requirements.txt

# ============================================================
# Code Documentation Assistant — dev branch requirements
# ============================================================

# --- LangGraph + LangChain (agent orchestration) ---
langgraph>=0.2.0
langchain>=0.3.0
langchain-core>=0.3.0
langchain-ollama>=0.2.0
langchain-openai>=0.2.0        # vLLM OpenAI-compatible endpoint
langchain-community>=0.3.0

# --- RAG / ingestion pipeline (retained from main) ---
llama-index-core>=0.11.0
llama-index-llms-ollama>=0.3.0
llama-index-embeddings-ollama>=0.3.0
llama-index-vector-stores-chroma>=0.2.0
llama-index-readers-file>=0.2.0
llama-index-readers-github>=0.2.0

# --- Vector DB ---
chromadb==0.6.3                # pinned — matches main branch

# --- Code parsing ---
tree-sitter>=0.21.0
tree-sitter-language-pack>=0.1.0

# --- Inference backends ---
# Ollama: via langchain-ollama above (default)
# vLLM:   exposes OpenAI-compatible API — langchain-openai handles both.
#         vLLM itself is not pip-installed: it runs in its own container
#         (docker-compose.dev.yml profile: vllm)

# --- Experiment tracking ---
mlflow>=2.15.0

# --- UI ---
streamlit>=1.37.0

# --- Workflow orchestration client ---
# Argo Workflows runs cluster-side; the Python client submits WorkflowTemplates
argo-workflows>=6.3.0

# --- Utilities ---
python-dotenv>=1.0.0
gitpython>=3.1.0
requests>=2.31.0