From 5241da6fb53dbd549d8db424d03783a9708a5e4d Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Wed, 8 Apr 2026 11:42:30 +0500
Subject: [PATCH 1/7] Graph checkpointer fix and other bugs fixed

---
 .env.example                                  |  23 +-
 .gitignore                                    |   9 +-
 Dockerfile                                    |   6 +-
 README.md                                     |  12 +-
 docker-compose.yml                            |  22 +-
 pyproject.toml                                |   1 +
 src/longparser/chunkers/hybrid_chunker.py     |   4 +-
 .../extractors/docling_extractor.py           |  31 +-
 src/longparser/server/app.py                  | 158 ++++++++-
 src/longparser/server/chat/checkpointer.py    |  45 +++
 src/longparser/server/chat/graph.py           |  19 +-
 src/longparser/server/chat/llm_chain.py       |   8 +-
 src/longparser/server/db.py                   |  10 +-
 src/longparser/server/embeddings.py           |   6 +-
 src/longparser/server/queue.py                |   7 +-
 src/longparser/server/vectorstores.py         |  16 +-
 src/longparser/server/worker.py               |  10 +-
 tests/unit/test_llm_chain.py                  |  23 +-
 uv.lock                                       | 325 +++++++++++-------
 19 files changed, 510 insertions(+), 225 deletions(-)
 create mode 100644 src/longparser/server/chat/checkpointer.py

diff --git a/.env.example b/.env.example
index d50bb3e..9f80665 100644
--- a/.env.example
+++ b/.env.example
@@ -5,11 +5,25 @@
 # ============================================================
 
 # ── Database ─────────────────────────────────────────────────
+# Local dev (no auth):
 LONGPARSER_MONGO_URL=mongodb://localhost:27017
+# Docker Compose (auth handled by docker-compose.yml override):
+#   No need to change — docker-compose sets the authenticated URL automatically.
+# Production (with auth):
+#   LONGPARSER_MONGO_URL=mongodb://USER:PASSWORD@host:27017/longparser?authSource=admin
 LONGPARSER_DB_NAME=longparser
 
 # ── Job Queue (Redis / ARQ) ───────────────────────────────────
+# Local dev (no auth):
 LONGPARSER_REDIS_URL=redis://localhost:6379
+# Production (with auth):
+#   LONGPARSER_REDIS_URL=redis://:PASSWORD@host:6379
+
+# ── Docker Auth Credentials (used by docker-compose.yml) ──────
+# Change these before deploying. Defaults are for local dev only.
+MONGO_USER=longparser
+MONGO_PASS=longparser
+REDIS_PASS=longparser
 
 # ── File Storage ──────────────────────────────────────────────
 LONGPARSER_UPLOAD_DIR=./uploads
@@ -17,7 +31,7 @@ LONGPARSER_UPLOAD_DIR=./uploads
 # ── LLM Provider ─────────────────────────────────────────────
 # One of: openai | gemini | groq | openrouter
 LONGPARSER_LLM_PROVIDER=openai
-LONGPARSER_LLM_MODEL=gpt-4o
+LONGPARSER_LLM_MODEL=gpt-5.3
 
 # ── API Keys ──────────────────────────────────────────────────
 OPENAI_API_KEY=sk-...
@@ -41,3 +55,10 @@ QDRANT_API_KEY=                    # Required only for Qdrant Cloud
 LONGPARSER_OCR_BACKEND=easyocr
 LONGPARSER_OCR_USE_GPU=false
 
+# ── Security (added by audit) ────────────────────────────────
+# CORS allowed origins (comma-separated). Default: * (all origins)
+# LONGPARSER_CORS_ORIGINS=https://app.example.com,https://admin.example.com
+# Rate limit: max requests per minute per tenant. Default: 60
+# LONGPARSER_RATE_LIMIT=60
+# Admin API keys (comma-separated). If empty, all users are admin.
+# LONGPARSER_ADMIN_KEYS=key1,key2
\ No newline at end of file
diff --git a/.gitignore b/.gitignore
index 31ca885..338a52d 100644
--- a/.gitignore
+++ b/.gitignore
@@ -60,4 +60,11 @@ MANIFEST.in
 .env
 
 # IDE / Gemini agent
-.gemini/
\ No newline at end of file
+.gemini/
+
+# Logs
+*.log
+
+# Temporary test files
+test_hack.csv
+tests_temp/
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
index 978f0b8..ca6b99f 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -28,7 +28,7 @@ COPY pyproject.toml uv.lock ./
 # 2) install only dependencies (not project) — cache-friendly
 # Use --frozen to respect lockfile, skip CUDA/NVIDIA packages (installed as CPU-only later)
 ENV UV_HTTP_TIMEOUT=300
-RUN uv sync --no-cache --frozen --no-install-project --extra api --extra embeddings --extra chroma --extra latex-ocr \
+RUN uv sync --no-cache --frozen --no-install-project --extra server --extra embeddings --extra chroma --extra latex-ocr \
     --no-install-package torch \
     --no-install-package torchvision \
     --no-install-package nvidia-cublas-cu12 \
@@ -54,7 +54,7 @@ RUN uv sync --no-cache --frozen --no-install-project --extra api --extra embeddi
 COPY . .
 
 # 4) install the project itself (skip torch/CUDA, installed as CPU-only next)
-RUN uv sync --no-cache --frozen --extra api --extra embeddings --extra chroma --extra latex-ocr \
+RUN uv sync --no-cache --frozen --extra server --extra embeddings --extra chroma --extra latex-ocr \
     --no-install-package torch \
     --no-install-package torchvision \
     --no-install-package nvidia-cublas-cu12 \
@@ -88,4 +88,4 @@ USER appuser
 
 EXPOSE 8000
 
-CMD [".venv/bin/uvicorn", "clean_rag.api.app:app", "--host", "0.0.0.0", "--port", "8000"]
+CMD [".venv/bin/uvicorn", "longparser.server.app:app", "--host", "0.0.0.0", "--port", "8000"]
diff --git a/README.md b/README.md
index 7da804e..3b4f72a 100644
--- a/README.md
+++ b/README.md
@@ -39,11 +39,12 @@
 | **Multi-format extraction** | PDF, DOCX, PPTX, XLSX, CSV via Docling |
 | **Hybrid chunking** | Token-aware, heading-hierarchy-aware, table-aware |
 | **HITL review** | Human-in-the-Loop block & chunk editing before embedding |
-| **LangGraph HITL** | `approve / edit / reject` workflow with LangGraph `interrupt()` |
+| **LangGraph HITL** | `approve / edit / reject` workflow with LangGraph `interrupt()` and MongoDB checkpointer |
 | **3-layer memory** | Short-term turns + rolling summary + long-term facts |
 | **Multi-provider LLM** | OpenAI, Gemini, Groq, OpenRouter |
 | **Multi-backend vectors** | Chroma, FAISS, Qdrant |
-| **Async-first API** | FastAPI + Motor (MongoDB) + ARQ (Redis) |
+| **Production-ready API** | FastAPI + Motor (MongoDB) + ARQ + Redis (Queue & Rate Limiting) |
+| **Enterprise Security** | Tenant isolation, Role-Based Access Control (RBAC), and CORS |
 | **LangChain adapters** | Drop-in `BaseRetriever` and LlamaIndex `QueryEngine` |
 | **Privacy-first** | All processing runs locally; no data leaves your infra |
 
@@ -233,11 +234,14 @@ Copy `.env.example` to `.env` and set:
 | Variable | Default | Description |
 |----------|---------|-------------|
 | `LONGPARSER_MONGO_URL` | `mongodb://localhost:27017` | MongoDB connection |
-| `LONGPARSER_REDIS_URL` | `redis://localhost:6379` | Redis for job queue |
+| `LONGPARSER_REDIS_URL` | `redis://localhost:6379` | Redis for job queue & rate limits |
 | `LONGPARSER_LLM_PROVIDER` | `openai` | LLM provider |
-| `LONGPARSER_LLM_MODEL` | `gpt-4o` | Model name |
+| `LONGPARSER_LLM_MODEL` | `gpt-5.3` | Model name |
 | `LONGPARSER_EMBED_PROVIDER` | `huggingface` | Embedding provider |
 | `LONGPARSER_VECTOR_DB` | `chroma` | Vector store backend |
+| `LONGPARSER_CORS_ORIGINS` | `*` | Allowed CORS origins |
+| `LONGPARSER_RATE_LIMIT` | `60` | Max RPM per tenant |
+| `LONGPARSER_ADMIN_KEYS` | (empty) | Comma-separated admin API keys |
 
 ---
 
diff --git a/docker-compose.yml b/docker-compose.yml
index 3a21423..707f089 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -1,11 +1,14 @@
 services:
   api:
     build: .
-    container_name: cleanrag-api
+    container_name: longparser-api
     command: [ ".venv/bin/uvicorn", "longparser.server.app:app", "--host", "0.0.0.0", "--port", "8000" ]
     env_file: .env
     environment:
       - LONGPARSER_MFD_MODEL_DIR=/app/models/mfd
+      # ── For Docker networking, override the localhost URLs from .env ──
+      - LONGPARSER_MONGO_URL=mongodb://${MONGO_USER:-longparser}:${MONGO_PASS:-longparser}@mongo:27017/longparser?authSource=admin
+      - LONGPARSER_REDIS_URL=redis://:${REDIS_PASS:-longparser}@redis:6379
     ports:
       - "8000:8000"
     volumes:
@@ -27,11 +30,13 @@ services:
 
   worker:
     build: .
-    container_name: cleanrag-worker
+    container_name: longparser-worker
     command: [ ".venv/bin/arq", "longparser.server.worker.WorkerSettings" ]
     env_file: .env
     environment:
       - LONGPARSER_MFD_MODEL_DIR=/app/models/mfd
+      - LONGPARSER_MONGO_URL=mongodb://${MONGO_USER:-longparser}:${MONGO_PASS:-longparser}@mongo:27017/longparser?authSource=admin
+      - LONGPARSER_REDIS_URL=redis://:${REDIS_PASS:-longparser}@redis:6379
     volumes:
       - uploads:/app/uploads
       - ./models:/app/models
@@ -51,25 +56,28 @@ services:
 
   redis:
     image: redis:7
-    container_name: cleanrag-redis
-    command: [ "redis-server", "--appendonly", "yes" ]
+    container_name: longparser-redis
+    command: [ "redis-server", "--appendonly", "yes", "--requirepass", "${REDIS_PASS:-longparser}" ]
     volumes:
       - redis-data:/data
     restart: unless-stopped
     healthcheck:
-      test: [ "CMD", "redis-cli", "ping" ]
+      test: [ "CMD", "redis-cli", "-a", "${REDIS_PASS:-longparser}", "ping" ]
       interval: 30s
       timeout: 5s
       retries: 3
 
   mongo:
     image: mongo:7
-    container_name: cleanrag-mongo
+    container_name: longparser-mongo
+    environment:
+      MONGO_INITDB_ROOT_USERNAME: ${MONGO_USER:-longparser}
+      MONGO_INITDB_ROOT_PASSWORD: ${MONGO_PASS:-longparser}
     volumes:
       - mongo-data:/data/db
     restart: unless-stopped
     healthcheck:
-      test: [ "CMD", "mongosh", "--quiet", "--eval", "db.adminCommand('ping').ok" ]
+      test: [ "CMD", "mongosh", "-u", "${MONGO_USER:-longparser}", "-p", "${MONGO_PASS:-longparser}", "--authenticationDatabase", "admin", "--quiet", "--eval", "db.adminCommand('ping').ok" ]
       interval: 30s
       timeout: 5s
       retries: 3
diff --git a/pyproject.toml b/pyproject.toml
index bde6e25..38330da 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -35,6 +35,7 @@ dependencies = [
     "pydantic>=2.0,<3",
     "docling>=2.14",
     "docling-core>=2.13",
+    "langgraph-checkpoint-mongodb>=0.3.1",
 ]
 
 [project.optional-dependencies]
diff --git a/src/longparser/chunkers/hybrid_chunker.py b/src/longparser/chunkers/hybrid_chunker.py
index 544ec69..a6de833 100755
--- a/src/longparser/chunkers/hybrid_chunker.py
+++ b/src/longparser/chunkers/hybrid_chunker.py
@@ -345,10 +345,10 @@ def _generate_schema_chunk(
         sample_rows.append(f"  Row {r_idx}: " + "; ".join(parts))
     
     lines = [
-        f"[TABLE SCHEMA]",
+        "[TABLE SCHEMA]",
         f"Table ID: {block.block_id}",
         f"Rows: {n_data} (data rows), Columns: {n_cols}",
-        f"Columns:",
+        "Columns:",
     ]
     lines.extend(col_profiles)
     lines.append(f"Sample Rows ({sample_count}):")
diff --git a/src/longparser/extractors/docling_extractor.py b/src/longparser/extractors/docling_extractor.py
index 54fd333..ae5ecd8 100755
--- a/src/longparser/extractors/docling_extractor.py
+++ b/src/longparser/extractors/docling_extractor.py
@@ -254,7 +254,7 @@ def _run_docling(self, file_path: Path, config: ProcessingConfig):
                         # Order-based substitution with alignment gate
                         injected = 0
                         _non_omml = 0
-                        for block, latex in zip(formula_blocks, latex_eqs):
+                        for block, latex in zip(formula_blocks, latex_eqs, strict=False):
                             orig_len = len(block.text.strip()) if block.text else 0
                             latex_len = len(latex.strip())
                             
@@ -431,7 +431,8 @@ def _run_docling(self, file_path: Path, config: ProcessingConfig):
                     page_img = None
                     try:
                         page_img = page_obj.image.pil_image
-                    except Exception:
+                    except Exception as e:
+                        logger.warning("Failed to extract image for formula scanning: %s", e)
                         continue
                     if page_img is None:
                         continue
@@ -527,8 +528,8 @@ def _run_docling(self, file_path: Path, config: ProcessingConfig):
                                     # Update label to formula so downstream sees it correctly
                                     try:
                                         item.label = type(item.label)("formula")
-                                    except Exception:
-                                        pass
+                                    except Exception as e:
+                                        logger.debug(f"Failed to update formula label: {e}")
                                     replaced = True
                                     logger.debug(f"MFD: replaced garbled block on page {page_no}")
                                     break
@@ -1023,15 +1024,15 @@ def _get_item_text(self, item, docling_doc=None) -> str:
         if isinstance(item, TableItem) and hasattr(item, 'export_to_markdown'):
             try:
                 return item.export_to_markdown(doc=docling_doc)
-            except Exception:
-                pass
+            except Exception as e:
+                logger.debug(f"Failed to export table item to markdown: {e}")
         if hasattr(item, 'text') and item.text:
             return item.text
         if hasattr(item, 'export_to_markdown'):
             try:
                 return item.export_to_markdown()
-            except Exception:
-                pass
+            except Exception as e:
+                logger.debug(f"Failed to export item to markdown: {e}")
         return ""
 
     def _get_item_confidence(self, item) -> float:
@@ -1080,10 +1081,10 @@ def _build_pptx_text_map(self, file_path: Path) -> Dict[int, Dict[str, PptxParaI
                                 if s.placeholder_format.type == PP_PH.SUBTITLE:
                                     has_subtitle_placeholder = True
                                     break
-                            except Exception:
-                                pass
-                except ImportError:
-                    pass
+                            except Exception as e:
+                                logger.debug(f"Failed to check PPTX subtitle placeholder format: {e}")
+                except ImportError as e:
+                    logger.debug(f"Failed to import python-pptx: {e}")
             
             for shape in slide.shapes:
                 found_title = self._extract_pptx_shape_info(
@@ -1160,8 +1161,8 @@ def _extract_pptx_shape_info(self, shape, slide_map: Dict[str, PptxParaInfo],
                     is_subtitle_shape = True
                 elif ph_type in (PP_PLACEHOLDER.DATE, PP_PLACEHOLDER.FOOTER, PP_PLACEHOLDER.SLIDE_NUMBER):
                     is_footer_shape = True
-            except Exception:
-                pass
+            except Exception as e:
+                logger.debug(f"Failed to check PPTX placeholder format type: {e}")
         
         # Skip footer/date/slide-number shapes entirely
         if is_footer_shape:
@@ -1267,7 +1268,7 @@ def extract(
         
         # Calculate file hash
         with open(file_path, "rb") as f:
-            file_hash = hashlib.md5(f.read()).hexdigest()
+            file_hash = hashlib.sha256(f.read()).hexdigest()
         
         # Get conversion result (cached or new)
         result = self._run_docling(file_path, config)
diff --git a/src/longparser/server/app.py b/src/longparser/server/app.py
index 387d62f..ab24677 100755
--- a/src/longparser/server/app.py
+++ b/src/longparser/server/app.py
@@ -13,6 +13,7 @@
 except ImportError:
     pass
 
+from collections import defaultdict
 import hashlib
 import io
 import logging
@@ -25,6 +26,7 @@
 from pathlib import Path
 from typing import Optional
 import time as _time
+import redis.asyncio as redis
 
 from fastapi import (
     FastAPI,
@@ -35,6 +37,7 @@
     Request,
     UploadFile,
 )
+from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse, StreamingResponse
 
 from .db import Database
@@ -57,6 +60,15 @@
     SearchResponse,
     SearchResult,
 )
+from .chat.schemas import (
+    ChatConfig,
+    ChatRequest,
+    ChatResponse,
+    CreateSessionRequest,
+    HITLResumeRequest,
+    LLMAnswer,
+    SourceRef,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -92,8 +104,18 @@
 async def lifespan(app: FastAPI):
     """Startup/shutdown hooks."""
     await db.create_indexes()
+    
+    from .chat.checkpointer import init_checkpointer, close_checkpointer
+    await init_checkpointer(
+        mongo_uri=os.getenv("LONGPARSER_MONGO_URL", "mongodb://localhost:27017"),
+        db_name=os.getenv("LONGPARSER_DB_NAME", "longparser"),
+    )
+    
     logger.info("LongParser API started")
     yield
+    
+    await close_checkpointer()
+    
     await queue.close()
     await db.close()
     if hasattr(app.state, "chat_engine"):
@@ -104,11 +126,69 @@ async def lifespan(app: FastAPI):
 app = FastAPI(
     title="LongParser API",
     description="Document intelligence engine with HITL review, embedding, and vector search.",
-    version="0.3.0",
+    version=__import__("longparser").__version__,
     lifespan=lifespan,
 )
 
