🚀 AutoTune Research Assistant

An Intelligent AI Fine-Tuning Research Assistant

Powered by Gemini AI • Searches HuggingFace, ArXiv & Kaggle • Generates Comprehensive Reports

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🌟 What is AutoTune?

AutoTune is an intelligent conversational AI assistant that helps researchers, developers, and AI enthusiasts find the perfect models, datasets, and approaches for their fine-tuning projects. Simply describe what you want to accomplish, and AutoTune will:

• 🔍 Search across HuggingFace Hub, ArXiv papers, and Kaggle datasets
• 🧠 Analyze your requirements using advanced AI
• 📊 Generate comprehensive research reports with recommendations
• 🎯 Provide actionable insights for your specific use case

✨ Key Features

🤖 Intelligent Analysis

• Natural Language Understanding: Describe your project in plain English
• Requirement Extraction: Automatically identifies task type, model size, performance needs
• Smart Query Generation: Creates optimized search queries for each platform

🔍 Multi-Platform Search

• HuggingFace Hub: Find pre-trained models with comprehensive metadata
• ArXiv Papers: Discover latest research and SOTA methods
• Kaggle Datasets: Locate relevant training data and benchmarks

📈 Advanced Intelligence

• Intelligent Keyword Matching: Uses TF-IDF and cosine similarity for better results
• Quality Scoring: Ranks results by downloads, citations, and relevance
• Accumulated Learning: Improves search terms over multiple queries

📋 Comprehensive Reports

• Model Recommendations: Top 3 models with pros/cons analysis
• Dataset Suggestions: Curated datasets with quality metrics
• Research Insights: Latest papers and SOTA developments
• Implementation Strategy: Step-by-step approach for your project
• Cost Analysis: Resource requirements and budget considerations

🚀 Quick Start

Prerequisites

pip install google-generativeai huggingface-hub requests pandas scikit-learn numpy

Basic Usage

from main import FineTuningAgent

# Initialize the assistant
agent = FineTuningAgent()

# Start interactive session
agent.start_conversation()

Example Interaction

🤖 Welcome to AutoTune Fine-Tuning Assistant!
💬 What would you like to fine-tune a model for? 
> I want to create a small model for mathematical reasoning

🔍 Analyzing your requirements...
📋 I understand you want to:
   • Task: reasoning
   • Model Size: small
   • Performance: medium

📊 Searching across HuggingFace, ArXiv, and Kaggle...
📝 Generating comprehensive research report...

🚀 Fine-Tuning Research Report
## 📋 Executive Summary
...

🛠️ Installation

Clone the Repository

git clone https://github.com/yourusername/autotune-research-assistant.git
cd autotune-research-assistant

Install Dependencies

pip install -r requirements.txt

Set Up API Keys

# Set your Gemini API key
export GEMINI_API_KEY="your_gemini_api_key_here"

# Optional: Set HuggingFace token for authenticated access
export HUGGINGFACE_TOKEN="your_hf_token_here"

📚 Usage Examples

1. Text Classification Project

agent = FineTuningAgent()
# Tell the agent: "I need a model for sentiment analysis on social media posts"

2. Code Generation Task

agent = FineTuningAgent()
# Tell the agent: "I want to fine-tune a model for Python code completion"

3. Multilingual Translation

agent = FineTuningAgent()
# Tell the agent: "I need a model for English to Persian translation"

🏗️ Architecture

AutoTune Research Assistant
├── 🤖 Main Agent (main.py)
│   ├── Requirement Analysis
│   ├── Query Generation
│   └── Report Generation
├── 🔍 Search Modules
│   ├── HuggingFace Search (huggingface_search.py)
│   ├── ArXiv Search (arxiv_search.py)
│   └── Kaggle Search (kaggle_search.py)
├── 🧠 Intelligence Layer
│   ├── Keyword Matcher (keyword_matcher.py)
│   └── Vocabulary System (vocabulary.py)
└── 📊 Generated Reports
    └── Fine-tuning Recommendations

🔧 Configuration

Environment Variables

# Required
GEMINI_API_KEY=your_gemini_api_key

# Optional
HUGGINGFACE_TOKEN=your_hf_token
KAGGLE_USERNAME=your_kaggle_username
KAGGLE_KEY=your_kaggle_key

Customization

• Search Limits: Modify max_results in search functions
• Quality Thresholds: Adjust filtering criteria
• Report Templates: Customize report generation prompts

📊 Supported Tasks

Task Category	Examples	Supported
Text Classification	Sentiment Analysis, Topic Classification	✅
Text Generation	Story Writing, Code Generation	✅
Question Answering	Reading Comprehension, Factual QA	✅
Summarization	Document Summarization, News Summarization	✅
Translation	Machine Translation, Multilingual	✅
Reasoning	Mathematical Reasoning, Logical Reasoning	✅
Code	Code Completion, Code Understanding	✅
Vision	Image Classification, Object Detection	✅
Speech	Speech Recognition, Text-to-Speech	✅

🎯 Model Size Support

• Small Models (<3B parameters): Mobile/laptop deployment
• Medium Models (<7B parameters): Balanced performance
• Large Models (>7B parameters): High performance, server deployment

📈 Performance Metrics

AutoTune evaluates models based on:

• Download Count: Popularity and adoption
• Citations: Research impact
• Benchmark Scores: Performance metrics
• Quality Score: Comprehensive evaluation (0-100)

🤝 Contributing

We welcome contributions! Here's how you can help:

🐛 Bug Reports

• Use GitHub Issues to report bugs
• Include error messages and steps to reproduce

💡 Feature Requests

• Suggest new features via GitHub Issues
• Describe the use case and expected behavior

🔧 Code Contributions

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

📝 Documentation

• Improve README sections
• Add code examples
• Translate to other languages

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Google Gemini AI for powerful language understanding
• HuggingFace for the amazing model hub
• ArXiv for open research papers
• Kaggle for datasets and competitions
• Open Source Community for inspiration and tools

📞 Support

• GitHub Issues: For bugs and feature requests
• Discussions: For questions and community support
• Email: [email protected]

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Made with ❤️ for the AI Research Community

⭐ Star this repo • 🐛 Report Bug • 💡 Request Feature

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🇮🇷 فارسی

خوش آمدید به AutoTune Research Assistant

AutoTune یک دستیار هوشمند تحقیقاتی است که به شما کمک می‌کند بهترین مدل‌ها، دیتاست‌ها و روش‌های fine-tuning را برای پروژه‌های هوش مصنوعی خود پیدا کنید.

ویژگی‌های کلیدی:

• 🔍 جستجوی هوشمند در HuggingFace، ArXiv و Kaggle
• 🧠 تحلیل پیشرفته نیازهای شما با استفاده از Gemini AI
• 📊 گزارش‌های جامع با توصیه‌های عملی
• 🎯 پیشنهادات شخصی‌سازی شده برای پروژه شما

نحوه استفاده:

from main import FineTuningAgent
agent = FineTuningAgent()
agent.start_conversation()

مثال:

💬 چه کاری می‌خواهید با fine-tuning انجام دهید؟
> می‌خواهم یک مدل کوچک برای استدلال ریاضی بسازم

🔍 در حال تحلیل نیازهای شما...
📊 جستجو در HuggingFace، ArXiv و Kaggle...
📝 تولید گزارش تحقیقاتی جامع...

پشتیبانی:

• برای گزارش باگ و درخواست ویژگی جدید از GitHub Issues استفاده کنید
• برای سوالات و بحث‌های جامعه از Discussions استفاده کنید

با ❤️ برای جامعه تحقیقاتی هوش مصنوعی ساخته شده است

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