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chilijung merged 2 commits into from
May 17, 2025
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Update README.md #1665

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113 changes: 27 additions & 86 deletions README.md
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Expand Up @@ -37,103 +37,30 @@
<img src="./misc/wren_workflow.png">
</p>

## 🕶 Try it yourself!

### GenBI (Generative Business Intelligence)

[Watch GenBI Demo](https://github.com/user-attachments/assets/90ad1d35-bb1e-490b-9676-b29863ff090b)

### Ask any questions


https://github.com/user-attachments/assets/f9c1cb34-5a95-4580-8890-ec9644da4160

👉 Try with your data on [Wren AI Cloud](https://getwren.ai/?utm_source=github&utm_medium=content&utm_campaign=readme) or [Install in your local environment](https://docs.getwren.ai/oss/installation/?utm_source=github&utm_medium=content&utm_campaign=readme)

## Supported LLM Models

Wren AI supports integration with various Large Language Models (LLMs), including but not limited to:
- OpenAI Models
- Azure OpenAI Models
- DeepSeek Models
- Google AI Studio – Gemini Models
- Vertex AI Models (Gemini + Anthropic)
- Bedrock Models
- Anthropic API Models
- Groq Models
- Ollama Models
- Databricks Models

Check [configuration examples here](https://github.com/Canner/WrenAI/tree/main/wren-ai-service/docs/config_examples)!

> [!CAUTION]
> The performance of Wren AI depends significantly on the capabilities of the LLM you choose. We strongly recommend using the most powerful model available for optimal results. Using less capable models may lead to reduced performance, slower response times, or inaccurate outputs.

## 🎯 Our Vision & Mission

At Wren AI, our mission is to revolutionize business intelligence by empowering organizations with seamless access to data through Generative Business Intelligence (GenBI). We aim to break down barriers to data insights with advanced AI-driven solutions, composable data frameworks, and semantic intelligence, enabling every team member to make faster, smarter, and data-driven decisions with confidence.

🤩 [Learn more about GenBI](https://getwren.ai/genbi?utm_source=github&utm_medium=content&utm_campaign=readme)

## 🤖 A User-Centric, End-to-End Open-source SQL AI Agent - Text-to-SQL Total Solution
## 🤖 Features

### 1. Talk to Your Data in Any Language

> Wren AI speaks [your language](https://docs.getwren.ai/oss/guide/settings/pj_settings#change-project-language?utm_source=github&utm_medium=content&utm_campaign=readme), such as English, German, Spanish, French, Japanese, Korean, Portuguese, Chinese, and more. Unlock valuable insights by asking your business questions to Wren AI. It goes beyond surface-level data analysis to reveal meaningful information and simplifies obtaining answers from lead scoring templates to customer segmentation.

<p align="center">
<img src="./misc/wren-lang.png" style="max-width: 700px"/>
</p>

### 2. GenBI Insights

> The GenBI feature empowers users with AI-generated summaries that provide key insights alongside SQL queries, simplifying complex data. Instantly convert query results into AI-generated reports, charts, transforming raw data into clear, actionable visuals. With GenBI, you can make faster, smarter decisions with ease.

<p align="center">
<img src="./misc/wren-genbi.png" alt="Screenshot of Wren AI's GenBI feature showing AI-generated summaries and visualizations" style="max-width: 700px"/>
</p>


### 3. AI-powered Data Exploration Features

> Beyond just retrieving data from your databases, Wren AI now answers exploratory questions like “What data do I have?” or “What are the columns in my customer tables?” Additionally, our AI dynamically generates recommended questions and intelligent follow-up queries tailored to your context, making data exploration smarter, faster, and more intuitive. Empower your team to unlock deeper insights effortlessly with AI.

