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agentops_integration #25

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50 changes: 42 additions & 8 deletions app/chat_gpt_client.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,34 +3,46 @@
import os
import logging
from typing import List
import agentops
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Initialize AgentOps
AGENTOPS_API_KEY = os.getenv("AGENTOPS_API_KEY")
if not AGENTOPS_API_KEY:
raise ValueError("AGENTOPS_API_KEY not found in environment variables")

agentops.init(AGENTOPS_API_KEY)
Comment on lines +9 to +17

@brylie brylie Jul 12, 2024

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This initialization should happen in the app.py only, since it only needs to happen when the app is bootstrapped.

Suggested change
# Load environment variables
load_dotenv()
# Initialize AgentOps
AGENTOPS_API_KEY = os.getenv("AGENTOPS_API_KEY")
if not AGENTOPS_API_KEY:
raise ValueError("AGENTOPS_API_KEY not found in environment variables")
agentops.init(AGENTOPS_API_KEY)


CHAT_GPT_DEFAULT_MODEL = os.getenv("CHAT_GPT_MODEL", "gpt-4o")
CHAT_GPT_DEFAULT_TEMPERATURE = float(os.getenv("CHAT_GPT_TEMPERATURE", "0.7"))
CHAT_GPT_DEFAULT_MAX_TOKENS = int(os.getenv("CHAT_GPT_MAX_TOKENS", "1500"))


class MessageRole(str, Enum):
user = "user"
assistant = "assistant"
system = "system"


class Message(BaseModel):
role: MessageRole
content: str


# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Configure OpenAI client
client = AsyncOpenAI(api_key=os.getenv("OPENAI_API_KEY"))
if not client.api_key:
raise ValueError("OPENAI_API_KEY not found in environment variables")
@agentops.record_function('configure_openai_client')
def configure_openai_client():
client = AsyncOpenAI(api_key=os.getenv("OPENAI_API_KEY"))
if not client.api_key:
raise ValueError("OPENAI_API_KEY not found in environment variables")
return client

client = configure_openai_client()

@agentops.record_function('get_chat_response_with_history')
async def get_chat_response_with_history(
messages: List[Message],
system_prompt: str = "You are a helpful assistant that always answers questions.",
Expand Down Expand Up @@ -60,5 +72,27 @@ async def get_chat_response_with_history(
)
return response.choices[0].message.content.strip()
except Exception as e:
logger.error(f"OpenAI API error: {str(e)}")
error_message = f"OpenAI API error: {str(e)}"
logger.error(error_message)
agentops.log_error(error_message)
return f"I'm sorry, but I encountered an error: {str(e)}"

@agentops.record_function('main')
async def main():
# Example usage
messages = [
Message(role=MessageRole.user, content="Hello, how are you?"),
Message(role=MessageRole.assistant, content="I'm doing well, thank you for asking. How can I assist you today?"),
Message(role=MessageRole.user, content="Can you tell me about the weather?"),
]
response = await get_chat_response_with_history(messages)
print(f"Assistant's response: {response}")

if __name__ == "__main__":
import asyncio
try:
asyncio.run(main())
except Exception as e:
agentops.log_error(str(e))
finally:
agentops.end_session('Success')
136 changes: 75 additions & 61 deletions app/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
from typing import List, Dict
import markdown2
import uuid
import agentops

from app.chat_gpt_client import get_chat_response_with_history, Message, MessageRole
from app.rag_service import RAGService
Expand All @@ -15,45 +16,47 @@
# Load environment variables
load_dotenv()

# Load configuration from environment variables with default values
CHAT_TITLE = os.getenv(
"CHAT_TITLE",
"AI Chat Assistant",
)
WELCOME_MESSAGE = os.getenv(
"WELCOME_MESSAGE",
"Welcome! How can I assist you today?",
)
SYSTEM_PROMPT = os.getenv(
"SYSTEM_PROMPT",
"You are a helpful assistant that answers questions based on the given context and chat history.",
)
# TODO: Move this to be a Pydantc Field on the AstraDBStore (AstraDBConfig?)
ASTRA_COLLECTION_NAME = os.getenv("ASTRA_COLLECTION_NAME")
# Initialize AgentOps
AGENTOPS_API_KEY = os.getenv("AGENTOPS_API_KEY")
if not AGENTOPS_API_KEY:
raise ValueError("AGENTOPS_API_KEY not found in environment variables")

agentops.init(AGENTOPS_API_KEY)

