dzhng/deep-research
Deep Research
This project is an AI research tool designed for autonomous web information gathering and automated topic research. It utilizes agent orchestration to combine search engines and web scraping, enabling the system to discover detailed information and build a comprehensive understanding of complex subjects without manual step-by-step guidance.
The tool employs an iterative research execution model that recursively generates targeted search queries and refines directions based on previous results. It includes a feedback loop that compares current findings against initial objectives to identify knowledge gaps, while providing parameters to control the breadth and depth of the exploration.
The system aggregates discoveries and references into structured research reports through automated synthesis. It supports concurrent task execution to process multiple search and scraping operations in parallel and allows for integration with various language model providers via custom API endpoints.
The application is provided as a containerized package to ensure consistent execution across different environments.
Features
- Recursive Research Agents - Implements a recursive exploration process that generates and follows search queries to deeply investigate complex subjects.
- Autonomous Web Agents - Employs autonomous web agents to perform recursive searching and scraping without manual guidance.
- Findings Aggregation - Gathers and organizes research discoveries and references into structured documents for improved readability.
- AI Research Tools - Provides a specialized tool for automated AI-driven research and information gathering.
- Feedback Loops - Implements a feedback loop that compares findings against objectives to identify and fill knowledge gaps.
- Targeted Query Generation - Uses LLMs to dynamically generate precise search queries based on research objectives and gathered findings.
- Multi-Agent Task Orchestrators - Orchestrates multi-step research workflows by integrating LLMs with search engines and scraping tools.
- Search Query Recursion - Dynamically generates new search terms from gathered data to deepen the research direction across iterations.
- Report Generation Tools - Transforms raw research discoveries and web data into structured, formatted final documents.
- Search and Research Agents - Utilizes autonomous AI agents to perform deep research through iterative web searching and data scraping.
- Research Synthesis - Uses large language models to synthesize raw scraped web content into coherent, structured research findings.
- Automated Report Generators - Automatically generates structured, citation-backed research reports from extracted learnings.
- Model Provider Integrations - Provides unified interfaces for configuring and connecting multiple language model providers via API endpoints.
- Scope Controls - Allows users to constrain the research process by limiting the number of recursive layers and total queries.
- LLM Provider Integrations - Supports custom API endpoints and identifiers for flexible integration with various LLM providers.
- Concurrent Query Processing - Processes multiple search and scraping queries concurrently to accelerate the information gathering phase.
- Crawl Depth Limiters - Restricts the number of recursive hops during web traversal to manage resource usage and prevent infinite loops.
- Concurrent Task Runners - Executes multiple search and web scraping operations in parallel to reduce total research latency.
- End-User Applications - AI-powered research assistant for iterative, deep research on any topic.
