iflow-mcp_finance-llms-deep-research

# OpenProvHop Deep Research An AI-powered research assistant that performs iterative, deep research on any topic by combining web search, content analysis, and large language models. **🔬 Simple yet powerful research automation in Python** The goal is to provide the simplest implementation of a deep research agent that can refine its research direction over time and dive deep into any topic. Optimized for ease of use and understanding. ## Features - **🔄 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 research scope (breadth: 1-20, depth: 1-10) - **🔮 Smart Follow-up**: Generates follow-up questions to better understand research needs - **📊 Web Dashboard**: Beautiful web interface with real-time progress tracking and organized result tabs - **🔗 API Server**: REST API for integration with other applications - **🚀 Concurrent Processing**: Handles multiple searches and result processing in parallel - **🤖 Multiple AI Providers**: Support for NVIDIA, OpenAI, Fireworks AI, OpenRouter, and local models - **✨ Advanced Features**: - **Semantic Re-ranking**: Orders results by relevance using sentence transformers - **Smart Deduplication**: Removes near-duplicate content automatically - **Freshness Filtering**: Prioritizes recent information (configurable) - **Provenance Tracking**: Transparent source attribution with supporting snippets and confidence scores ## Quick Start ### 1. Installation ```bash git clone https://github.com/Finance-LLMs/deep-research-python.git cd deep-research-python pip install -r requirements.txt ``` ### 2. Configuration Create a `.env.local` file with your API keys: ```bash # Required: Web search and scraping FIRECRAWL_KEY="your_firecr…