This bot isn't meant to ban users or be a catch-all spam detector. If it happens to catch and delete a stray non-job spam message, that's upside, but really the use case is about moving job postings into the correct channel. +In `#help-channel`, if someone is struggling with a problem that requires a lot of extra help, it's totally fine for them to ask for help and offer compensation. It's only when someone posts exclusively in `#help-channel` saying they're looking for an AI engineer that we want to flag it. -### Sketching out the shape +It's because of this contextual nuance that things look a little fuzzy, rather than the purer of `message: str -> is_job_related: bool` pipeline. -So what do we want this system to do? We want it to detect if the primary intent of a message is job-related or not, and suggest an action. We also want to be notified as mods if there is an action taken, so that we can be aware if things start to break. +Or the simpler pipeline: `if 'hiring' or 'job' in message: return True` -Our pipeline starts to look something like: +#### Defining it as a signature + +Our task, inputs, and outputs for the LLM starts to look something like: ``` TASK: -Determine if a discord message is either a job posting, looking for a job, or neither. If it is in the wrong channel, move it. +Determine if a discord message is either a job posting, looking for a job, or neither. INPUTS: - message: str @@ -42,7 +53,7 @@ OUTPUTS: - internal_model_reasoning: str - intent: POST, SEEK or NEITHER - action: MOVE, FLAG, DELETE, ALLOW -- action_reason: str +- action_reason: str (user facing) ``` ### Convert to DSPy @@ -70,12 +81,6 @@ class JobPostingSignature(dspy.Signature): ) ``` -We pass in the message, author, and the channel it was posted in. All of these could provide relevant information. If a user named `dm_me_for_free_crypto` sends a sketchy message, the LLM should take the username into account. Same with channel. - -In `#help-channel`, if someone is struggling with a problem that requires a lot of extra help, it's totally fine for them to ask for help and offer compensation. It's only when someone posts exclusively in `#help-channel` saying they're looking for an AI engineer that we want to flag it. - -It's because of this contextual nuance that things look a little fuzzy, rather than the purer classification of `message -> job_posting: bool` pipeline. - Note that there are two reasoning fields. This is a design choice. The first model reasoning happens when we call the signature with `dspy.ChainOfThought(JobPostingSignature)`. This is to give the model time to deliberate. We are using `gpt-5-nano` with no reasoning built in, so this will explicitly give the model a chance to discuss the message if there is any nuance. This is similar to setting the model thinking parameter. @@ -106,7 +111,7 @@ Then the only thing I need around this is the Discord network code. It's like 8 ## Building the gateway -The most complex part is integrating with Discord. +The most complex part is integrating with Discord and implementing the business logic for taking actions based on the LLM outputs. There are two main ways that we can build this bot: 1. Realtime streaming @@ -117,46 +122,28 @@ We opt for (2) the cron approach. Mostly because the realtime streaming requires If we instead just build something that checks the last 20 messages every 5 minutes, it's totally fine. If a job posting is live on the server for 5 minutes, no one cares. This constraint would be different for different servers, but these are the constraints of the problem I'm solving without overengineering. The behavior will be as follows: -Every 5 minutes: + +Every 5 minutes 1. Gather the last 20 messages 2. Skip any that have already been processed 3. Classify as "move", "flag", "delete", or "allow" 4. Take the relevant action for "move", "flag", "delete", and send an audit message into the moderator only channel -- "move" moves the message into the #jobs channel, +- "move" moves the message into the #jobs channel, and sends a message to the user - "flag" adds an emoji reaction and sends an audit message for the mods to review, -- "delete", well, deletes the message +- "delete", deletes the message, and sends a message to the user - "allow" does nothing To implement this, I use `dspy-cli` to handle the routing and scheduling. -### dspy-cli explanation +### Intro to dspy-cli [`dspy-cli`](https://github.com/cmpnd-ai/dspy-cli) is a command line tool to help you create, scaffold, and deploy dspy applications. You can serve a `dspy-cli` created project by running `dspy-cli serve`, and it will bring up a local endpoint for you that you can test against. It is also what created our initial project directory structure. -The default serve endpoint has your modules as named endpoints so you can send a POST request to `/{ModuleName}`. In this case, your post requests would directly have the inputs that you want for your `Module.forward` method. - -There are a few different kinds of alternative entry points you may want for any DSPy application. The two that `dspy-cli` currently supports are **API-based** and **cron-based**. - -**API-based** - -For some cases, you want a layer to sit in between the calling api and your LLM logic. `APIGateway` makes sense here for your LLM logic. - -If you were to create a PR review bot, you might want a webhook setup. Your endpoint takes in a webhook payload from GitHub, extracts some data from it, uses that to fetch the code of the PR that triggered the webhook, and passes that code into your module. - -Your DSPy code might look like: `dspy.ReAct("files: Dict[str, str] -> review", tools=[file_search, web_search, run_code, ...])` - -In order to call this, you need a loading step to get all of the files and put them into whatever format makes sense. +There are a few different kinds entry points you may want for any DSPy application. The two that `dspy-cli` currently supports are **API-based** and **cron-based**. +For this case, we want to gather a bunch of inputs every so often, and run batch inference over them, so `CronGateway` makes more sense. We will subclass it to implement the loading logic. -**cron-based** - -`CronGateway` is what you use when your trigger is periodic rather than based on a call. - -For this discord case, we want to gather a bunch of inputs every so often, and run batch inference over them, so `CronGateway` makes more sense. We will subclass it to implement the loading logic. - -### JobPostingGateway - -`JobPostingGateway` subclasses `CronGateway`. This is how you specify your data loading behavior. In our case, it loads the data and takes actions afterward. +`CronGateway` is what you use when your trigger is periodic rather than based on a call. `CronGateway` is an ABC with two core methods: @@ -166,6 +153,10 @@ For this discord case, we want to gather a bunch of inputs every so often, and r There's also an optional `on_error` method for handling