Metadata-Version: 2.3
Name: aibaba_ai
Version: 0.3.33
Summary: Framework for building and deploying LLM-powered applications.
License: MIT
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
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
Requires-Dist: PyYAML (>=5.3)
Requires-Dist: SQLAlchemy (>=1.4,<3)
Requires-Dist: aibaba_ai_core (>=0.3.31,<0.4.0)
Requires-Dist: aibaba_ai_text_splitters (>=0.3.6,<0.4.0)
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Requires-Dist: async-timeout (>=4.0.0,<5.0.0) ; python_version < "3.11"
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Project-URL: Repository, https://github.com/aibaba-ai/aibaba-ai
Project-URL: Release Notes, https://github.com/aibaba-ai/aibaba-ai/releases?q=tag%3A%22aiagentsforce%3D%3D0%22&expanded=true
Project-URL: Source Code, https://github.com/aibaba-ai/aibaba-ai/tree/master/libs/aibaba-ai
Description-Content-Type: text/markdown

# �� Aibaba AI

⚡ Unleashing LLM Potential Through Modular Architecture ⚡

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## Quick Install

`pip install aibaba_ai`

## 🤔 Overview

Large Language Models (LLMs) are revolutionizing software development, but their true potential lies in integration rather than isolation. The real power emerges when combining LLMs with diverse computational resources and knowledge bases.

Aibaba AI facilitates this integration, enabling developers to build sophisticated applications such as:

**❓ Advanced RAG-based Q&A Systems**

- [Documentation](https://docs.aibaba.world/docs/use_cases/question_answering/)
- Live Demo: [Chat Aibaba AI](https://chat.aibaba.world) ([Source Code](https://github.com/Aibaba AI-ai/chat-Aibaba AI))

**🧱 Data Structure Extraction**

- [Documentation](https://docs.aibaba.world/docs/use_cases/extraction/)
- Example Implementation: [SQL Llama2 Template](https://github.com/aibaba-ai/aibaba-ai-extract/)

**🤖 Intelligent Conversational Systems**

- [Documentation](https://docs.aibaba.world/docs/use_cases/chatbots)
- Live Demo: [Web Aibaba AI](https://webAibabaAI.vercel.app) ([Source Code](https://github.com/Aibaba AI-ai/webAibabaAI))

## 📖 Documentation

Our [comprehensive documentation](https://docs.aibaba.world) covers:

- Getting Started: Installation, setup, and basic examples
- Practical Guides: Demonstrations, integrations, and utility functions
- API Reference: Complete technical documentation
- Learning Resources: Core concept explanations

## 🚀 Core Capabilities

Aibaba AI excels in five key areas, arranged by complexity:

**📃 LLM Integration & Prompt Engineering**

Streamlined prompt management, optimization, and a unified interface for LLM interactions.

**🔗 Chain Architecture**

Orchestrate complex sequences of LLM calls and utility functions with our standardized chain interface and rich tool integrations.

**📚 Enhanced Retrieval & Generation**

Specialized chains for intelligent data retrieval and content generation, perfect for text summarization and context-aware Q&A systems.

**🤖 Autonomous Agents**

Framework for creating decision-making agents that can execute actions, process feedback, and adapt their behavior iteratively.

**🧐 Performance Assessment**

[BETA] Advanced evaluation frameworks using LLMs themselves to assess output quality and performance.

For detailed insights into these capabilities, visit our [documentation](https://docs.aibaba.world).

## 💁 Contributing

We welcome contributions in all forms - from new features to infrastructure improvements and documentation enhancements. Our field evolves rapidly, and community involvement is crucial.

For contribution guidelines, please consult our [Contributing Guide](https://docs.aibaba.world/docs/contributing/).

