# Dependencies to run the crewai-mongodb-memory demos (memory_demo.py + agent_demo.py).
#
# Install from this directory:
#     pip install -r requirements.txt
# then add ATLAS_URI / VOYAGE_API_KEY / GEMINI_API_KEY to demo/.env and run:
#     python demo/memory_demo.py     # vector recall over the canonical corpus
#     python demo/agent_demo.py      # Gemini agent with long-term preference memory

# The integration package itself (provides MongoDBStorageBackend + embed_text).
# From the repo, install the local package instead:  pip install -e ..
crewai-mongodb-memory>=0.1.0

# MongoDB driver (also pulled in by crewai-mongodb-memory; pinned here for clarity).
pymongo>=4.6

# Voyage AI 3.5 embeddings (bring-your-own 1024-dim query/document vectors).
voyageai>=0.3.0

# Loads demo/.env automatically.
python-dotenv>=1.0

# Pretty terminal UI for the interactive CLI demo (cli_demo.py).
rich>=13.0

# CrewAI + its native Google Gemini provider (agent_demo.py only).
crewai>=0.100
crewai[google-genai]

# Web search in cli_demo.py is provided through CrewAI's native MCP support
# (Agent(mcps=["https://connect.composio.dev/mcp"])). The Composio "connect" MCP
# endpoint needs no API key. Override the endpoint via COMPOSIO_MCP_URL if desired.
# If your CrewAI build packages MCP support as an extra, install it too:
#     crewai[mcp]