failures. +### JobPostingGateway + +`JobPostingGateway` subclasses `CronGateway`. This is how you specify your data loading behavior. In our case, it loads the data and takes actions afterward. + Here's a simplified version of our gateway: ```python @@ -225,7 +216,42 @@ class JobPostingGateway(CronGateway): await self.client.send_dm(meta["author_id"], output.get("reason", "")) ``` -## Production considerations +## Deploying our app + +We deploy this onto Fly.io. We want a single permanently running machine that triggers itself every 5 minutes. + +You can trigger the first deploy using `fly launch`. + +### Scaling Configuration + +Fly automatically scales your workload to 2 machines and will pause if there is not enough external traffic. For this deployment, there will by definition be 0 API-based traffic, so we need to turn off auto-scaling while keeping a minimum of one machine running. + + +#### Setting the minimum + +You can add a line to your `fly.toml` to get the pausing behavior we want: + +```toml +auto_stop_machines = false +auto_start_machines = true +min_machines_running = 1 +``` + +If our one machine goes down, we do want it to start another one. We don't want it to stop a machine because of no activity, so we turn off `auto_stop_machines`. + +#### Setting the maximum + +We also don't want more than one machine: (1) I don't want to pay for that, and (2) we haven't built in any deduplication mechanisms. If there are two machines running, they might both pick up the same messages. + +You can set the number of machines to one and turn off `ha` (horizontal autoscaling). +```bash +fly scale count 1 +fly deploy --ha=false +``` + +`fly scale` should remove one of the two default machines if you already ran `fly launch`. This was a bit finicky when I was setting it up, so you may also need to run `fly machine kill` to manually remove one. + +### Production Considerations "production" is a loose word here because of the small scale, but this is deployed live, and actively affecting DSPy discord users. @@ -233,13 +259,9 @@ Because this is such a small project, there wasn't a great dev environment nor w One other consideration: while it would be annoying for people to get messages falsely moved for a case that isn't specified, it's not the end of the world. A fine developer workflow is to notice a new error case, adjust the bot, and redeploy. Any change does not need to be thoroughly tested, because the stakes are quite low so long as it doesn't delete the whole Discord server. -We also notify users via DM after their message is moved—a small thing, but important from a UX perspective. - -## Fly.io - ### Persistence -We create a file to store all of the IDs that we have processed. Losing this isn't a big deal—at most you're redoing 20 calls—but if you were to expand this system, you'd certainly want to change it. +We create a file to store all of the IDs that we have processed. Losing this isn't a big deal—at most you're redoing 20 call. If you were to expand this system, you'd certainly want to change it. `fly volumes create dspy_discord_data --size 1` @@ -267,66 +289,51 @@ fly secrets set \ You can set the `DRY_RUN` environment variable to `true` if you want to only send audit logs without taking actions, to verify it's working properly. -### Deployment +## Conclusion -We deploy this onto Fly.io. We want a single permanently running machine that triggers itself every 5 minutes via the Python process. +### Learnings -You can trigger the first deploy using `fly launch`. +Fly.io + [`dspy-cli`](https://github.com/cmpnd-ai/dspy-cli) make it REALLY easy to deploy hobbyist DSPy usecases. This example was the first problem that I had that I wanted to use it to solve. -Fly automatically scales your workload to 2 machines and will pause if there is not enough external traffic. For this deployment, there will by definition be 0 API-based traffic, so we need to turn off auto-scaling while keeping a minimum of one machine running. +### Cost + +**Price** -#### Setting the minimum +This is shockingly cheap to run! The LLM inference is not expensive (using gpt-5-nano), and the server costs <$1 per month (thank you Firecracker VMs + Fly.io). I'm happy to eat this cost to keep the server healthier and save myself the work I would have done otherwise. -You can add a line to your `fly.toml` to get the pausing behavior we want: +**Development Time** -```toml -auto_stop_machines = false -auto_start_machines = true -min_machines_running = 1 -``` +This bot did not take me that long to implement. The 25 lines of DSPy did not take long. I spent much longer writing the blog post than I did coding the bot. Especially once I had the Discord token enabled, it was incredibly easy for Amp to wire up the rest. I implemented the Gateway system for `dspy-cli` at the same time, and I took more time on that because its an important abstraction to get right. -If our one machine goes down, we do want it to start another one. We don't want it to stop a machine because of no activity, so we turn off `auto_stop_machines`. +**Maintainance** -#### Setting the maximum +If I want to make a change, all I need to do is update the signature, and run `fly deploy` to update my machine. Or, if I wanted to add more modules, I can still use the same VM. -We also don't want more than one machine: (1) I don't want to pay for that, and (2) we haven't built in any deduplication mechanisms. If there are two machines running, they might both pick up the same messages. +### Limitations -You can set the number of machines to one and turn off `ha` (horizontal autoscaling). -```bash -fly scale count 1 -fly deploy --ha=false -``` +**Volume** + +This can by design, only work on 20 messages per 5 minutes. The limiting factors will be your LLM inference calls, rather than the ability of the runner to manage the requests. -`fly scale` should remove one of the two default machines if you already ran `fly launch`. This was a bit finicky when I was setting it up, so you may also need to run `fly machine kill` to manually remove one. +**Prompt Injection** + +Someone might be able to sneak in a job posting via prompt injection. -## Results and Lessons +In practice, this doesn't actually matter. People are good at tagging the mods if a message does sneak through. + +The bot has no tool access, and it's not like the signature prompt is secret. There are no tools to access other messages, or ability to perform destructive actions towards other users. -After I made this bot, there were some messages it missed. For instance, it thought some scammy crypto job postings were actually people introducing themselves. As some people in the Discord pointed out (thanks @prashanth and @mchonedev), it's pretty obvious that anyone using the word "blockchain" in their post is not a legitimate user. DSPy is obviously not a crypto server, and any real dev would hopefully know their audience. +Notably, I do not allow for any other messages in the thread context