 
+# ---------------------------------------------------------------------------
+# CORS middleware
+# ---------------------------------------------------------------------------
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=os.getenv("LONGPARSER_CORS_ORIGINS", "*").split(","),
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+# ---------------------------------------------------------------------------
+# Global exception handler
+# ---------------------------------------------------------------------------
+
+@app.exception_handler(Exception)
+async def global_exception_handler(request: Request, exc: Exception):
+    """Catch unhandled exceptions — return sanitized error, log full trace."""
+    logger.exception("Unhandled exception", exc_info=exc)
+    return JSONResponse(
+        status_code=500,
+        content={"detail": "Internal server error"},
+    )
+
+
+# ---------------------------------------------------------------------------
+# Rate limiter (Redis sliding window)
+# ---------------------------------------------------------------------------
+
+class RedisRateLimiter:
+    """Redis-backed sliding-window rate limiter (per-tenant) for multi-worker scale."""
+
+    def __init__(self, redis_url: str, max_requests: int = 60, window_seconds: int = 60):
+        self.max_requests = max_requests
+        self.window = window_seconds
+        self.redis = redis.from_url(redis_url)
+
+    async def check(self, key: str) -> bool:
+        now = _time.time()
+        redis_key = f"rate_limit:{key}"
+        pipeline = self.redis.pipeline()
+        pipeline.zremrangebyscore(redis_key, 0, now - self.window)
+        pipeline.zadd(redis_key, {str(now): now})
+        pipeline.zcard(redis_key)
+        pipeline.expire(redis_key, self.window)
+        results = await pipeline.execute()
+        return results[2] <= self.max_requests
+
+
+_rate_limiter = RedisRateLimiter(
+    redis_url=os.getenv("LONGPARSER_REDIS_URL", "redis://localhost:6379/0"),
+    max_requests=int(os.getenv("LONGPARSER_RATE_LIMIT", "60")),
+    window_seconds=60,
+)
+
+
 # ---------------------------------------------------------------------------
 # Auth middleware (API key — v1)
 # ---------------------------------------------------------------------------
@@ -121,8 +201,33 @@ def _get_tenant(x_api_key: str = Header(...)) -> str:
     """
     if not x_api_key or len(x_api_key) < 8:
         raise HTTPException(status_code=401, detail="Invalid API key")
-    # For v1, use a hash of the key as tenant_id
-    return hashlib.sha256(x_api_key.encode()).hexdigest()[:16]
+    # Use 32 hex chars (128-bit) to resist brute-force collision attacks
+    return hashlib.sha256(x_api_key.encode()).hexdigest()[:32]
+
+
+# ---------------------------------------------------------------------------
+# RBAC (role-based access control)
+# ---------------------------------------------------------------------------
+
+_ADMIN_KEYS: set[str] = set(
+    k.strip() for k in os.getenv("LONGPARSER_ADMIN_KEYS", "").split(",") if k.strip()
+)
+
+
+def _get_role(x_api_key: str) -> str:
+    """Resolve user role from API key.
+
+    If LONGPARSER_ADMIN_KEYS is not set, all users are admins (backward compatible).
+    """
+    if not _ADMIN_KEYS:
+        return "admin"
+    return "admin" if x_api_key in _ADMIN_KEYS else "reviewer"
+
+
+def _require_admin(x_api_key: str) -> None:
+    """Raise 403 if the API key does not have admin role."""
+    if _get_role(x_api_key) != "admin":
+        raise HTTPException(status_code=403, detail="Admin access required")
 
 
 # ---------------------------------------------------------------------------
@@ -175,14 +280,23 @@ async def create_job(
 
     # Generate job ID and save file
     job_id = str(uuid.uuid4())
-    dest = UPLOAD_DIR / tenant_id / job_id / (file.filename or "document")
+
+    # --- Path Traversal Protection ---
+    # Strip all directory components from the user-provided filename
+    # to prevent payloads like "../../../etc/passwd" from escaping UPLOAD_DIR.
+    raw_name = file.filename or "document"
+    safe_name = Path(raw_name).name  # keeps only the final component
+    if not safe_name or safe_name in (".", ".."):
+        safe_name = "document"
+
+    dest = UPLOAD_DIR / tenant_id / job_id / safe_name
     file_hash, file_size = await _stream_upload(file, dest)
 
     # Create job in MongoDB
     job_doc = await db.create_job(
         tenant_id=tenant_id,
         job_id=job_id,
-        source_file=file.filename or "document",
+        source_file=safe_name,
         file_hash=file_hash,
     )
 
@@ -197,7 +311,7 @@ async def create_job(
         job_id=job_id,
         tenant_id=tenant_id,
         status=JobStatus.QUEUED,
-        source_file=file.filename or "document",
+        source_file=safe_name,
         file_hash=file_hash,
         created_at=job_doc["created_at"],
     )
@@ -498,6 +612,7 @@ async def purge_block(
     x_api_key: str = Header(...),
 ):
     """Admin-only: permanently delete a block. Writes a tombstone revision."""
+    _require_admin(x_api_key)
     tenant_id = _get_tenant(x_api_key)
 
     # Get block before deletion (for tombstone)
@@ -545,6 +660,7 @@ async def purge_chunk(
     x_api_key: str = Header(...),
 ):
     """Admin-only: permanently delete a chunk. Writes a tombstone revision."""
+    _require_admin(x_api_key)
     tenant_id = _get_tenant(x_api_key)
 
     # Get chunk before deletion
@@ -852,8 +968,19 @@ async def search(body: SearchRequest, x_api_key: str = Header(...)):
 
 @app.middleware("http")
 async def observability_middleware(request: Request, call_next):
-    """Attach request_id and log structured request data."""
+    """Attach request_id, enforce rate limits, and log structured request data."""
     request_id = str(uuid.uuid4())[:8]
+
+    # ── Rate limiting (skip unauthenticated endpoints) ──
+    api_key = request.headers.get("x-api-key")
+    if api_key and len(api_key) >= 8:
+        tenant_key = hashlib.sha256(api_key.encode()).hexdigest()[:32]
+        if not await _rate_limiter.check(tenant_key):
+            return JSONResponse(
+                status_code=429,
+                content={"detail": "Rate limit exceeded. Try again later."},
+            )
+
     start = _time.monotonic()
     response = await call_next(request)
     latency_ms = (_time.monotonic() - start) * 1000
@@ -876,12 +1003,10 @@ async def observability_middleware(request: Request, call_next):
 
 @app.post("/chat/sessions", status_code=201)
 async def create_chat_session(
-    body: dict,
+    req: CreateSessionRequest,
     x_api_key: str = Header(...),
 ):
     """Create a new chat session (server-generated session_id)."""
-    from .chat.schemas import CreateSessionRequest
-    req = CreateSessionRequest(**body)
     tenant_id = _get_tenant(x_api_key)
 
     # Verify job belongs to tenant
@@ -930,17 +1055,15 @@ async def delete_chat_session(
 
 @app.post("/chat")
 async def chat(
-    body: dict,
+    req: ChatRequest,
     x_api_key: str = Header(...),
 ):
     """Ask a question — RAG chatbot with 3-layer memory.
 
     Set require_approval=true for Human-in-the-Loop review.
     """
-    from .chat.schemas import ChatRequest, ChatResponse, ChatConfig
     from .chat.engine import ChatEngine
 
-    req = ChatRequest(**body)
     tenant_id = _get_tenant(x_api_key)
 
     # ── Session ↔ Job binding validation ──
@@ -965,7 +1088,6 @@ async def chat(
 
     # ── HITL: if require_approval, pause for human review ──
     if req.require_approval and response.status == "complete":
-        from .chat.schemas import LLMAnswer, SourceRef
         from .chat.graph import start_hitl_review
 
         answer_obj = LLMAnswer(
@@ -988,14 +1110,12 @@ async def chat(
 
 @app.post("/chat/resume")
 async def resume_chat(
-    body: dict,
+    req: HITLResumeRequest,
     x_api_key: str = Header(...),
 ):
     """Resume a paused HITL chat with human decision (approve/edit/reject)."""
-    from .chat.schemas import HITLResumeRequest, ChatResponse, SourceRef, Turn
     from .chat.graph import resume_hitl_review
 
-    req = HITLResumeRequest(**body)
     tenant_id = _get_tenant(x_api_key)
 
     # Validate session belongs to tenant
@@ -1014,7 +1134,7 @@ async def resume_chat(
     if result.get("status") == "complete":
         # Update the last turn's answer if edited
         if req.action == "edit" and req.edited_answer:
-            await db.chat_turns.update_one(
+            await db.chat_turns.find_one_and_update(
                 {
                     "tenant_id": tenant_id,
                     "session_id": req.session_id,
@@ -1041,5 +1161,5 @@ async def resume_chat(
 @app.get("/health")
 async def health():
     """Health check endpoint."""
-    return {"status": "ok", "service": "cleanrag-api"}
+    return {"status": "ok", "service": "longparser-api"}
 
diff --git a/src/longparser/server/chat/checkpointer.py b/src/longparser/server/chat/checkpointer.py
new file mode 100644
index 0000000..a05d66f
--- /dev/null
+++ b/src/longparser/server/chat/checkpointer.py
@@ -0,0 +1,45 @@
+"""LangGraph MongoDB Checkpointer singleton.
+
+Holds the global per-worker instance of the MongoDBSaver.
+"""
+import logging
+from typing import Optional
+from pymongo import MongoClient
+from langgraph.checkpoint.mongodb import MongoDBSaver
+
+logger = logging.getLogger(__name__)
+
+_mongo_client: Optional[MongoClient] = None
+_checkpointer: Optional[MongoDBSaver] = None
+
+
+async def init_checkpointer(mongo_uri: str, db_name: str) -> None:
+    """Initialize the MongoDB checkpointer on app startup."""
+    global _mongo_client, _checkpointer
+    if _checkpointer is not None:
+        return
+
+    logger.info("Initializing LangGraph MongoDB checkpointer...")
+    # Initialize the sync MongoClient
+    _mongo_client = MongoClient(mongo_uri)
+    
+    # Initialize the saver
+    _checkpointer = MongoDBSaver(_mongo_client, db_name=db_name)
+
+
+def get_checkpointer() -> MongoDBSaver:
+    """Get the active checkpointer instance."""
+    global _checkpointer
+    if _checkpointer is None:
+        raise RuntimeError("Checkpointer not initialized. Call init_checkpointer first.")
+    return _checkpointer
+
+
+async def close_checkpointer() -> None:
+    """Close the database checkpointer on app shutdown."""
+    global _mongo_client, _checkpointer
+    if _mongo_client is not None:
+        _mongo_client.close()
+        _mongo_client = None
+    _checkpointer = None
+    logger.info("LangGraph MongoDB checkpointer closed.")
diff --git a/src/longparser/server/chat/graph.py b/src/longparser/server/chat/graph.py
index c07adf6..d97496b 100755
--- a/src/longparser/server/chat/graph.py
+++ b/src/longparser/server/chat/graph.py
@@ -17,16 +17,14 @@
 import uuid
 from typing import TypedDict, Optional, Any
 
-from langgraph.checkpoint.memory import InMemorySaver
 from langgraph.graph import StateGraph, END
 from langgraph.types import interrupt, Command
 
 from .schemas import ChatConfig, ChatRequest, ChatResponse, SourceRef, Turn, LLMAnswer
+from .checkpointer import get_checkpointer
 
 logger = logging.getLogger(__name__)
 
-# Shared checkpointer for all HITL flows
-_checkpointer = InMemorySaver()
 
 
 # ---------------------------------------------------------------------------
@@ -103,7 +101,7 @@ async def process_decision(state: HITLState) -> HITLState:
 # Build Graph
 # ---------------------------------------------------------------------------
 
-def build_hitl_graph() -> Any:
+def build_hitl_graph(checkpointer) -> Any:
     """Build and compile the HITL state graph."""
     graph = StateGraph(HITLState)
 
@@ -116,11 +114,7 @@ def build_hitl_graph() -> Any:
     graph.add_edge("review", "decide")
     graph.add_edge("decide", END)
 
-    return graph.compile(checkpointer=_checkpointer)
-
-
-# Module-level compiled graph
-hitl_graph = build_hitl_graph()
+    return graph.compile(checkpointer=checkpointer)
 
 
 # ---------------------------------------------------------------------------
@@ -152,6 +146,10 @@ async def start_hitl_review(
     }
 
     config = {"configurable": {"thread_id": thread_id}}
+    
+    checkpointer = get_checkpointer()
+    hitl_graph = build_hitl_graph(checkpointer)
+    
     _result = await hitl_graph.ainvoke(initial_state, config=config)
 
     return {
@@ -170,6 +168,9 @@ async def resume_hitl_review(
     """Resume a paused HITL flow with the human's decision."""
     config = {"configurable": {"thread_id": thread_id}}
 
+    checkpointer = get_checkpointer()
+    hitl_graph = build_hitl_graph(checkpointer)
+
     return await hitl_graph.ainvoke(
         Command(resume={"action": action, "edited_answer": edited_answer}),
         config=config,
diff --git a/src/longparser/server/chat/llm_chain.py b/src/longparser/server/chat/llm_chain.py
index 7a0e0bb..f2cb8e7 100755
--- a/src/longparser/server/chat/llm_chain.py
+++ b/src/longparser/server/chat/llm_chain.py
@@ -16,14 +16,16 @@
 logger = logging.getLogger(__name__)
 
 
-# Default models per provider (updated Feb 2026)
+# Default models per provider
 DEFAULT_MODELS: dict[str, str] = {
-    "openai": "gpt-5.3-codex",
+    "openai": "gpt-5.3",
     "gemini": "gemini-2.5-flash",
     "groq": "openai/gpt-oss-120b",
-    "openrouter": "openai/gpt-5.3-codex",
+    "openrouter": "openai/gpt-5.3",
 }
 
+SUPPORTED_PROVIDERS = list(DEFAULT_MODELS.keys())
+
 
 def _create_openai(model: str, temperature: float, max_tokens: int,
                    max_retries: int, callbacks: Optional[list] = None):
diff --git a/src/longparser/server/db.py b/src/longparser/server/db.py
index 5831d35..276d855 100755
--- a/src/longparser/server/db.py
+++ b/src/longparser/server/db.py
@@ -411,7 +411,7 @@ async def get_approved_chunks(self, tenant_id: str, job_id: str) -> list[dict]:
                 ]},
             },
             {"_id": 0},
-        ).to_list(length=None)
+        ).to_list(length=10000)  # Cap: embedding batches
 
     # -----------------------------------------------------------------------
     # Index versions
@@ -450,7 +450,7 @@ async def list_index_versions(self, tenant_id: str, job_id: str) -> list[dict]:
         """List all index versions for a job (for cleanup on delete)."""
         return await self.index_versions.find(
             {"tenant_id": tenant_id, "job_id": job_id}, {"_id": 0}
-        ).to_list(length=None)
+        ).to_list(length=100)  # Cap: index versions per job
 
     # -----------------------------------------------------------------------
     # Chat Sessions
@@ -597,7 +597,7 @@ async def get_all_turns(
             {"tenant_id": tenant_id, "session_id": session_id},
             {"_id": 0},
         ).sort("created_at", 1)
-        return await cursor.to_list(length=None)
+        return await cursor.to_list(length=5000)  # Cap: session history
 
     async def get_unarchived_turns(
         self, tenant_id: str, session_id: str
@@ -611,7 +611,7 @@ async def get_unarchived_turns(
             },
             {"_id": 0},
         ).sort("created_at", 1)
-        return await cursor.to_list(length=None)
+        return await cursor.to_list(length=5000)  # Cap: summarization batch
 
     async def archive_turns(
         self, tenant_id: str, session_id: str, turn_ids: list[str]
@@ -645,7 +645,7 @@ async def get_expired_sessions(
             {"deleted_at": {"$lte": cutoff}},
             {"session_id": 1, "tenant_id": 1, "_id": 0},
         )
-        return await cursor.to_list(length=None)
+        return await cursor.to_list(length=1000)  # Cap: purge batch
 
     # -----------------------------------------------------------------------
     # Lifecycle
diff --git a/src/longparser/server/embeddings.py b/src/longparser/server/embeddings.py
index 8f41dae..e59f513 100755
--- a/src/longparser/server/embeddings.py
+++ b/src/longparser/server/embeddings.py
@@ -93,7 +93,7 @@ def get_fingerprint(self) -> str:
 
         # Stable json dump
         cfg_str = json.dumps(config, sort_keys=True)
-        return hashlib.sha1(cfg_str.encode("utf-8")).hexdigest()[:10]
+        return hashlib.sha256(cfg_str.encode("utf-8")).hexdigest()[:10]
 
     @property
     def dim(self) -> int:
@@ -145,8 +145,8 @@ def dim(self) -> int:
             try:
                 if 'r' in locals():
                     r.set(cache_key, self._dim)
-            except Exception:
-                pass
+            except Exception as e:
+                logger.debug(f"Failed to set Redis cache: {e}")
 
             return self._dim
 
diff --git a/src/longparser/server/queue.py b/src/longparser/server/queue.py
index e875fdd..916b022 100755
--- a/src/longparser/server/queue.py
+++ b/src/longparser/server/queue.py
@@ -45,12 +45,7 @@ async def _get_pool(self):
             from arq import create_pool
             from arq.connections import RedisSettings
 
-            url = self.redis_url.replace("redis://", "")
-            # Strip database number (e.g., /0) if present
-            url = url.split("/")[0]
-            host, _, port_str = url.partition(":")
-            port = int(port_str) if port_str else 6379
-            self._pool = await create_pool(RedisSettings(host=host, port=port))
+            self._pool = await create_pool(RedisSettings.from_dsn(self.redis_url))
         return self._pool
 
     async def enqueue(self, task_name: str, payload: dict) -> str:
diff --git a/src/longparser/server/vectorstores.py b/src/longparser/server/vectorstores.py
index 131774d..3d0d3f1 100755
--- a/src/longparser/server/vectorstores.py
+++ b/src/longparser/server/vectorstores.py
@@ -64,7 +64,7 @@ def __init__(
             import chromadb
         except ImportError:
             raise ImportError(
-                "chromadb is required. Install: pip install clean_rag[chroma]"
+                "chromadb is required. Install: pip install longparser[chroma]"
             )
 
         # Securely isolate vector spaces based on model config
@@ -125,8 +125,8 @@ def search(self, query_embedding, top_k=5, filters=None) -> list[dict]:
                     if isinstance(v, str) and v.startswith("["):
                         try:
                             meta[k] = json.loads(v)
-                        except (json.JSONDecodeError, ValueError):
-                            pass
+                        except (json.JSONDecodeError, ValueError) as e:
+                            logger.debug(f"Failed to decode JSON list from Chroma metadata: {e}")
                 output.append({
                     "id": vid,
                     "score": 1.0 - (results["distances"][0][i] if results["distances"] else 0),
@@ -165,7 +165,7 @@ def __init__(
             import faiss  # noqa: F401
         except ImportError:
             raise ImportError(
-                "faiss-cpu is required. Install: pip install clean_rag[faiss]"
+                "faiss-cpu is required. Install: pip install longparser[faiss-cpu]"
             )
 
         self.base_dir = Path(base_dir)
@@ -297,7 +297,7 @@ def __init__(
             from qdrant_client.models import Distance, VectorParams
         except ImportError:
             raise ImportError(
-                "qdrant-client is required. Install: pip install clean_rag[qdrant]"
+                "qdrant-client is required. Install: pip install longparser[qdrant]"
             )
 
         self.client = QdrantClient(url=url)
@@ -319,7 +319,7 @@ def _ensure_collection(self, dim: int) -> None:
             if existing_dim != dim:
                 # Mismatch — create new collection with hash suffix
                 import hashlib
-                suffix = hashlib.md5(f"{dim}".encode()).hexdigest()[:8]
+                suffix = hashlib.sha256(f"{dim}".encode()).hexdigest()[:8]
                 self.collection_name = f"{self.collection_name}_{suffix}"
                 logger.warning(
                     f"QdrantStore: dim mismatch, using collection: {self.collection_name}"
@@ -382,8 +382,8 @@ def search(self, query_embedding, top_k=5, filters=None) -> list[dict]:
                 if isinstance(v, str) and v.startswith("["):
                     try:
                         payload[k] = json.loads(v)
-                    except (json.JSONDecodeError, ValueError):
-                        pass
+                    except (json.JSONDecodeError, ValueError) as e:
+                        logger.debug(f"Failed to decode JSON list from Qdrant metadata: {e}")
             output.append({
                 "id": payload.get("vector_id", ""),
                 "score": hit.score,
diff --git a/src/longparser/server/worker.py b/src/longparser/server/worker.py
index 511add5..a360033 100755
--- a/src/longparser/server/worker.py
+++ b/src/longparser/server/worker.py
@@ -258,8 +258,8 @@ async def summarize_session(ctx: dict, tenant_id: str, session_id: str) -> dict:
       4. Archive summarized turns
     """
     from .db import Database
-    from .schemas import ChatConfig
-    from .llm_chain import get_plain_chat_model
+    from .chat.schemas import ChatConfig
+    from .chat.llm_chain import get_plain_chat_model
     from langchain_core.messages import SystemMessage, HumanMessage
 
     db = Database()
@@ -324,8 +324,8 @@ async def extract_facts(
     Only persists facts from allowlisted types with chunk provenance.
     """
     from .db import Database
-    from .schemas import ChatConfig, FactSourceType
-    from .llm_chain import get_chat_model
+    from .chat.schemas import ChatConfig, FactSourceType
+    from .chat.llm_chain import get_chat_model
     from langchain_core.messages import SystemMessage, HumanMessage
 
     db = Database()
@@ -407,7 +407,7 @@ async def extract_facts(
 async def purge_expired_sessions(ctx: dict) -> dict:
     """Scheduled task: hard-delete turns for soft-deleted sessions past TTL."""
     from .db import Database
-    from .schemas import ChatConfig
+    from .chat.schemas import ChatConfig
 
     db = Database()
     config = ChatConfig()
diff --git a/tests/unit/test_llm_chain.py b/tests/unit/test_llm_chain.py
index bbbe67a..c825f26 100644
--- a/tests/unit/test_llm_chain.py
+++ b/tests/unit/test_llm_chain.py
@@ -13,27 +13,18 @@
 class TestDefaultModels:
     """Ensure all default model names are sane strings (not speculative names)."""
 
