Deep Research Agent is an autonomous AI system that takes a natural-language research question and returns a structured, cited markdown report — without manual searching, reading, or summarizing. Powered by Google Gemini and DuckDuckGo, it runs a multi-step pipeline: planning sub-queries, fetching credible sources, detecting knowledge gaps, and synthesizing findings into a professional report with numbered citations.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/IconDean/research-agent/llms.txt
Use this file to discover all available pages before exploring further.
Quickstart
Set up the backend and run your first research query in under five minutes.
Configuration
Configure API keys, model selection, and agent constraints.
Research Pipeline
Understand the five-stage agentic loop from planning to report synthesis.
REST API
Integrate the research agent into your own applications via HTTP.
What it does
The agent follows a five-stage research pipeline for every question:Plan
Gemini decomposes the question into prioritized sub-queries and selects a search strategy (breadth-first or deep-dive).
First-round research
The agent searches DuckDuckGo and fetches the top pages, scoring each source for credibility before reading it.
Gap detection
Gemini reviews initial findings and identifies unanswered aspects, generating targeted follow-up queries.
Second-round research
The agent searches and fetches again — focused on filling the identified gaps.
Two ways to use it
CLI
Run
python main.py "your question" from any terminal. Progress prints to stderr; the report prints to stdout.Web UI
Start the FastAPI backend and the React frontend to get a live activity log and rendered report in your browser.
Key capabilities
Credibility Scoring
Sources are scored 0–1 based on domain authority, recency signals, and relevance. Low-scoring sources are blocked automatically.
Report Format
Every report follows a consistent structure: Methodology, Executive Summary, Main Findings, Conflicting Information, and Sources.
Python Modules
Use
AgentRunner directly in your Python scripts for programmatic access to the full research pipeline.Error Handling
Failed searches and fetches are logged and skipped — the agent continues and still produces a report.