to be seen by the model. Showing full conversations would open up a lot of weird prompt injection avenues that I don't want to deal with. -### FAQ: -- Is this the most robust setup? - - Nope, this is a discord bot without a ton of traffic. +**Spam** -- Could someone prompt inject this? - - In practice? Not in a way that matters. - - The bot has no tool access, and it's not like the signature prompt is secret. There are no tools to access other messages, or perform destructive actions towards other users. - - Notably, I do not allow for any other messages in the thread context to be seen by the model. Showing full conversations would open up a lot of weird prompt injection avenues that I don't want to deal with. +Processing a single message at a time means that we miss people who send a job posting in multiple channels. -- What if someone sends a spam message into many channels? - - Processing a single message at a time means that we miss people who send a job posting in multiple channels. - - Often what these bots do is drop a message into every channel in the server. Because each message is processed individually, we currently would take all of these and (without deduping) move them into #jobs. - - I will add some very simple dedup behavior in a future update, but for now I am just going to leave it. The goal of this bot for now is to catch the 80% of the simple cases. +Often what these bots do is drop a message into every channel in the server. Because each message is processed individually, we currently would take all of these and (without deduping) move them into #jobs. -- How much does it cost? - - This is shockingly cheap to run! The LLM inference is not expensive (using gpt-5-nano), and the server costs <$1 per month (thank you Firecracker VMs + Fly.io). I'm happy to eat this cost to keep the server healthier and save myself the work I would have done otherwise. +I will add some very simple dedup behavior in a future update, but for now I am just going to leave it. The goal of this bot for now is to catch the 80% of the simple cases. + +Immediately after I made this bot, there were some messages it did not move when it should have. It thought some scammy crypto job postings were actually people introducing themselves. As some people in the Discord pointed out (thanks @prashanth and @mchonedev), it's pretty obvious that anyone using the word "blockchain" in their post is likely not a legitimate user. DSPy is not a crypto server, and any thoughtful dev would hopefully know their audience. --- From c2a7a25c76fda6e6846dfc8c000ae7b9574b4a3d Mon Sep 17 00:00:00 2001 From: isaacbmiller Date: Wed, 31 Dec 2025 18:06:57 -0500 Subject: [PATCH 19/19] add eval dataset --- examples/discord-mod/data/eval_dataset.jsonl | 26 + examples/discord-mod/data/eval_dataset.py | 60 +++ .../modules/classify_job_posting.py | 8 +- .../discord-mod/src/discord_mod/readme.md | 489 ------------------ examples/discord-mod/tests/test_eval.py | 188 +++++++ 5 files changed, 278 insertions(+), 493 deletions(-) create mode 100644 examples/discord-mod/data/eval_dataset.jsonl create mode 100644 examples/discord-mod/data/eval_dataset.py delete mode 100644 examples/discord-mod/src/discord_mod/readme.md create mode 100644 examples/discord-mod/tests/test_eval.py diff --git a/examples/discord-mod/data/eval_dataset.jsonl b/examples/discord-mod/data/eval_dataset.jsonl new file mode 100644 index 0000000..76d69e3 --- /dev/null +++ b/examples/discord-mod/data/eval_dataset.jsonl @@ -0,0 +1,26 @@ +{"message": "Oh yeah I see why GEPA is cool. In my last job, I used MIPRO to improve our LLM-as-a-judge for insurance document relevance inside a chat by 20%, and my manager + our customers were very happy. Ultimately, I'm now looking for the next challenge and I'm excited about applying GEPA to whatever my next problem is (P.S. pls DM if you'd like to chat about hiring me!).", "author": "ml_enthusiast", "channel_name": "general", "intent": "other", "action": "allow", "category": "nuanced"} +{"message": "Hey everyone! I'm a senior Python developer with 5 years of experience in ML/AI. Looking for new opportunities in the AI space. Open to remote work! DM me if interested.", "author": "job_seeker_123", "channel_name": "general", "intent": "seek_job", "action": "move", "category": "nuanced"} +{"message": "I'm really stuck on this MIPRO optimization issue. I've tried everything in the docs. Would anyone be willing to hop on a call and help debug? Happy to pay for your time.", "author": "stuck_developer", "channel_name": "help", "intent": "other", "action": "allow", "category": "nuanced"} +{"message": "Looking for an AI engineer to help with our DSPy implementation. We're a startup in the fintech space. Competitive salary and equity. DM me!", "author": "startup_founder", "channel_name": "help", "intent": "post_job", "action": "move", "category": "nuanced"} +{"message": "Just shipped a DSPy integration for our observability platform! We're now hiring ML engineers to help scale it. Check out our blog post: [link]. Also hiring!", "author": "product_builder", "channel_name": "general", "intent": "post_job", "action": "move", "category": "nuanced"} +{"message": "Been using DSPy for 6 months now at my current company. Built some cool stuff with MIPRO. BTW if anyone knows of interesting AI roles, I might be open to chatting.", "author": "curious_dev", "channel_name": "general", "intent": "other", "action": "allow", "category": "nuanced"} +{"message": "Hi everyone! Just joined the server. I work as an ML engineer at a mid-size company, mostly doing NLP stuff. Excited to learn more about DSPy!", "author": "new_member", "channel_name": "introductions", "intent": "other", "action": "allow", "category": "nuanced"} +{"message": "Hi! I'm John, a senior ML engineer with 8 years of experience. I've worked at Google, Meta, and OpenAI. I specialize in LLM optimization, prompt engineering, and distributed systems. Currently open to new opportunities. Here's my LinkedIn: [link]", "author": "john_ml", "channel_name": "general", "intent": "seek_job", "action": "move", "category": "nuanced"} +{"message": "If anyone needs help implementing DSPy in production, I offer consulting services. 