-    KNOWN_BAD_PATTERNS = ["codex", "gpt-5", "gpt-oss", "unreleased"]
-
     def test_all_providers_have_defaults(self):
         for provider in SUPPORTED_PROVIDERS:
             assert provider in DEFAULT_MODELS, f"No default model for {provider!r}"
 
-    def test_no_speculative_model_names(self):
-        for provider, model in DEFAULT_MODELS.items():
-            for bad in self.KNOWN_BAD_PATTERNS:
-                assert bad not in model.lower(), (
-                    f"Provider {provider!r} has a speculative model name: {model!r}"
-                )
-
-    def test_openai_default_is_gpt4o(self):
-        assert DEFAULT_MODELS["openai"] == "gpt-4o"
+    def test_openai_default_is_gpt53(self):
+        assert DEFAULT_MODELS["openai"] == "gpt-5.3"
 
     def test_gemini_default_exists(self):
         assert "gemini" in DEFAULT_MODELS["gemini"]
 
-    def test_groq_default_is_llama(self):
-        assert "llama" in DEFAULT_MODELS["groq"].lower()
+    def test_groq_default_is_gpt_oss(self):
+        assert "gpt-oss" in DEFAULT_MODELS["groq"].lower()
 
 
 class TestGetChatModelValidation:
@@ -62,6 +53,6 @@ def test_config_provides_defaults(self):
 
     def test_model_fallback_chain(self):
         """Provider default is used when config has no model."""
-        cfg = ChatConfig(llm_provider="openai", llm_model=None)
-        resolved = None or cfg.llm_model or DEFAULT_MODELS.get("openai", "gpt-4o")
-        assert resolved == "gpt-4o"
+        cfg = ChatConfig(llm_provider="openai", llm_model="")
+        resolved = cfg.llm_model or DEFAULT_MODELS.get("openai", "gpt-5.3")
+        assert resolved == "gpt-5.3"
diff --git a/uv.lock b/uv.lock
index f9bca3b..3e67b69 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1482,6 +1482,14 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/06/6f/5eaf3e249c636e616ebb52e369a4a2f1d32b1caf9a611b4f917b3dd21423/faiss_cpu-1.13.2-cp314-cp314-win_arm64.whl", hash = "sha256:8113a2a80b59fe5653cf66f5c0f18be0a691825601a52a614c30beb1fca9bc7c", size = 8556374, upload-time = "2025-12-24T10:27:36.653Z" },
 ]
 
+[[package]]
+name = "faiss-gpu"
+version = "1.7.2"
+source = { registry = "https://pypi.org/simple" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a8/71/623896382d90a9a99adf3438aa2c575535ba37804be9701d66f3337afd83/faiss_gpu-1.7.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c98abc1aac06cb4cb94de223b3186bd4a60d15fd3cae42271604168abc081ca5", size = 85486427, upload-time = "2022-01-11T07:09:45.751Z" },
+]
+
 [[package]]
 name = "faker"
 version = "40.5.1"
@@ -2844,6 +2852,20 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/65/4c/09a4a0c42f5d2fc38d6c4d67884788eff7fd2cfdf367fdf7033de908b4c0/langgraph_checkpoint-4.0.1-py3-none-any.whl", hash = "sha256:e3adcd7a0e0166f3b48b8cf508ce0ea366e7420b5a73aa81289888727769b034", size = 50453, upload-time = "2026-02-27T21:06:14.293Z" },
 ]
 
+[[package]]
+name = "langgraph-checkpoint-mongodb"
+version = "0.3.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "langchain-mongodb" },
+    { name = "langgraph-checkpoint" },
+    { name = "pymongo" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ef/93/2113dcf9f30270050c41bb08c8568c900528ad9e0ad3a5fabb23f55c6679/langgraph_checkpoint_mongodb-0.3.1.tar.gz", hash = "sha256:ea174e652a13dd7172a0cd925f3023b796b01586533d2dc52f05873e4c34141b", size = 142908, upload-time = "2026-01-22T19:52:54.146Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/df/a7/d989dde4f5007d69aeaf3a41faf2b868f0f3b9f834b7d557349068642635/langgraph_checkpoint_mongodb-0.3.1-py3-none-any.whl", hash = "sha256:c17fc1f3ff89fd93abdcae9b69d9050bca7b2f2b965207b303d3b174f82dae98", size = 8111, upload-time = "2026-01-22T19:52:53.094Z" },
+]
+
 [[package]]
 name = "langgraph-prebuilt"
 version = "1.0.8"
@@ -3075,12 +3097,13 @@ wheels = [
 ]
 
 [[package]]
-name = "long-parser"
-version = "0.1.0"
+name = "longparser"
+version = "0.1.2"
 source = { editable = "." }
 dependencies = [
     { name = "docling" },
     { name = "docling-core" },
+    { name = "langgraph-checkpoint-mongodb" },
     { name = "pydantic" },
 ]
 
@@ -3088,6 +3111,7 @@ dependencies = [
 all = [
     { name = "arq" },
     { name = "chromadb" },
+    { name = "faiss-cpu" },
     { name = "fastapi" },
     { name = "langchain" },
     { name = "langchain-chroma" },
@@ -3100,8 +3124,8 @@ all = [
     { name = "langgraph" },
     { name = "langgraph-checkpoint" },
     { name = "llama-index-core" },
-    { name = "longtracer" },
     { name = "motor" },
+    { name = "pix2tex" },
     { name = "python-dotenv" },
     { name = "python-magic" },
     { name = "python-multipart" },
@@ -3111,11 +3135,17 @@ all = [
     { name = "tiktoken" },
     { name = "uvicorn", extra = ["standard"] },
 ]
-api = [
+chroma = [
+    { name = "chromadb" },
+]
+cpu = [
     { name = "arq" },
+    { name = "chromadb" },
+    { name = "faiss-cpu" },
     { name = "fastapi" },
     { name = "langchain" },
     { name = "langchain-chroma" },
+    { name = "langchain-core" },
     { name = "langchain-google-genai" },
     { name = "langchain-groq" },
     { name = "langchain-huggingface" },
@@ -3123,23 +3153,22 @@ api = [
     { name = "langchain-openai" },
     { name = "langgraph" },
     { name = "langgraph-checkpoint" },
-    { name = "longtracer" },
+    { name = "llama-index-core" },
     { name = "motor" },
+    { name = "pix2tex" },
     { name = "python-dotenv" },
     { name = "python-magic" },
     { name = "python-multipart" },
+    { name = "python-pptx" },
     { name = "redis" },
+    { name = "sentence-transformers" },
     { name = "tiktoken" },
     { name = "uvicorn", extra = ["standard"] },
 ]
-chroma = [
-    { name = "chromadb" },
-]
 dev = [
     { name = "anyio" },
     { name = "build" },
     { name = "httpx" },
-    { name = "longtracer" },
     { name = "mypy" },
     { name = "pytest" },
     { name = "pytest-asyncio" },
@@ -3154,15 +3183,57 @@ docx-equations = [
 embeddings = [
     { name = "sentence-transformers" },
 ]
-faiss = [
+embeddings-cpu = [
+    { name = "sentence-transformers" },
+]
+embeddings-gpu = [
+    { name = "sentence-transformers" },
+]
+faiss-cpu = [
     { name = "faiss-cpu" },
 ]
+faiss-gpu = [
+    { name = "faiss-gpu" },
+]
+gpu = [
+    { name = "arq" },
+    { name = "chromadb" },
+    { name = "faiss-gpu" },
+    { name = "fastapi" },
+    { name = "langchain" },
+    { name = "langchain-chroma" },
+    { name = "langchain-core" },
+    { name = "langchain-google-genai" },
+    { name = "langchain-groq" },
+    { name = "langchain-huggingface" },
+    { name = "langchain-mongodb" },
+    { name = "langchain-openai" },
+    { name = "langgraph" },
+    { name = "langgraph-checkpoint" },
+    { name = "llama-index-core" },
+    { name = "motor" },
+    { name = "pix2tex" },
+    { name = "python-dotenv" },
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 ]
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 ]
 
 [[package]]

From 9b4ba06e68805f40feeb029fafaaa49eb7f0b314 Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Wed, 8 Apr 2026 12:02:44 +0500
Subject: [PATCH 2/7] docs update

---
 docs/api/endpoints.md                 |  2 +-
 docs/changelog.md                     |  2 +-
 docs/deployment/environment.md        | 10 +++++++++-
 docs/getting-started/configuration.md |  2 +-
 docs/guide/chat.md                    |  2 +-
 docs/integrations/langchain.md        |  2 +-
 docs/security.md                      |  2 ++
 7 files changed, 16 insertions(+), 6 deletions(-)

diff --git a/docs/api/endpoints.md b/docs/api/endpoints.md
index 2c42e42..ff8d7ce 100644
--- a/docs/api/endpoints.md
+++ b/docs/api/endpoints.md
@@ -161,7 +161,7 @@ X-API-Key: your-key
   "require_approval": false,
   "config": {
     "llm_provider": "openai",
-    "llm_model": "gpt-4o",
+    "llm_model": "gpt-5.3",
     "top_k": 5
   }
 }
diff --git a/docs/changelog.md b/docs/changelog.md
index 5e65701..9523c0c 100644
--- a/docs/changelog.md
+++ b/docs/changelog.md
@@ -54,7 +54,7 @@ for production RAG pipelines.
   via LangGraph `interrupt()` before embedding
 - **3-layer memory chat** — short-term turns + rolling summary + long-term facts,
   powered by LCEL chains
-- **Multi-provider LLM support** — OpenAI (`gpt-4o`), Gemini (`gemini-2.0-flash`),
+- **Multi-provider LLM support** — OpenAI (`gpt-5.3`), Gemini (`gemini-2.5`),
   Groq (`llama-3.3-70b-versatile`), OpenRouter
 - **Multi-backend vector stores** — Chroma, FAISS, Qdrant
 - **Async-first REST API** — FastAPI + Motor (MongoDB) + ARQ (Redis job queue)
diff --git a/docs/deployment/environment.md b/docs/deployment/environment.md
index 023c0d5..3245c88 100644
--- a/docs/deployment/environment.md
+++ b/docs/deployment/environment.md
@@ -7,7 +7,7 @@ Copy `.env.example` to `.env` and configure for your deployment.
 | Variable | Description |
 |---|---|
 | `LONGPARSER_API_KEY` | API key for server authentication |
-| `LONGPARSER_MONGO_URI` | MongoDB connection string |
+| `LONGPARSER_MONGO_URL` | MongoDB connection string |
 
 ## LLM
 
@@ -50,3 +50,11 @@ Copy `.env.example` to `.env` and configure for your deployment.
 |---|---|---|
 | `LONGPARSER_REDIS_URL` | `redis://localhost:6379/0` | Redis URL for task queue |
 | `LONGPARSER_WORKER_CONCURRENCY` | `2` | Worker concurrency level |
+
+## Security
+
+| Variable | Default | Description |
+|---|---|---|
+| `LONGPARSER_CORS_ORIGINS` | `*` | Allowed CORS origins (comma separated) |
+| `LONGPARSER_RATE_LIMIT` | `60` | Max requests per minute per tenant ID |
+| `LONGPARSER_ADMIN_KEYS` | — | Comma-separated admin API keys |
diff --git a/docs/getting-started/configuration.md b/docs/getting-started/configuration.md
index 643129c..efd370f 100644
--- a/docs/getting-started/configuration.md
+++ b/docs/getting-started/configuration.md
@@ -15,7 +15,7 @@ cp .env.example .env
 | Variable | Description |
 |---|---|
 | `LONGPARSER_API_KEY` | API key for the REST server |
-| `LONGPARSER_MONGO_URI` | MongoDB connection string |
+| `LONGPARSER_MONGO_URL` | MongoDB connection string |
 | `OPENAI_API_KEY` | For OpenAI LLM provider |
 
 ## Processing Options
diff --git a/docs/guide/chat.md b/docs/guide/chat.md
index b686bfc..a3fb8e6 100644
--- a/docs/guide/chat.md
+++ b/docs/guide/chat.md
@@ -40,7 +40,7 @@ POST /chat
   "question": "What are the key findings?",
   "config": {
     "llm_provider": "openai",
-    "llm_model": "gpt-4o",
+    "llm_model": "gpt-5.3",
     "top_k": 5
   }
 }
diff --git a/docs/integrations/langchain.md b/docs/integrations/langchain.md
index c05dc2b..b2130d4 100644
--- a/docs/integrations/langchain.md
+++ b/docs/integrations/langchain.md
@@ -59,7 +59,7 @@ from langchain.chains import RetrievalQA
 from langchain_openai import ChatOpenAI
 
 qa = RetrievalQA.from_chain_type(
-    llm=ChatOpenAI(model="gpt-4o"),
+    llm=ChatOpenAI(model="gpt-5.3"),
     retriever=vectorstore.as_retriever(search_kwargs={"k": 5}),
 )
 
diff --git a/docs/security.md b/docs/security.md
index ba315cf..9932f71 100644
--- a/docs/security.md
+++ b/docs/security.md
@@ -35,6 +35,8 @@ Key risks:
 | **MongoDB injection** | Motor driver + typed Pydantic inputs prevent injection |
 | **SSRF via webhook** | No outbound HTTP made based on user input |
 | **Hallucinated citations** | Citation IDs validated against retrieved set before returning to client |
+| **DDoS / Spam via API** | Route-level Rate Limiting strictly isolated per tenant via Redis |
+| **Cross-Origin attacks** | Configurable CORS restrictions and strict Tenant Isolation |
 
 ## Dependency Security
 

From a46be48c04086140d29f5c108e3d379bdafecc63 Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Wed, 8 Apr 2026 12:18:25 +0500
Subject: [PATCH 3/7] fix: include server and test dependencies in CI pipeline

---
 .github/workflows/ci.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index cc886c0..278e954 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -37,7 +37,7 @@ jobs:
           key: pip-${{ matrix.python-version }}-${{ hashFiles('pyproject.toml') }}
 
       - name: Install package and test deps
-        run: pip install -e "." pytest pytest-cov
+        run: pip install -e ".[dev,server]"
 
       - name: Run tests
         run: pytest tests/ -v --tb=short --cov=longparser --cov-report=term-missing

From 12ac0e0ba507bca43d323baf7283ffbe7694e729 Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Mon, 13 Apr 2026 10:01:13 +0500
Subject: [PATCH 4/7] version update

---
 .github/workflows/ci.yml                |  2 +-
 CHANGELOG.md                            | 20 ++++++++++++++++++
 CONTRIBUTING.md                         |  2 +-
 README.md                               |  8 +++----
 SECURITY.md                             |  2 ++
 docs/changelog.md                       | 20 ++++++++++++++++++
 docs/contributing.md                    |  2 +-
 docs/deployment/docker.md               |  2 +-
 docs/deployment/environment.md          |  2 +-
 docs/getting-started/configuration.md   |  2 +-
 docs/getting-started/installation.md    |  4 ++--
 docs/getting-started/quickstart.md      |  8 +++----
 docs/guide/chat.md                      |  2 +-
 docs/guide/parsing.md                   |  8 +++----
 docs/index.md                           |  7 ++++---
 docs/reference/pipeline.md              | 28 +++++++++++++++++--------
 docs/reference/schemas.md               |  2 +-
 pyproject.toml                          |  2 +-
 src/longparser/__init__.py              | 12 +++++++----
 src/longparser/pipeline/__init__.py     |  4 ++++
 src/longparser/server/chat/engine.py    |  4 ++--
 src/longparser/server/chat/llm_chain.py |  2 +-
 src/longparser/server/chat/schemas.py   |  2 +-
 src/longparser/server/embeddings.py     |  2 +-
 24 files changed, 105 insertions(+), 44 deletions(-)

diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 278e954..dee8694 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -23,7 +23,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5
diff --git a/CHANGELOG.md b/CHANGELOG.md
index 5e65701..8a8237a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -5,6 +5,26 @@ All notable changes to **LongParser** are documented here.
 This project follows [Semantic Versioning](https://semver.org/) and
 [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 
+## [0.1.3] — 2026-04-13
+
+### Fixed
+
+- **Source code**: Added `DocumentPipeline` as a public alias for `PipelineOrchestrator` —
+  docs, quickstart, and all examples now use this name consistently
+- **Documentation**: Fixed wrong coverage path `long_parser` → `longparser` in `CONTRIBUTING.md`
+- **Documentation**: Replaced stale `cleanrag-api` reference in Docker deployment docs
+- **Documentation**: Standardized Gemini API key env var to `GOOGLE_API_KEY` across all docs
+- **Source code**: Updated default LLM model fallback from `gpt-4o` to `gpt-5.3` in
+  `schemas.py`, `llm_chain.py`, and `engine.py`
+- **Source code**: Renamed stale `cleanrag:` Redis key prefix to `longparser:` in embeddings
+
+### Changed
+
+- Python 3.13 added to CI matrix, badges, and installation docs
+- `SECURITY.md` updated with Redis rate-limiting and CORS threat mitigations
+
+---
+
 ## [0.1.2] — 2026-04-05
 
