updated code for marketplace readiness

Author: nitinaggarwal-databricks

agent_genie/app.yaml

@@ -2,12 +2,14 @@ command: [
   "uvicorn",
   "app:app",
   "--host",
-  "127.0.0.1",
+  "0.0.0.0",
   "--port",
   "8000"
 ]
 env:
   - name: "SPACE_ID"
-    value: genie-space
+    valueFrom: genie-space
   - name: "SERVING_ENDPOINT_NAME"
-    value: serving-endpoint
+    valueFrom: serving-endpoint
+  - name: "TAVILY_API_KEY"
+    value: "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"

agent_genie/manual_ai_content.py

@@ -35,8 +35,8 @@
                             description,
                             ai_classify(description, ARRAY('clothing', 'shoes', 'accessories', 'furniture')) AS category
                         FROM
-                            products
-                        ;""",
+                            products;
+                        shoes""",
 
     "ai_extract": """Syntax
                         ai_extract(content, labels)
@@ -101,15 +101,13 @@
                             Summer Bike Sale: Grab Your Dream Bike at 20% Off!
 
                             > SELECT
-                                question,
+                                'What is the impact of AI on reducing hospital readmissions?',
                                 ai_gen(
-                                'You are a teacher. Answer the students question in 50 words: ' || question
+                                'Answer the question: ' || 'What is the impact of AI on reducing hospital readmissions?'
                                 ) AS answer
                             FROM
-                                questions
-                            ;
-
-                            """,
+                                questions;
+                            AI helps identify high-risk patients early by analyzing EHR data, lifestyle, and treatment patterns. Predictive models enable proactive care coordination and follow-up, reducing avoidable hospital readmissions and improving patient outcomes while optimizing resource utilization and lowering costs.""",
     "ai_mask": """Syntax
                             ai_mask(content, labels)
 
@@ -244,10 +242,8 @@
                                 horizon => '2016-03-31',
                                 time_col => 'ds',
                                 value_col => 'revenue'
-                                );
-                                                                    
-                                                                                                """,
-                "ai_query": """Syntax
+                                );""",
+    "ai_query": """Syntax
                                 To query an endpoint that serves a foundation model:
 
                                 ai_query(endpoint, request)
@@ -262,4 +258,4 @@
                                 FROM uc_catalog.schema.table;
 
                                 """  # For general predictive queries
-}
+}

agent_genie/templates/index.html

@@ -1348,7 +1348,7 @@ <h1>Databricks Genie++ Omni-Analytics Platform</h1>
         </div>
 
         <div class="section-description">
-            A multi-agent AI engine that answers questions, forecasts trends, classifies data, summarizes records, translates languages, and recommends next-best actions.
+            A multi-agent AI engine that answers questions, forecasts trends, classifies data, summarizes records, translates languages, and recommends next-best actions. For any questions or feedback, please reach out to nitin.aggarwal@databricks.com 
         </div>
 
         <!-- Collapsible Elements Container -->
@@ -1430,8 +1430,8 @@ <h1>Databricks Genie++ Omni-Analytics Platform</h1>
                             <button onclick="askFixedQuestion('Summarize the record into Spanish')">
                                 Summarize the record into Spanish
                             </button>
-                            <button onclick="askFixedQuestion('Classify each record into categories: High, Medium, and Low. Also, specify the reason')">
-                                Classify each record using categories: High, Medium, and Low. Also, specify the reason
+                            <button onclick="askFixedQuestion('Classify each record into categories: High, Medium, Low and specify the reason')">
+                                Classify each record into categories: High, Medium, Low and specify the reason
                             </button>
                             <button onclick="askFixedQuestion('Summarize the record, and suggest one next best action for the analyst supporting the business')">
                                 Summarize the record, and suggest one next best action for the analyst supporting the business
@@ -2645,4 +2645,4 @@ <h1>Databricks Genie++ Omni-Analytics Platform</h1>
         });
     </script>
 </body>
-</html>
+</html>

agent_genie_git_old/.databricks/bundle/dev/vscode.bundlevars.json

@@ -0,0 +1 @@
+{}

agent_genie_git_old/.databricks/bundle/dev/vscode.overrides.json

@@ -0,0 +1 @@
+{}

agent_genie_git_old/CODEOWNERS

@@ -0,0 +1,22 @@
+# There can be only one CODEOWNERS file in the repo for clarity. See https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners#codeowners-file-location
+
+# Catch-all rule comes first
+
+* @databrickslabs/sandbox-write
+
+# Specific owners are listed last. Please keep this list in the alphabetical order
+
+acceptance                 @nfx @alexott
+conversational-agent-app   @vivian-xie-db @yuanchaoma-db
+database-diagram-builder   @alexott
+downstreams                @nfx @alexott
+feature-registry-app       @yang-chengg @mparkhe @mingyangge-db @stephanielu5
+go-libs                    @nfx @alexott
+ip_access_list_analyzer    @alexott
+ka-chat-bot                @taiga-db
+metascan                   @nfx @alexott
+runtime-packages           @nfx @alexott
+sql_migration_copilot      @robertwhiffin
+tacklebox                  @Jonathan-Choi
+uc-catalog-cloning         @esiol-db @vasco-lopes
+.github                    @nfx @alexott @gueniai

