Metadata-Version: 2.4
Name: pylibseekdb_runtime
Version: 1.0.0.post1
Summary: OceanBase SeekDB
Home-page: https://github.com/oceanbase/seekdb
Author: OceanBase
Author-email: open_oceanbase@oceanbase.com
Maintainer: OceanBase
Maintainer-email: open_oceanbase@oceanbase.com
License: Apache 2.0
Project-URL: Homepage, https://github.com/oceanbase/seekdb
Project-URL: Repository, https://github.com/oceanbase/seekdb
Project-URL: Documentation, https://github.com/oceanbase/seekdb
Project-URL: Bug Tracker, https://github.com/oceanbase/seekdb/issues
Keywords: database,oceanbase,embed,sql,AI
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Programming Language :: C++
Classifier: Topic :: Database
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: maintainer
Dynamic: maintainer-email
Dynamic: project-url
Dynamic: requires-python
Dynamic: summary

<div align="center">

### **🔷 The AI-native hybrid search database**

**Powerful AI search capabilities · Lightweight · Production-ready**

</div>

---
<p align="center">
    <a href="https://oceanbase.ai">
        <img alt="Documentation" height="20" src="https://img.shields.io/badge/OceanBase.ai-4285F4?style=for-the-badge&logo=read-the-docs&logoColor=white" />
    </a>
    <a href="https://www.linkedin.com/company/oceanbase" target="_blank">
        <img src="https://custom-icon-badges.demolab.com/badge/LinkedIn-0A66C2?logo=linkedin-white&logoColor=fff" alt="follow on LinkedIn">
    </a>
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        <img alt="Static Badge" src="https://img.shields.io/badge/YouTube-red?logo=youtube">
    </a>
    <a href="https://discord.gg/74cF8vbNEs">
        <img alt="Discord" src="https://img.shields.io/discord/74cF8vbNEs?label=Discord&logo=discord&style=flat-square&color=5865F2" />
    </a>
    <a href="https://pepy.tech/projects/">
        <img alt="Downloads" src="https://static.pepy.tech/badge/seekdb" />
    </a>
    <a href="https://github.com/oceanbase/seekdb/blob/master/LICENSE">
        <img alt="License" src="https://img.shields.io/badge/License-Apache_2.0-blue.svg" />
    </a>
</p>

<div align="center">

---

</div>

## 🚀 What is OceanBase SeekDB?

**OceanBase SeekDB** is the lightweight, embedded version of OceanBase Database - a powerful AI search database designed for the AI applications. It combines enterprise-grade database capabilities with cutting-edge **AI search ** features, such as Vector search, fulltext search, Json. 

---

## 🔥 Why OceanBase SeekDB?

---
| Feature | OceanBase SeekDB | Traditional DB | Vector-only DB | Full-Text Engine |
|---------|----------------|----------------|----------------|------------------|
| **Embedded Mode** | ✅ Native | ⚠️ Possible | ⚠️ Possible | ⚠️ Possible |
| **SQL Support** | ✅ Full SQL | ✅ Full SQL | ❌ Limited | ❌ Limited |
| **Vector Search** | ✅ Built-in | ❌ Limited | ✅ Supported | ❌ Limited |
| **Full-Text Search** | ✅ Built-in | ✅ Supported | ❌ Limited | ✅ Advanced |
| **Json** | ✅ Yes | ⚠️ Varies by Product | ❌ Not Supported | ❌ Not Supported |
| **ACID Transactions** | ✅ Full | ✅ Full | ❌ Limited | ❌ Limited |
| **Easy Migration** | ✅ MySQL Compatible | ✅ Standard | ❌ No | ❌ No |


---

## ✨ Key Features

### 🎯 **AI-Powered Search**
- **Vector Similarity Search**: Optimize vector query accuracy, performance, and cost for different scenarios using different algorithms
- **Hybrid Search**: Combine vector search, scalar search, and full-text retrieval for optimal results
- **Full-Text Search**: Built-in full-text indexing for keyword-based searches
- **Json**：Built-in Json schema and query, support Json index.

