# open-deep-research

**Repository Path**: tgrape_admin/open-deep-research

## Basic Information

- **Project Name**: open-deep-research
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-02-24
- **Last Updated**: 2025-03-07

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Open Deep Research

An Open-Source clone of Open AI's Deep Research experiment. Instead of using a fine-tuned version of o3, this method uses [Firecrawl's extract + search](https://firecrawl.dev/) with a reasoning model to deep research the web.

Check out the demo [here](https://x.com/nickscamara_/status/1886459999905521912)

![Open Deep Research Hero](public/open-deep-researched-pic.png)

## Features

- [Firecrawl](https://firecrawl.dev) Search + Extract
  - Feed realtime data to the AI via search
  - Extract structured data from multiple websites via extract
- [Next.js](https://nextjs.org) App Router
  - Advanced routing for seamless navigation and performance
  - React Server Components (RSCs) and Server Actions for server-side rendering and increased performance
- [AI SDK](https://sdk.vercel.ai/docs)
  - Unified API for generating text, structured objects, and tool calls with LLMs
  - Hooks for building dynamic chat and generative user interfaces
  - Supports OpenAI (default), Anthropic, Cohere, and other model providers
- [shadcn/ui](https://ui.shadcn.com)
  - Styling with [Tailwind CSS](https://tailwindcss.com)
  - Component primitives from [Radix UI](https://radix-ui.com) for accessibility and flexibility
- Data Persistence
  - [Vercel Postgres powered by Neon](https://vercel.com/storage/postgres) for saving chat history and user data
  - [Vercel Blob](https://vercel.com/storage/blob) for efficient file storage
- [NextAuth.js](https://github.com/nextauthjs/next-auth)
  - Simple and secure authentication

## Model Providers

This template ships with OpenAI `gpt-4o` as the default. However, with the [AI SDK](https://sdk.vercel.ai/docs), you can switch LLM providers to [OpenAI](https://openai.com), [Anthropic](https://anthropic.com), [Cohere](https://cohere.com/), and [many more](https://sdk.vercel.ai/providers/ai-sdk-providers) with just a few lines of code.

This repo is compatible with [OpenRouter](https://openrouter.ai/) and [OpenAI](https://openai.com/). To use OpenRouter, you need to set the `OPENROUTER_API_KEY` environment variable.

## Function Max Duration

By default, the function timeout is set to 300 seconds (5 minutes). If you're using Vercel's Hobby tier, you'll need to reduce this to 60 seconds. You can adjust this by changing the `MAX_DURATION` environment variable in your `.env` file:

```bash
MAX_DURATION=60
```

Learn more about it [here](https://vercel.com/docs/functions/configuring-functions/duration#duration-limits)

## Deploy Your Own

You can deploy your own version of the Next.js AI Chatbot to Vercel with one click:

[![Deploy with Vercel](https://vercel.com/button)](https://vercel.com/new/clone?repository-url=https%3A%2F%2Fgithub.com%2Fnickscamara%2Fopen-deep-research&env=AUTH_SECRET,OPENAI_API_KEY,OPENROUTER_API_KEY,FIRECRAWL_API_KEY,BLOB_READ_WRITE_TOKEN,POSTGRES_URL,UPSTASH_REDIS_REST_URL,UPSTASH_REDIS_REST_TOKEN,REASONING_MODEL,BYPASS_JSON_VALIDATION,TOGETHER_API_KEY,MAX_DURATION&envDescription=Learn%20more%20about%20how%20to%20get%20the%20API%20Keys%20for%20the%20application&envLink=https%3A%2F%2Fgithub.com%2Fvercel%2Fai-chatbot%2Fblob%2Fmain%2F.env.example&demo-title=AI%20Chatbot&demo-description=An%20Open-Source%20AI%20Chatbot%20Template%20Built%20With%20Next.js%20and%20the%20AI%20SDK%20by%20Vercel.&demo-url=https%3A%2F%2Fchat.vercel.ai&stores=[{%22type%22:%22postgres%22},{%22type%22:%22blob%22}])

## Running locally

You will need to use the environment variables [defined in `.env.example`](.env.example) to run Next.js AI Chatbot. It's recommended you use [Vercel Environment Variables](https://vercel.com/docs/projects/environment-variables) for this, but a `.env` file is all that is necessary.

> Note: You should not commit your `.env` file or it will expose secrets that will allow others to control access to your various OpenAI and authentication provider accounts.

1. Install Vercel CLI: `npm i -g vercel`
2. Link local instance with Vercel and GitHub accounts (creates `.vercel` directory): `vercel link`
3. Download your environment variables: `vercel env pull`

# 1. First install all dependencies
```bash
pnpm install
```

# 2. Then run database migrations
```bash
pnpm db:migrate
```

# 3. Run the app
```bash
pnpm dev
```

Your app template should now be running on [localhost:3000](http://localhost:3000/).


# Models dependencies

If you want to use a model other than the default, you will need to install the dependencies for that model.


TogetherAI's Deepseek:
```bash
pnpm add @ai-sdk/togetherai
```

Note: Maximum rate limit https://docs.together.ai/docs/rate-limits

## Reasoning Model Configuration

The application uses a separate model for reasoning tasks (like research analysis and structured outputs). This can be configured using the `REASONING_MODEL` environment variable.

### Available Options

| Provider | Models | Notes |
|----------|--------|-------|
| OpenAI | `gpt-4o`, `o1`, `o3-mini` | Native JSON schema support |
| TogetherAI | `deepseek-ai/DeepSeek-R1` | Requires `BYPASS_JSON_VALIDATION=true` |

### Important Notes

- Only certain OpenAI models (gpt-4o, o1, o3-mini) natively support structured JSON outputs
- Other models (deepseek-reasoner) can be used but may require disabling JSON schema validation
- When using models that don't support JSON schema:
  - Set `BYPASS_JSON_VALIDATION=true` in your .env file
  - This allows non-OpenAI models to be used for reasoning tasks
  - Note: Without JSON validation, the model responses may be less structured
- The reasoning model is used for tasks that require structured thinking and analysis, such as:
  - Research analysis
  - Document suggestions
  - Data extraction
  - Structured responses
- If no `REASONING_MODEL` is specified, it defaults to `o1-mini`
- If an invalid model is specified, it will fall back to `o1-mini`

### Usage

Add to your `.env` file:
```bash
# Choose one of: deepseek-reasoner, deepseek-ai/DeepSeek-R1
REASONING_MODEL=deepseek-ai/DeepSeek-R1

# Required when using models that don't support JSON schema (like deepseek-reasoner)
BYPASS_JSON_VALIDATION=true
```

The reasoning model is automatically used when the application needs structured outputs or complex analysis, regardless of which model the user has selected for general chat.