agent_genie_git_old/app.py

@@ -0,0 +1,156 @@
+import os
+import json
+import requests
+from flask import Flask, render_template, request, jsonify
+from databricks.sdk.core import Config
+from databricks.sdk import WorkspaceClient
+from databricks.sdk.service.serving import ChatMessage, ChatMessageRole
+
+# Initialize Flask app
+app = Flask(__name__, static_folder='static', template_folder='static')
+
+cfg = Config()
+client = WorkspaceClient()
+
+# Model serving endpoint name
+ENDPOINT_NAME = "agents_ws_vfc_demo-sch_vfc_demo-fashion_merchandising_agent"
+
+@app.route('/')
+def index():
+    """Serve the main HTML page"""
+    return render_template('index.html')
+
+@app.route('/api/chat', methods=['POST'])
+def chat():
+    """Handle chat requests and forward to model serving endpoint using Databricks SDK"""
+    try:
+        # Get the message history from the request
+        data = request.get_json()
+        messages = data.get('messages', [])
+        
+        if not messages:
+            return jsonify({'error': 'No messages provided'}), 400
+        
+        # Convert messages to ChatMessage objects
+        chat_messages = []
+        for msg in messages:
+            role = msg.get('role', 'user')
+            content = msg.get('content', '')
+            
+            # Map roles to ChatMessageRole enum
+            if role == 'user':
+                chat_role = ChatMessageRole.USER
+            elif role == 'assistant':
+                chat_role = ChatMessageRole.ASSISTANT
+            elif role == 'system':
+                chat_role = ChatMessageRole.SYSTEM
+            else:
+                chat_role = ChatMessageRole.USER  # Default to user
+            
+            chat_messages.append(ChatMessage(role=chat_role, content=content))
+        
+        # Get user information for logging
+        user_email = request.headers.get('X-Forwarded-Email')
+        app.logger.info(f"Making request to model endpoint for user: {user_email}")
+        
+        # Make request to model serving endpoint using Databricks SDK
+        response = client.serving_endpoints.query(
+            name=ENDPOINT_NAME,
+            messages=chat_messages
+        )
+        
+        # Extract the response content
+        if response and hasattr(response, 'choices') and response.choices:
+            # Get the first choice
+            choice = response.choices[0]
+            if hasattr(choice, 'message') and choice.message:
+                result_content = choice.message.content
+                return jsonify({'content': result_content})
+            else:
+                return jsonify({'error': 'No message content in response'}), 500
+        else:
+            return jsonify({'error': 'No response choices received'}), 500
+            
+    except Exception as e:
+        error_msg = str(e)
+        app.logger.error(f"Error calling model endpoint: {error_msg}")
+        
+        # Handle specific error types
+        if "authentication" in error_msg.lower() or "unauthorized" in error_msg.lower():
+            return jsonify({
+                'error': 'Authentication failed. Your Databricks token may have expired.',
+                'details': 'Please refresh the page or log in again.'
+            }), 401
+        elif "permission" in error_msg.lower() or "forbidden" in error_msg.lower():
+            return jsonify({
+                'error': 'Access denied. You may not have permission to access this model endpoint.',
+                'details': 'Please contact your Databricks administrator.'
+            }), 403
+        elif "timeout" in error_msg.lower():
+            return jsonify({'error': 'Request timed out. Please try again.'}), 504
+        else:
+            return jsonify({
+                'error': f'Unexpected error: {error_msg}',
+                'details': 'Please try again or contact support if the issue persists.'
+            }), 500
+
+@app.route('/health')
+def health():
+    """Health check endpoint"""
+    user_email = request.headers.get('X-Forwarded-Email')
+    
+    try:
+        # Test the client connection
+        client.current_user.me()
+        client_healthy = True
+    except Exception as e:
+        client_healthy = False
+        app.logger.error(f"Client health check failed: {str(e)}")
+    
+    return jsonify({
+        'status': 'healthy',
+        'client_authenticated': client_healthy,
+        'user_email': user_email if user_email else 'anonymous',
+        'endpoint_name': ENDPOINT_NAME
+    })
+
+@app.route('/api/debug')
+def debug():
+    """Debug endpoint to check authentication and endpoint status"""
+    headers_info = {
+        'X-Forwarded-Access-Token': 'present' if request.headers.get('X-Forwarded-Access-Token') else 'missing',
+        'X-Forwarded-Email': request.headers.get('X-Forwarded-Email', 'not provided'),
+        'User-Agent': request.headers.get('User-Agent', 'not provided'),
+        'Authorization': 'present' if request.headers.get('Authorization') else 'missing'
+    }
+    
+    try:
+        # Check if we can access the serving endpoint
+        endpoint_info = client.serving_endpoints.get(name=ENDPOINT_NAME)
+        endpoint_status = endpoint_info.state.value if endpoint_info.state else 'unknown'
+    except Exception as e:
+        endpoint_status = f'error: {str(e)}'
+    
+    try:
+        # Check current user
+        current_user = client.current_user.me()
+        user_info = current_user.user_name if current_user else 'unknown'
+    except Exception as e:
+        user_info = f'error: {str(e)}'
+    
+    return jsonify({
+        'message': 'Debug information for Databricks App',
+        'headers': headers_info,
+        'endpoint_name': ENDPOINT_NAME,
+        'endpoint_status': endpoint_status,
+        'current_user': user_info,
+        'sdk_config': {
+            'host': cfg.host if hasattr(cfg, 'host') else 'not set',
+            'auth_type': cfg.auth_type if hasattr(cfg, 'auth_type') else 'not set'
+        }
+    })
+
+if __name__ == '__main__':
+    # Get port from environment variable or default to 8080
+    port = int(os.environ.get('PORT', 8080))
+    app.run(host='0.0.0.0', port=port, debug=False)

