Deploy AnySecret Chat Assistant

- Gradio-based chat interface
- Llama 3.2 3B Instruct with LoRA fine-tuning
- Specialized for AnySecret configuration management
- Professional UI with examples and advanced settings
- Ready for production deployment

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual environments
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# IDEs
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Gradio
+gradio_cached_examples/
+flagged/
+
+# Model cache
+.cache/
+models/
+
+# Logs
+*.log

Dockerfile

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+# Dockerfile for AnySecret Chat Assistant
+# Optimized for HuggingFace Spaces deployment
+
+FROM python:3.10-slim
+
+# Set working directory
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    git \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for better caching
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application files
+COPY . .
+
+# Create non-root user for security
+RUN useradd -m -u 1000 anysecret
+RUN chown -R anysecret:anysecret /app
+USER anysecret
+
+# Expose port
+EXPOSE 7860
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=30s --start-period=60s --retries=3 \
+    CMD curl -f http://localhost:7860/ || exit 1
+
+# Set environment variables
+ENV GRADIO_SERVER_NAME=0.0.0.0
+ENV GRADIO_SERVER_PORT=7860
+
+# Run the application
+CMD ["python", "app.py"]

README.md

@@ -1,12 +1,96 @@
 ---
-title: Anysecret Chat
-emoji: 📉
+title: AnySecret Chat Assistant
+emoji: 🔐
 colorFrom: indigo
-colorTo: pink
+colorTo: purple
 sdk: gradio
-sdk_version: 5.44.1
+sdk_version: 4.44.0
 app_file: app.py
-pinned: false
+pinned: true
+license: mit
+short_description: AI assistant for AnySecret configuration management
+hardware: cpu-upgrade
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 🔐 AnySecret Chat Assistant
+
+An AI-powered assistant specialized in AnySecret configuration management, trained to help with:
+
+- **Multi-cloud configuration** (AWS, GCP, Azure, Kubernetes)
+- **CLI commands** and usage patterns
+- **CI/CD integration** (GitHub Actions, Jenkins, GitLab)
+- **Python SDK** implementation
+- **Security best practices** for secrets management
+- **Migration guidance** from other tools
+
+## 🚀 Features
+
+- **Specialized Knowledge**: Trained specifically on AnySecret documentation and patterns
+- **Interactive Chat**: Real-time conversation interface
+- **Code Examples**: Provides practical, copy-pasteable code snippets
+- **Multi-cloud Expertise**: Understands differences between cloud providers
+- **Production Ready**: Includes enterprise deployment guidance
+
+## 💬 Example Questions
+
+Try asking:
+- "How do I configure AnySecret for AWS?"
+- "Show me a GitHub Actions workflow with AnySecret"
+- "What's the difference between secrets and parameters?"
+- "How do I migrate from AWS Parameter Store?"
+- "Can you show me Python SDK examples?"
+
+## 🛠️ Technical Details
+
+- **Base Model**: Meta Llama 3.2 3B Instruct
+- **Fine-tuning**: LoRA (Low-Rank Adaptation) on AnySecret-specific data
+- **Training Data**: 43 curated examples across 7 categories
+- **Framework**: Transformers + PEFT + Gradio
+
+## 📚 Related Links
+
+- **Website**: [anysecret.io](https://anysecret.io)
+- **Documentation**: [docs.anysecret.io](https://docs.anysecret.io)
+- **GitHub**: [anysecret-io/anysecret-lib](https://github.com/anysecret-io/anysecret-lib)
+- **Commercial License**: [License Terms](https://github.com/anysecret-io/anysecret-lib/blob/main/LICENSE-COMMERCIAL)
+
+## 🔧 Local Development
+
+```bash
+# Clone this space
+git clone https://huggingface.co/spaces/anysecret-io/anysecret-chat
+cd anysecret-chat
+
+# Install dependencies
+pip install -r requirements.txt
+
+# Run locally
+python app.py
+```
+
+## 📖 Model Information
+
+This assistant uses a fine-tuned version of Llama 3.2 3B Instruct, specifically trained on AnySecret patterns and best practices. The model can:
+
+- Generate CLI commands with proper syntax
+- Explain configuration concepts clearly
+- Provide code examples in multiple languages
+- Suggest architectural patterns for different scales
+- Help troubleshoot common issues
+
+## ⚠️ Limitations
+
+- **Training Data**: Based on AnySecret v1.x documentation
+- **Not Official Support**: For production issues, use official support channels
+- **General Purpose**: May not have latest feature updates
+- **Experimental**: This is a demonstration of AI-assisted documentation
+
+## 📄 License
+
+This chat interface is MIT licensed. The underlying AnySecret software is dual-licensed:
+- **AGPL-3.0** for open source use
+- **Commercial License** for business use
+
+---
+
+Built with ❤️ by the AnySecret team • [Get Commercial License](https://anysecret.io/#license)