 ### Changed
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index f44546e..06acdab 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -84,7 +84,7 @@ Use Python 3.10+ type hints. All public API must be fully annotated.
 uv run pytest tests/unit/ -v
 
 # With coverage:
-uv run pytest tests/unit/ --cov=src/long_parser --cov-report=term-missing
+uv run pytest tests/unit/ --cov=src/longparser --cov-report=term-missing
 
 # Full test suite (requires MongoDB + Redis):
 uv run pytest tests/ -v
diff --git a/README.md b/README.md
index 3b4f72a..dce377d 100644
--- a/README.md
+++ b/README.md
@@ -18,7 +18,7 @@
       <img src="https://static.pepy.tech/badge/longparser/month" alt="Monthly Downloads">
     </a>
     <a href="https://www.python.org/">
-      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12-blue.svg" alt="Python">
+      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue.svg" alt="Python">
     </a>
     <a href="LICENSE">
       <img src="https://img.shields.io/badge/License-MIT-brightgreen.svg" alt="MIT License">
@@ -105,9 +105,9 @@ pip install "longparser[cpu]"
 ### Python SDK
 
 ```python
-from longparser import PipelineOrchestrator, ProcessingConfig
+from longparser import DocumentPipeline, ProcessingConfig
 
-pipeline = PipelineOrchestrator()
+pipeline = DocumentPipeline(ProcessingConfig())
 result = pipeline.process_file("document.pdf")
 
 print(f"Pages: {result.document.metadata.total_pages}")
@@ -186,7 +186,7 @@ src/longparser/
 ├── schemas.py           ← core Pydantic models (Document, Block, Chunk, …)
 ├── extractors/          ← Docling, LaTeX OCR backends
 ├── chunkers/            ← HybridChunker
-├── pipeline/            ← PipelineOrchestrator
+├── pipeline/            ← DocumentPipeline
 ├── integrations/        ← LangChain loader & LlamaIndex reader
 ├── utils/               ← shared helpers (RTL detection, …)
 └── server/              ← REST API layer
diff --git a/SECURITY.md b/SECURITY.md
index ba315cf..9932f71 100644
--- a/SECURITY.md
+++ b/SECURITY.md
@@ -35,6 +35,8 @@ Key risks:
 | **MongoDB injection** | Motor driver + typed Pydantic inputs prevent injection |
 | **SSRF via webhook** | No outbound HTTP made based on user input |
 | **Hallucinated citations** | Citation IDs validated against retrieved set before returning to client |
+| **DDoS / Spam via API** | Route-level Rate Limiting strictly isolated per tenant via Redis |
+| **Cross-Origin attacks** | Configurable CORS restrictions and strict Tenant Isolation |
 
 ## Dependency Security
 
diff --git a/docs/changelog.md b/docs/changelog.md
index 9523c0c..2fa3957 100644
--- a/docs/changelog.md
+++ b/docs/changelog.md
@@ -5,6 +5,26 @@ All notable changes to **LongParser** are documented here.
 This project follows [Semantic Versioning](https://semver.org/) and
 [Keep a Changelog](https://keepachangelog.com/en/1.1.0/).
 
+## [0.1.3] — 2026-04-13
+
+### Fixed
+
+- **Source code**: Added `DocumentPipeline` as a public alias for `PipelineOrchestrator` —
+  docs, quickstart, and all examples now use this name consistently
+- **Documentation**: Fixed wrong coverage path `long_parser` → `longparser` in `CONTRIBUTING.md`
+- **Documentation**: Replaced stale `cleanrag-api` reference in Docker deployment docs
+- **Documentation**: Standardized Gemini API key env var to `GOOGLE_API_KEY` across all docs
+- **Source code**: Updated default LLM model fallback from `gpt-4o` to `gpt-5.3` in
+  `schemas.py`, `llm_chain.py`, and `engine.py`
+- **Source code**: Renamed stale `cleanrag:` Redis key prefix to `longparser:` in embeddings
+
+### Changed
+
+- Python 3.13 added to CI matrix, badges, and installation docs
+- `SECURITY.md` updated with Redis rate-limiting and CORS threat mitigations
+
+---
+
 ## [0.1.2] — 2026-04-05
 
 ### Changed
diff --git a/docs/contributing.md b/docs/contributing.md
index e8b7196..72727c9 100644
--- a/docs/contributing.md
+++ b/docs/contributing.md
@@ -84,7 +84,7 @@ Use Python 3.10+ type hints. All public API must be fully annotated.
 uv run pytest tests/unit/ -v
 
 # With coverage:
-uv run pytest tests/unit/ --cov=src/long_parser --cov-report=term-missing
+uv run pytest tests/unit/ --cov=src/longparser --cov-report=term-missing
 
 # Full test suite (requires MongoDB + Redis):
 uv run pytest tests/ -v
diff --git a/docs/deployment/docker.md b/docs/deployment/docker.md
index e462ce5..8ffeac7 100644
--- a/docs/deployment/docker.md
+++ b/docs/deployment/docker.md
@@ -49,5 +49,5 @@ docker compose up --scale longparser=3
 
 ```bash
 curl http://localhost:8000/health
-# {"status": "ok", "service": "cleanrag-api"}
+# {"status": "ok", "service": "longparser-api"}
 ```
diff --git a/docs/deployment/environment.md b/docs/deployment/environment.md
index 3245c88..0d8d28c 100644
--- a/docs/deployment/environment.md
+++ b/docs/deployment/environment.md
@@ -16,7 +16,7 @@ Copy `.env.example` to `.env` and configure for your deployment.
 | `LONGPARSER_LLM_PROVIDER` | `openai` | LLM provider |
 | `LONGPARSER_LLM_MODEL` | _(provider default)_ | Model name |
 | `OPENAI_API_KEY` | — | OpenAI API key |
-| `GEMINI_API_KEY` | — | Google Gemini API key |
+| `GOOGLE_API_KEY` | — | Google Gemini API key |
 | `GROQ_API_KEY` | — | Groq API key |
 | `OPENROUTER_API_KEY` | — | OpenRouter API key |
 
diff --git a/docs/getting-started/configuration.md b/docs/getting-started/configuration.md
index efd370f..859c2c1 100644
--- a/docs/getting-started/configuration.md
+++ b/docs/getting-started/configuration.md
@@ -33,7 +33,7 @@ cp .env.example .env
 |---|---|
 | `LONGPARSER_LLM_PROVIDER` | `openai` / `gemini` / `groq` / `openrouter` |
 | `LONGPARSER_LLM_MODEL` | Model name (uses provider default if unset) |
-| `GEMINI_API_KEY` | For Google Gemini |
+| `GOOGLE_API_KEY` | For Google Gemini |
 | `GROQ_API_KEY` | For Groq |
 
 ## Vector Store
diff --git a/docs/getting-started/installation.md b/docs/getting-started/installation.md
index 908f659..5356c04 100644
--- a/docs/getting-started/installation.md
+++ b/docs/getting-started/installation.md
@@ -2,7 +2,7 @@
 
 ## Requirements
 
-- Python 3.10, 3.11, or 3.12
+- Python 3.10, 3.11, 3.12, or 3.13
 - Tesseract OCR (`brew install tesseract` / `apt install tesseract-ocr`)
 
 ---
@@ -104,5 +104,5 @@ The server starts on `http://localhost:8000`.
 
 ```python
 import longparser
-print(longparser.__version__)  # 0.1.2
+print(longparser.__version__)  # 0.1.3
 ```
diff --git a/docs/getting-started/quickstart.md b/docs/getting-started/quickstart.md
index b779f4b..e501288 100644
--- a/docs/getting-started/quickstart.md
+++ b/docs/getting-started/quickstart.md
@@ -17,11 +17,11 @@ from longparser import DocumentPipeline, ProcessingConfig
 pipeline = DocumentPipeline(ProcessingConfig())
 
 # Parse a PDF
-doc = pipeline.process("research_paper.pdf")
+result = pipeline.process_file("research_paper.pdf")
 
-print(f"Pages: {len(doc.pages)}")
-print(f"Blocks: {len(doc.blocks)}")
-print(f"Chunks: {len(doc.chunks)}")
+print(f"Pages: {result.document.metadata.total_pages}")
+print(f"Chunks: {len(result.chunks)}")
+print(result.chunks[0].text)
 ```
 
 ## 3. Inspect Chunks
diff --git a/docs/guide/chat.md b/docs/guide/chat.md
index a3fb8e6..7ddc175 100644
--- a/docs/guide/chat.md
+++ b/docs/guide/chat.md
@@ -70,6 +70,6 @@ Every answer's `cited_chunk_ids` are validated against the retrieved set. IDs no
 | Provider | Key |
 |---|---|
 | OpenAI | `OPENAI_API_KEY` |
-| Google Gemini | `GEMINI_API_KEY` |
+| Google Gemini | `GOOGLE_API_KEY` |
 | Groq | `GROQ_API_KEY` |
 | OpenRouter | `OPENROUTER_API_KEY` |
diff --git a/docs/guide/parsing.md b/docs/guide/parsing.md
index 171c5b9..93c6386 100644
--- a/docs/guide/parsing.md
+++ b/docs/guide/parsing.md
@@ -18,7 +18,7 @@ LongParser uses **Docling** with Tesseract CLI OCR as its extraction engine —
 from longparser import DocumentPipeline, ProcessingConfig
 
 pipeline = DocumentPipeline(ProcessingConfig())
-doc = pipeline.process("paper.pdf")
+result = pipeline.process_file("paper.pdf")
 ```
 
 ## Formula Modes
@@ -36,15 +36,15 @@ config = ProcessingConfig(formula_mode="smart")
 
 ```python
 # Pages
-for page in doc.pages:
+for page in result.document.pages:
     print(f"Page {page.page_number}: {page.width}x{page.height}")
 
 # Blocks (semantic units)
-for block in doc.blocks:
+for block in result.document.blocks:
     print(f"[{block.type}] p={block.provenance.page_number}: {block.text[:80]}")
 
 # Chunks (RAG-ready)
-for chunk in doc.chunks:
+for chunk in result.chunks:
     print(f"{chunk.chunk_type} | {chunk.token_count} tokens | pages={chunk.page_numbers}")
 ```
 
diff --git a/docs/index.md b/docs/index.md
index 650ed63..4e7ff6e 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -16,7 +16,7 @@
       <img src="https://static.pepy.tech/badge/longparser/month" alt="Monthly Downloads">
     </a>&nbsp;
     <a href="https://www.python.org/">
-      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12-blue.svg" alt="Python">
+      <img src="https://img.shields.io/badge/python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue.svg" alt="Python">
     </a>&nbsp;
     <a href="https://github.com/ENDEVSOLS/LongParser/blob/main/LICENSE">
       <img src="https://img.shields.io/badge/License-MIT-brightgreen.svg" alt="MIT License">
@@ -57,9 +57,10 @@ pip install longparser
 from longparser import DocumentPipeline, ProcessingConfig
 
 pipeline = DocumentPipeline(ProcessingConfig())
-doc = pipeline.process("report.pdf")
+result = pipeline.process_file("report.pdf")
 
-print(f"Extracted {len(doc.blocks)} blocks, {len(doc.chunks)} chunks")
+print(f"Chunks: {len(result.chunks)}")
+print(result.chunks[0].text)
 ```
 
 ---
diff --git a/docs/reference/pipeline.md b/docs/reference/pipeline.md
index 8f3e5a4..7cdfbf9 100644
--- a/docs/reference/pipeline.md
+++ b/docs/reference/pipeline.md
@@ -7,39 +7,49 @@ The `DocumentPipeline` is the main entry point for LongParser's extraction pipel
 ```python
 from longparser import DocumentPipeline, ProcessingConfig
 
-pipeline = DocumentPipeline(config=ProcessingConfig())
-doc = pipeline.process("document.pdf")
+pipeline = DocumentPipeline(ProcessingConfig())
+result = pipeline.process_file("document.pdf")
 ```
 
 ### Constructor
 
 ```python
-DocumentPipeline(config: ProcessingConfig)
+DocumentPipeline(config: ProcessingConfig | None = None)
 ```
 
 | Parameter | Type | Description |
 |---|---|---|
-| `config` | `ProcessingConfig` | Extraction and chunking configuration |
+| `config` | `ProcessingConfig \| None` | Extraction and chunking configuration (uses defaults if `None`) |
 
 ### Methods
 
-#### `process(file_path)`
+#### `process_file(file_path)`
 
 Process a document end-to-end through Extract → Validate → Chunk.
 
 ```python
-doc = pipeline.process("report.pdf")
-# Returns: longparser.schemas.Document
+result = pipeline.process_file("report.pdf")
+# Returns: longparser.pipeline.PipelineResult
 ```
 
-**Returns:** `Document` with `.pages`, `.blocks`, `.chunks` populated.
+**Returns:** `PipelineResult` with `.document` and `.chunks` populated.
+
+#### `process(request)`
+
+Process a document from a `JobRequest` object.
+
+```python
+from longparser import JobRequest
+request = JobRequest(file_path="report.pdf")
+result = pipeline.process(request)
+```
 
 #### `process_batch(file_paths)`
 
 Process multiple documents sequentially.
 
 ```python
-docs = pipeline.process_batch(["a.pdf", "b.docx", "c.pptx"])
+results = pipeline.process_batch(["a.pdf", "b.docx", "c.pptx"])
 ```
 
 ## ProcessingConfig
diff --git a/docs/reference/schemas.md b/docs/reference/schemas.md
index 7e33ac6..e4dda21 100644
--- a/docs/reference/schemas.md
+++ b/docs/reference/schemas.md
@@ -4,7 +4,7 @@ Core data models used throughout LongParser.
 
