An Open-Source Alternative to OpenAI's Deep Research: Open Deep Research
I want to mention Nicolas Silberstein Camara for his great action against Openai Deep Research. Here is the details and tutorial.
Open-Source Deep Research: Overview
Open Deep Research is an open-source clone of OpenAI's Deep Research experiment. Unlike OpenAI's proprietary model, this project leverages Firecrawl’s extract + search technology combined with a reasoning model to conduct deep research across the web.
Open-Source Deep Research: Key Features
-
Firecrawl Extract + Search
- Feeds real-time data to the AI via search.
- Extracts structured data from multiple websites.
-
Next.js App Router
- Uses React Server Components (RSCs) for efficient rendering.
- Supports server-side rendering for performance optimization.
-
AI SDK Integration
- Supports multiple LLM providers:
- OpenAI (default: gpt-4o)
- Anthropic, Cohere, DeepSeek, and more.
-
Advanced UI Components
- Styled with Tailwind CSS.
- Uses shadcn/ui with Radix UI for flexible component handling.
-
Data Persistence
- Uses Vercel Postgres (Neon) for chat history and user data.
- Stores files efficiently with Vercel Blob.
-
Authentication System
- Implemented using NextAuth.js for secure user login.
Open Deep Research: Installation Guide (Run Locally)
1. Clone the Repository
Open your terminal and run:
git clone https://github.com/nickscamara/open-deep-research.git
cd open-deep-research
2. Install Dependencies
Install pnpm if not installed:
npm install -g pnpm
Then install all dependencies:
pnpm install
3. Set Up Environment Variables
You'll need to define environment variables in .env using the .env.example file as a reference.
To automatically configure environment variables:
vercel env pull
Or manually create a .env file and include:
OPENAI_API_KEY=your_openai_api_key
FIRECRAWL_API_KEY=your_firecrawl_api_key
AUTH_SECRET=your_auth_secret
⚠️ Do not commit the .env file to avoid exposing sensitive API keys.
4. Run Database Migrations
pnpm db:migrate
5. Start the Application
pnpm dev
Your app should now be running at:
🔗 http://localhost:3000
Alternative Deployment: One-Click Deploy to Vercel
If you prefer not to run it locally, you can deploy to Vercel in one click:
Model Providers
By default, the project uses OpenAI's GPT-4o.
However, it supports multiple LLM providers via Vercel's AI SDK, including:
- Anthropic (Claude)
- Cohere
- DeepSeek
- TogetherAI
- OpenRouter
Switching Models
Modify the .env file:
REASONING_MODEL=deepseek-reasoner
BYPASS_JSON_VALIDATION=true
Adding Model Dependencies
If you want to use a model other than GPT-4o, install the respective dependency.
DeepSeek AI Model
pnpm add @ai-sdk/deepseek
TogetherAI Model
pnpm add @ai-sdk/togetherai
🚨 Check TogetherAI rate limits:
🔗 Rate Limit Info
Reasoning Model Configuration
This project includes a reasoning model for structured outputs such as research analysis, data extraction, and document summarization.
| Provider | Models Supported | Notes |
|---|---|---|
| OpenAI |
gpt-4o, o1, o3-mini
|
Native JSON support |
| TogetherAI | deepseek-ai/DeepSeek-R1 |
Requires BYPASS_JSON_VALIDATION=true
|
| DeepSeek | deepseek-reasoner |
Requires BYPASS_JSON_VALIDATION=true
|
Key Notes
- GPT-4o, o1, o3-mini → Natively support structured JSON outputs.
-
DeepSeek & TogetherAI → Need
BYPASS_JSON_VALIDATION=true. -
If no model is set, it defaults to
o1-mini. -
If an invalid model is chosen, it falls back to
o1-mini.
To use DeepSeek as the reasoning model, add this to .env:
REASONING_MODEL=deepseek-reasoner
BYPASS_JSON_VALIDATION=true
Open-Source Deep Research: Conclusion
Open Deep Research by Nicolas Silberstein Camara is a powerful, open-source alternative to OpenAI’s Deep Research.
It allows users to autonomously research the web, retrieve structured data, and leverage multiple AI models.
By following the steps above, you can:
✅ Run it locally
✅ Deploy it to Vercel
✅ Customize model providers
For the latest updates, visit the GitHub Repository.
Developer: Nicolas Silberstein Camara
GitHub Repository: Github
Demo: Live Demo
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