change readme

README.md

@@ -1,147 +1,4 @@
-# 🤖 PDF AI Assistant
-
-A multilingual PDF processing application that leverages various AI models to analyze, summarize, and interact with PDF documents. Built with Python, Gradio, and LangChain.
-
-## 🌟 Features
-
-- **Multiple AI Models Support**:
-
-  - OpenAI GPT-4
-  - IBM Granite 3.1
-  - Mistral Small 24B
-  - SmolLM2 1.7B
-  - Local Ollama models
-
-- **Multilingual Interface**:
-
-  - English
-  - Español
-  - Deutsch
-  - Français
-  - Português
-
-- **Core Functionalities**:
-  - 📝 Text extraction from PDFs
-  - 💬 Interactive Q&A with document content
-  - 📋 Document summarization
-  - 👨‍💼 Customizable specialist advisor
-  - 🔄 Dynamic chunk size and overlap settings
-
-## 🛠️ Installation
-
-1. Clone the repository:
-
-```bash
-git clone <repository-url>
-cd pdf-ai-assistant
-```
-
-2. Install required dependencies:
-
-```bash
-pip install -r requirements.txt
-```
-
-3. Set up environment variables:
-
-```bash
-# Create .env file
-touch .env
-
-# Add your API keys (if using)
-WATSONX_APIKEY=your_watsonx_api_key
-WATSONX_PROJECT_ID=your_watsonx_project_id
-```
-
-## 📦 Dependencies
-
-- gradio
-- langchain
-- chromadb
-- PyPDF2
-- ollama (for local models)
-- python-dotenv
-- requests
-- ibm-watsonx-ai
-
-## 🚀 Usage
-
-1. Start the application:
-
-```bash
-python app.py
-```
-
-2. Open your web browser and navigate to the provided URL (usually http://localhost:7860)
-
-3. Select your preferred:
-
-   - Language
-   - AI Model
-   - Model Type (Local/API)
-
-4. Upload a PDF file and process it
-
-5. Use any of the three main features:
-   - Ask questions about the document
-   - Generate a comprehensive summary
-   - Get specialized analysis using the custom advisor
-
-## 💡 Features in Detail
-
-### Q&A System
-
-- Interactive chat interface
-- Context-aware responses
-- Source page references
-
-### Summarization
-
-- Chunk-based processing
-- Configurable chunk sizes
-- Comprehensive document overview
-
-### Specialist Advisor
-
-- Customizable expert roles
-- Detailed analysis based on expertise
-- Structured insights and recommendations
-
-## 🔧 Configuration
-
-The application supports various AI models:
-
-- Local models via Ollama
-- API-based models (OpenAI, IBM WatsonX)
-- Hugging Face models
-
-For Ollama local models, ensure:
-
-```bash
-ollama pull granite3.1-dense
-ollama pull granite-embedding:278m
-```
-
-## 🌐 Language Support
-
-The interface and AI responses are available in:
-
-- English
-- Spanish
-- German
-- French
-- Portuguese
-
-## 📝 License
-
-[MIT License]
-
-## 🤝 Contributing
-
-Contributions, issues, and feature requests are welcome!
-
 ---
-
 title: PDF Chatbot
 emoji: 🌍
 colorFrom: blue
@@ -150,7 +7,6 @@ sdk: gradio
 sdk_version: 5.19.0
 app_file: app.py
 pinned: true
-
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

readme-1.md

@@ -0,0 +1,141 @@
+# 🤖 PDF AI Assistant
+
+A multilingual PDF processing application that leverages various AI models to analyze, summarize, and interact with PDF documents. Built with Python, Gradio, and LangChain.
+
+## 🌟 Features
+
+- **Multiple AI Models Support**:
+
+  - OpenAI GPT-4
+  - IBM Granite 3.1
+  - Mistral Small 24B
+  - SmolLM2 1.7B
+  - Local Ollama models
+
+- **Multilingual Interface**:
+
+  - English
+  - Español
+  - Deutsch
+  - Français
+  - Português
+
+- **Core Functionalities**:
+  - 📝 Text extraction from PDFs
+  - 💬 Interactive Q&A with document content
+  - 📋 Document summarization
+  - 👨‍💼 Customizable specialist advisor
+  - 🔄 Dynamic chunk size and overlap settings
+
+## 🛠️ Installation
+
+1. Clone the repository:
+
+```bash
+git clone <repository-url>
+cd pdf-ai-assistant
+```
+
+2. Install required dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+
+3. Set up environment variables:
+
+```bash
+# Create .env file
+touch .env
+
+# Add your API keys (if using)
+WATSONX_APIKEY=your_watsonx_api_key
+WATSONX_PROJECT_ID=your_watsonx_project_id
+```
+
+## 📦 Dependencies
+
+- gradio
+- langchain
+- chromadb
+- PyPDF2
+- ollama (for local models)
+- python-dotenv
+- requests
+- ibm-watsonx-ai
+
+## 🚀 Usage
+
+1. Start the application:
+
+```bash
+python app.py
+```
+
+2. Open your web browser and navigate to the provided URL (usually http://localhost:7860)
+
+3. Select your preferred:
+
+   - Language
+   - AI Model
+   - Model Type (Local/API)
+
+4. Upload a PDF file and process it
+
+5. Use any of the three main features:
+   - Ask questions about the document
+   - Generate a comprehensive summary
+   - Get specialized analysis using the custom advisor
+
+## 💡 Features in Detail
+
+### Q&A System
+
+- Interactive chat interface
+- Context-aware responses
+- Source page references
+
+### Summarization
+
+- Chunk-based processing
+- Configurable chunk sizes
+- Comprehensive document overview
+
+### Specialist Advisor
+
+- Customizable expert roles
+- Detailed analysis based on expertise
+- Structured insights and recommendations
+
+## 🔧 Configuration
+
+The application supports various AI models:
+
+- Local models via Ollama
+- API-based models (OpenAI, IBM WatsonX)
+- Hugging Face models
+
+For Ollama local models, ensure:
+
+```bash
+ollama pull granite3.1-dense
+ollama pull granite-embedding:278m
+```
+
+## 🌐 Language Support
+
+The interface and AI responses are available in:
+
+- English
+- Spanish
+- German
+- French
+- Portuguese
+
+## 📝 License
+
+[MIT License]
+
+## 🤝 Contributing
+
+Contributions, issues, and feature requests are welcome!