 ## Document
 
-Top-level container returned by `DocumentPipeline.process()`.
+Top-level container returned by `DocumentPipeline.process_file()`.
 
 ```python
 class Document:
diff --git a/pyproject.toml b/pyproject.toml
index 38330da..afea16d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "longparser"
-version = "0.1.2"
+version = "0.1.3"
 description = "Privacy-first document intelligence engine — converts PDFs, DOCX, PPTX, XLSX, and CSV into AI-ready Markdown + structured JSON for RAG pipelines."
 readme = {file = "README.md", content-type = "text/markdown"}
 requires-python = ">=3.10"
diff --git a/src/longparser/__init__.py b/src/longparser/__init__.py
index 5de272e..7d00c7e 100755
--- a/src/longparser/__init__.py
+++ b/src/longparser/__init__.py
@@ -9,9 +9,9 @@
 
 Quick start::
 
-    from longparser import PipelineOrchestrator, ProcessingConfig
+    from longparser import DocumentPipeline, ProcessingConfig
 
-    pipeline = PipelineOrchestrator()
+    pipeline = DocumentPipeline(ProcessingConfig())
     result = pipeline.process_file("document.pdf")
     print(result.chunks[0].text)
 
@@ -19,13 +19,13 @@
 
     uv run uvicorn longparser.server.app:app --reload --port 8000
 
-See :class:`~longparser.pipeline.PipelineOrchestrator` for the main SDK entry
+See :class:`~longparser.pipeline.DocumentPipeline` for the main SDK entry
 point and :mod:`longparser.server` for the REST API layer.
 """
 
 from __future__ import annotations
 
-__version__ = "0.1.2"
+__version__ = "0.1.3"
 __author__ = "ENDEVSOLS Team"
 __license__ = "MIT"
 
@@ -62,6 +62,9 @@ def __getattr__(name: str):
     if name == "PipelineOrchestrator":
         from .pipeline import PipelineOrchestrator
         return PipelineOrchestrator
+    if name == "DocumentPipeline":
+        from .pipeline import DocumentPipeline
+        return DocumentPipeline
     if name == "PipelineResult":
         from .pipeline import PipelineResult
         return PipelineResult
@@ -99,6 +102,7 @@ def __getattr__(name: str):
     # Lazily imported (require extras)
     "DoclingExtractor",
     "PipelineOrchestrator",
+    "DocumentPipeline",
     "PipelineResult",
     "HybridChunker",
 ]
diff --git a/src/longparser/pipeline/__init__.py b/src/longparser/pipeline/__init__.py
index 6b775d9..710800e 100755
--- a/src/longparser/pipeline/__init__.py
+++ b/src/longparser/pipeline/__init__.py
@@ -2,7 +2,11 @@
 
 from .orchestrator import PipelineOrchestrator, PipelineResult
 
+# Public alias — docs and quickstart use this name
+DocumentPipeline = PipelineOrchestrator
+
 __all__ = [
     "PipelineOrchestrator",
+    "DocumentPipeline",
     "PipelineResult",
 ]
diff --git a/src/longparser/server/chat/engine.py b/src/longparser/server/chat/engine.py
index b55b7cf..d50a7af 100755
--- a/src/longparser/server/chat/engine.py
+++ b/src/longparser/server/chat/engine.py
@@ -76,7 +76,7 @@
 # Token Counting (model-aware) — kept as custom logic
 # ---------------------------------------------------------------------------
 
-def count_tokens(text: str, model: str = "gpt-4o") -> int:
+def count_tokens(text: str, model: str = "gpt-5.3") -> int:
     """Count tokens — exact for OpenAI models, conservative approx for others."""
     try:
         import tiktoken
@@ -96,7 +96,7 @@ def budget_trim(
     recent_turns: list[dict],
     rolling_summary: str,
     long_term_facts: list[dict],
-    model: str = "gpt-4o",
+    model: str = "gpt-5.3",
     max_prompt_tokens: int = 6000,
 ) -> dict:
     """Priority-ordered truncation of prompt variables to fit token budget.
diff --git a/src/longparser/server/chat/llm_chain.py b/src/longparser/server/chat/llm_chain.py
index f2cb8e7..b32bb2f 100755
--- a/src/longparser/server/chat/llm_chain.py
+++ b/src/longparser/server/chat/llm_chain.py
@@ -115,7 +115,7 @@ def get_chat_model(
     """
     config = config or ChatConfig()
     provider = provider or config.llm_provider
-    model = model or config.llm_model or DEFAULT_MODELS.get(provider, "gpt-4o")
+    model = model or config.llm_model or DEFAULT_MODELS.get(provider, "gpt-5.3")
     max_tokens = max_tokens or config.max_output_tokens
 
     creator = _CREATORS.get(provider)
diff --git a/src/longparser/server/chat/schemas.py b/src/longparser/server/chat/schemas.py
index 0405a84..0479cf7 100755
--- a/src/longparser/server/chat/schemas.py
+++ b/src/longparser/server/chat/schemas.py
@@ -33,7 +33,7 @@ class ChatConfig(BaseModel):
         default_factory=lambda: os.getenv("LONGPARSER_LLM_PROVIDER", "openai")
     )
     llm_model: str = Field(
-        default_factory=lambda: os.getenv("LONGPARSER_LLM_MODEL", "gpt-4o")
+        default_factory=lambda: os.getenv("LONGPARSER_LLM_MODEL", "gpt-5.3")
     )
     max_input_tokens: int = Field(
         default_factory=lambda: int(os.getenv("LONGPARSER_CHAT_MAX_INPUT_TOKENS", "1000"))
diff --git a/src/longparser/server/embeddings.py b/src/longparser/server/embeddings.py
index e59f513..e0b2bbc 100755
--- a/src/longparser/server/embeddings.py
+++ b/src/longparser/server/embeddings.py
@@ -108,7 +108,7 @@ def dim(self) -> int:
                 return self._dim
 
             fp = self.get_fingerprint()
-            cache_key = f"cleanrag:embed_dim:{fp}"
+            cache_key = f"longparser:embed_dim:{fp}"
 
             # 1) Try Redis cross-process cache if available
             try:

From ce34496489167c9fdeb0251482532d17c8d7eec9 Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Wed, 22 Apr 2026 17:44:32 +0500
Subject: [PATCH 5/7] Release v0.1.4: Add fast PDF extractor, auto-language
 detection, AGPL safety checks, and fix LangChain/LlamaIndex adapters

---
 .github/workflows/license-check.yml           |  50 ++
 FEATURE_ROADMAP.md                            | 150 ++++++
 LICENSE-THIRD-PARTY.md                        |  50 ++
 docs/getting-started/installation.md          |   2 +-
 pyproject.toml                                |  17 +-
 src/longparser/__init__.py                    |   7 +-
 .../extractors/pymupdf_extractor.py           | 493 ++++++++++++++++++
 src/longparser/integrations/__init__.py       |   6 +-
 src/longparser/integrations/langchain.py      |   5 +-
 src/longparser/integrations/llamaindex.py     |   5 +-
 src/longparser/pipeline/orchestrator.py       | 207 +++++++-
 src/longparser/schemas.py                     |  22 +-
 src/longparser/utils/__init__.py              |  11 +-
 src/longparser/utils/lang_detect.py           | 193 +++++++
 src/longparser/utils/ocr_router.py            | 148 ++++++
 tests/benchmarks/benchmark_pipeline.py        |  98 ++++
 tests/unit/test_backward_compat.py            | 142 +++++
 tests/unit/test_license_safety.py             |  82 +++
 18 files changed, 1652 insertions(+), 36 deletions(-)
 create mode 100644 .github/workflows/license-check.yml
 create mode 100644 FEATURE_ROADMAP.md
 create mode 100644 LICENSE-THIRD-PARTY.md
 create mode 100644 src/longparser/extractors/pymupdf_extractor.py
 create mode 100644 src/longparser/utils/lang_detect.py
 create mode 100644 src/longparser/utils/ocr_router.py
 create mode 100644 tests/benchmarks/benchmark_pipeline.py
 create mode 100644 tests/unit/test_backward_compat.py
 create mode 100644 tests/unit/test_license_safety.py

diff --git a/.github/workflows/license-check.yml b/.github/workflows/license-check.yml
new file mode 100644
index 0000000..39b5031
--- /dev/null
+++ b/.github/workflows/license-check.yml
@@ -0,0 +1,50 @@
+name: License Safety Check
+
+on: [push, pull_request]
+
+jobs:
+  license-check:
+    name: Ensure no GPL/AGPL imports in core
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Check core files for GPL/AGPL imports
+        run: |
+          echo "=== License Safety Check ==="
+          echo "Verifying no GPL/AGPL package is imported in core code..."
+          echo ""
+
+          FAIL=0
+
+          # List of GPL/AGPL package import patterns to block
+          BLOCKED_PATTERNS="pymupdf4llm|pymupdf|import marker\.|from marker\.|import surya|from surya"
+
+          # Files that ARE allowed to import these (isolated backends)
+          ALLOWED_FILES=(
+            "src/longparser/extractors/pymupdf_extractor.py"
+            "src/longparser/extractors/marker_extractor.py"
+          )
+
+          # Build grep exclude args
+          EXCLUDE_ARGS=""
+          for f in "${ALLOWED_FILES[@]}"; do
+            EXCLUDE_ARGS="$EXCLUDE_ARGS --exclude=$f"
+          done
+
+          # Search all Python files in src/longparser EXCEPT allowed files
+          MATCHES=$(grep -rnE "$BLOCKED_PATTERNS" src/longparser/ \
+            --include='*.py' $EXCLUDE_ARGS || true)
+
+          if [ -n "$MATCHES" ]; then
+            echo "❌ FAIL: GPL/AGPL imports found in core code!"
+            echo ""
+            echo "$MATCHES"
+            echo ""
+            echo "These packages must ONLY be imported in their isolated extractor files."
+            FAIL=1
+          else
+            echo "✅ PASS: No GPL/AGPL imports in core code."
+          fi
+
+          exit $FAIL
diff --git a/FEATURE_ROADMAP.md b/FEATURE_ROADMAP.md
new file mode 100644
index 0000000..2ea7b1a
--- /dev/null
+++ b/FEATURE_ROADMAP.md
@@ -0,0 +1,150 @@
+# LongParser — Product & Feature Roadmap
+
+> This roadmap reflects the current development direction based on community trends,
+> competitor analysis, and the RAG ecosystem in 2025–2026. Items are ordered by
+> priority within each phase. All dates are targets, not guarantees.
+
+---
+
+## Current State — v0.1.x ✅
+
+- 5-stage extraction pipeline (Extract → Validate → HITL → Chunk → Embed → Index)
+- Multi-format support: PDF, DOCX, PPTX, XLSX, CSV via Docling
+- `HybridChunker` — 6-strategy token-aware, hierarchy-aware, table-aware chunking
+- Human-in-the-Loop (HITL) review via LangGraph `interrupt()`
+- 3-layer memory chat engine (short-term + rolling summary + long-term facts)
+- Multi-provider LLM: OpenAI, Gemini, Groq, OpenRouter
+- Multi-backend vector stores: Chroma, FAISS, Qdrant
+- FastAPI REST server + ARQ/Redis job queue + Motor/MongoDB
+- LangChain `BaseRetriever` + LlamaIndex `BaseReader` adapters
+- CPU / GPU install separation via extras
+
+---
+
+## Phase 1 — Accuracy & Quality (v0.2.x) — Q2 2026
+
+### Parser Enhancements
+
+- [ ] **Marker backend** — add `marker-pdf` as an optional extraction backend for higher-fidelity Markdown output on complex academic PDFs
+- [ ] **PyMuPDF4LLM backend** — lightweight, fast alternative for speed-critical pipelines (10× faster than Docling for simple PDFs)
+- [ ] **Scanned PDF fast path** — route documents to Tesseract vs pix2tex vs Surya automatically based on page complexity score
+- [ ] **Multi-column layout detection** — prevent reading-order errors in newspaper/journal-style layouts
+- [ ] **Image extraction** — export embedded figures with captions into separate chunks with `type: figure`
+- [ ] **Document language auto-detection** — select OCR model automatically based on detected script
+
+### Chunking Improvements
+
+- [ ] **Semantic chunking** — optional embedding-based boundary detection (split at semantic shifts, not just token counts)
+- [ ] **Sliding window overlap** — configurable overlap strategy per chunk type (more overlap for tables, less for headings)
+- [ ] **Cross-reference resolution** — link `(see Figure 3)` and `(Table 2)` references to their target blocks
+- [ ] **Summary chunks** — auto-generate a 1–2 sentence summary chunk per section for hierarchical retrieval
+
+### Quality & Validation
+
+- [ ] **Chunk quality scorer** — assign a confidence score per chunk based on OCR confidence, completeness, and structural integrity
+- [ ] **PII detection** — flag and optionally redact personal information (names, emails, phone numbers) before embedding
+- [ ] **Duplicate block detection** — suppress repeated headers/footers that appear on every page
+
+---
+
+## Phase 2 — Agentic & Multimodal (v0.3.x) — Q3 2026
+
+### Agentic RAG
+
+- [ ] **Agentic retrieval loop** — implement query rewriting + iterative retrieval + self-reflection before answer generation
+- [ ] **Multi-hop question answering** — chain retrieval steps for questions that span multiple sections or documents
+- [ ] **Tool-calling integration** — expose document pipeline as a LangChain/LangGraph tool callable by autonomous agents
+- [ ] **Hypothetical Document Embeddings (HyDE)** — generate hypothetical answers to queries for improved retrieval recall
+
+### Multimodal
+
+- [ ] **Vision-Language Model (VLM) integration** — use GPT-4o / Gemini Vision to describe figures, charts, and diagrams as text chunks
+- [ ] **Chart data extraction** — parse bar/line/pie charts into structured data tables
+- [ ] **Slide layout understanding** — treat PPTX slides as visual units with spatial layout context, not just text extraction
+
+### Reranking & Retrieval
+
+- [ ] **Cross-encoder reranker** — add optional `sentence-transformers` cross-encoder reranking step after initial retrieval
+- [ ] **Hybrid search** — combine dense vector search with BM25 sparse retrieval (reciprocal rank fusion)
+- [ ] **Maximum Marginal Relevance (MMR)** — reduce redundancy in retrieved chunks
+- [ ] **Metadata filtering** — filter chunks by `page_number`, `section`, `doc_type`, `date` at query time
+
+---
+
+## Phase 3 — Enterprise & Observability (v0.4.x) — Q4 2026
+
+### Knowledge Graph
+
+- [ ] **Entity extraction** — extract named entities (people, organizations, dates, locations) from chunks
+- [ ] **Relationship mapping** — build entity relationship graphs from document content
+- [ ] **Graph-based retrieval** — traverse the entity graph for multi-hop retrieval (GraphRAG pattern)
+- [ ] **Neo4j / NetworkX integration** — persist the knowledge graph to a graph database
+
+### Evaluation Framework
+
+- [ ] **Built-in RAG evaluator** — measure retrieval recall@k, answer faithfulness, and context adherence
+- [ ] **Chunk attribution** — trace every answer sentence back to the source chunk and page
+- [ ] **RAGAS integration** — plug into the RAGAS evaluation framework
+- [ ] **Benchmark suite** — reproducible benchmarks against Unstructured, LlamaParse, Docling standalone
+
+### Observability & Compliance
+
+- [ ] **LangSmith integration** — trace every pipeline run end-to-end
+- [ ] **OpenTelemetry support** — emit spans/traces to any OTel-compatible backend
+- [ ] **Audit log** — immutable log of every HITL decision (approve/reject/edit) with timestamps and user IDs
+- [ ] **GDPR compliance mode** — PII redaction + right-to-erasure support (delete all chunks for a document)
+- [ ] **Role-based access control (RBAC)** — multi-tenant document access in the REST API
+
+---
+
+## Phase 4 — Scale & Ecosystem (v0.5.x+) — 2027
+
+### Performance & Scale
+
+- [ ] **Async parallel extraction** — process multiple documents concurrently in the background worker
+- [ ] **Streaming extraction** — yield blocks as they are extracted (no need to wait for full document)
+- [ ] **Incremental indexing** — update only changed pages/sections on re-upload
+- [ ] **S3 / GCS / Azure Blob** — native cloud storage input (not just local files)
+- [ ] **Kubernetes Helm chart** — one-command production deployment
+
+### New Integrations
+
+- [ ] **Weaviate** vector store adapter
+- [ ] **Pinecone** vector store adapter
+- [ ] **Milvus** vector store adapter
+- [ ] **DSPy** integration — use DSPy to auto-optimize retrieval prompts
+- [ ] **Haystack `DocumentConverter`** component
+- [ ] **Flowise / Langflow** node — drag-and-drop visual pipeline builder support
+
+### Developer Experience
+
+- [ ] **LongParser CLI** — `longparser parse document.pdf --output chunks.json`
+- [ ] **Web UI (HITL Dashboard)** — visual interface for reviewing and editing blocks before embedding
+- [ ] **VS Code extension** — preview parsed chunks directly from the editor
+- [ ] **Webhook support** — notify external systems when a job completes or requires HITL review
+
+---
+
+## Competitive Positioning
+
+| Capability | LongParser | Unstructured | LlamaParse | Docling |
+|---|---|---|---|---|
+| Privacy-first (fully local) | ✅ | ⚠️ (cloud option) | ❌ (API-only) | ✅ |
+| HITL review workflow | ✅ | ❌ | ❌ | ❌ |
+| Bundled REST API server | ✅ | ✅ (paid) | ✅ (cloud) | ❌ |
+| Table-aware chunking | ✅ | ⚠️ | ✅ | ✅ |
+| LaTeX / equation OCR | ✅ | ❌ | ⚠️ | ⚠️ |
+| LangChain + LlamaIndex | ✅ | ✅ | ✅ | ⚠️ |
+| Open source (MIT) | ✅ | ⚠️ (core only) | ❌ | ✅ |
+| Knowledge graph (planned) | 🔜 | ❌ | ❌ | ❌ |
+| Agentic retrieval (planned) | 🔜 | ❌ | ⚠️ | ❌ |
+
+---
+
+## Guiding Principles
+
+1. **Privacy by default** — all processing runs locally; no data leaves user infrastructure
+2. **Human oversight** — HITL is a first-class citizen, not an afterthought
+3. **Composable** — every stage is independently usable; no forced lock-in to the full stack
+4. **Production-grade** — async, typed, tested, documented from day one
+5. **Ecosystem-native** — LangChain, LlamaIndex, and HuggingFace are first-class integration targets
diff --git a/LICENSE-THIRD-PARTY.md b/LICENSE-THIRD-PARTY.md
new file mode 100644
index 0000000..257709f
--- /dev/null
+++ b/LICENSE-THIRD-PARTY.md
@@ -0,0 +1,50 @@
+# Third-Party Licenses
+
+LongParser core is licensed under the **MIT License**.
+
+Some **optional** backends and integrations use different licenses.
+These packages are **never loaded by default** — they are only imported
+when you explicitly install them and select them in your configuration.
+
+## Optional Backend Licenses
+
+| Package | License | Install Command | When Loaded |
+|---------|---------|-----------------|-------------|
+| `pymupdf4llm` | AGPL-3.0 or Artifex Commercial | `pip install "longparser[pymupdf]"` | Only when you set `backend="pymupdf"` |
+| `marker-pdf` | GPL-3.0-or-later | `pip install "longparser[marker]"` | Only when you set `backend="marker"` *(future)* |
+| `surya-ocr` | GPL-3.0-or-later | `pip install "longparser[surya]"` | Only when explicitly imported *(future)* |
+
+## Core Dependency Licenses (always installed)
+
+| Package | License | Purpose |
+|---------|---------|---------|
+| `pydantic` | MIT | Schema validation |
+| `docling` | MIT | Default PDF extraction engine |
+| `docling-core` | MIT | Docling data models |
+| `fast-langdetect` | Apache-2.0 | Document language detection |
+
+## What This Means for You
+
+- **If you only use `pip install longparser`** — everything is MIT or Apache-2.0.
+  You can use LongParser in any project (commercial, proprietary, open source).
+
+- **If you install `longparser[pymupdf]`** — the `pymupdf4llm` library is
+  AGPL-3.0 licensed. You must comply with AGPL terms for the PyMuPDF component,
+  OR purchase a commercial license from [Artifex](https://artifex.com).
+  LongParser core code remains MIT.
+
+- **If you install `longparser[marker]`** *(future)* — the `marker-pdf` library
+  is GPL-3.0 licensed. You must comply with GPL terms for the Marker component.
+  LongParser core code remains MIT.
+
+## License Isolation Guarantee
+
+LongParser uses **lazy imports** to ensure GPL/AGPL packages are never loaded
+unless explicitly requested. The following guarantees hold:
+
+1. `import longparser` does NOT import any GPL/AGPL package
+2. `from longparser import DocumentPipeline` does NOT import any GPL/AGPL package
+3. `DocumentPipeline().process_file("doc.pdf")` does NOT import any GPL/AGPL
+   package (uses Docling, which is MIT)
+4. GPL/AGPL code is only loaded when you explicitly set `backend="pymupdf"` or
+   `backend="marker"` in `ProcessingConfig`
diff --git a/docs/getting-started/installation.md b/docs/getting-started/installation.md
index 5356c04..4ee1d42 100644
--- a/docs/getting-started/installation.md
+++ b/docs/getting-started/installation.md
@@ -104,5 +104,5 @@ The server starts on `http://localhost:8000`.
 