### 📦 **Embedded & Lightweight**
- **Zero Dependencies**: Run embedded in your application - no separate database server required
- **Tiny Footprint**: Minimal memory and disk usage, perfect for edge devices and containers
- **Single Binary**: Easy to deploy and distribute with your application
- **Local-First**: Work offline, sync when ready

### ⚡ **Simple & Developer-Friendly**
- **MySQL Compatible**: Use familiar SQL syntax - no learning curve
- **Instant Setup**: Get started in seconds, not minutes
- **Rich APIs**: Support for Python, Java, Go, and more
- **Comprehensive Docs**: Clear documentation with examples for every use case

### 🚀 **Production-Ready**
- **Stability**: More than 15 years of technical expertise and 4000+ enterprise implementations
- **ACID Compliance**: Full transaction support with strong consistency guarantees
- **Horizontal Scalability**: Scale from single node to distributed cluster seamlessly
- **Enterprise Security**: Built-in encryption, authentication, and access control

---

## 🎬 Quick Start

### Installation

```bash
pip install pylibseekdb
```

### Requirements

- CPython 3.8+
- Linux x86_64, aarch64/arm64 with glibc version >= 2.28 (Alpine Linux is not supported yet)

### 🎯 AI Search Example

Build a semantic search system in 5 minutes:

🗄️ 🐍 Python SDK
```bash
# install sdk first
pip install -U pyseekdb
```

```python
import pyseekdb
client = pyseekdb.Client()

collection = client.get_or_create_collection(name="my_collection")

collection.upsert(
    ids=["1", "2", "3"],
    documents=[
        "It's rainy today",
        "It was cloudy yesterday",
        "The forecast for tomorrow is fine weather"
   ]
)

results = collection.query(
    query_texts=[" What's the weather like today"], # SeekDB will embed this for you
    n_results=2 # how many results to return
)

print(results)
```

🗄️ SQL

```python
import pylibseekdb as seekdb

# Open a database
seekdb.open()

# Connect to a database
conn = seekdb.connect()

# Use the connection
cursor = conn.cursor()
cursor.execute("""-- Create table with vector column
CREATE TABLE articles (
    id INT PRIMARY KEY,
    title TEXT,
    content TEXT,
    embedding VECTOR(384)
);""")

cursor.execute("""-- Create vector index for fast similarity search
CREATE INDEX idx_vector ON articles USING VECTOR (embedding);""")

cursor.execute("""-- Insert documents with embeddings
-- Note: Embeddings should be pre-computed using your embedding model
INSERT INTO articles (id, title, content, embedding) 
VALUES 
    (1, 'AI and Machine Learning', 'Artificial intelligence is transforming...', '[0.1, 0.2, ...]'),
    (2, 'Database Systems', 'Modern databases provide high performance...', '[0.3, 0.4, ...]'),
    (3, 'Vector Search', 'Vector databases enable semantic search...', '[0.5, 0.6, ...]');""")

cursor.execute("""-- Example: Hybrid search combining vector and full-text
-- Replace '[query_embedding]' with your actual query embedding vector
SELECT 
    title,
    content,
    embedding <-> '[query_embedding]' AS vector_distance,
    MATCH(content) AGAINST('your keywords' IN NATURAL LANGUAGE MODE) AS text_score
FROM articles
WHERE MATCH(content) AGAINST('your keywords' IN NATURAL LANGUAGE MODE)
ORDER BY vector_distance ASC, text_score DESC
LIMIT 10;""")

results = cursor.fetchall()

# Close the connection
conn.close()
```

## 📚 Use Cases

<div align="center">

| 🎯 **RAG Systems** | 🔍 **Semantic Search** | 💬 **Chatbots** | 🎬 **Recommendations** |
|:---:|:---:|:---:|:---:|
| Build retrieval-augmented generation pipelines with vector search | Power semantic search across documents, images, and multimedia | Create intelligent chatbots with memory and context | Build recommendation engines with hybrid search |

</div>

### 🎯 Real-World Examples

- **📚 Document Q&A**: Build ChatGPT-like document search with RAG
- **🖼️ Image Search**: Find similar images using vision embeddings
- **💼 E-commerce**: Semantic product search and recommendations
- **🔬 Scientific Research**: Search through research papers and datasets
- **📊 Business Intelligence**: Combine SQL analytics with AI search

