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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
An agentic company research tool powered by LangGraph and Tavily that conducts deep diligence on companies using a multi-agent framework. It leverages OpenRouter on the backend for rapid inference with any leading model.
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Today
— stars today
This week
+5 stars this week
This month
+21 stars this month
Momentum
50.0
growth rate 0.22%/day
# Company Research Agent
An agentic research tool that turns a company name into a structured, source-backed briefing. The FastAPI backend coordinates specialized research and synthesis steps; the React interface tracks the job and lets you export the finished report as a PDF.
## What it does
- Researches a company’s business, industry, financial context, and recent news.
- Uses Tavily search and relevance scoring to find and curate source material.
- Runs on any model available through [OpenRouter](https://openrouter.ai) — pick it from the in-app Settings — or on direct OpenAI/Gemini keys.
- Streams research progress to the browser and supports PDF export.
- Optionally persists jobs and reports in MongoDB.
## Architecture
```text
React + Vite UI
│ POST /research
▼
FastAPI application
│
▼
Research graph
analyzers → collector → curator → briefing → editor
│
├── Tavily: research and relevance scoring
└── LLM: query generation, briefings, final editing
(OpenRouter model chosen in Settings, or OpenAI/Gemini directly)
```
The UI connects to the API with `VITE_API_URL` and receives incremental updates from `GET /research/{job_id}/stream`.
## Prerequisites
- Python 3.11 or later
- Node.js 18 or later
- An [OpenRouter API key](https://openrouter.ai/keys) — set in the backend `.env` or pasted into the app's Settings (alternatively, an OpenAI key, plus an optional Gemini key)
- A Tavily API key entered in the app for each research session (or a backend fallback key)
- A Google Maps API key only if you want location autocomplete
- MongoDB only if you want persistent jobs and reports
## Run locally
1. Create a virtual environment and install the backend dependencies:
```bash
uv venv .venv
uv pip install -r requirements.txt
```
If you do not use `uv`, create the environment with `python -m venv .venv` and install with `pip install -r requirements.txt`.
2. Create `.env` from the example and set the required backend keys:
```bash
cp .env.example .env
```
```env
# Recommended: one key for every model (or paste a key in the app's Settings instead)
OPENROUTER_API_KEY=your_openrouter_key
# Optional default model; users can still pick another in Settings
# OPENROUTER_MODEL=anthropic/claude-sonnet-5.5
# Alternative to OpenRouter: direct provider keys
# OPENAI_API_KEY=your_openai_key
# GEMINI_API_KEY=your_gemini_key
# Optional fallback when no per-session Tavily key is supplied
TAVILY_API_KEY=your_tavily_key
# MONGODB_URI=optional_mongodb_connection_string
```
3. Configure the frontend:
```bash
cp ui/.env.development.example ui/.env.development.local
cd ui && npm install && cd ..
```
Set `VITE_API_URL=http://localhost:8000` in `ui/.env.development.local`. Add `VITE_GOOGLE_MAPS_API_KEY` only when location autocomplete is needed.
4. Start the API in one terminal:
```bash
.venv/bin/uvicorn application:app --reload --port 8000
```
5. Start the UI in a second terminal:
```bash
cd ui
npm run dev
```
Open [http://localhost:5174](http://localhost:5174). The API is available at [http://localhost:8000/docs](http://localhost:8000/docs).
Alternatively, `./setup.sh` installs everything, asks for your Tavily and OpenRouter keys, and writes `.env` for you.
### Choosing a model
Click the model button in the top-right corner to open **Settings**. There you can paste an OpenRouter key (stored only in your browser and sent with each research request) and search or filter the full OpenRouter catalog by provider. The selected model is used for every step of the research pipeline. If no OpenRouter key is available, the backend falls back to `OPENAI_API_KEY` (with Gemini for briefings when `GEMINI_API_KEY` is set).
## Docker
After creating the root `.env` and `ui/.env.development.local` files, run:
```bash
docker compose up --Excerpt of 6,189 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:bf5e3dca8d0f2b21, topic:agents, topic:multi-agent-systems, readme:ai agents