deep-research-langchain

name	deep-research-langchain
description	Run LangChain Open Deep Research or LangGraph-based iterative research workflows with configurable retrieval, reflection, and server-backed execution. Use when a benchmark or task needs inspectable graph orchestration rather than a single hosted research API.

LangChain Open Deep Research

Use this skill when you need an inspectable graph workflow with iterative research, reflection, and configurable retrieval.

Environment

op run --env-file .env.climbhill -- python .agents/skills/deep-research-langchain/scripts/research.py \
  --query "AI for Science agents: current systems and evidence" \
  --max-iterations 2

Common 1Password-backed variables:

• OPENAI_API_KEY or ANTHROPIC_API_KEY
• TAVILY_API_KEY

Cost Controls

• Keep --max-iterations at 1 or 2 for benchmark tasks.
• Use a low-cost model for reflection and summarization.
• Skip this benchmark when the local LangGraph server is not running.

Source Link

• https://github.com/langchain-ai/open_deep_research