Add DevOps AI Assistant with Gradio interface and knowledge base functionality

week5/community-contributions/salah/devops-ai-assistance/app.py

@@ -0,0 +1,196 @@
+import os
+import gradio as gr
+from devops_ai_assistance import create_assistant, DevOpsAIAssistant
+
+
+assistant = None
+status_info = None
+
+
+def initialize_assistant(kb_path: str):
+    """Initialize the assistant with knowledge base"""
+    global assistant, status_info
+
+    try:
+        kb_path = kb_path.strip()
+        if not kb_path:
+            return "Error: Please provide a valid knowledge base path"
+
+        print(f"\n🚀 Initializing with knowledge base: {kb_path}")
+        assistant = create_assistant(kb_path)
+        status_info = assistant.get_status()
+
+        status_message = f"""
+✅ **DevOps AI Assistant Initialized Successfully!**
+
+📊 **Knowledge Base Statistics:**
+- Documents Loaded: {status_info['documents_loaded']}
+- Chunks Created: {status_info['chunks_created']}
+- Vectors in Store: {status_info['vectors_in_store']}
+- Knowledge Base Path: {status_info['knowledge_base_path']}
+
+🎯 **Ready to Answer Questions About:**
+- Kubernetes infrastructure configuration
+- ArgoCD deployment manifests
+- Helm charts and values
+- Infrastructure as Code (IaC)
+- DevOps best practices in your environment
+
+Start by asking questions about your k8s cluster infrastructure!
+"""
+        return status_message
+
+    except Exception as e:
+        error_msg = f"Error initializing assistant: {str(e)}"
+        print(f"❌ {error_msg}")
+        return f"❌ {error_msg}"
+
+
+def chat_with_assistant(message: str, history):
+    """Chat function for the assistant"""
+    global assistant
+
+    if not assistant:
+        bot_response = "❌ Assistant not initialized. Please provide a knowledge base path first."
+        history.append((message, bot_response))
+        return history, ""
+
+    if not message.strip():
+        bot_response = "Please enter a question about your DevOps infrastructure."
+        history.append((message, bot_response))
+        return history, ""
+
+    try:
+        result = assistant.ask(message)
+        answer = result.get('answer', '')
+
+        sources_text = ""
+        if result.get('sources'):
+            sources_text = "\n\n📚 **Sources:**\n"
+            for i, source in enumerate(result['sources'], 1):
+                source_file = source.get('source', 'Unknown')
+                file_type = source.get('file_type', 'Unknown')
+                sources_text += f"\n{i}. **{source_file}** ({file_type})"
+
+        bot_response = answer + sources_text if sources_text else answer
+
+    except Exception as e:
+        bot_response = f"Error processing question: {str(e)}"
+
+    history.append((message, bot_response))
+    return history, ""
+
+
+def create_interface():
+    """Create the Gradio interface"""
+    global assistant
+
+    with gr.Blocks(title="DevOps AI Assistant") as interface:
+
+        gr.Markdown("# 🤖 DevOps AI Assistant")
+        gr.Markdown("Intelligent Q&A system for your Kubernetes infrastructure powered by RAG and LLM")
+
+        gr.Markdown("## 🔧 Configuration")
+        gr.Markdown("Enter the path to your GitOps repository (knowledge base) to initialize the assistant")
+
+        with gr.Row():
+            kb_path_input = gr.Textbox(
+                label="Knowledge Base Path",
+                placeholder="/workspace/aau/repositories/infra-gitops/",
+                lines=1,
+                value="/workspace/aau/repositories/infra-gitops/"
+            )
+            init_button = gr.Button("🚀 Initialize Assistant")
+
+        status_output = gr.Markdown(value="⏳ Waiting for initialization...")
+
+        gr.Markdown("## 💬 Chat Interface")
+
+        chatbot = gr.Chatbot(
+            label="Conversation",
+            height=500,
+            show_copy_button=True,
+            avatar_images=("👤", "🤖"),
+            bubble_full_width=False
+        )
+
+        with gr.Row():
+            msg_input = gr.Textbox(
+                label="Your Question",
+                placeholder="Ask about your k8s infrastructure, ArgoCD, Helm charts, etc...",
+                lines=2,
+                scale=5
+            )
+            send_button = gr.Button("Send 💬", scale=1)
+
+        with gr.Row():
+            clear_button = gr.Button("🗑️ Clear Chat", scale=2)
+
+        with gr.Accordion("📋 Example Questions", open=False):
+            gr.Markdown("""
+**Infrastructure & Deployment:**
+- How is the Kubernetes cluster configured?
+- What ArgoCD applications are deployed?
+- Show me the Helm chart values for nginx
+- What storage solutions are available?
+
+**Monitoring & Observability:**
+- How is Prometheus configured?
+- What monitoring exporters are installed?
+- Tell me about the metrics server setup
+
+**Security & Access:**
+- How are RBAC policies configured?
+- What authentication methods are used?
+- Explain the network policies
+
+**DevOps Practices:**
+- What is the deployment pipeline?
+- How are secrets managed?
+- Show me the backup strategy
+            """)
+
+        init_button.click(
+            initialize_assistant,
+            inputs=[kb_path_input],
+            outputs=[status_output]
+        )
+
+        msg_input.submit(
+            chat_with_assistant,
+            inputs=[msg_input, chatbot],
+            outputs=[chatbot, msg_input]
+        )
+
+        send_button.click(
+            chat_with_assistant,
+            inputs=[msg_input, chatbot],
+            outputs=[chatbot, msg_input]
+        )
+
+        clear_button.click(lambda: [], outputs=chatbot)
+
+    return interface
+
+
+def main():
+    """Main entry point"""
+    print("\n" + "=" * 60)
+    print("🚀 DevOps AI Assistant - RAG System")
+    print("=" * 60)
+    print("Starting Gradio server...")
+    print("\nAccess the application at: http://127.0.0.1:7860")
+    print("=" * 60 + "\n")
+
+    interface = create_interface()
+    interface.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=False,
+        show_error=True,
+        show_api=False
+    )
+
+
+if __name__ == "__main__":
+    main()