<p align="center">
<img src="./misc/AI-generated-understanding_recommend_questions.png" style="max-width: 700px"/>
</p>

### 4. Semantic Indexing with a Well-Crafted UI/UX
### 3. Semantic Layer with a Well-Crafted UI/UX

> Wren AI has implemented a [semantic engine architecture](https://www.getwren.ai/post/how-we-design-our-semantic-engine-for-llms-the-backbone-of-the-semantic-layer-for-llm-architecture/?utm_source=github&utm_medium=content&utm_campaign=readme) to provide the LLM context of your business; you can easily establish a logical presentation layer on your data schema that helps LLM learn more about your business context.

<p align="center">
<img src="./misc/wren-modeling.png" style="max-width: 700px"/>
</p>

### 5. Generate SQL Queries with Context

> With Wren AI, you can process metadata, schema, terminology, data relationships, and the logic behind calculations and aggregations with [“Modeling Definition Language”](https://docs.getwren.ai/oss/engine/concept/what_is_mdl/?utm_source=github&utm_medium=content&utm_campaign=readme), reducing duplicate coding and simplifying data joins.

<p align="center">
<img src="./misc/wren-context.png" style="max-width: 700px"/>
</p>

### 6. Get Insights without Writing Code

> When starting a new conversation in Wren AI, your question is used to find the most relevant tables. From these, LLM generates the most relevant question for the user. You can also ask follow-up questions to get deeper insights.

<p align="center">
<img src="./misc/wren-insight.png" style="max-width: 700px"/>
</p>

### 7. Embedded AI-Powered SQL and Charts with the Wren AI API
### 4. Embedded AI-Powered SQL and Charts with the Wren AI API

> Unlock the full power of Wren AI in your own applications. Our API lets you generate SQL queries and rich charts from natural language, effortlessly embedding Wren AI’s intelligence into your workflows. Plus, monitor and manage every interaction with our built-in API History for complete transparency and control.

<p align="center">
<img src="./misc/API_doc.png" style="max-width: 700px"/>
</p>

Check out the [full API documentation here](https://wrenai.readme.io/reference/welcome)

## 🤔 Why Wren AI?
Expand All @@ -152,23 +79,37 @@ We focus on providing an open, secure, and accurate SQL AI Agent for everyone.

> Deploy Wren AI anywhere you like on your own data, LLM APIs, and environment, it's free.

### 4. Embedded AI with Wren AI API
## 🕶 Try it yourself!

> Build your own AI agents and applications with accurate and powerful GenBI capabilities powered by Wren AI API.
### GenBI (Generative Business Intelligence)

## 🤖 Wren AI Text-to-SQL Agentic Architecture
[Watch GenBI Demo](https://github.com/user-attachments/assets/90ad1d35-bb1e-490b-9676-b29863ff090b)

@coderabbitai coderabbitai Bot May 17, 2025

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💡 Verification agent

🧩 Analysis chain

Verify demo link validity. GitHub attachment URLs can change—please confirm it returns HTTP 200 and points to the intended media asset:

🏁 Script executed:

#!/bin/bash
curl -s -o /dev/null -w "%{http_code}\n" https://github.com/user-attachments/assets/90ad1d35-bb1e-490b-9676-b29863ff090b

Length of output: 126

Ensure README demo link returns HTTP 200
The current attachment URL responds with HTTP 302 (redirect) rather than directly serving the media asset. Please update the link to point at the raw file and confirm it returns 200:

– File: README.md
– Line: 86
– Current snippet:

[Watch GenBI Demo](https://github.com/user-attachments/assets/90ad1d35-bb1e-490b-9676-b29863ff090b)

– Action:
• Replace with the raw asset URL (for example, add ?raw=true or use the raw.githubusercontent.com path)
• Verify with:
shell curl -sL -o /dev/null -w "%{http_code}\n" <updated-URL>
and ensure it returns 200.

🤖 Prompt for AI Agents 
In README.md at line 86, the demo link currently points to a GitHub attachment
URL that returns HTTP 302 instead of directly serving the media asset. Update
the link to use the raw file URL by either appending '?raw=true' to the existing
URL or replacing it with the corresponding raw.githubusercontent.com path. After
updating, verify the link returns HTTP 200 by running a curl command with the
updated URL.