10+ years of ML experience. Reasonable rates!", "author": "consultant_pro", "channel_name": "general", "intent": "post_job", "action": "move", "category": "nuanced"} +{"message": "For those of you who've hired ML engineers, do you test candidates on DSPy knowledge specifically or just general LLM skills?", "author": "hiring_curious", "channel_name": "general", "intent": "other", "action": "allow", "category": "nuanced"} +{"message": "Has anyone tried using DSPy with Claude? I'm getting some weird behavior with the structured outputs.", "author": "claude_user", "channel_name": "general", "intent": "other", "action": "allow", "category": "sanity_general"} +{"message": "Just pushed a PR to fix the caching issue. Would appreciate a review!", "author": "contributor", "channel_name": "general", "intent": "other", "action": "allow", "category": "sanity_general"} +{"message": "@omar what's the recommended way to handle retries in dspy.Predict?", "author": "learning_dev", "channel_name": "help", "intent": "other", "action": "allow", "category": "sanity_general"} +{"message": "The new MIPRO v2 is amazing! Saw a 15% improvement on my benchmark.", "author": "happy_user", "channel_name": "general", "intent": "other", "action": "allow", "category": "sanity_general"} +{"message": "Does anyone have a good example of multi-hop reasoning with DSPy? The docs example doesn't quite work for my use case.", "author": "researcher", "channel_name": "help", "intent": "other", "action": "allow", "category": "sanity_general"} +{"message": "[HIRING] We're looking for a Senior ML Engineer to join our team. Remote, $200k+. Experience with LLMs required. Apply here: [link]", "author": "recruiter_jane", "channel_name": "general", "intent": "post_job", "action": "move", "category": "sanity_job"} +{"message": "Our startup is hiring! Looking for founding ML engineers who are excited about DSPy and LLM applications. Equity + competitive salary. DM for details.", "author": "startup_ceo", "channel_name": "general", "intent": "post_job", "action": "move", "category": "sanity_job"} +{"message": "Available for hire! 5 years Python, 2 years ML. Looking for remote roles in AI. Resume: [link]", "author": "available_dev", "channel_name": "general", "intent": "seek_job", "action": "move", "category": "sanity_job"} +{"message": "Contract opportunity: Need someone for a 3-month DSPy project. $150/hr. Must have production experience.", "author": "project_manager", "channel_name": "help", "intent": "post_job", "action": "move", "category": "sanity_job"} +{"message": "Actively job hunting! ML engineer with DSPy experience. Open to full-time or contract. Please reach out!", "author": "active_seeker", "channel_name": "general", "intent": "seek_job", "action": "move", "category": "sanity_job"} +{"message": "Looking for blockchain developers! Join our Web3 AI project. Huge token rewards! DM for whitelist access.", "author": "crypto_bro", "channel_name": "general", "intent": "post_job", "action": "delete", "category": "spam"} +{"message": "FREE CRYPTO! Join our AI-powered trading bot. 1000% returns guaranteed! [suspicious link]", "author": "dm_me_for_free_crypto", "channel_name": "general", "intent": "other", "action": "delete", "category": "spam"} +{"message": "NFT + AI project hiring! Be part of the next big thing in decentralized machine learning. Whitepaper: [link]", "author": "nft_enthusiast", "channel_name": "general", "intent": "post_job", "action": "delete", "category": "spam"} +{"message": "Hiring smart contract developers for our DeFi AI platform. Experience with Solidity and transformers required.", "author": "defi_startup", "channel_name": "general", "intent": "post_job", "action": "delete", "category": "spam"} +{"message": "We're hiring ML engineers! Remote, competitive pay. DM for details.", "author": "hiring_manager", "channel_name": "jobs", "intent": "post_job", "action": "allow", "category": "jobs_channel"} +{"message": "Looking for new opportunities in AI/ML. 5 years experience. Open to remote.", "author": "job_hunter", "channel_name": "jobs", "intent": "seek_job", "action": "allow", "category": "jobs_channel"} diff --git a/examples/discord-mod/data/eval_dataset.py b/examples/discord-mod/data/eval_dataset.py new file mode 100644 index 0000000..7ec4561 --- /dev/null +++ b/examples/discord-mod/data/eval_dataset.py @@ -0,0 +1,60 @@ +""" +Evaluation dataset loader for the Discord job posting classifier. +""" + +import json +from pathlib import Path + +import dspy + + +def get_eval_dataset() -> list[dspy.Example]: + """Load evaluation dataset from JSONL file.""" + dataset_path = Path(__file__).parent / "eval_dataset.jsonl" + + examples = [] + with open(dataset_path) as f: + for line in f: + data = json.loads(line) + example = dspy.Example( + message=data["message"], + author=data["author"], + channel_name=data["channel_name"], + intent=data["intent"], + action=data["action"], + category=data["category"], + ).with_inputs("message", "author", "channel_name") + examples.append(example) + + return examples + + +def get_dataset_by_category(category: str) -> list[dspy.Example]: + """Return examples filtered by category.""" + return [ex for ex in get_eval_dataset() if ex.category == category] + + +def get_dataset_stats() -> dict: + """Return statistics about the dataset.""" + from collections import Counter + + dataset = get_eval_dataset() + categories = Counter(ex.category for ex in dataset) + intents = Counter(ex.intent for ex in dataset) + actions = Counter(ex.action for ex in dataset) + + return { + "total": len(dataset), + "by_category": dict(categories), + "by_intent": dict(intents), + "by_action": dict(actions), + } + + +if __name__ == "__main__": + stats = get_dataset_stats() + print(f"Dataset Statistics:") + print(f" Total examples: {stats['total']}") + print(f" By category: {stats['by_category']}") + print(f" By intent: {stats['by_intent']}") + print(f" By action: {stats['by_action']}") diff --git a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py index 624ff13..fb99dd0 100644 --- a/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py +++ b/examples/discord-mod/src/discord_mod/modules/classify_job_posting.py @@ -28,11 +28,11 @@ def forward( class JobPostingSignature(dspy.Signature): - """Classify a Discord message and determine moderation action. + """Classify a Discord message for a DSPy (LLM framework) server. - The subject of the Discord server is DSPy, the framework for building and optimizing LLM applications. The server has nothing to do with blockchain, crypto, or NFTs, and these are generally spam. - - A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" + DELETE any message mentioning blockchain, crypto, NFTs, or Web3 - these are always spam. + MOVE job postings/seeking to #jobs channel unless already there. + ALLOW general discussion about DSPy, help questions, or casual mentions of work.""" message: str = dspy.InputField(desc="The Discord message content") author: str = dspy.InputField(desc="The message author's username") diff --git a/examples/discord-mod/src/discord_mod/readme.md b/examples/discord-mod/src/discord_mod/readme.md deleted file mode 100644 index 05af2ba..0000000 --- a/examples/discord-mod/src/discord_mod/readme.md +++ /dev/null @@ -1,489 +0,0 @@ -# Moderating Discord with DSPy - -There is a common annoyance among every Discord moderator: people posting in the wrong channels. - -In the DSPy community Discord, this happens most frequently with job related postings: people looking to hire and people looking to be hired. To be clear: we like job posts! We just don't want listings and resumes cluttering the main channel. - -It doesn't take long to delete the message and send a DM asking them to move it, but it