open-deep-research

Open Deep Research is a fully open-source autonomous research agent built on LangGraph. This is a fork of the original open_deep_research by LangChain AI. Give it any topic or question and it will scope the research (optionally asking clarifying questions), spin up parallel sub-agents to search the web, and synthesize findings into a well-structured, cited report.

Example prompts:

• "What are the latest developments in fusion energy?"
• "Compare the top vector database providers for production use"
• "Write a competitive analysis of the API management market"
• "Summarize the current state of AI regulation in the EU"

Configuration

All settings are optional — sensible defaults are provided. Configure via deployment inputs:

Input	Default	Description
TAVILY_API_KEY	—	Required when SEARCH_API=tavily (default)
SEARCH_API	tavily	Search backend: tavily, openai, anthropic, none
RESEARCH_MODEL	openai:gpt-4.1	Model used by research sub-agents
FINAL_REPORT_MODEL	openai:gpt-4.1	Model that writes the final report
SUMMARIZATION_MODEL	openai:gpt-4.1-mini	Model for summarizing raw search results
COMPRESSION_MODEL	openai:gpt-4.1	Model for compressing sub-agent findings
MAX_CONCURRENT_RESEARCH_UNITS	5	Number of parallel sub-agents (1–20)
ALLOW_CLARIFICATION	true	Ask a clarifying question before starting

Getting a Tavily API Key

Tavily is the default search backend. To get an API key:

1. Go to app.tavily.com and create a free account
2. After signing in, navigate to API Keys in the dashboard
3. Copy your API key and set it as the TAVILY_API_KEY deployment input

The free tier includes 1,000 searches/month. For higher usage, see tavily.com/pricing.

Tip: If you don't want to use Tavily, set SEARCH_API to openai or anthropic to use those providers' built-in search tools instead — no Tavily key needed.

Limitations

• Research quality depends on the configured search API and model; Tavily + GPT-4.1 is the recommended default
• High concurrency settings may hit provider rate limits