#1111th of 18 in Agent backends
data-enrichment
LangGraph agent that researches the web to fill your JSON schema
- Stars
- 258
- License
- MIT
- Last commit
- Oct 2026
- Language
- Jupyter Notebook
Overview
A Python LangGraph graph that takes a research topic and a JSON extraction_schema, searches with Tavily, reads pages, fills the schema and checks the result for completeness before returning. The model is a provider/model string (default claude-3-5-sonnet-20240620, OpenAI supported), and it runs in LangGraph Studio or through the LangGraph API. For teams building lead or dataset enrichment pipelines.
Who it is for: Teams building lead or dataset enrichment pipelines
Strengths
- Schema-driven output: change the JSON schema, not the code, to extract different fields
- Includes a validation step before returning results
- Unit tests in CI; opens in Studio
Weaknesses
- Default model string is dated (claude-3-5-sonnet-20240620)
- Tavily is the only search tool
- No batch runner; one topic per invocation
- No UI beyond Studio
What it needs
- Jupyter Notebook, langgraph, anthropic, openai
- Needs anthropic-or-openai-api-key, tavily-api-key, langgraph-cli
- GitHub template
- env example file
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