agent_genie_git_old/app.yaml

@@ -0,0 +1,15 @@
+command: [
+  "uvicorn",
+  "app:app",
+  "--host",
+  "127.0.0.1",
+  "--port",
+  "8000"
+]
+env:
+  - name: "SPACE_ID"
+    value: "01f03de6df76113387ccc36242e6c804"
+  - name: "SERVING_ENDPOINT_NAME"
+    value: "databricks-gpt-oss-120b"
+  - name: "TAVILY_API_KEY"
+    value: "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"

agent_genie_git_old/databricks.yml

@@ -0,0 +1,95 @@
+bundle:
+  name: agent-genie-app
+
+variables:
+  project_name:
+    description: "Display name for the app"
+    default: "agent-genie"
+
+  # Env-only fallback; will also be persisted to a secret by the installer job if possible
+  tavily_api_key:
+    description: "Tavily API key (installer job will try to store in a secret scope)"
+    default: ""
+
+  # Where to persist the secret (customize if you already have a scope)
+  secret_scope:
+    description: "Workspace secret scope to store Tavily key"
+    default: "agent_genie_secrets"
+
+  secret_key:
+    description: "Secret key name for Tavily key inside the scope"
+    default: "TAVILY_API_KEY"
+
+  environment:
+    description: "Deployment environment (dev, staging, prod)"
+    default: "dev"
+
+targets:
+  dev:
+    default: true
+    mode: development
+
+resources:
+  apps:
+    agent_genie:
+      name: "${var.project_name}"
+      description: "FastAPI app with Genie + Serving Endpoint integration"
+      source_code_path: "."
+
+      command: [
+        "uvicorn",
+        "app:app",
+        "--host",
+        "127.0.0.1",
+        "--port",
+        "8000"
+      ]
+
+      # Inject env for your app at runtime
+      env:
+        - name: "SPACE_ID"
+          value_from: "genie-space"
+        - name: "SERVING_ENDPOINT_NAME"
+          value_from: "serving-endpoint"
+        - name: "TAVILY_API_KEY"
+          value: "${var.tavily_api_key}"   # app can use this directly; secret is optional hardening
+
+      # --- App Resources (end-user picks these at install) ---
+      app_resources:
+        - key: "serving-endpoint"
+          serving_endpoint_spec:
+            permission: "CAN_QUERY"
+        - key: "genie-space"
+          genie_space_spec:
+            permission: "CAN_RUN"
+
+      # --- User Authorized Scopes (Preview) ---
+      user_authorized_scopes:
+        - "sql"
+        - "dashboards.genie"
+        - "files.files"
+        - "serving.serving-endpoints"
+        - "vectorsearch.vector-search-indexes"
+        - "catalog.connections"
+
+  # --- Installer job to persist Tavily key into a secret and write optional config ---
+  jobs:
+    install_app:
+      name: "${var.project_name} - Install/Configure"
+      tasks:
+        - task_key: configure_app
+          notebook_task:
+            notebook_path: "./notebooks/setup_app"   # create this notebook
+            base_parameters:
+              TAVILY_API_KEY: "${var.tavily_api_key}"
+              SECRET_SCOPE: "${var.secret_scope}"
+              SECRET_KEY: "${var.secret_key}"
+          # Add compute for your workspace (example placeholders):
+          # existing_cluster_id: "<your-cluster-id>"
+          # OR:
+          # job_clusters:
+          #   - job_cluster_key: "install_cluster"
+          #     new_cluster:
+          #       spark_version: "14.3.x-scala2.12"
+          #       node_type_id: "i3.xlarge"
+          #       num_workers: 0