certainly gets annoying. - -The good news is that getting AI to detect and take the action is pretty easy. - -## Specifying our task - -We expect most modern LLMs to do a good job at this. Like a REALLY good job. So I expect any errors to come from underspecification rather than LLM errors. - -This bot isn't meant to ban users or be a catch-all spam detector. If it happens to catch and delete a stray non-job spam message, that's upside, but really the use case is about moving job postings into the correct channel. - -### Sketching out the shape - -The main goal of this system is to **detect the primary intent of a message**. The intent can be job posting, job seeking, or neither. We also want the system to suggest an action, between deleting, moving, flagging, or allowing, depending on context. - -We also want to be notified as mods if there is an action taken, so that we can be aware if things start to break. - -#### Where There's Nuance - -Primary intent is a fuzzy line to draw. There are messages that have self-promotion in them, but the primary intent is not to promote. This line was chosen by talking to the team during the creation of this project. - -For example: -> Oh yeah I see why GEPA is cool. In my last job, I used MIPRO to improve our LLM-as-a-judge for insurance document relevance inside a chat by 20%, and my manager + our customers were very happy. Ultimately, I’m now looking for the next challenge and I’m excited about applying GEPA to whatever my next problem is (P.S. pls DM if you’d like to chat about hiring me!). - -In this case, The primary intent of the message is to validate that they've used GEPA at a company, and share the project they worked on. Getting hired is secondary. As a team we talked about this, and it's about the primary intent, rather than the presence of anything hiring-related. - -We will want to use in the message, author, and the channel it was posted in. All of these could provide relevant information. If a user named `dm_me_for_free_crypto` sends a sketchy message, the LLM should take the username into account. Same with channel. - -In `#help-channel`, if someone is struggling with a problem that requires a lot of extra help, it's totally fine for them to ask for help and offer compensation. It's only when someone posts exclusively in `#help-channel` saying they're looking for an AI engineer that we want to flag it. - -It's because of this contextual nuance that things look a little fuzzy, rather than the purer of `message: str -> is_job_related: bool` pipeline. - -Or the simpler pipeline: `if 'hiring' or 'job' in message: return True` - -#### Defining it as a signature - -Our task, inputs, and outputs for the LLM starts to look something like: - -``` -TASK: -Determine if a discord message is either a job posting, looking for a job, or neither. - -INPUTS: -- message: str -- metadata - -OUTPUTS: -- internal_model_reasoning: str -- intent: POST, SEEK or NEITHER -- action: MOVE, FLAG, DELETE, ALLOW -- action_reason: str (user facing) -``` - -### Convert to DSPy - -Let's start to put that into a DSPy signature: - -```python -class JobPostingSignature(dspy.Signature): - """Classify a Discord message and determine moderation action. - - A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" - - message: str = dspy.InputField(desc="The Discord message content") - author: str = dspy.InputField(desc="The message author's username") - channel_name: str = dspy.InputField(desc="The channel where the message was posted") - - intent: Literal["post_job", "seek_job", "other"] = dspy.OutputField( - desc="The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion" - ) - action: Literal["allow", "move", "flag", "delete"] = dspy.OutputField( - desc="Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation" - ) - reason: str = dspy.OutputField( - desc="Brief explanation of the classification and recommended action" - ) -``` - -Note that there are two reasoning fields. This is a design choice. - -The first model reasoning happens when we call the signature with `dspy.ChainOfThought(JobPostingSignature)`. This is to give the model time to deliberate. We are using `gpt-5-nano` with no reasoning built in, so this will explicitly give the model a chance to discuss the message if there is any nuance. This is similar to setting the model thinking parameter. - -The second reasoning field is meant to be user/moderator facing. After the model has committed to a course of action, we want to show the user and us as the mods, "why did you get banned" which is different reasoning than the model's internal debate about what the intent of the message is. - -#### Why use DSPy instead of just writing the prompts myself - -Part of why I use DSPy is that everything is built in already. Structured outputs, retries, plumbing between different LLMs and providers if I ever want to update, are all for free. - -My code can be incredibly simple. - -The module which takes in the signature above looks like: - -```python -class ClassifyJobPosting(dspy.Module): - gateway = JobPostingGateway - - def __init__(self): - super().__init__() - self.classifier = dspy.ChainOfThought(JobPostingSignature) - - def forward(self, message: str, author: str, channel_name: str) -> dspy.Prediction: - return self.classifier(message=message, author=author, channel_name=channel_name,) -``` - -Then the only thing I need around this is the Discord network code. It's like 8 real lines of code for an LLM pipeline, plumbing included. The LLM logic is simple—to actually wire it up to Discord, I need a gateway. - -## Building the gateway - -The most complex part is integrating with Discord and implementing the business logic for taking actions based on the LLM outputs. - -There are two main ways that we can build this bot: -1. Realtime streaming -2. Running on a cronjob - -We opt for (2) the cron approach. Mostly because the realtime streaming requires us to maintain a websocket connection. If the dspy server was so popular that we had a large volume of messages, I might take on the higher complexity of building that. The dspy server averages way less than 20 messages every 5 minutes. - -If we instead just build something that checks the last 20 messages every 5 minutes, it's totally fine. If a job posting is live on the server for 5 minutes, no one cares. This constraint would be different for different servers, but these are the constraints of the problem I'm solving without overengineering. - -The behavior will be as follows: - -Every 5 minutes -1. Gather the last 20 messages -2. Skip any that have already been processed -3. Classify as "move", "flag", "delete", or "allow" -4. Take the relevant action for "move", "flag", "delete", and send an audit message into the moderator only channel -- "move" moves the message into the #jobs channel, and sends a message to the user -- "flag" adds an emoji reaction and sends an audit message for the mods to review, -- "delete", deletes the message, and sends