---

## 🌟 Ecosystem & Integrations

<div align="center">

<p>
    <a href="https://huggingface.co">
        <img src="https://img.shields.io/badge/HuggingFace-✅-00A67E?style=flat-square&logo=huggingface" alt="HuggingFace" />
    </a>
    <a href="https://github.com/langchain-ai/langchain/pulls?q=is%3Apr+is%3Aclosed+oceanbase">
        <img src="https://img.shields.io/badge/LangChain-✅-00A67E?style=flat-square&logo=langchain" alt="LangChain" />
    </a>
    <a href="https://github.com/langchain-ai/langchain/pulls?q=is%3Apr+is%3Aclosed+oceanbase">
        <img src="https://img.shields.io/badge/LangGraph-✅-00A67E?style=flat-square&logo=langgrap" alt="LangGraph" />
    </a>
    <a href="https://github.com/langgenius/dify/pulls?q=is%3Apr+is%3Aclosed+oceanbase">
        <img src="https://img.shields.io/badge/Dify-✅-00A67E?style=flat-square&logo=dify" alt="Dify" />
    </a>
    <a href="https://github.com/coze-dev/coze-studio/pulls?q=is%3Apr+oceanbase+is%3Aclosed">
        <img src="https://img.shields.io/badge/Coze-✅-00A67E?style=flat-square&logo=coze" alt="Coze" />
    </a>
    <a href="https://github.com/run-llama/llama_index/pulls?q=is%3Apr+is%3Aclosed+oceanbase">
        <img src="https://img.shields.io/badge/LlamaIndex-✅-00A67E?style=flat-square&logo=llama" alt="LlamaIndex" />
    </a>
    <a href="https://firecrawl.dev">
        <img src="https://img.shields.io/badge/Firecrawl-✅-00A67E?style=flat-square&logo=firecrawl" alt="Firecrawl" />
    </a>
    <a href="https://github.com/labring/FastGPT/pulls?q=is%3Apr+oceanbase+is%3Aclosed">
        <img src="https://img.shields.io/badge/FastGPT-✅-00A67E?style=flat-square&logo=FastGPT" alt="FastGPT" />
    </a>
    <a href="https://db-gpt.io">
        <img src="https://img.shields.io/badge/DB--GPT-✅-00A67E?style=flat-square&logo=db-gpt" alt="DB-GPT" />
    </a>
    <a href="https://github.com/camel-ai/camel/pulls?q=is%3Apr+oceanbase+is%3Aclosed">
        <img src="https://img.shields.io/badge/camel-✅-00A67E?style=flat-square&logo=camel" alt="Camel-AI" />
    </a>
    <a href="https://github.com/alibaba/spring-ai-alibaba">
        <img src="https://img.shields.io/badge/spring--ai--alibaba-✅-00A67E?style=flat-square&logo=spring" alt="spring-ai-alibaba" />
    </a>
    <a href="https://developers.cloudflare.com/workers-ai">
        <img src="https://img.shields.io/badge/Cloudflare%20Workers%20AI-✅-00A67E?style=flat-square&logo=cloudflare" alt="Cloudflare Workers AI" />
    </a>
    <a href="https://jina.ai">
        <img src="https://img.shields.io/badge/Jina%20AI-✅-00A67E?style=flat-square&logo=jina" alt="Jina AI" />
    </a>
    <a href="https://ragas.io">
        <img src="https://img.shields.io/badge/Ragas-✅-00A67E?style=flat-square&logo=ragas" alt="Ragas" />
    </a>
    <a href="https://jxnl.github.io/instructor">
        <img src="https://img.shields.io/badge/Instructor-✅-00A67E?style=flat-square&logo=instructor" alt="Instructor" />
    </a>
    <a href="https://baseten.co">
        <img src="https://img.shields.io/badge/Baseten-✅-00A67E?style=flat-square&logo=baseten" alt="Baseten" />
    </a>
</p>


</div>

---


## 🤝 Community & Support

<div align="center">

<p>
    <a href="https://discord.gg/74cF8vbNEs">
        <img src="https://img.shields.io/badge/Discord-Join%20Chat-5865F2?style=for-the-badge&logo=discord&logoColor=white" alt="Discord" />
    </a>
    <a href="https://github.com/oceanbase/seekdb/discussions">
        <img src="https://img.shields.io/badge/GitHub%20Discussion-181717?style=for-the-badge&logo=github&logoColor=white" alt="GitHub Discussion" />
    </a>
    <a href="https://ask.oceanbase.com/">
        <img src="https://img.shields.io/badge/Forum-Chinese%20Community-FF6900?style=for-the-badge" alt="Forum" />
    </a>
</p>

</div>

---

## 📄 License

OceanBase SeekDB is licensed under the Apache License, Version 2.0.


