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advanced AI-powered research assistant that creates comprehensive, well-researched blog posts on any topic by combining web search, content analysis, and automated writing capabilities.","maintainers":[{"name":"subeshb1","email":"subeshb1@gmail.com"}],"readme":"# Deep Research Agent\n\nAn advanced AI-powered research assistant that creates comprehensive, well-researched blog posts on any topic by combining web search, content analysis, and automated writing capabilities.\n\n## Features\n\n- 🔍 Intelligent web searching across multiple sources\n- 📝 Automated content extraction and analysis\n- ✍️ Well-structured blog post generation\n- 📚 Proper citation and source attribution\n- 💾 Organized research storage\n\n## Prerequisites\n\nBefore you begin, ensure you have the following installed:\n- Node.js (v16 or higher)\n- pnpm (recommended) or npm\n- Ollama (if using default LLM provider)\n\n## Installation\n\n1. Clone the repository:\n```bash\ngit clone <repository-url>\ncd deep-research-agent\n```\n\n2. Install dependencies:\n```bash\npnpm install\n# or\nnpm install\n```\n\n## Environment Variables\n\nThe agent uses environment variables for LLM configuration. Create a `.env` file in the root directory:\n\n```env\n# LLM Provider Configuration (Optional)\nLLM_PROVIDER=ollama    # Options: 'ollama' (default) or 'bedrock'\nLLM_MODEL_ID=llama3.2  # Default model for Ollama\n\n# If using AWS Bedrock (only needed if LLM_PROVIDER=bedrock)\nAWS_ACCESS_KEY_ID=your_aws_access_key\nAWS_SECRET_ACCESS_KEY=your_aws_secret_key\nAWS_REGION=us-west-2\n```\n\nBy default, the agent uses Ollama with the llama3.2 model. Make sure you have Ollama installed and the model downloaded if using the default configuration.\n\n## Usage\n\nRun the agent with a research query:\n\n```bash\npnpm start -- \"your research query\"\n# or\nnpm start -- \"your research query\"\n```\n\nExamples:\n```bash\npnpm start -- \"What are the latest developments in quantum computing?\"\npnpm start -- \"What is the current state of renewable energy?\"\n```\n\n## How It Works\n\nThe Deep Research Agent follows a sophisticated process to create high-quality blog posts:\n\n1. **Web Search**: \n   - Searches for the most relevant and authoritative sources\n   - Identifies key resources and references\n\n2. **Content Analysis**:\n   - Scrapes and analyzes content from selected sources\n   - Extracts important information and insights\n   - Maintains source attribution\n\n3. **Content Generation**:\n   - Synthesizes information from multiple sources\n   - Creates well-structured blog posts\n   - Includes proper citations and references\n\n4. **Output**:\n   - Saves the generated blog post in the `research` directory\n   - Provides progress updates during the research process\n   - Shows token usage statistics upon completion\n\n## Output Structure\n\nThe agent creates a `research` directory containing:\n- Generated blog post in markdown format\n- Source attribution and references\n- Metadata about the research process\n\n## Notes\n\n- The research process may take several minutes depending on the topic complexity\n- Internet connection is required for web search and content analysis\n- The quality of results depends on the availability of reliable sources\n- Token usage is tracked and displayed after completion\n\n## License\n\nMIT\n","readmeFilename":"README.md"}