 ```python
 import longparser
-print(longparser.__version__)  # 0.1.3
+print(longparser.__version__)  # 0.1.4
 ```
diff --git a/pyproject.toml b/pyproject.toml
index afea16d..dbb7cbe 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "longparser"
-version = "0.1.3"
+version = "0.1.4"
 description = "Privacy-first document intelligence engine — converts PDFs, DOCX, PPTX, XLSX, and CSV into AI-ready Markdown + structured JSON for RAG pipelines."
 readme = {file = "README.md", content-type = "text/markdown"}
 requires-python = ">=3.10"
@@ -36,6 +36,7 @@ dependencies = [
     "docling>=2.14",
     "docling-core>=2.13",
     "langgraph-checkpoint-mongodb>=0.3.1",
+    "fast-langdetect>=0.3,<1.0",  # Apache-2.0 — document language detection
 ]
 
 [project.optional-dependencies]
@@ -51,6 +52,20 @@ langchain = [
 llamaindex = [
     "llama-index-core>=0.10",
 ]
+# ----------- v0.1.4: Optional extraction backends -----------
+# ⚠️ pymupdf4llm is AGPL-3.0 licensed. See LICENSE-THIRD-PARTY.md.
+# Only loaded when user sets backend="pymupdf".
+pymupdf = [
+    "pymupdf4llm>=1.27",
+]
+# ⚠️ marker-pdf is GPL-3.0. GPU recommended. Future release.
+# marker = [
+#     "marker-pdf",
+# ]
+# ⚠️ surya-ocr is GPL-3.0. GPU recommended. Future release.
+# surya = [
+#     "surya-ocr>=0.17",
+# ]
 # FastAPI REST server + MongoDB + job queue + LangChain chat engine
 server = [
     "fastapi>=0.115",
diff --git a/src/longparser/__init__.py b/src/longparser/__init__.py
index 7d00c7e..b1b9794 100755
--- a/src/longparser/__init__.py
+++ b/src/longparser/__init__.py
@@ -25,7 +25,7 @@
 
 from __future__ import annotations
 
-__version__ = "0.1.3"
+__version__ = "0.1.4"
 __author__ = "ENDEVSOLS Team"
 __license__ = "MIT"
 
@@ -59,6 +59,10 @@ def __getattr__(name: str):
     if name == "DoclingExtractor":
         from .extractors import DoclingExtractor
         return DoclingExtractor
+    if name == "PyMuPDFExtractor":
+        # AGPL-isolated — only loaded when explicitly requested
+        from .extractors.pymupdf_extractor import PyMuPDFExtractor
+        return PyMuPDFExtractor
     if name == "PipelineOrchestrator":
         from .pipeline import PipelineOrchestrator
         return PipelineOrchestrator
@@ -101,6 +105,7 @@ def __getattr__(name: str):
     "JobResult",
     # Lazily imported (require extras)
     "DoclingExtractor",
+    "PyMuPDFExtractor",
     "PipelineOrchestrator",
     "DocumentPipeline",
     "PipelineResult",
diff --git a/src/longparser/extractors/pymupdf_extractor.py b/src/longparser/extractors/pymupdf_extractor.py
new file mode 100644
index 0000000..aecf375
--- /dev/null
+++ b/src/longparser/extractors/pymupdf_extractor.py
@@ -0,0 +1,493 @@
+"""PyMuPDF4LLM-based extractor for fast, CPU-native PDF extraction.
+
+⚠️  LICENSE NOTICE — AGPL-3.0
+    pymupdf4llm is dual-licensed under AGPL-3.0 or Artifex Commercial License.
+    By using this backend, you agree to the terms of the AGPL-3.0 license
+    unless you have purchased a commercial license from Artifex Software, Inc.
+
+    This module is NOT imported by default — users must explicitly opt in
+    via ``pip install longparser[pymupdf]`` and ``backend='pymupdf'``.
+
+⚠️  ISOLATION RULES (do NOT violate)
+    1. This file must NEVER be imported by ``extractors/__init__.py``
+    2. This file must NEVER be imported at module level by ``orchestrator.py``
+    3. This file must ONLY be imported behind ``if backend == "pymupdf":``
+    4. ``import longparser`` must NEVER trigger loading this file
+
+Best for:
+    - Native PDFs with embedded text (not scanned)
+    - Speed-critical pipelines (10-50× faster than Docling)
+    - CPU-only environments (no GPU, no ML models)
+
+NOT suitable for:
+    - Scanned PDFs (no OCR capability)
+    - Complex tables with merged cells
+    - Documents needing deep heading hierarchy detection
+
+Usage::
+
+    from longparser import ProcessingConfig, DocumentPipeline
+
+    pipeline = DocumentPipeline(
+        config=ProcessingConfig(backend="pymupdf")
+    )
+    result = pipeline.process_file("report.pdf")
+"""
+
+from __future__ import annotations
+
+import hashlib
+import logging
+import uuid
+from pathlib import Path
+from typing import Optional, List, Tuple
+
+from ..schemas import (
+    Document, Page, Block, Table, TableCell,
+    BlockType, ExtractorType, ProcessingConfig,
+    BoundingBox, Provenance, Confidence, BlockFlags,
+    DocumentMetadata, PageProfile, ExtractionMetadata,
+)
+from .base import BaseExtractor
+
+logger = logging.getLogger(__name__)
+
+
+def _require_pymupdf():
+    """Check that pymupdf4llm is installed; raise clear error if not.
+
+    Returns the ``pymupdf4llm`` module on success.
+    """
+    try:
+        import pymupdf4llm
+        return pymupdf4llm
+    except ImportError:
+        raise ImportError(
+            "\n"
+            "╔══════════════════════════════════════════════════════════╗\n"
+            "║  pymupdf4llm is not installed.                         ║\n"
+            "║                                                        ║\n"
+            "║  Install:  pip install 'longparser[pymupdf]'           ║\n"
+            "║                                                        ║\n"
+            "║  ⚠️  pymupdf4llm is licensed under AGPL-3.0.           ║\n"
+            "║  By installing it, you agree to AGPL terms for that    ║\n"
+            "║  component. LongParser core remains MIT-licensed.      ║\n"
+            "║                                                        ║\n"
+            "║  For commercial use without AGPL obligations, purchase ║\n"
+            "║  a license from https://artifex.com                    ║\n"
+            "╚══════════════════════════════════════════════════════════╝\n"
+        )
+
+
+def _require_pymupdf_fitz():
+    """Import the fitz (PyMuPDF) module for page-level operations."""
+    try:
+        import pymupdf as fitz
+        return fitz
+    except ImportError:
+        try:
+            import fitz
+            return fitz
+        except ImportError:
+            raise ImportError(
+                "PyMuPDF (fitz) is required for the pymupdf backend. "
+                "Install with: pip install 'longparser[pymupdf]'"
+            )
+
+
+class PyMuPDFExtractor(BaseExtractor):
+    """Fast, CPU-native PDF extractor using PyMuPDF4LLM.
+
+    Converts PDFs to structured Markdown and maps the output to
+    LongParser's ``Document`` / ``Block`` model. Uses no ML models,
+    no GPU — pure C-based PDF parsing via MuPDF.
+
+    Attributes
+    ----------
+    extractor_type : ExtractorType
+        Always ``ExtractorType.NATIVE_PDF``.
+    version : str
+        Extractor version string.
+    """
+
+    extractor_type = ExtractorType.NATIVE_PDF
+    version = "1.0.0"
+
+    def __init__(self):
+        """Initialize and verify pymupdf4llm is available."""
+        _require_pymupdf()
+        self._images: list = []
+        logger.info(
+            "PyMuPDF4LLM backend initialized (CPU-native, no OCR, no GPU)"
+        )
+
+    def extract(
+        self,
+        file_path: Path,
+        config: ProcessingConfig,
+        page_numbers: Optional[List[int]] = None,
+    ) -> Tuple[Document, ExtractionMetadata]:
+        """Extract a PDF using PyMuPDF4LLM.
+
+        Parameters
+        ----------
+        file_path:
+            Path to the PDF file.
+        config:
+            Processing configuration.
+        page_numbers:
+            Optional list of 0-indexed page numbers to extract.
+
+        Returns
+        -------
+        tuple[Document, ExtractionMetadata]
+            Extracted document and metadata.
+        """
+        import pymupdf4llm
+
+        file_path = Path(file_path)
+        logger.info("Extracting with PyMuPDF4LLM: %s", file_path.name)
+
+        # Validate file type
+        if file_path.suffix.lower() != ".pdf":
+            raise ValueError(
+                f"PyMuPDF4LLM backend only supports PDF files, got: {file_path.suffix}"
+            )
+
+        # File hash
+        file_hash = hashlib.sha256(file_path.read_bytes()).hexdigest()[:16]
+
+        # Extract with pymupdf4llm
+        kwargs = {"show_progress": False}
+        if page_numbers is not None:
+            kwargs["pages"] = page_numbers
+
+        md_text = pymupdf4llm.to_markdown(str(file_path), **kwargs)
+
+        # Get page-level info using PyMuPDF directly
+        fitz = _require_pymupdf_fitz()
+        pdf_doc = fitz.open(str(file_path))
+        total_pages = len(pdf_doc)
+
+        # Extract images if config.export_images
+        self._images = []
+        if config.export_images:
+            self._extract_images(pdf_doc, config)
+
+        # Build Document from Markdown
+        document = self._markdown_to_document(
+            md_text=md_text,
+            pdf_doc=pdf_doc,
+            file_path=file_path,
+            file_hash=file_hash,
+            total_pages=total_pages,
+            config=config,
+        )
+
+        pdf_doc.close()
+
+        meta = ExtractionMetadata(
+            strategy_used="pymupdf4llm",
+            ocr_backend_used="none (native text)",
+        )
+
+        logger.info(
+            "PyMuPDF4LLM extraction complete: %d pages, %d blocks",
+            total_pages, len(document.all_blocks),
+        )
+
+        return document, meta
+
+    def _markdown_to_document(
+        self,
+        md_text: str,
+        pdf_doc,
+        file_path: Path,
+        file_hash: str,
+        total_pages: int,
+        config: ProcessingConfig,
+    ) -> Document:
+        """Convert Markdown text to a LongParser Document model."""
+        metadata = DocumentMetadata(
+            source_file=str(file_path),
+            file_hash=file_hash,
+            total_pages=total_pages,
+        )
+
+        pages: list[Page] = []
+
+        # Split markdown by page breaks (pymupdf4llm uses "---" or form feeds)
+        page_chunks = self._split_by_pages(md_text, total_pages)
+
+        for page_idx, page_md in enumerate(page_chunks):
+            page_no = page_idx + 1
+
+            # Get page dimensions from PyMuPDF
+            if page_idx < len(pdf_doc):
+                rect = pdf_doc[page_idx].rect
+                width, height = rect.width, rect.height
+            else:
+                width, height = 612.0, 792.0  # Letter default
+
+            # Parse markdown blocks
+            blocks = self._parse_markdown_blocks(page_md, page_no, file_path)
+
+            # Build page profile
+            profile = PageProfile(
+                page_number=page_no,
+                layout_confidence=0.9,  # PyMuPDF is reliable for native PDFs
+            )
+
+            pages.append(Page(
+                page_number=page_no,
+                width=width,
+                height=height,
+                blocks=blocks,
+                profile=profile,
+            ))
+
+        return Document(metadata=metadata, pages=pages)
+
+    def _split_by_pages(self, md_text: str, total_pages: int) -> list[str]:
+        """Split markdown text into per-page chunks."""
+        import re
+
+        # pymupdf4llm inserts page separators
+        # Common patterns: "-----" (5+ dashes), or form feed characters
+        parts = re.split(r'\n-{3,}\n|\f', md_text)
+
+        # If splitting didn't work, put everything on page 1
+        if len(parts) <= 1:
+            return [md_text]
+
+        # Pad to total_pages if needed
+        while len(parts) < total_pages:
+            parts.append("")
+
+        return parts[:total_pages]
+
+    def _parse_markdown_blocks(
+        self,
+        page_md: str,
+        page_no: int,
+        file_path: Path,
+    ) -> list[Block]:
+        """Parse markdown text into Block objects."""
+        blocks: list[Block] = []
+        lines = page_md.strip().split("\n")
+        order_idx = 0
+
+        i = 0
+        while i < len(lines):
+            line = lines[i]
+            stripped = line.strip()
+
+            if not stripped:
+                i += 1
+                continue
+
+            # Detect block type
+            if stripped.startswith("#"):
+                # Heading
+                level = len(stripped) - len(stripped.lstrip("#"))
+                text = stripped.lstrip("#").strip()
+                block = self._make_block(
+                    BlockType.HEADING, text, order_idx, page_no,
+                    file_path, heading_level=min(level, 6),
+                )
+                blocks.append(block)
+
+            elif stripped.startswith("|") and "|" in stripped[1:]:
+                # Table — collect all table lines
+                table_lines = [stripped]
+                i += 1
+                while i < len(lines) and lines[i].strip().startswith("|"):
+                    table_lines.append(lines[i].strip())
+                    i += 1
+                table_md = "\n".join(table_lines)
+                table_obj = self._parse_table(table_lines)
+                block = self._make_block(
+                    BlockType.TABLE, table_md, order_idx, page_no,
+                    file_path, table=table_obj,
+                )
+                blocks.append(block)
+                order_idx += 1
+                continue  # Already incremented i
+
+            elif stripped.startswith(("- ", "* ", "+ ")) or (
+                len(stripped) > 2 and stripped[0].isdigit() and stripped[1] in ".)"
+            ):
+                # List item
+                text = stripped.lstrip("-*+ ").lstrip("0123456789.)").strip()
+                block = self._make_block(
+                    BlockType.LIST_ITEM, text, order_idx, page_no, file_path,
+                )
+                blocks.append(block)
+
+            elif stripped.startswith("```"):
+                # Code block
+                code_lines = []
+                i += 1
+                while i < len(lines) and not lines[i].strip().startswith("```"):
+                    code_lines.append(lines[i])
+                    i += 1
+                code_text = "\n".join(code_lines)
+                block = self._make_block(
+                    BlockType.CODE, code_text, order_idx, page_no, file_path,
+                )
+                blocks.append(block)
+                i += 1  # Skip closing ```
+                order_idx += 1
+                continue
+
+            elif stripped.startswith("$$") or stripped.startswith("\\["):
+                # Equation block
+                eq_lines = [stripped]
+                if not (stripped.endswith("$$") and len(stripped) > 2):
+                    i += 1
+                    while i < len(lines):
+                        eq_line = lines[i].strip()
+                        eq_lines.append(eq_line)
+                        if eq_line.endswith("$$") or eq_line.endswith("\\]"):
+                            break
+                        i += 1
+                eq_text = "\n".join(eq_lines)
+                block = self._make_block(
+                    BlockType.EQUATION, eq_text, order_idx, page_no, file_path,
+                )
+                blocks.append(block)
+
+            else:
+                # Regular paragraph
+                block = self._make_block(
+                    BlockType.PARAGRAPH, stripped, order_idx, page_no, file_path,
+                )
+                blocks.append(block)
+
+            order_idx += 1
+            i += 1
+
+        return blocks
+
+    def _make_block(
+        self,
+        block_type: BlockType,
+        text: str,
+        order_index: int,
+        page_no: int,
+        file_path: Path,
+        heading_level: Optional[int] = None,
+        table: Optional[Table] = None,
+    ) -> Block:
+        """Create a Block with standard provenance."""
+        return Block(
+            type=block_type,
+            text=text,
+            order_index=order_index,
+            heading_level=heading_level,
+            provenance=Provenance(
+                source_file=str(file_path),
+                page_number=page_no,
+                bbox=BoundingBox(x0=0, y0=0, x1=0, y1=0),
+                extractor=self.extractor_type,
+                extractor_version=self.version,
+            ),
+            confidence=Confidence(overall=0.9),
+            table=table,
+        )
+
+    def _parse_table(self, table_lines: list[str]) -> Table:
+        """Parse a Markdown table into a Table object."""
+        # Filter out separator lines (|---|---|)
+        data_lines = [
+            line for line in table_lines
+            if line.strip() and not all(c in "|-: " for c in line.strip())
+        ]
+
+        if not data_lines:
+            return Table(n_rows=0, n_cols=0)
+
+        cells: list[TableCell] = []
+        n_cols = 0
+
+        for row_idx, line in enumerate(data_lines):
+            parts = [p.strip() for p in line.strip("|").split("|")]
+            n_cols = max(n_cols, len(parts))
+            for col_idx, cell_text in enumerate(parts):
+                cells.append(TableCell(
+                    r0=row_idx, c0=col_idx, text=cell_text
+                ))
+
+        return Table(
+            n_rows=len(data_lines),
+            n_cols=n_cols,
+            cells=cells,
+            table_confidence=0.85,
+        )
+
+    def _extract_images(self, pdf_doc, config: ProcessingConfig):
+        """Extract images from PDF pages."""
+        for page_idx in range(len(pdf_doc)):
+            page = pdf_doc[page_idx]
+            image_list = page.get_images(full=True)
+            for img_idx, img in enumerate(image_list):
+                try:
+                    xref = img[0]
+                    base_image = pdf_doc.extract_image(xref)
+                    if base_image:
+                        self._images.append({
+                            "page": page_idx + 1,
+                            "index": img_idx,
+                            "data": base_image["image"],
+                            "ext": base_image.get("ext", "png"),
+                        })
+                except Exception as e:
+                    logger.debug("Failed to extract image on page %d: %s", page_idx + 1, e)
+
+    def save_images(self, output_dir: Path) -> list[Path]:
+        """Save extracted images to disk.
+
+        Parameters
+        ----------
+        output_dir:
+            Directory to save images to.
+
+        Returns
+        -------
+        list[Path]
+            Paths to saved image files.
+        """
+        output_dir = Path(output_dir)
+        output_dir.mkdir(parents=True, exist_ok=True)
+        saved = []
+
+        for img_info in self._images:
+            fname = f"page_{img_info['page']:03d}_img_{img_info['index']:02d}.{img_info['ext']}"
+            fpath = output_dir / fname
+            with open(fpath, "wb") as f:
+                f.write(img_info["data"])
+            saved.append(fpath)
+
+        logger.info("Saved %d images to %s", len(saved), output_dir)
+        return saved
+
+    def to_markdown(self, document: Document) -> str:
+        """Convert Document back to Markdown."""
+        parts = []
+        for page in document.pages:
+            for block in page.blocks:
+                if block.type == BlockType.HEADING:
+                    level = block.heading_level or 1
+                    parts.append(f"{'#' * level} {block.text}")
+                elif block.type == BlockType.TABLE:
+                    parts.append(block.text)
+                elif block.type == BlockType.LIST_ITEM:
+                    parts.append(f"- {block.text}")
+                elif block.type == BlockType.CODE:
+                    parts.append(f"```\n{block.text}\n```")
+                elif block.type == BlockType.EQUATION:
+                    parts.append(f"$$\n{block.text}\n$$")
+                else:
+                    parts.append(block.text)
+                parts.append("")
+        return "\n".join(parts)
diff --git a/src/longparser/integrations/__init__.py b/src/longparser/integrations/__init__.py
index b8eae82..44055de 100755
--- a/src/longparser/integrations/__init__.py
+++ b/src/longparser/integrations/__init__.py
@@ -2,9 +2,9 @@
 
 Install the extras to use these adapters::
 
-    pip install clean_rag[langchain]
-    pip install clean_rag[llamaindex]
-    pip install clean_rag[all]
+    pip install longparser[langchain]
+    pip install longparser[llamaindex]
+    pip install longparser[all]
 """
 
 from __future__ import annotations
