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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.
Agentic RAG for any scenario. Customize sources, depth, and width
| Date | Stars |
|---|---|
| 2026-07-31 | 291 |
| 2026-08-06 | 291 |
Today
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growth rate 0.00%/day
<p align="center">
<img src="chat_interface/public/title3.svg" alt="Open Deep Wide Research" />
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<h1 align="center">Open Deep Wide Research</h1>
<p align="center">
<a href="https://go.deepwideresearch.com/4o5mSMy" target="_blank">
<img src="https://img.shields.io/badge/Web-deepwideresearch.com-39BC66?style=flat&logo=google-chrome&logoColor=white" alt="Homepage" height="22" />
</a>
<a href="https://x.com/deepwiderag" target="_blank">
<img src="https://img.shields.io/badge/X-@deepwiderag-000000?style=flat&logo=x&logoColor=white" alt="X (Twitter)" height="22" />
</a>
<a href="https://discord.gg/Dt5sh4DmZk" target="_blank">
<img src="https://img.shields.io/badge/Discord-Join-5865F2?style=flat&logo=discord&logoColor=white" alt="Discord" height="22" />
</a>
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<img src="https://img.shields.io/badge/[email protected]?style=flat&logo=gmail&logoColor=white" alt="Support" height="22" />
</a>
</p>
<p align="center">
Agentic RAG for any scenario<br>Customize sources, depth, and width
</p>
<p align="center">
<img src="chat_interface/public/chat_interface.png" alt="Deep & Wide Research Chat Interface" />
</p>
## Why Do You Need Open Deep Wide Research?
In 2025, we observed 2 critical trends reshaping the Retrieval-Augmented Generation (RAG) tech stacks:
1. Traditional, Rigid, pipeline-driven RAG is giving way to more dynamic agentic RAG systems.
2. The emergence of MCP is dramatically lowering the complexity of developing enterprise level Agentic RAG.
However, a core pain point remains:
1. **Developers still struggle to balance response quality, speed, and cost, as most agentic solutions offer a rigid, one-size-fits-all approach.**
Based on these trends and the core pain point, the market needs a single, open-source RAG agent that is MCP-compatible and offers granular control over performance, scope, and cost.
We built **Open Deep Wide Research** to be that solution, providing one agent for all RAG scenarios. It gives you granular control over the core dimensions of agentic research:
* **Sources**: Connect custom data sources, from internal knowledge bases to specialized APIs.
* **Deep**: Controls response time and reasoning depth.
* **Wide**: Controls information breadth across your selected sources.
The "Deep × Wide" coordinate system also transparently predicts the cost of each response, giving you full budget control.
**Example Scenarios:**
<table>
<thead>
<tr>
<th align="left"><sub>User Story</sub></th>
<th align="left"><sub>Settings</sub></th>
<th align="left"><sub>Example Query</sub></th>
<th align="center"><sub>Time</sub></th>
<th align="center"><sub>Cost</sub></th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><sub><b>Customer Service Bot</b></sub></td>
<td align="left"><sub>Deep: <code>███░░░░░░░░░</code> 25%<br/>Wide: <code>███░░░░░░░░░</code> 25%</sub></td>
<td align="left"><sub>"What glasses do you provide?"</sub></td>
<td align="center"><sub>~10s</sub></td>
<td align="center"><sub>~$0.01</sub></td>
</tr>
<tr>
<td align="left"><sub><b>Market Research</b></sub></td>
<td align="left"><sub>Deep: <code>███░░░░░░░░░</code> 25%<br/>Wide: <code>████████████</code> 100%</sub></td>
<td align="left"><sub>"100 Notion and Airtable alternatives"</sub></td>
<td align="center"><sub>~2-3min</sub></td>
<td align="center"><sub>~$0.10</sub></td>
</tr>
<tr>
<td align="left"><sub><b>Enterprise Analytics</b></sub></td>
<td align="left"><sub>Deep: <code>████████████</code> 100%<br/>Wide: <code>████████████</code> 100%</sub></td>
<td align="left"><sub>"What was the ROI of our latest marketing campaign?"</sub></td>
<td align="center"><sub>~5min</sub></td>
<td align="center"><sub>~$1.00</sub></td>
</tr>
</tbody>
</table>
> If this mission resonates with you, please give us a star ⭐ and fork it! 🤞
## Features
- **Deep × Wide Control** – Tune the depth of reasoning and breadth of information sources to perfectly match any RAG sceExcerpt of 10,424 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4702d4ba0ea9bc0f, llm:Topics: agent, agentic-workflow, mcp, rag, rag-chatbot; description: 'Agentic RAG for any scenario. Customize sources, depth, and width'
matched fp:4702d4ba0ea9bc0f, llm:Topics: agent, agentic-workflow, mcp, rag, rag-chatbot; description: 'Agentic RAG for any scenario. Customize sources, depth, and width'
matched fp:4702d4ba0ea9bc0f, llm:Topics: agent, agentic-workflow, mcp, rag, rag-chatbot; description: 'Agentic RAG for any scenario. Customize sources, depth, and width'