app.py

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+#!/usr/bin/env python3
+"""
+AnySecret Chat Assistant - HuggingFace Spaces Gradio Interface
+A specialized AI assistant for AnySecret configuration management
+"""
+
+import os
+import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Model configuration
+BASE_MODEL = "meta-llama/Llama-3.2-3B-Instruct"
+PEFT_MODEL = "anysecret-io/anysecret-assistant"
+
+# Global variables for model and tokenizer
+model = None
+tokenizer = None
+device = None
+
+def load_model():
+    """Load the model and tokenizer"""
+    global model, tokenizer, device
+    
+    try:
+        # Determine device
+        device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        logger.info(f"Using device: {device}")
+        
+        # Load tokenizer
+        logger.info("Loading tokenizer...")
+        tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL, use_fast=True)
+        if tokenizer.pad_token is None:
+            tokenizer.pad_token = tokenizer.eos_token
+        tokenizer.padding_side = "left"  # Better for chat
+        
+        # Load base model
+        logger.info("Loading base model...")
+        base_model = AutoModelForCausalLM.from_pretrained(
+            BASE_MODEL,
+            torch_dtype=torch.float16 if device.type == "cuda" else torch.float32,
+            device_map="auto" if device.type == "cuda" else None,
+            trust_remote_code=True,
+            low_cpu_mem_usage=True
+        )
+        
+        # Load LoRA adapter
+        logger.info("Loading LoRA adapter...")
+        model = PeftModel.from_pretrained(
+            base_model, 
+            PEFT_MODEL,
+            torch_dtype=torch.float16 if device.type == "cuda" else torch.float32
+        )
+        
+        # Move to device if not using device_map
+        if device.type != "cuda":
+            model = model.to(device)
+        
+        model.eval()
+        logger.info("Model loaded successfully!")
+        return True
+        
+    except Exception as e:
+        logger.error(f"Error loading model: {e}")
+        return False
+
+def generate_response(message, history, max_new_tokens=512, temperature=0.1, top_p=0.9):
+    """Generate response from the model"""
+    if model is None or tokenizer is None:
+        return "Model not loaded. Please try again."
+    
+    try:
+        # Format the conversation with proper prompt structure
+        conversation = ""
+        
+        # Add conversation history
+        for user_msg, assistant_msg in history:
+            conversation += f"### Instruction:\n{user_msg}\n\n### Response:\n{assistant_msg}\n\n"
+        
+        # Add current message
+        conversation += f"### Instruction:\n{message}\n\n### Response:\n"
+        
+        # Tokenize
+        inputs = tokenizer(
+            conversation, 
+            return_tensors="pt", 
+            truncation=True, 
+            max_length=1024,  # Leave room for generation
+            padding=True
+        ).to(device)
+        
+        # Generate
+        with torch.no_grad():
+            outputs = model.generate(
+                **inputs,
+                max_new_tokens=max_new_tokens,
+                temperature=temperature,
+                top_p=top_p,
+                do_sample=True,
+                pad_token_id=tokenizer.pad_token_id,
+                eos_token_id=tokenizer.eos_token_id,
+                repetition_penalty=1.1
+            )
+        
+        # Decode response
+        full_response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        
+        # Extract just the new response
+        if "### Response:\n" in full_response:
+            response = full_response.split("### Response:\n")[-1].strip()
+        else:
+            response = full_response[len(conversation):].strip()
+        
+        # Clean up response
+        response = response.replace("### Instruction:", "").strip()
+        
+        return response
+        
+    except Exception as e:
+        logger.error(f"Error generating response: {e}")
+        return f"Sorry, I encountered an error: {str(e)}"
+
+def chat_interface(message, history):
+    """Main chat interface function for Gradio"""
+    response = generate_response(message, history)
+    return response
+
+# Custom CSS for AnySecret branding
+css = """
+.gradio-container {
