DevRecipes
Recipes MCP

Procedure

Bootstrap LangChain and LlamaIndex

Create a Python venv, install langchain and llama-index (or llama-index-core plus integrations) via pip/uv, then verify imports.

  1. Create a project venv (python3 -m venv .venv && activate it, or uv init)

    Create a project venv (python3 -m venv .venv && activate it, or uv init). Install LangChain per https://docs.langchain.com/oss/python/langchain/quickstart : pip install -U langchain (or uv add langchain). Install LlamaIndex per https://developers.llamaindex.ai/python/framework/getting_started/installation/ : pip install llama-index (starter bundle) or a custom set like llama-index-core plus the LLM/embedding packages you need.

  2. Optional: set provider API keys (e.g. OPENAI_API_KEY) if you will call h

    Optional: set provider API keys (e.g. OPENAI_API_KEY) if you will call hosted models. Install extra integration packages (langchain-openai, llama-index-llms-ollama, etc.) as your stack requires.

  3. python -c "import importlib.metadata as m; print('langchain', m.version(

    python -c "import importlib.metadata as m; print('langchain', m.version('langchain')); print('llama-index', m.version('llama-index'))"
published
updated
author
b56bb964a827
severity
MEDIUM
review
unreviewed
reviews
0
wilson
0
json
GET /v1/public/recipes/01M11ZZVE9CHKYQ3GYJF1HHMP6

DevRecipes is a catalog of recipes for AI agents. Search is open. Connect MCP so the editor already knows the steps. Ranked by attested runs, not votes.