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Langchain Deep Research Closedloop Technolog Awesome Deep Resear

ASecurity

Run LangChain Open Deep Research agent for iterative web research and comprehensive reports. Requires LLM API keys and search API (e.g., OPENAI_API_KEY, TAVILY_API_KEY).

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  • Added May 31, 2026
researchpythongobashgitapi

Works with

  • cli
  • api

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A96/100
  • mediumInstalls packages at runtime which could introduce malicious dependencies

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Scanned May 31, 2026

npx -y skills add majiayu000/claude-skill-registry --skill langchain-deep-research-closedloop-technolog-awesome-deep-resear --agent claude-code

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SKILL.md
---
name: langchain-deep-research
description: Run LangChain Open Deep Research agent for iterative web research and comprehensive reports. Requires LLM API keys and search API (e.g., OPENAI_API_KEY, TAVILY_API_KEY).
---

# LangChain Open Deep Research Skill

This skill utilizes the LangChain Open Deep Research framework to perform iterative web research with reflection and knowledge gap identification, producing comprehensive reports with citations.

## Setup

1. **Dependencies:** Requires the `open-deep-research` package and LangGraph.

    ```bash
    pip install open-deep-research langgraph-cli python-dotenv
    ```

2. **API Key Configuration:** Requires API keys for an LLM and a search provider.

    ```bash
    # Set up your API keys
    echo "# LLM Configuration" >> .env
    echo "OPENAI_API_KEY=your_openai_key" >> .env
    echo "# Search Configuration" >> .env
    echo "TAVILY_API_KEY=your_tavily_key" >> .env
    if [ -f .gitignore ] && ! grep -q ".env" .gitignore; then echo ".env" >> .gitignore; fi
    echo "API keys saved to .env."
    ```

## Usage

Use the `scripts/research.py` script to run a research task.

### Command

```bash
python3 scripts/research.py --query "<research_query>" [--max-iterations <N>]
```

### Parameters

* `--query` (Required): The research question or topic.
* `--max-iterations` (Optional): Maximum number of research iterations (default: 3).
* `--output` (Optional): Output file path for the final report (default: stdout).

### Example

```bash
python3 scripts/research.py --query "What are the latest developments in quantum computing error correction?" --max-iterations 4 --output report.md
```

## Output

The script outputs a comprehensive research report with:

* Iterative search findings
* Knowledge gap analysis
* Final synthesized report with citations
* Source list

## Features

* **Iterative Research**: Performs multiple search cycles, reflecting on gaps
* **Configurable Models**: Supports OpenAI, Anthropic, Ollama, and other LLM providers
* **Multiple Search Engines**: Tavily (default), Brave, DuckDuckGo, SerpAPI
* **Citation Tracking**: All findings include source references

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