+    max-width: 1000px !important;
+}
+
+.header {
+    text-align: center;
+    padding: 20px 0;
+    background: linear-gradient(135deg, #6366f1 0%, #818cf8 100%);
+    color: white;
+    margin-bottom: 20px;
+    border-radius: 10px;
+}
+
+.header h1 {
+    margin: 0;
+    font-size: 2.5em;
+    font-weight: bold;
+}
+
+.header p {
+    margin: 10px 0 0 0;
+    font-size: 1.1em;
+    opacity: 0.9;
+}
+
+.footer {
+    text-align: center;
+    padding: 20px 0;
+    color: #666;
+    font-size: 0.9em;
+}
+
+.examples-container {
+    margin: 20px 0;
+}
+
+.examples-container h3 {
+    color: #374151;
+    margin-bottom: 10px;
+}
+"""
+
+# Load model on startup
+logger.info("Initializing AnySecret Chat Assistant...")
+model_loaded = load_model()
+
+if not model_loaded:
+    logger.error("Failed to load model!")
+
+# Create Gradio interface
+with gr.Blocks(css=css, title="AnySecret Chat Assistant") as demo:
+    # Header
+    gr.HTML("""
+    <div class="header">
+        <h1>🔐 AnySecret Chat Assistant</h1>
+        <p>Your AI assistant for configuration management across any cloud provider</p>
+    </div>
+    """)
+    
+    if model_loaded:
+        # Main chat interface
+        chatbot = gr.ChatInterface(
+            fn=chat_interface,
+            title="",
+            description="Ask me anything about AnySecret configuration management, CLI commands, cloud integrations, or best practices!",
+            examples=[
+                "How do I configure AnySecret for AWS?",
+                "What's the difference between secrets and parameters?",
+                "Show me how to use anysecret in a GitHub Actions workflow",
+                "How do I set up AnySecret with Kubernetes?",
+                "What are the best practices for managing secrets in production?",
+                "How do I migrate from AWS Parameter Store to AnySecret?",
+                "Can you show me a Python example using the AnySecret SDK?"
+            ],
+            retry_btn="🔄 Retry",
+            undo_btn="↩️ Undo",
+            clear_btn="🗑️ Clear Chat",
+            submit_btn="Send",
+            stop_btn="⏹️ Stop",
+            theme="default"
+        )
+        
+        # Advanced settings
+        with gr.Accordion("⚙️ Advanced Settings", open=False):
+            with gr.Row():
+                max_tokens = gr.Slider(
+                    minimum=50, 
+                    maximum=1024, 
+                    value=512, 
+                    label="Max Response Length",
+                    info="Maximum number of tokens to generate"
+                )
+                temperature = gr.Slider(
+                    minimum=0.1, 
+                    maximum=1.0, 
+                    value=0.1, 
+                    label="Temperature",
+                    info="Higher values make responses more creative"
+                )
+    else:
+        gr.HTML("""
+        <div style="text-align: center; padding: 40px; color: #dc2626;">
+            <h2>⚠️ Model Loading Failed</h2>
+            <p>The AnySecret assistant model could not be loaded. Please try refreshing the page or contact support.</p>
+        </div>
+        """)
+    
+    # Footer
+    gr.HTML("""
+    <div class="footer">
+        <p>
+            Powered by <strong>AnySecret.io</strong> • 
+            <a href="https://anysecret.io" target="_blank">Website</a> • 
+            <a href="https://docs.anysecret.io" target="_blank">Documentation</a> • 
+            <a href="https://github.com/anysecret-io/anysecret-lib" target="_blank">GitHub</a>
+        </p>
+        <p style="font-size: 0.8em; margin-top: 10px; opacity: 0.7;">
+            This assistant is trained on AnySecret documentation and best practices. 
+            For production support, please visit our official channels.
+        </p>
+    </div>
+    """)
+
+# Launch configuration
+if __name__ == "__main__":
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        debug=False,
+        show_error=True,
+        quiet=False
+    )

requirements.txt

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+# Core dependencies for AnySecret Chat Assistant
+torch>=2.0.0
+transformers>=4.35.0
+peft>=0.6.0
+accelerate>=0.24.0
+gradio>=4.0.0
+
+# Optional: Better performance on GPU
+# bitsandbytes>=0.41.0
+
+# Utilities
+numpy
+requests
+huggingface_hub>=0.17.0