app = FastAPI()
# Load configuration from environment variables with default values
CHAT_TITLE = os.getenv("CHAT_TITLE", "AI Chat Assistant")
WELCOME_MESSAGE = os.getenv("WELCOME_MESSAGE", "Welcome! How can I assist you today?")
SYSTEM_PROMPT = os.getenv("SYSTEM_PROMPT", "You are a helpful assistant that answers questions based on the given context and chat history.")
ASTRA_COLLECTION_NAME = os.getenv("ASTRA_COLLECTION_NAME")

templates_directory = os.path.join(os.path.dirname(__file__), "templates")
templates = Jinja2Templates(directory=templates_directory)
@agentops.record_function('create_app')
def create_app():
app = FastAPI()

templates_directory = os.path.join(os.path.dirname(__file__), "templates")
templates = Jinja2Templates(directory=templates_directory)

static_directory = os.path.join(os.path.dirname(__file__), "static")
app.mount("/static", StaticFiles(directory=static_directory), name="static")

return app, templates

# Mount the static directory
static_directory = os.path.join(os.path.dirname(__file__), "static")
app.mount("/static", StaticFiles(directory=static_directory), name="static")
app, templates = create_app()

# Simulating a database with an in-memory list
chat_history: List[Message] = []

# Get the absolute path to the project root
project_root = os.path.dirname(os.path.abspath(__file__))

# Initialize RAG service with ChromaDBStore
chroma_db_path = os.path.join(project_root, "db")
vector_store = AstraDBStore(collection_name=ASTRA_COLLECTION_NAME)
rag_service = RAGService(vector_store)
@agentops.record_function('initialize_rag_service')
def initialize_rag_service():
chroma_db_path = os.path.join(project_root, "db")
vector_store = AstraDBStore(collection_name=ASTRA_COLLECTION_NAME)
return RAGService(vector_store)

rag_service = initialize_rag_service()

@app.get("/", response_class=HTMLResponse)
@agentops.record_function('read_root')
async def read_root(request: Request) -> HTMLResponse:
return templates.TemplateResponse(
"chat.html",
Expand All @@ -64,48 +67,59 @@ async def read_root(request: Request) -> HTMLResponse:
},
)


@app.post("/chat")
@agentops.record_function('chat')
async def chat(request: Request, message: str = Form(...)) -> HTMLResponse:
# Prepare messages with the correct order
prepared_messages, citations = await rag_service.prepare_messages_with_sources(
system_prompt=f"<system-prompt>{SYSTEM_PROMPT}</system-prompt>",
chat_history=chat_history[-5:], # Last 5 messages for context
user_message=message,
)

# Get response from ChatGPT using prepared messages
bot_response = await get_chat_response_with_history(prepared_messages)

# Render Markdown to HTML (with safety features)
bot_response_html = markdown2.markdown(bot_response, safe_mode="escape")

# Add user message and bot response to chat history
chat_history.append(Message(role=MessageRole.user, content=message))
chat_history.append(Message(role=MessageRole.assistant, content=bot_response))

message_id = str(uuid.uuid4())

response_html = templates.TemplateResponse(
"bot_message.html",
{
"request": request,
"bot_response_html": bot_response_html,
"citations": citations,
"message_id": message_id,
},
)

return response_html

try:
prepared_messages, citations = await rag_service.prepare_messages_with_sources(
system_prompt=f"<system-prompt>{SYSTEM_PROMPT}</system-prompt>",
chat_history=chat_history[-5:],
user_message=message,
)

bot_response = await get_chat_response_with_history(prepared_messages)
bot_response_html = markdown2.markdown(bot_response, safe_mode="escape")

chat_history.append(Message(role=MessageRole.user, content=message))
chat_history.append(Message(role=MessageRole.assistant, content=bot_response))

message_id = str(uuid.uuid4())

response_html = templates.TemplateResponse(
"bot_message.html",
{
"request": request,
"bot_response_html": bot_response_html,
"citations": citations,
"message_id": message_id,
},
)

return response_html
except Exception as e:
agentops.log_error(f"Error in chat endpoint: {str(e)}")
raise

@app.get("/api/chat_history")
@agentops.record_function('get_chat_history')
async def get_chat_history() -> List[Dict[str, str]]:
return [message.model_dump() for message in chat_history]


# Optional: Add a route to clear chat history (for testing/demo purposes)
@app.post("/api/clear_history")
@agentops.record_function('clear_history')
async def clear_history() -> Dict[str, str]:
chat_history.clear()
return {"message": "Chat history cleared"}

@agentops.record_function('main')
def main():
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)

if __name__ == "__main__":
try:
main()
except Exception as e:
agentops.log_error(str(e))
finally:
agentops.end_session('Success')
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