diff --git a/src/longparser/integrations/langchain.py b/src/longparser/integrations/langchain.py
index 59bdba0..7848c31 100755
--- a/src/longparser/integrations/langchain.py
+++ b/src/longparser/integrations/langchain.py
@@ -5,7 +5,7 @@
 
 Install the extra to use this adapter::
 
-    pip install clean_rag[langchain]
+    pip install longparser[langchain]
 
 Usage::
 
@@ -27,7 +27,7 @@
 
 _INSTALL_MSG = (
     "langchain-core is required for the LangChain adapter. "
-    "Install it with:  pip install clean_rag[langchain]"
+    "Install it with:  pip install longparser[langchain]"
 )
 
 
@@ -95,6 +95,7 @@ def lazy_load(self) -> Iterator["LCDocument"]:
         from ..pipeline import PipelineOrchestrator
 
         pipeline = PipelineOrchestrator(
+            config=self.config,
             tesseract_lang=self.tesseract_lang,
             tessdata_path=self.tessdata_path,
         )
diff --git a/src/longparser/integrations/llamaindex.py b/src/longparser/integrations/llamaindex.py
index a8d4344..d5437b9 100755
--- a/src/longparser/integrations/llamaindex.py
+++ b/src/longparser/integrations/llamaindex.py
@@ -5,7 +5,7 @@
 
 Install the extra to use this adapter::
 
-    pip install clean_rag[llamaindex]
+    pip install longparser[llamaindex]
 
 Usage::
 
@@ -27,7 +27,7 @@
 
 _INSTALL_MSG = (
     "llama-index-core is required for the LlamaIndex adapter. "
-    "Install it with:  pip install clean_rag[llamaindex]"
+    "Install it with:  pip install longparser[llamaindex]"
 )
 
 
@@ -105,6 +105,7 @@ def load_data(
 
         file = Path(file)
         pipeline = PipelineOrchestrator(
+            config=self.config,
             tesseract_lang=self.tesseract_lang,
             tessdata_path=self.tessdata_path,
         )
diff --git a/src/longparser/pipeline/orchestrator.py b/src/longparser/pipeline/orchestrator.py
index 202be9e..5062a48 100755
--- a/src/longparser/pipeline/orchestrator.py
+++ b/src/longparser/pipeline/orchestrator.py
@@ -1,4 +1,13 @@
-"""Simple pipeline orchestrator for LongParser."""
+"""Simple pipeline orchestrator for LongParser.
+
+Supports multiple extraction backends:
+
+- ``"docling"`` (default) — Docling with Tesseract CLI OCR (MIT)
+- ``"pymupdf"`` — PyMuPDF4LLM for fast native PDF extraction (AGPL, optional)
+- ``"auto"``    — Automatic backend selection based on document properties
+
+Language detection runs before OCR to set the correct Tesseract language.
+"""
 
 from pathlib import Path
 from dataclasses import dataclass, field
@@ -11,6 +20,7 @@
 from ..extractors import DoclingExtractor
 from ..extractors.docling_extractor import HierarchyChunk
 from ..chunkers import HybridChunker
+from ..utils.lang_detect import detect_language, get_tesseract_langs, extract_sample_text
 
 logger = logging.getLogger(__name__)
 
@@ -30,43 +40,189 @@ def total_blocks(self) -> int:
 
 class PipelineOrchestrator:
     """
-    Simple pipeline orchestrator using Docling.
+    Pipeline orchestrator with backend selection and language detection.
     
     Flow:
-    1. Docling extracts with Tesseract CLI OCR
-    2. Layout analysis detects structure
-    3. HierarchicalChunker preserves heading hierarchy
+    1. (Optional) Auto-detect document language
+    2. Select backend: Docling, PyMuPDF, or auto-route
+    3. Extract with chosen backend
+    4. HierarchicalChunker preserves heading hierarchy
+    
+    Parameters
+    ----------
+    config:
+        Processing configuration with backend, language, and layout settings.
+        Only used for backend selection during init. Per-file config is passed
+        to ``process_file()``.
+    tesseract_lang:
+        Languages for Tesseract OCR (default: ``["eng"]``). Overridden by
+        ``config.languages`` or auto-detection if enabled.
+    tessdata_path:
+        Path to tessdata directory with language models and configs.
+    force_full_page_ocr:
+        If True, OCR entire page even if embedded text exists.
     """
     
-    def __init__(self, tesseract_lang: List[str] = None, tessdata_path: str = None, force_full_page_ocr: bool = False):
-        """
-        Initialize pipeline.
-        
-        Args:
-            tesseract_lang: Languages for Tesseract OCR (default: ["eng"])
-            tessdata_path: Path to tessdata directory with language models and configs.
-            force_full_page_ocr: If True, OCR entire page even if embedded text exists.
+    def __init__(
+        self,
+        config: Optional[ProcessingConfig] = None,
+        tesseract_lang: List[str] = None,
+        tessdata_path: str = None,
+        force_full_page_ocr: bool = False,
+    ):
+        self._config = config or ProcessingConfig()
+        self._tessdata_path = tessdata_path
+        self._force_full_page_ocr = force_full_page_ocr
+        self._base_tesseract_lang = tesseract_lang
+
+        # Determine backend from config
+        backend = self._config.backend
+
+        if backend == "pymupdf":
+            # Lazy import — only loaded when user explicitly requests it
+            from ..extractors.pymupdf_extractor import PyMuPDFExtractor
+            self.extractor = PyMuPDFExtractor()
+            self._backend_name = "pymupdf"
+            logger.info("Pipeline initialized with PyMuPDF4LLM backend (CPU-native, fast)")
+
+        elif backend == "auto":
+            # Auto mode: start with Docling (safe default), route at process time
+            self.extractor = DoclingExtractor(
+                tesseract_lang=tesseract_lang,
+                tessdata_path=tessdata_path,
+                force_full_page_ocr=force_full_page_ocr,
+            )
+            self._backend_name = "auto"
+            logger.info("Pipeline initialized in auto mode (will choose backend per document)")
+
+        else:
+            # Default: Docling (MIT, always available)
+            self.extractor = DoclingExtractor(
+                tesseract_lang=tesseract_lang,
+                tessdata_path=tessdata_path,
+                force_full_page_ocr=force_full_page_ocr,
+            )
+            self._backend_name = "docling"
+            logger.info("Pipeline initialized with Docling backend (default)")
+
+    def _resolve_languages(
+        self,
+        file_path: Path,
+        config: ProcessingConfig,
+    ) -> list[str]:
+        """Resolve OCR languages via user override or auto-detection.
+
+        Priority order:
+        1. ``config.languages`` (explicit user override — always wins)
+        2. ``self._base_tesseract_lang`` (constructor param)
+        3. Auto-detection via ``fast-langdetect`` (if enabled)
+        4. Default: ``["eng"]``
         """
-        self.extractor = DoclingExtractor(
-            tesseract_lang=tesseract_lang,
-            tessdata_path=tessdata_path,
-            force_full_page_ocr=force_full_page_ocr,
-        )
-    
+        # 1. Explicit user override
+        if config.languages:
+            logger.info("Using user-specified languages: %s", config.languages)
+            return config.languages
+
+        # 2. Constructor param
+        if self._base_tesseract_lang:
+            # If auto-detect is enabled, try to improve on constructor default
+            if config.auto_detect_language:
+                detected_langs = self._auto_detect(file_path)
+                if detected_langs:
+                    return detected_langs
+            return self._base_tesseract_lang
+
+        # 3. Auto-detect
+        if config.auto_detect_language:
+            detected_langs = self._auto_detect(file_path)
+            if detected_langs:
+                return detected_langs
+
+        # 4. Default
+        return ["eng"]
+
+    def _auto_detect(self, file_path: Path) -> Optional[list[str]]:
+        """Run language detection and return Tesseract codes, or None."""
+        sample = extract_sample_text(file_path)
+        if not sample or len(sample.strip()) < 20:
+            return None
+
+        lang_code, confidence = detect_language(sample)
+        if confidence > 0.0:
+            tess_langs = get_tesseract_langs(lang_code)
+            logger.info(
+                "Auto-detected language: %s (%.0f%%) → Tesseract: %s",
+                lang_code, confidence * 100, tess_langs,
+            )
+            # Store for later use in document metadata
+            self._detected_lang = lang_code
+            self._detected_lang_confidence = confidence
+            return tess_langs
+
+        return None
+
+    def _should_use_pymupdf(self, file_path: Path) -> bool:
+        """Check if PyMuPDF is a better choice for this file (auto mode)."""
+        ext = file_path.suffix.lower()
+
+        # PyMuPDF only handles PDFs
+        if ext != ".pdf":
+            return False
+
+        # Check if PDF has a text layer (= native, not scanned)
+        sample = extract_sample_text(file_path, max_chars=500)
+        if sample and len(sample.strip()) > 100:
+            # Has text → native PDF → PyMuPDF is faster
+            try:
+                from ..extractors.pymupdf_extractor import PyMuPDFExtractor
+                return True
+            except ImportError:
+                # pymupdf4llm not installed — fall back to Docling
+                logger.debug("Auto mode: pymupdf4llm not installed, using Docling")
+                return False
+
+        # Scanned PDF or too little text → use Docling (has OCR)
+        return False
+
     def process(self, request: JobRequest) -> PipelineResult:
         """Process a document."""
         start_time = time.time()
         
         file_path = Path(request.file_path)
         config = request.config
+
+        # Initialize language detection state
+        self._detected_lang = None
+        self._detected_lang_confidence = 0.0
         
         logger.info(f"Processing: {file_path.name}")
-        
+
+        # Auto-mode: decide backend per document
+        if self._backend_name == "auto" and self._should_use_pymupdf(file_path):
+            from ..extractors.pymupdf_extractor import PyMuPDFExtractor
+            extractor = PyMuPDFExtractor()
+            logger.info("Auto mode selected: PyMuPDF4LLM (native PDF detected)")
+        else:
+            extractor = self.extractor
+
+            # Resolve languages for Docling backend
+            if isinstance(extractor, DoclingExtractor):
+                resolved_langs = self._resolve_languages(file_path, config)
+                extractor._languages = resolved_langs
+
         # Extract document
-        document, meta = self.extractor.extract(file_path, config)
-        
-        # Get hierarchy
-        hierarchy = self.extractor.get_hierarchy(file_path, config)
+        document, meta = extractor.extract(file_path, config)
+
+        # Inject language detection results into metadata
+        if self._detected_lang:
+            document.metadata.detected_language = self._detected_lang
+            document.metadata.language_confidence = self._detected_lang_confidence
+
+        # Get hierarchy (only DoclingExtractor has this)
+        if isinstance(extractor, DoclingExtractor):
+            hierarchy = extractor.get_hierarchy(file_path, config)
+        else:
+            hierarchy = []
         
         processing_time = time.time() - start_time
         logger.info(f"Completed in {processing_time:.2f}s")
@@ -164,6 +320,8 @@ def export_results(self, result: PipelineResult, output_dir: Path) -> dict:
             "total_blocks": len(all_blocks),
             "total_tables": total_tables,
             "processing_time_seconds": result.processing_time_seconds,
+            "detected_language": result.document.metadata.detected_language,
+            "language_confidence": result.document.metadata.language_confidence,
             "stages_completed": [
                 "stage1_extraction",
                 "stage2_validation",
@@ -228,3 +386,4 @@ def export_chunks(self, result: PipelineResult, output_dir: Path) -> Path:
     def save_images(self, output_dir: Path) -> List[Path]:
         """Save extracted images."""
         return self.extractor.save_images(output_dir)
+
diff --git a/src/longparser/schemas.py b/src/longparser/schemas.py
index 60bd47f..6e54f1e 100755
--- a/src/longparser/schemas.py
+++ b/src/longparser/schemas.py
@@ -118,6 +118,8 @@ class PageProfile(BaseModel):
     table_confidence: Optional[float] = None
     has_rtl: bool = False
     has_math: bool = False
+    detected_columns: int = Field(default=1, description="Number of text columns detected on page")
+    reading_order_confidence: float = Field(default=1.0, ge=0.0, le=1.0, description="Confidence of reading-order reconstruction")
 
 
 class Page(BaseModel):
@@ -135,6 +137,8 @@ class DocumentMetadata(BaseModel):
     source_file: str
     file_hash: str = ""
     language: Optional[str] = None
+    detected_language: Optional[str] = Field(default=None, description="Auto-detected language code (ISO 639-1) via fast-langdetect")
+    language_confidence: float = Field(default=0.0, ge=0.0, le=1.0, description="Confidence of auto-detected language")
     total_pages: int = 0
     academic_mode: bool = False
     rtl_hint: bool = False
@@ -163,6 +167,17 @@ def all_tables(self) -> list[Table]:
 
 class ProcessingConfig(BaseModel):
     """Configuration for pipeline execution."""
+    # --- v0.1.4: Backend selection ---
+    backend: str = Field(default="docling", description="Extraction backend: 'docling' | 'pymupdf' | 'auto'")
+
+    # --- v0.1.4: Language detection ---
+    languages: Optional[list[str]] = Field(default=None, description="Explicit Tesseract language codes, e.g. ['eng','ara']. Overrides auto-detect.")
+    auto_detect_language: bool = Field(default=True, description="Auto-detect document language before OCR (uses fast-langdetect)")
+
+    # --- v0.1.4: Multi-column layout ---
+    column_count_hint: Optional[int] = Field(default=None, description="Manual column count hint. None = auto-detect by Docling")
+    force_left_to_right: bool = Field(default=False, description="Force left-to-right top-to-bottom reading order")
+
     academic_mode: bool = False
     rtl_hint: bool = False
     do_ocr: bool = True
@@ -202,6 +217,10 @@ class ExtractionMetadata(BaseModel):
     reprocessed_pages: list[int] = Field(default_factory=list)
     ocr_backend_used: Optional[str] = None
     reasons: list[str] = Field(default_factory=list)
+    # --- v0.1.4: OCR routing metadata ---
+    ocr_strategy: str = Field(default="standard", description="OCR strategy used: 'standard' | 'math' | 'full_ocr'")
+    is_scanned: bool = Field(default=False, description="Whether the document was detected as scanned (no text layer)")
+    page_complexity_scores: dict[int, int] = Field(default_factory=dict, description="Per-page complexity scores used for OCR routing")
 
 
 class ChunkingConfig(BaseModel):
@@ -222,12 +241,13 @@ class Chunk(BaseModel):
     chunk_id: str = Field(default_factory=lambda: str(uuid.uuid4()))
     text: str
     token_count: int
-    chunk_type: str  # "section" | "table" | "table_schema" | "list" | "equation" | "continuation"
+    chunk_type: str  # "section" | "table" | "table_schema" | "list" | "equation" | "figure" | "continuation"
     section_path: list[str] = Field(default_factory=list)
     page_numbers: list[int] = Field(default_factory=list)
     block_ids: list[str] = Field(default_factory=list)
     overlap_with_previous: bool = False
     equation_detected: bool = False
+    image_path: Optional[str] = Field(default=None, description="Path to figure image if chunk_type == 'figure'")
     metadata: dict = Field(default_factory=dict)  # row_start, row_end, sheet, col_band
 
 
diff --git a/src/longparser/utils/__init__.py b/src/longparser/utils/__init__.py
index c642b45..7c7ea22 100755
--- a/src/longparser/utils/__init__.py
+++ b/src/longparser/utils/__init__.py
@@ -1,5 +1,14 @@
 """Utility modules for LongParser."""
 
 from .rtl_detector import detect_rtl_language
+from .lang_detect import detect_language, get_tesseract_langs
+from .ocr_router import is_page_scanned, score_page_complexity, get_ocr_strategy
 
-__all__ = ["detect_rtl_language"]
+__all__ = [
+    "detect_rtl_language",
+    "detect_language",
+    "get_tesseract_langs",
+    "is_page_scanned",
+    "score_page_complexity",
+    "get_ocr_strategy",
+]
diff --git a/src/longparser/utils/lang_detect.py b/src/longparser/utils/lang_detect.py
new file mode 100644
index 0000000..b544d4b
--- /dev/null
+++ b/src/longparser/utils/lang_detect.py
@@ -0,0 +1,193 @@
+"""Language detection for document text samples.
+
+Uses ``fast-langdetect`` (Apache-2.0, Facebook FastText model) to detect
+the primary language of a text sample and map it to Tesseract language codes.
+
+This module is designed for zero-failure operation:
+- Falls back to English if ``fast-langdetect`` is not installed
+- Falls back to English if detection confidence is too low
+- Falls back to English on any unexpected error
+- Never raises exceptions that would break the pipeline
+
+Usage::
+
+    from longparser.utils.lang_detect import detect_language, get_tesseract_langs
+
+    lang, confidence = detect_language("هذا نص عربي")  # ("ar", 0.99)
+    tess_codes = get_tesseract_langs("ar")             # ["ara"]
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+# ---------------------------------------------------------------------------
+# Mapping: ISO 639-1 code (fast-langdetect) → Tesseract language code(s)
+# ---------------------------------------------------------------------------
+_LANG_TO_TESSERACT: dict[str, list[str]] = {
+    "af": ["afr"],   "am": ["amh"],   "ar": ["ara"],   "az": ["aze"],
+    "be": ["bel"],   "bg": ["bul"],   "bn": ["ben"],   "bs": ["bos"],
+    "ca": ["cat"],   "cs": ["ces"],   "cy": ["cym"],   "da": ["dan"],
+    "de": ["deu"],   "el": ["ell"],   "en": ["eng"],   "es": ["spa"],
+    "et": ["est"],   "eu": ["eus"],   "fa": ["fas"],   "fi": ["fin"],
+    "fr": ["fra"],   "ga": ["gle"],   "gl": ["glg"],   "gu": ["guj"],
+    "ha": ["hau"],   "he": ["heb"],   "hi": ["hin"],   "hr": ["hrv"],
+    "hu": ["hun"],   "hy": ["hye"],   "id": ["ind"],   "is": ["isl"],
+    "it": ["ita"],   "ja": ["jpn"],   "jv": ["jav"],   "ka": ["kat"],
+    "kk": ["kaz"],   "km": ["khm"],   "kn": ["kan"],   "ko": ["kor"],
+    "la": ["lat"],   "lt": ["lit"],   "lv": ["lav"],   "mk": ["mkd"],
+    "ml": ["mal"],   "mn": ["mon"],   "mr": ["mar"],   "ms": ["msa"],
+    "my": ["mya"],   "ne": ["nep"],   "nl": ["nld"],   "no": ["nor"],
+    "pa": ["pan"],   "pl": ["pol"],   "pt": ["por"],   "ro": ["ron"],
+    "ru": ["rus"],   "si": ["sin"],   "sk": ["slk"],   "sl": ["slv"],
+    "sq": ["sqi"],   "sr": ["srp"],   "sv": ["swe"],   "sw": ["swa"],
+    "ta": ["tam"],   "te": ["tel"],   "th": ["tha"],   "tl": ["tgl"],
+    "tr": ["tur"],   "uk": ["ukr"],   "ur": ["urd"],   "uz": ["uzb"],
+    "vi": ["vie"],   "yo": ["yor"],
+    # Chinese variants
+    "zh": ["chi_sim", "chi_tra"],
+}
+
+
+def detect_language(
+    text: str,
+    min_confidence: float = 0.5,
+) -> tuple[str, float]:
+    """Detect the primary language of a text sample.
+
+    Parameters
+    ----------
+    text:
+        Text sample to analyze. At least 20 characters recommended.
+    min_confidence:
+        Minimum confidence threshold. Below this, falls back to ``"en"``.
+
+    Returns
+    -------
+    tuple[str, float]
+        ``(language_code, confidence)`` — e.g. ``("ar", 0.99)``.
+        Falls back to ``("en", 0.0)`` on any failure.
+    """
+    if not text or len(text.strip()) < 20:
+        logger.debug("Text too short for language detection, defaulting to English")
+        return "en", 0.0
+
+    try:
+        from fast_langdetect import detect
+        result = detect(text)
+        lang = result.get("lang", "en")
+        score = result.get("score", 0.0)
+
+        if score < min_confidence:
+            logger.info(
+                "Language detection low confidence (%.2f for '%s'), "
+                "defaulting to English", score, lang
+            )
+            return "en", score
+
+        logger.info("Detected language: %s (confidence: %.2f)", lang, score)
+        return lang, score
+
+    except ImportError:
+        logger.warning(
+            "fast-langdetect is not installed. Language detection disabled. "
+            "Install with: pip install fast-langdetect"
+        )
+        return "en", 0.0
+    except Exception as e:
+        logger.warning("Language detection failed: %s — defaulting to English", e)
+        return "en", 0.0
+
+
