This is a fork of Open Deep Research by @dzhng, enhanced with REST API implementation and integrated into the CodeGuide platform.

An AI-powered research assistant that performs iterative, deep research on any topic by combining search engines, web scraping, and large language models. This enhanced version provides a REST API interface and is integrated into the CodeGuide platform.

The core functionality remains true to the original project's goal of providing a simple implementation of a deep research agent - one that can refine its research direction overtime and deep dive into a topic.

This service is available to all CodeGuide members at app.codeguide.dev. You'll have access to the following features:

• User-friendly interface for conducting research
• Real-time results and generated reports
• Integrations with other CodeGuide features (coming soon)

flowchart TB
    subgraph Input
        Q[User Query]
        B[Breadth Parameter]
        D[Depth Parameter]
    end

    DR[Deep Research] -->
    SQ[SERP Queries] -->
    PR[Process Results]

    subgraph Results[Results]
        direction TB
        NL((Learnings))
        ND((Directions))
    end

    PR --> NL
    PR --> ND

    DP{depth > 0?}

    RD["Next Direction:
    - Prior Goals
    - New Questions
    - Learnings"]

    MR[Markdown Report]

    %% Main Flow
    Q & B & D --> DR

    %% Results to Decision
    NL & ND --> DP

    %% Circular Flow
    DP -->|Yes| RD
    RD -->|New Context| DR

    %% Final Output
    DP -->|No| MR

    %% Styling
    classDef input fill:#7bed9f,stroke:#2ed573,color:black
    classDef process fill:#70a1ff,stroke:#1e90ff,color:black
    classDef recursive fill:#ffa502,stroke:#ff7f50,color:black
    classDef output fill:#ff4757,stroke:#ff6b81,color:black
    classDef results fill:#a8e6cf,stroke:#3b7a57,color:black

    class Q,B,D input
    class DR,SQ,PR process
    class DP,RD recursive
    class MR output
    class NL,ND results

• REST API Implementation: Full REST API support with comprehensive documentation
• CodeGuide Integration: Seamlessly integrated with the CodeGuide platform
• API Documentation: Interactive Swagger/OpenAPI documentation
• Iterative Research: Performs deep research by iteratively generating search queries, processing results, and diving deeper based on findings
• Intelligent Query Generation: Uses LLMs to generate targeted search queries based on research goals and previous findings
• Depth & Breadth Control: Configurable parameters to control how wide (breadth) and deep (depth) the research goes
• Smart Follow-up: Generates follow-up questions to better understand research needs
• Comprehensive Reports: Produces detailed markdown reports with findings and sources
• Concurrent Processing: Handles multiple searches and result processing in parallel for efficiency

You can access the API locally or by self-hosting it.

All API requests require authentication that will be defined in the .env file.

# .env
API_KEY="your_development_api_key"

The research process consists of three main steps:

1. Generate Clarifying Questions

# Step 1: Generate questions to better understand the research direction
curl -X POST http://localhost:3000/api/research/questions \
  -H "x-api-key: API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Your research query",
    "numQuestions": 3
  }'

1. Perform Deep Research

# Step 2: Conduct the research with your answers to the clarifying questions
curl -X POST http://localhost:3000/api/research \
  -H "x-api-key: API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Your research query",
    "breadth": 6,
    "depth": 3,
    "questionAnswers": [
      {
        "question": "Question from step 1",
        "answer": "Your answer to the question"
      }
    ]
  }'

1. Generate Final Report

# Step 3: Generate a comprehensive report using the research results
curl -X POST http://localhost:3000/api/report \
  -H "x-api-key: API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Original research query",
    "learnings": ["Learning 1", "Learning 2"],  # From research response
    "visitedUrls": ["url1", "url2"]            # From research response
  }'

The flow allows for an iterative and thorough research process:

1. First, generate clarifying questions to better understand the research needs
2. Use these questions and your answers to guide the deep research process
3. Finally, generate a comprehensive report based on the research findings

1. Clone the repository
2. Install dependencies:

npm install

1. Set up environment variables in a .env file:

FIRECRAWL_KEY="your_firecrawl_key"
# If you want to use your self-hosted Firecrawl, add the following below:
# FIRECRAWL_BASE_URL="http://localhost:3002"

OPENAI_KEY="your_openai_key"

# API Configuration
PORT=3000
API_KEY="your_development_api_key"

Start the API server:

npm run dev

The API will be available at http://localhost:3000 with documentation at http://localhost:3000/api-docs.

MIT License - feel free to use and modify as needed.

This project is a fork of Open Deep Research by @dzhng. We've extended it with REST API capabilities and integrated it into the CodeGuide platform while maintaining the core functionality of the original project.