Wren AI consists of three core services:
### Ask any questions

- ***[Wren UI](https://github.com/Canner/WrenAI/tree/main/wren-ui):*** An intuitive user interface for asking questions, defining data relationships, and integrating data sources.

- ***[Wren AI Service](https://github.com/Canner/WrenAI/tree/main/wren-ai-service):*** Processes queries using a vector database for context retrieval, guiding LLMs to produce precise SQL outputs.
https://github.com/user-attachments/assets/f9c1cb34-5a95-4580-8890-ec9644da4160

@coderabbitai coderabbitai Bot May 17, 2025

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⚠️ Potential issue

Eliminate bare URL (MD034). Replace the raw link with descriptive anchor text. For example:

-[https://github.com/user-attachments/assets/f9c1cb34-5a95-4580-8890-ec9644da4160]
+[Ask a question demo](https://github.com/user-attachments/assets/f9c1cb34-5a95-4580-8890-ec9644da4160)

Committable suggestion skipped: line range outside the PR's diff.

🧰 Tools
🪛 markdownlint-cli2 (0.17.2)

91-91: Bare URL used
null

(MD034, no-bare-urls)

🤖 Prompt for AI Agents 
In README.md at line 91, replace the bare URL with descriptive anchor text by
embedding the URL within markdown link syntax. Use meaningful text that
describes the link destination instead of showing the raw URL.


- ***[Wren Engine](https://github.com/Canner/wren-engine):*** Serves as the semantic engine, mapping business terms to data sources, defining relationships, and incorporating predefined calculations and aggregations.
👉 Try with your data on [Wren AI Cloud](https://getwren.ai/?utm_source=github&utm_medium=content&utm_campaign=readme) or [Install in your local environment](https://docs.getwren.ai/oss/installation/?utm_source=github&utm_medium=content&utm_campaign=readme)

<p align="center">
<img src="./misc/how_wrenai_works.png" style="max-width: 1000px;">
</p>
## Supported LLM Models

Wren AI supports integration with various Large Language Models (LLMs), including but not limited to:
- OpenAI Models
- Azure OpenAI Models
- DeepSeek Models
- Google AI Studio – Gemini Models
- Vertex AI Models (Gemini + Anthropic)
- Bedrock Models
- Anthropic API Models
- Groq Models
- Ollama Models
- Databricks Models

Check [configuration examples here](https://github.com/Canner/WrenAI/tree/main/wren-ai-service/docs/config_examples)!

> [!CAUTION]
> The performance of Wren AI depends significantly on the capabilities of the LLM you choose. We strongly recommend using the most powerful model available for optimal results. Using less capable models may lead to reduced performance, slower response times, or inaccurate outputs.

Comment on lines +111 to 113

@coderabbitai coderabbitai Bot May 17, 2025

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🛠️ Refactor suggestion

Use GitHub-compatible caution styling. The [!CAUTION] admonition isn’t supported in standard README.md. Replace with a warning emoji and bold label:

-> [!CAUTION]
-> The performance of Wren AI depends significantly...
+> ⚠️ **Caution:** The performance of Wren AI depends significantly...
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
> [!CAUTION]
> The performance of Wren AI depends significantly on the capabilities of the LLM you choose. We strongly recommend using the most powerful model available for optimal results. Using less capable models may lead to reduced performance, slower response times, or inaccurate outputs.
> ⚠️ **Caution:** The performance of Wren AI depends significantly on the capabilities of the LLM you choose. We strongly recommend using the most powerful model available for optimal results. Using less capable models may lead to reduced performance, slower response times, or inaccurate outputs.
🤖 Prompt for AI Agents 
In README.md around lines 111 to 113, replace the unsupported `[!CAUTION]`
admonition with a GitHub-compatible format by using a warning emoji followed by
a bold "Caution:" label. This ensures the caution message is clearly visible and
properly rendered on GitHub without relying on unsupported syntax.

## ❤️ Knowledge Sharing From Wren AI

Expand Down