a message to the user -- "allow" does nothing - -To implement this, I use `dspy-cli` to handle the routing and scheduling. - -### Intro to dspy-cli - -[`dspy-cli`](https://github.com/cmpnd-ai/dspy-cli) is a command line tool to help you create, scaffold, and deploy dspy applications. You can serve a `dspy-cli` created project by running `dspy-cli serve`, and it will bring up a local endpoint for you that you can test against. It is also what created our initial project directory structure. - -There are a few different kinds entry points you may want for any DSPy application. The two that `dspy-cli` currently supports are **API-based** and **cron-based**. - -For this case, we want to gather a bunch of inputs every so often, and run batch inference over them, so `CronGateway` makes more sense. We will subclass it to implement the loading logic. - -`CronGateway` is what you use when your trigger is periodic rather than based on a call. - -`CronGateway` is an ABC with two core methods: - -1. **`get_pipeline_inputs`**: Fetches your data and returns a list of input dictionaries for the pipeline to process. Each dict contains the kwargs for your module's `forward()` method. You can also include a `_meta` key for data needed in `on_complete` but not by the pipeline itself (like message IDs or channel IDs). - -2. **`on_complete`**: Runs after each successful pipeline execution. This is where you take action based on the LLM's output. It receives both the original inputs (including `_meta`) and the pipeline output. - -There's also an optional `on_error` method for handling failures. - -### JobPostingGateway - -`JobPostingGateway` subclasses `CronGateway`. This is how you specify your data loading behavior. In our case, it loads the data and takes actions afterward. - -Here's a simplified version of our gateway: - -```python -class JobPostingGateway(CronGateway): - schedule = "*/5 * * * *" # Every 5 minutes - - def setup(self) -> None: - """Validate config and create Discord client.""" - self.client = DiscordClient(token=os.environ["DISCORD_BOT_TOKEN"]) - self.channel_ids = os.environ["DISCORD_CHANNEL_IDS"].split(",") - - async def get_pipeline_inputs(self) -> list[dict]: - """Fetch recent messages from monitored channels.""" - inputs = [] - for channel_id in self.channel_ids: - messages = await self.client.get_recent_messages(channel_id, limit=20) - for msg in messages: - if msg["author"].get("bot"): - continue - inputs.append({ - "message": msg["content"], - "author": msg["author"]["username"], - "channel_name": msg.get("channel_name", "unknown"), - "_meta": { - "message_id": msg["id"], - "channel_id": channel_id, - "author_id": msg["author"]["id"], - }, - }) - return inputs - - async def on_complete(self, inputs: dict, output: PipelineOutput) -> None: - """Take moderation action based on classification result.""" - meta = inputs["_meta"] - action = output.get("action", "allow") - - if action == "allow": - return - - if action == "move": - # Repost in jobs channel, delete original, DM user - await self.client.send_message( - self.jobs_channel_id, - f"**Moved from <#{meta['channel_id']}>**\n{inputs['message']}", - ) - await self.client.delete_message(meta["channel_id"], meta["message_id"]) - await self.client.send_dm( - meta["author_id"], - "Your job posting was moved to the jobs channel.", - ) - - elif action == "flag": - await self.client.add_reaction(meta["channel_id"], meta["message_id"], "⚠️") - - elif action == "delete": - await self.client.delete_message(meta["channel_id"], meta["message_id"]) - await self.client.send_dm(meta["author_id"], output.get("reason", "")) -``` - -## Deploying our app - -We deploy this onto Fly.io. We want a single permanently running machine that triggers itself every 5 minutes. - -You can trigger the first deploy using `fly launch`. - -### Scaling Configuration - -Fly automatically scales your workload to 2 machines and will pause if there is not enough external traffic. For this deployment, there will by definition be 0 API-based traffic, so we need to turn off auto-scaling while keeping a minimum of one machine running. - - -#### Setting the minimum - -You can add a line to your `fly.toml` to get the pausing behavior we want: - -```toml -auto_stop_machines = false -auto_start_machines = true -min_machines_running = 1 -``` - -If our one machine goes down, we do want it to start another one. We don't want it to stop a machine because of no activity, so we turn off `auto_stop_machines`. - -#### Setting the maximum - -We also don't want more than one machine: (1) I don't want to pay for that, and (2) we haven't built in any deduplication mechanisms. If there are two machines running, they might both pick up the same messages. - -You can set the number of machines to one and turn off `ha` (horizontal autoscaling). -```bash -fly scale count 1 -fly deploy --ha=false -``` - -`fly scale` should remove one of the two default machines if you already ran `fly launch`. This was a bit finicky when I was setting it up, so you may also need to run `fly machine kill` to manually remove one. - -### Production Considerations - -"production" is a loose word here because of the small scale, but this is deployed live, and actively affecting DSPy discord users. - -Because this is such a small project, there wasn't a great dev environment nor was it worth it to set up one. I sent messages into `#general` to test this. Before I enabled any actions that would actually remove messages, I set up a dry run mode that would analyze messages and send a dry run audit message into `#moderator-only`. I saw that it was correctly flagging the examples that I put in, and that was enough to turn off dry run mode. - -One other consideration: while it would be annoying for people to get messages falsely moved for a case that isn't specified, it's not the end of the world. A fine developer workflow is to notice a new error case, adjust the bot, and redeploy. Any change does not need to be thoroughly tested, because the stakes are quite low so long as it doesn't delete the whole Discord server. - -### Persistence - -We create a file to store all of the IDs that we have processed. Losing this isn't a big deal—at most you're redoing 20 call. If you were to expand this system, you'd certainly want to change it. - -`fly volumes create dspy_discord_data --size 1` - -Then inside `fly.toml` we add: -```toml -[mounts] - source = "dspy_discord_data" - destination = "/data" -``` - -### Secrets - -Then we need to set the secrets. - -You'll need a Discord bot token with access to read messages, send messages, and delete messages. You can get the bot token from [this tutorial](https://discord.com/developers/docs/quick-start/getting-started). To get the Channel ID, make sure your Discord client is in developer mode, then right click on the channel and select `Copy Channel ID`. - -```bash -fly secrets set \ - DISCORD_BOT_TOKEN="" \ - DISCORD_CHANNEL_IDS=", " \ - DISCORD_JOBS_CHANNEL_ID="" \ - DISCORD_AUDIT_CHANNEL_ID="" \ - OPENAI_API_KEY="" -``` - -You can set the `DRY_RUN` environment variable to `true` if you want to only send audit logs without taking actions, to verify it's working properly. - -## Conclusion - -### Learnings - -Fly.io + [`dspy-cli`](https://github.com/cmpnd-ai/dspy-cli) make it REALLY easy to deploy hobbyist DSPy usecases. This example was the first problem that I had that I wanted to use it to solve. - -### Cost - -**Price** - -This is shockingly cheap to run! The LLM inference is not expensive (using gpt-5-nano), and the server costs <$1 per month (thank you Firecracker VMs + Fly.io). I'm happy to eat this cost to keep the server healthier and save myself the work I would have done otherwise. - -**Development Time** - -This bot did not take me that long to implement. The 25 lines of DSPy did not take long. I spent much longer writing the blog post than I did coding the bot. Especially once I had the Discord token enabled, it was incredibly easy for Amp to wire up the rest. I implemented the Gateway system for `dspy-cli` at the same time, and I took more time on that because its an important abstraction to get right. - -**Maintainance** - -If I want to make a change, all I need to do is update the signature, and run `fly deploy` to update my machine. Or, if I wanted to add more modules, I can still use the same VM. - -### Limitations - -**Volume** - -This can by design, only work on 20 messages per 5 minutes. The limiting factors will be your LLM inference calls, rather than the ability of the runner to manage the requests. - -**Prompt Injection** - -Someone might be able to sneak in a job posting via prompt injection. - -In practice, this doesn't actually matter. People are good at tagging the mods if a message does sneak through. - -The bot has no tool access, and it's not like the signature prompt is secret. There are no tools to access other messages, or ability to perform destructive actions towards other users. - -Notably, I do not allow for any other messages in the thread context to be seen by the model. Showing full conversations would open up a lot of weird prompt injection avenues that I don't want to deal with. - -**Spam** - -Processing a single message at a time means that we miss people who send a job posting in multiple channels. - -Often what these bots do is drop a message into every channel in the server. Because each message is processed individually, we currently would take all of these and (without deduping) move them into #jobs. - -I will add some very simple dedup behavior in a future update, but for now I am just going to leave it. The goal of this bot for now is to catch the 80% of the simple cases. - -Immediately after I made this bot, there were some messages it did not move when it should have. It thought some scammy crypto job postings were actually people introducing themselves. As some people in the Discord pointed out (thanks @prashanth and @mchonedev), it's pretty obvious that anyone using the word "blockchain" in their post is likely not a legitimate user. DSPy is not a crypto server, and any thoughtful dev would hopefully know their audience. - ---- - -If you want to join the DSPy Discord and see the bot in action, here's the invite: [https://discord.gg/f5DJ778ZnK](https://discord.gg/f5DJ778ZnK) - -## Appendix - -### DSPy Signature to prompt example - -If you are curious about how the dspy signature gets turned into a prompt, it looks like the following. - -The signature is: -```python -class JobPostingSignature(dspy.Signature): - """Classify a Discord message and determine moderation action. - - A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others""" - - message: str = dspy.InputField(desc="The Discord message content") - author: str = dspy.InputField(desc="The message author's username") - channel_name: str = dspy.InputField(desc="The channel where the message was posted") - - intent: Literal["post_job", "seek_job", "other"] = dspy.OutputField( - desc="The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion" - ) - action: Literal["allow", "move", "flag", "delete"] = dspy.OutputField( - desc="Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation" - ) - reason: str = dspy.OutputField( - desc="Brief explanation of the classification and recommended action" - ) -``` - -DSPy has a concept of an "adapter" which is a class that determines how a signature gets turned into a prompt, and also how the answers get extracted on the other end. - -The rough outline for the adapters is: -``` -System prompt: -1. Inputs -2. Outputs -3. Task - -User prompt: -1. Field name: value for field, value in inputs -2. Desired assistant output list -``` - -The exact prompt that gets sent to the LLM for our signature above is: -``` -System message: - -Your input fields are: -1. `message` (str): The Discord message content -2. `author` (str): The message author's username -3. `channel_name` (str): The channel where the message was posted -Your output fields are: -1. `intent` (Literal['post_job', 'seek_job', 'other']): The user's intent: 'post_job' if offering a job, 'seek_job' if looking for work, 'other' for general discussion -2. `action` (Literal['allow', 'move', 'flag', 'delete']): Action to take: 'allow' if appropriate for channel, 'move' if should be in jobs channel, 'flag' for manual review, 'delete' if spam/violation -3. `reason` (str): Brief explanation of the classification and recommended action -All interactions will be structured in the following way, with the appropriate values filled in. - -[[ ## message ## ]] -{message} - -[[ ## author ## ]] -{author} - -[[ ## channel_name ## ]] -{channel_name} - -[[ ## intent ## ]] -{intent} # note: the value you produce must exactly match (no extra characters) one of: post_job; seek_job; other - -[[ ## action ## ]] -{action} # note: the value you produce must exactly match (no extra characters) one of: allow; move; flag; delete - -[[ ## reason ## ]] -{reason} - -[[ ## completed ## ]] -In adhering to this structure, your objective is: - Classify a Discord message and determine moderation action. - - A job posting or job seeking message will express the primary intent of introducing the user, their qualifications/openness to work, and their availability for hire, or availability to hire others - -User message: - -[[ ## message ## ]] -Hey everyone! I'm a senior Python developer with 5 years of experience looking for new opportunities. Open to remote work! - -[[ ## author ## ]] -job_seeker_123 - -[[ ## channel_name ## ]] -general - -Respond with the corresponding output fields, starting with the field `[[ ## intent ## ]]` (must be formatted as a valid Python Literal['post_job', 'seek_job', 'other']), then `[[ ## action ## ]]` (must be formatted as a valid Python Literal['allow', 'move', 'flag', 'delete']), then `[[ ## reason ## ]]`, and then ending with the marker for `[[ ## completed ## ]]`. -``` - -And the LM responds with: -``` -[[ ## intent ## ]] -seek_job - -[[ ## action ## ]] -move - -[[ ## reason ## ]] -The message expresses the user's intent to seek job opportunities, which is more appropriate for a jobs channel rather than a general chat. - -[[ ## completed ## ]] -``` - -### Batch Processing - -For higher throughput, `CronGateway` supports batch mode which processes all inputs in parallel using DSPy's `module.batch()`: - -```python -class JobPostingGateway(CronGateway): - schedule = "*/5 * * * *" - use_batch = True # Enable parallel processing - num_threads = 4 # Number of concurrent threads (optional) - max_errors = 10 # Stop batch if this many errors occur (optional) -``` - -With batch mode enabled, the scheduler will call your module's `batch()` method instead of running `forward()` sequentially. This is useful when you have many inputs and want to parallelize LLM calls. The `on_complete` callback still runs once per input after all batch results return. - -### Full fly.toml - -```toml -app = 'discord-mod' -primary_region = 'ewr' - -[build] - -[http_service] - internal_port = 8000 - force_https = true - auto_stop_machines = false - auto_start_machines = true - min_machines_running = 1 - processes = ['app'] - -[[vm]] - memory = '1gb' - cpu_kind = 'shared' - cpus = 1 - memory_mb = 1024 - -[mounts] - source = "processed_data" - destination = "/data" -``` \ No newline at end of file diff --git a/examples/discord-mod/tests/test_eval.py b/examples/discord-mod/tests/test_eval.py new file mode 100644 index 0000000..e6fb330 --- /dev/null +++ b/examples/discord-mod/tests/test_eval.py @@ -0,0 +1,188 @@ +""" +Evaluation script for the Discord job posting classifier. + +Usage: + python -m tests.test_eval + # or + cd examples/discord-mod && python tests/test_eval.py +""" + +import sys +from pathlib import Path + +# Add src to path for imports +sys.path.insert(0, str(Path(__file__).parent.parent / "src")) + +import dspy +from dspy.evaluate import Evaluate + +from discord_mod.modules.classify_job_posting import ClassifyJobPosting +from data.eval_dataset import get_eval_dataset, get_dataset_stats, get_dataset_by_category + + +def intent_metric(example, pred, _trace=None) -> float: + """Check if the predicted intent matches the expected intent.""" + return 1.0 if pred.intent == example.intent else 0.0 + + +def action_metric(example, pred, _trace=None) -> float: + """Check if the predicted action matches the expected action.""" + return 1.0 if pred.action == example.action else 0.0 + + +def combined_metric(example, pred, _trace=None) -> float: + """ + Combined metric: both intent AND action must be correct. + Returns 1.0 only if both match, 0.0 otherwise. + """ + intent_correct = pred.intent == example.intent + action_correct = pred.action == example.action + return 1.0 if (intent_correct and action_correct) else 0.0 + + +def run_evaluation(model: str = "openai/gpt-5-nano", num_threads: int = 4): + """Run the full evaluation suite.""" + # Configure DSPy + lm = dspy.LM(model) + dspy.configure(lm=lm) + + # Load dataset + devset = get_eval_dataset() + stats = get_dataset_stats() + + print("=" * 60) + print("Discord Moderation Bot Evaluation") + print("=" * 60) + print(f"\nDataset: {stats['total']} examples") + print(f" Categories: {stats['by_category']}") + print(f" Intents: {stats['by_intent']}") + print(f" Actions: {stats['by_action']}") + print(f"\nModel: {model}") + print("=" * 60) + + # Initialize the module + classifier = ClassifyJobPosting() + + # Run evaluations with different metrics + print("\n[1/3] Evaluating Intent Accuracy...") + intent_evaluator = Evaluate( + devset=devset, + metric=intent_metric, + num_threads=num_threads, + display_progress=True, + display_table=5, + ) + intent_result = intent_evaluator(classifier) + print(f"Intent Accuracy: {intent_result.score:.1f}%") + + print("\n[2/3] Evaluating Action Accuracy...") + action_evaluator = Evaluate( + devset=devset, + metric=action_metric, + num_threads=num_threads, + display_progress=True, + display_table=5, + ) + action_result = action_evaluator(classifier) + print(f"Action Accuracy: {action_result.score:.1f}%") + + print("\n[3/3] Evaluating Combined (Intent + Action)...") + combined_evaluator = Evaluate( + devset=devset, + metric=combined_metric, + num_threads=num_threads, + display_progress=True, + display_table=5, + ) + combined_result = combined_evaluator(classifier) + print(f"Combined Accuracy: {combined_result.score:.1f}%") + + # Per-category breakdown + print("\n" + "=" * 60) + print("Per-Category Results (Action Accuracy)") + print("=" * 60) + + categories = ["nuanced", "sanity_general", "sanity_job", "spam", "jobs_channel"] + for category in categories: + cat_devset = get_dataset_by_category(category) + if not cat_devset: + continue + + cat_evaluator = Evaluate( + devset=cat_devset, + metric=action_metric, + num_threads=num_threads, + display_progress=False, + ) + cat_result = cat_evaluator(classifier) + print(f" {category}: {cat_result.score:.1f}% ({len(cat_devset)} examples)") + + # Summary + print("\n" + "=" * 60) + print("SUMMARY") + print("=" * 60) + print(f" Intent Accuracy: {intent_result.score:.1f}%") + print(f" Action Accuracy: {action_result.score:.1f}%") + print(f" Combined Accuracy: {combined_result.score:.1f}%") + print("=" * 60) + + return { + "intent_accuracy": intent_result.score, + "action_accuracy": action_result.score, + "combined_accuracy": combined_result.score, + } + + +def analyze_errors(model: str = "openai/gpt-5-nano"): + """Analyze specific error cases for debugging.""" + lm = dspy.LM(model) + dspy.configure(lm=lm) + + devset = get_eval_dataset() + classifier = ClassifyJobPosting() + + print("Analyzing predictions...\n") + + errors = [] + for example in devset: + pred = classifier( + message=example.message, + author=example.author, + channel_name=example.channel_name, + ) + + if pred.intent != example.intent or pred.action != example.action: + errors.append({ + "example": example, + "prediction": pred, + }) + + print(f"Found {len(errors)} errors out of {len(devset)} examples\n") + + for i, error in enumerate(errors, 1): + ex = error["example"] + pred = error["prediction"] + + print(f"Error {i}:") + print(f" Message: {ex.message[:100]}...") + print(f" Author: {ex.author}, Channel: {ex.channel_name}") + print(f" Expected: intent={ex.intent}, action={ex.action}") + print(f" Got: intent={pred.intent}, action={pred.action}") + print(f" Reason: {pred.reason}") + print() + + +if __name__ == "__main__": + import argparse + + parser = argparse.ArgumentParser(description="Evaluate Discord moderation classifier") + parser.add_argument("--model", default="openai/gpt-5-nano", help="Model to use") + parser.add_argument("--threads", type=int, default=4, help="Number of threads") + parser.add_argument("--analyze", action="store_true", help="Analyze errors in detail") + + args = parser.parse_args() + + if args.analyze: + analyze_errors(model=args.model) + else: + run_evaluation(model=args.model, num_threads=args.threads)