Research Orchestration

🚀 Research Orchestration Service

The Research Orchestration Service is an advanced system based on Cloudflare Workers. It aims to automate and optimize the research process by integrating various third - party APIs and tools. This service utilizes big data analysis, machine learning, and natural language processing technologies to help users efficiently collect, organize, and analyze information.

🚀 Quick Start

1. Install and configure the necessary API keys.
2. Deploy the service to the Cloudflare Workers platform.
3. Call the provided API interfaces to perform research tasks.

✨ Features

Core Features

• Multi - source Data Aggregation: Retrieve relevant information from multiple sources, including internet searches, academic databases, news media, etc.
• Intelligent Tool Orchestration: Automatically select and invoke the most suitable combination of tools for the current task.
• Context - aware Processing: Dynamically adjust search strategies and analysis methods based on the research topic and objectives.
• Result Optimization and Presentation: Organize, analyze, and present the collected information in a user - friendly format.

Advanced Features

Targeted Follow - up Queries

The system generates follow - up queries highly targeted at specific information gaps. These queries:

• Focus specifically on the missing information.
• Use precise terms related to the identified gaps.
• Avoid repeating the information already obtained.
• Include explanations for the missing aspects.

Intelligent Tool Reuse

Unlike traditional systems, this system allows tools to be reused in new contexts:

• Exclude previously used tools in the initial query.
• Subsequent queries can reuse tools to handle new aspects.
• Prevent consecutive reuse of the same toolset.
• Ensure comprehensive coverage of the topic.

Metadata - rich Execution

Tool execution includes rich context information:

• Iteration number.
• Original and current queries.
• Follow - up query indicators.
• Extracted URLs and media IDs.

📦 Installation

Prerequisite Environment Variables

# Core API Keys
BRAVE_API_KEY=your_brave_api_key
TAVILY_API_KEY=your_tavily_api_key
GITHUB_TOKEN=your_github_token
FIRE_CRAWL_API_KEY=your_fire_crawl_api_key
NEWS_API_KEY=your_news_api_key
PATENTSVIEW_API_KEY=your_patentsview_api_key

# LLM API Keys
OPENAI_API_KEY=your_openai_api_key
GROQ_API_KEY=your_groq_api_key

# Cloudflare Resources
SHARED_SECRET=your_shared_secret     # For API authentication
RESEARCH_CACHE=your_kv_namespace     # For result caching

Installation Steps

1. Clone the repository:

   git clone https://github.com/yourusername/research-orchestration-service.git
   cd research-orchestration-service
   

2. Install dependencies:

   npm install
   

3. Configure environment variables:

   cp .env.example .env
   # Edit the .env file and fill in your API keys
   

4. Deploy to Cloudflare Workers:

   wrangler publish
   

💻 Usage Examples

Basic Usage

const response = await fetch('/api/research', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    query: "Recent trends in artificial intelligence development",
    options: {
      depth: 3,
      tools: ['web_search', 'academic_retrieval', 'news_aggregation']
    }
  })
});

const result = await response.json();

📚 Documentation

Technical Architecture

The service adopts a modular design and mainly consists of the following parts:

1. Request Processing Module

Responsible for receiving user query requests, parsing them, and generating a preliminary research plan.

2. Tool Orchestrator

Selects the appropriate combination of tools based on the research topic and objectives and coordinates their execution order.

3. Data Collection Module

Retrieves relevant information from multiple data sources, such as internet searches and academic databases.

4. Analysis and Aggregation Module

Cleans, analyzes, and aggregates the collected information to extract key information.

5. Result Generator

Generates the final research report based on the analysis results and presents it to the user in multiple formats.

Error Handling

The service implements comprehensive error handling:

• Automatically retry temporary failures.
• Have backup strategies for tool failures.
• Provide detailed error reports.
• Perform request validation.

Future Improvement Directions

• [ ] Add support for more professional research tools.
• [ ] Implement advanced caching strategies.
• [ ] Enhance natural language processing capabilities.
• [ ] Support domain - specific research workflows.
• [ ] Improve source verification and fact - checking.
• [ ] Support output in multiple result formats.

📄 License

This project is licensed under the MIT License.

📞 Contact

For more information, please visit our official website or contact us via email.