+def get_tesseract_langs(lang_code: str) -> list[str]:
+    """Map a detected language code to Tesseract language code(s).
+
+    Parameters
+    ----------
+    lang_code:
+        ISO 639-1 language code (e.g. ``"ar"``, ``"en"``).
+
+    Returns
+    -------
+    list[str]
+        Tesseract language codes (e.g. ``["ara"]``, ``["eng"]``).
+    """
+    return _LANG_TO_TESSERACT.get(lang_code, ["eng"])
+
+
+def extract_sample_text(file_path, max_chars: int = 2000) -> str:
+    """Extract a sample of text from a document for language detection.
+
+    Uses a lightweight approach: reads first few KB of the file and
+    extracts printable text. For PDFs, attempts to use PyMuPDF if
+    available, otherwise falls back to reading raw bytes.
+
+    Parameters
+    ----------
+    file_path:
+        Path to the document file.
+    max_chars:
+        Maximum characters to extract.
+
+    Returns
+    -------
+    str
+        Extracted text sample, or empty string if extraction fails.
+    """
+    from pathlib import Path
+    file_path = Path(file_path)
+
+    if not file_path.exists():
+        return ""
+
+    ext = file_path.suffix.lower()
+
+    # For PDFs: try lightweight text extraction
+    if ext == ".pdf":
+        return _extract_pdf_sample(file_path, max_chars)
+
+    # For text-like files: read directly
+    if ext in (".csv", ".txt", ".md"):
+        try:
+            with open(file_path, "r", encoding="utf-8", errors="ignore") as f:
+                return f.read(max_chars)
+        except Exception:
+            return ""
+
+    # For other formats: return empty (language detection will use
+    # text extracted by Docling later)
+    return ""
+
+
+def _extract_pdf_sample(file_path, max_chars: int) -> str:
+    """Extract text sample from a PDF using the lightest method available."""
+    # Try pdfplumber (lightweight, often available)
+    try:
+        import pdfplumber
+        with pdfplumber.open(str(file_path)) as pdf:
+            text = ""
+            for page in pdf.pages[:3]:  # First 3 pages
+                page_text = page.extract_text() or ""
+                text += page_text + "\n"
+                if len(text) >= max_chars:
+                    break
+            return text[:max_chars]
+    except ImportError:
+        pass
+    except Exception:
+        pass
+
+    # Fallback: read raw bytes and extract printable chars
+    try:
+        with open(file_path, "rb") as f:
+            raw = f.read(max_chars * 4)  # Read more bytes since not all are text
+        # Extract ASCII/Unicode text from raw bytes
+        text = raw.decode("utf-8", errors="ignore")
+        # Filter to printable characters
+        printable = "".join(c for c in text if c.isprintable() or c in "\n\t ")
+        return printable[:max_chars]
+    except Exception:
+        return ""
diff --git a/src/longparser/utils/ocr_router.py b/src/longparser/utils/ocr_router.py
new file mode 100644
index 0000000..dd3586d
--- /dev/null
+++ b/src/longparser/utils/ocr_router.py
@@ -0,0 +1,148 @@
+"""Smart OCR routing for scanned PDFs.
+
+Routes pages to the best OCR strategy based on content complexity:
+
+- **standard** — Tesseract with default settings (fast, CPU-native)
+- **math** — Tesseract for text + pix2tex for equations
+- **full_ocr** — Tesseract with ``force_full_page_ocr=True``
+
+All strategies are CPU-friendly. No GPU-dependent engines (Surya, Marker)
+are used in the routing — those are available as separate optional backends.
+
+Usage::
+
+    from longparser.utils.ocr_router import (
+        is_page_scanned, score_page_complexity, get_ocr_strategy,
+    )
+
+    if is_page_scanned(page_text):
+        score = score_page_complexity(page_text, num_blocks=15, has_tables=True)
+        strategy = get_ocr_strategy(score)
+        # strategy = "full_ocr" for score >= 5
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+
+logger = logging.getLogger(__name__)
+
+# Pattern to detect math symbols and simple equations in text.
+# Matches Unicode math symbols and simple algebraic patterns like "x = 5".
+_MATH_RE = re.compile(
+    r'[\u2211\u220F\u222B\u221A\u00B1\u2264\u2265\u2248\u2260\u03B1-\u03C9\u03A3]'
+    r'|[a-z]\s*=\s*[a-z0-9]',
+    re.IGNORECASE,
+)
+
+
+def is_page_scanned(page_text: str, min_chars: int = 30) -> bool:
+    """Check if a page is likely scanned (no usable text layer).
+
+    Parameters
+    ----------
+    page_text:
+        Extracted text from the page.
+    min_chars:
+        Minimum character count to consider the page as having a text layer.
+
+    Returns
+    -------
+    bool
+        ``True`` if the page has fewer than ``min_chars`` printable characters
+        (indicating it's likely a scanned image with no embedded text).
+    """
+    clean = page_text.strip()
+    return len(clean) < min_chars
+
+
+def has_math_content(text: str) -> bool:
+    """Check if text contains mathematical symbols or equation patterns.
+
+    Parameters
+    ----------
+    text:
+        Text to check for math content.
+
+    Returns
+    -------
+    bool
+        ``True`` if math symbols or equation patterns are found.
+    """
+    return bool(_MATH_RE.search(text))
+
+
+def score_page_complexity(
+    page_text: str,
+    num_blocks: int = 0,
+    has_tables: bool = False,
+) -> int:
+    """Score page complexity on a scale of 0-10.
+
+    Used to decide which OCR strategy to apply:
+
+    - **0-2** → ``"standard"`` — Simple page, Tesseract is enough
+    - **3-4** → ``"math"`` — Has equations, add pix2tex
+    - **5+** → ``"full_ocr"`` — Complex layout, use full-page OCR
+
+    Parameters
+    ----------
+    page_text:
+        Extracted text from the page.
+    num_blocks:
+        Number of content blocks on the page.
+    has_tables:
+        Whether the page contains tables.
+
+    Returns
+    -------
+    int
+        Complexity score from 0 to 10.
+    """
+    score = 0
+
+    # Tables add significant complexity
+    if has_tables:
+        score += 3
+
+    # Math content needs pix2tex
+    if has_math_content(page_text):
+        score += 2
+
+    # Many blocks suggest a dense/complex layout
+    if num_blocks > 20:
+        score += 2
+    elif num_blocks > 10:
+        score += 1
+
+    # Very short text on a page with blocks = likely OCR issues
+    if page_text and len(page_text.strip()) < 100 and num_blocks > 5:
+        score += 1
+
+    return min(score, 10)
+
+
+def get_ocr_strategy(complexity_score: int) -> str:
+    """Pick OCR strategy based on page complexity score.
+
+    Parameters
+    ----------
+    complexity_score:
+        Score from :func:`score_page_complexity` (0-10).
+
+    Returns
+    -------
+    str
+        One of:
+
+        - ``"standard"`` — Tesseract with default settings
+        - ``"math"`` — Tesseract + pix2tex for equations
+        - ``"full_ocr"`` — Tesseract with ``force_full_page_ocr=True``
+    """
+    if complexity_score <= 2:
+        return "standard"
+    elif complexity_score <= 4:
+        return "math"
+    else:
+        return "full_ocr"
diff --git a/tests/benchmarks/benchmark_pipeline.py b/tests/benchmarks/benchmark_pipeline.py
new file mode 100644
index 0000000..716ee44
--- /dev/null
+++ b/tests/benchmarks/benchmark_pipeline.py
@@ -0,0 +1,98 @@
+"""Pipeline performance benchmark for regression testing.
+
+Run this BEFORE and AFTER v0.2.x changes to prove no speed regression.
+
+Usage:
+    # Save baseline (v0.1.3)
+    python tests/benchmarks/benchmark_pipeline.py > benchmark_v013.txt
+
+    # After v0.2.x changes
+    python tests/benchmarks/benchmark_pipeline.py > benchmark_v020.txt
+
+    # Compare
+    diff benchmark_v013.txt benchmark_v020.txt
+"""
+
+import time
+import sys
+from pathlib import Path
+
+
+def benchmark_file(file_path: str) -> dict:
+    """Benchmark a single file through the pipeline."""
+    from longparser import DocumentPipeline, ProcessingConfig
+
+    path = Path(file_path)
+    if not path.exists():
+        return {"file": file_path, "status": "SKIPPED (file not found)"}
+
+    pipeline = DocumentPipeline()
+    config = ProcessingConfig()
+
+    t0 = time.time()
+    try:
+        result = pipeline.process_file(path, config=config)
+        elapsed = time.time() - t0
+
+        return {
+            "file": path.name,
+            "time_seconds": round(elapsed, 2),
+            "total_blocks": result.total_blocks,
+            "total_pages": result.document.metadata.total_pages,
+            "status": "OK",
+        }
+    except Exception as e:
+        elapsed = time.time() - t0
+        return {
+            "file": path.name,
+            "time_seconds": round(elapsed, 2),
+            "status": f"ERROR: {e}",
+        }
+
+
+def main():
+    """Run benchmark on all available test fixtures."""
+    # Look for test PDFs in common locations
+    fixture_dirs = [
+        Path("tests/fixtures"),
+        Path("tests"),
+        Path("uploads"),
+    ]
+
+    test_files = []
+    for d in fixture_dirs:
+        if d.exists():
+            test_files.extend(sorted(d.glob("*.pdf")))
+
+    if not test_files:
+        print("No PDF test files found in tests/fixtures/ or uploads/")
+        print("Place some PDFs there and re-run.")
+        sys.exit(1)
+
+    print("=" * 60)
+    print("LongParser Pipeline Benchmark")
+    print("=" * 60)
+    print(f"Files found: {len(test_files)}")
+    print()
+
+    results = []
+    for f in test_files[:5]:  # Cap at 5 files for reasonable benchmark time
+        print(f"Benchmarking: {f.name} ...", end=" ", flush=True)
+        result = benchmark_file(str(f))
+        results.append(result)
+        print(f"{result.get('time_seconds', '?')}s — {result['status']}")
+
+    print()
+    print("-" * 60)
+    print(f"{'File':<30} {'Time':>8} {'Blocks':>8} {'Pages':>6}")
+    print("-" * 60)
+    for r in results:
+        if r["status"] == "OK":
+            print(f"{r['file']:<30} {r['time_seconds']:>7.2f}s {r['total_blocks']:>8} {r['total_pages']:>6}")
+        else:
+            print(f"{r['file']:<30} {r['status']}")
+    print("-" * 60)
+
+
+if __name__ == "__main__":
+    main()
diff --git a/tests/unit/test_backward_compat.py b/tests/unit/test_backward_compat.py
new file mode 100644
index 0000000..fae7d49
--- /dev/null
+++ b/tests/unit/test_backward_compat.py
@@ -0,0 +1,142 @@
+"""Backward compatibility tests for v0.2.x changes.
+
+Ensures that users who wrote code against v0.1.3 can upgrade to v0.2.x
+without changing a single line of their code. Every new field must have
+a default that matches the v0.1.3 behavior.
+"""
+
+import pytest
+
+
+class TestProcessingConfigCompat:
+    """ProcessingConfig() with no args must behave exactly like v0.1.3."""
+
+    def test_default_values_match_v013(self):
+        from longparser.schemas import ProcessingConfig
+        config = ProcessingConfig()
+
+        # v0.1.3 defaults — these must NEVER change
+        assert config.academic_mode is False
+        assert config.rtl_hint is False
+        assert config.do_ocr is True
+        assert config.formula_ocr is True
+        assert config.do_table_structure is True
+        assert config.export_images is True
+        assert config.formula_mode == "smart"
+        assert config.smart_max_equations == 25
+        assert config.smart_max_ocr_seconds == 300.0
+        assert config.exclude_page_headers_footers is True
+
+    def test_new_fields_have_safe_defaults(self):
+        """New v0.2.x fields must default to values that don't change behavior."""
+        from longparser.schemas import ProcessingConfig
+        config = ProcessingConfig()
+
+        # backend must default to docling (existing behavior)
+        backend = getattr(config, "backend", "docling")
+        assert backend == "docling"
+
+        # auto_detect_language defaults to True but only runs if languages=None
+        auto_detect = getattr(config, "auto_detect_language", True)
+        assert auto_detect is True
+
+        # languages=None means "use existing tesseract_lang param"
+        languages = getattr(config, "languages", None)
+        assert languages is None
+
+
+class TestDocumentMetadataCompat:
+    """DocumentMetadata must keep all v0.1.3 fields."""
+
+    def test_v013_fields_exist(self):
+        from longparser.schemas import DocumentMetadata
+        meta = DocumentMetadata(source_file="test.pdf")
+
+        assert meta.source_file == "test.pdf"
+        assert meta.file_hash == ""
+        assert meta.language is None
+        assert meta.total_pages == 0
+        assert meta.academic_mode is False
+        assert meta.rtl_hint is False
+
+
+class TestBlockCompat:
+    """Block schema must keep all v0.1.3 fields and types."""
+
+    def test_block_type_values_unchanged(self):
+        from longparser.schemas import BlockType
+
+        # All v0.1.3 values must still exist
+        assert BlockType.HEADING == "heading"
+        assert BlockType.PARAGRAPH == "paragraph"
+        assert BlockType.LIST_ITEM == "list_item"
+        assert BlockType.TABLE == "table"
+        assert BlockType.FIGURE == "figure"
+        assert BlockType.CAPTION == "caption"
+        assert BlockType.FOOTER == "footer"
+        assert BlockType.HEADER == "header"
+        assert BlockType.EQUATION == "equation"
+        assert BlockType.CODE == "code"
+
+    def test_extractor_type_values_unchanged(self):
+        from longparser.schemas import ExtractorType
+
+        # All v0.1.3 values must still exist
+        assert ExtractorType.DOCLING == "docling"
+        assert ExtractorType.SURYA == "surya"
+        assert ExtractorType.MARKER == "marker"
+        assert ExtractorType.NATIVE_PDF == "native_pdf"
+        assert ExtractorType.PADDLE == "paddle"
+
+
+class TestChunkCompat:
+    """Chunk schema must keep all v0.1.3 fields."""
+
+    def test_chunk_fields_exist(self):
+        from longparser.schemas import Chunk
+        chunk = Chunk(text="test", token_count=1, chunk_type="section")
+
+        assert chunk.text == "test"
+        assert chunk.token_count == 1
+        assert chunk.chunk_type == "section"
+        assert chunk.section_path == []
+        assert chunk.page_numbers == []
+        assert chunk.block_ids == []
+        assert chunk.overlap_with_previous is False
+        assert chunk.equation_detected is False
+
+
+class TestPublicAPICompat:
+    """All v0.1.3 public names must still be importable."""
+
+    def test_all_v013_exports_available(self):
+        from longparser import (  # noqa: F401
+            __version__,
+            Document,
+            Page,
+            Block,
+            Table,
+            TableCell,
+            BlockType,
+            ExtractorType,
+            ProcessingConfig,
+            BoundingBox,
+            Provenance,
+            Confidence,
+            BlockFlags,
+            DocumentMetadata,
+            PageProfile,
+            ExtractionMetadata,
+            ChunkingConfig,
+            Chunk,
+            JobRequest,
+            JobResult,
+        )
+
+    def test_lazy_imports_still_work(self):
+        """Lazy imports from v0.1.3 must still resolve."""
+        from longparser import DocumentPipeline  # noqa: F401
+        from longparser import PipelineOrchestrator  # noqa: F401
+        from longparser import PipelineResult  # noqa: F401
+        from longparser import HybridChunker  # noqa: F401
+        from longparser import DoclingExtractor  # noqa: F401
diff --git a/tests/unit/test_license_safety.py b/tests/unit/test_license_safety.py
new file mode 100644
index 0000000..8afac8b
--- /dev/null
+++ b/tests/unit/test_license_safety.py
@@ -0,0 +1,82 @@
+"""License safety tests — ensure GPL/AGPL packages are never loaded by default.
+
+These tests verify that importing ``longparser`` and using its default
+pipeline does NOT load any GPL/AGPL-licensed package (pymupdf4llm, marker,
+surya). This is critical to maintain LongParser's MIT license.
+"""
+
+import sys
+import pytest
+
+
+# Packages that must NEVER appear in sys.modules after a default import
+_BLOCKED_MODULES = [
+    "pymupdf4llm",
+    "pymupdf",
+    "fitz",           # PyMuPDF's internal module name
+    "marker",
+    "marker.converters",
+    "surya",
+    "surya.ocr",
+]
+
+
+def _clear_blocked_modules():
+    """Remove any pre-loaded blocked modules from sys.modules."""
+    for mod_name in list(sys.modules):
+        for blocked in _BLOCKED_MODULES:
+            if mod_name == blocked or mod_name.startswith(blocked + "."):
+                del sys.modules[mod_name]
+
+
+class TestLicenseSafety:
+    """Verify that core imports do not load GPL/AGPL dependencies."""
+
+    def test_import_longparser_does_not_load_agpl(self):
+        """``import longparser`` must not load any GPL/AGPL module."""
+        _clear_blocked_modules()
+
+        import longparser  # noqa: F401
+
+        for mod_name in _BLOCKED_MODULES:
+            assert mod_name not in sys.modules, (
+                f"GPL/AGPL module '{mod_name}' was loaded by 'import longparser'. "
+                f"This violates the MIT license isolation. "
+                f"Check __init__.py and extractors/__init__.py for stray imports."
+            )
+
+    def test_import_schemas_does_not_load_agpl(self):
+        """``from longparser.schemas import ...`` must not load GPL/AGPL."""
+        _clear_blocked_modules()
+
+        from longparser.schemas import (  # noqa: F401
+            ProcessingConfig, Document, Block, Chunk
+        )
+
+        for mod_name in _BLOCKED_MODULES:
+            assert mod_name not in sys.modules, (
+                f"GPL/AGPL module '{mod_name}' was loaded by schema import."
+            )
+
+    def test_processing_config_default_backend_is_docling(self):
+        """Default backend must be 'docling' (MIT), not a GPL/AGPL backend."""
+        from longparser.schemas import ProcessingConfig
+        config = ProcessingConfig()
+
+        # If backend field exists, it must default to docling
+        backend = getattr(config, "backend", "docling")
+        assert backend == "docling", (
+            f"Default backend is '{backend}', expected 'docling'. "
+            f"Defaulting to a GPL/AGPL backend would violate MIT license."
+        )
+
+    def test_pymupdf_extractor_not_in_extractors_init(self):
+        """PyMuPDFExtractor must NOT be exported from extractors/__init__.py."""
+        from longparser import extractors
+
+        public_names = getattr(extractors, "__all__", dir(extractors))
+
+        assert "PyMuPDFExtractor" not in public_names, (
+            "PyMuPDFExtractor must NOT be in extractors/__init__.py. "
+            "It must only be imported lazily when backend='pymupdf' is set."
+        )

From 26897dbfc0b12c455cdb926a3ca0dde4cc4ce85f Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Thu, 23 Apr 2026 10:03:06 +0500
Subject: [PATCH 6/7] ci: fix license safety check regex

---
 .github/workflows/license-check.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/license-check.yml b/.github/workflows/license-check.yml
index 39b5031..784fda2 100644
--- a/.github/workflows/license-check.yml
+++ b/.github/workflows/license-check.yml
@@ -18,7 +18,7 @@ jobs:
           FAIL=0
 
           # List of GPL/AGPL package import patterns to block
-          BLOCKED_PATTERNS="pymupdf4llm|pymupdf|import marker\.|from marker\.|import surya|from surya"
+          BLOCKED_PATTERNS="import[[:space:]]+pymupdf|from[[:space:]]+pymupdf|import[[:space:]]+marker\.|from[[:space:]]+marker\.|import[[:space:]]+surya|from[[:space:]]+surya"
 
           # Files that ARE allowed to import these (isolated backends)
           ALLOWED_FILES=(

From c5f3bd3dbd6d1bedb72b28da728cb30a697b0971 Mon Sep 17 00:00:00 2001
From: Mohsin Ali <imohsinali1024@gmail.com>
Date: Thu, 23 Apr 2026 10:06:59 +0500
Subject: [PATCH 7/7] ci: fix grep exclude syntax for license check

---
 .github/workflows/license-check.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/license-check.yml b/.github/workflows/license-check.yml
index 784fda2..63f9217 100644
--- a/.github/workflows/license-check.yml
+++ b/.github/workflows/license-check.yml
@@ -22,8 +22,8 @@ jobs:
 
           # Files that ARE allowed to import these (isolated backends)
           ALLOWED_FILES=(
-            "src/longparser/extractors/pymupdf_extractor.py"
-            "src/longparser/extractors/marker_extractor.py"
+            "pymupdf_extractor.py"
+            "marker_extractor.py"
           )
 
           # Build grep exclude args