Production-grade AI agent systems built from scratch in JavaScript, covering agent fundamentals, LangGraph workflows, multi-agent collaboration, RAG, vector databases, and AI productization.
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HiteshNathbuva / repository
Production-grade Multi-Agent AI Research Platform built with FastAPI, OpenRouter, and modular AI agents.
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Build intelligent research workflows using multiple AI agents, FastAPI, and OpenRouter.
AutoResearchAI is a production-style Multi-Agent AI Research Platform designed to automate the complete research workflow.
Instead of relying on a single AI response, the system divides research into specialized AI agents that collaborate to produce higher-quality, structured, and verifiable results.
The project follows modern AI engineering practices including modular architecture, workflow orchestration, session management, REST APIs, and scalable backend design.
User
│
▼
FastAPI REST API
│
▼
Workflow Orchestrator
│
┌───────────────┼───────────────┐
▼ ▼ ▼
Planner Agent Research Agent Session Manager
│
▼
Verification Agent
│
▼
Writer Agent
│
▼
Professional Report
User Query
│
▼
Planner Agent (Hidden)
│
▼
Research Agent
│
▼
Research Results
│
├──────────────► AI Fact Check
│ │
│ ▼
│ Verifier Agent
│ │
│ ▼
│ Verified Report
│
└──────────────► Generate Report
│
▼
Writer Agent
│
▼
Professional Report
| Category | Technologies |
|---|---|
| Language | Python |
| Backend | FastAPI |
| AI Provider | OpenRouter |
| AI Model | OpenRouter Auto |
| API Style | REST API |
| Configuration | Pydantic Settings |
| Validation | Pydantic |
| Server | Uvicorn |
| Version Control | Git + GitHub |
AutoResearchAI/
backend/
│
├── agents/
├── api/
├── core/
├── prompts/
├── schemas/
├── utils/
│
├── main.py
│
tests/
│
requirements.txt
README.md
| Method | Endpoint | Description |
|---|---|---|
| GET | / | Health Check |
| POST | /research | Generate Research |
| POST | /verify/{session_id} | AI Fact Check |
| POST | /report/{session_id} | Generate Professional Report |
git clone https://github.com/hiteshnathbuva/AutoResearchAI.git
cd AutoResearchAI
python -m venv .venv
Activate environment
Windows
.venv\Scripts\activate
Linux / macOS
source .venv/bin/activate
pip install -r requirements.txt
Create a .env file in the project root.
OPENROUTER_API_KEY=your_api_key_here
python -m uvicorn backend.main:app --reload
Open
http://127.0.0.1:8000/docs
Contributions, issues, and feature requests are welcome.
Feel free to fork the project and submit pull requests.
This project is licensed under the MIT License.
Hitesh Nathbuva
GitHub
https://github.com/hiteshnathbuva
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