[RHDHPAI-978] Topic summary of initial query

docs/openapi.json

@@ -744,7 +744,9 @@
                         },
                         "conversations": [
                             {
-                                "conversation_id": "123e4567-e89b-12d3-a456-426614174000"
+                                "conversation_id": "123e4567-e89b-12d3-a456-426614174000",
+                                "topic_summary": "This is a topic summary",
+                                "last_message_timestamp": "2024-01-01T00:00:00Z"
                             }
                         ]
                     }
@@ -1419,6 +1421,37 @@
                 "title": "ConversationCacheConfiguration",
                 "description": "Conversation cache configuration."
             },
+            "ConversationData": {
+                "properties": {
+                    "conversation_id": {
+                        "type": "string",
+                        "title": "Conversation Id"
+                    },
+                    "topic_summary": {
+                        "anyOf": [
+                            {
+                                "type": "string"
+                            },
+                            {
+                                "type": "null"
+                            }
+                        ],
+                        "title": "Topic Summary"
+                    },
+                    "last_message_timestamp": {
+                        "type": "number",
+                        "title": "Last Message Timestamp"
+                    }
+                },
+                "type": "object",
+                "required": [
+                    "conversation_id",
+                    "topic_summary",
+                    "last_message_timestamp"
+                ],
+                "title": "ConversationData",
+                "description": "Model representing conversation data returned by cache list operations.\n\nAttributes:\n    conversation_id: The conversation ID\n    topic_summary: The topic summary for the conversation (can be None)\n    last_message_timestamp: The timestamp of the last message in the conversation"
+            },
             "ConversationDeleteResponse": {
                 "properties": {
                     "conversation_id": {
@@ -1536,14 +1569,29 @@
                             "openai",
                             "gemini"
                         ]
+                    },
+                    "topic_summary": {
+                        "anyOf": [
+                            {
+                                "type": "string"
+                            },
+                            {
+                                "type": "null"
+                            }
+                        ],
+                        "title": "Topic Summary",
+                        "description": "Topic summary for the conversation",
+                        "examples": [
+                            "Openshift Microservices Deployment Strategies"
+                        ]
                     }
                 },
                 "type": "object",
                 "required": [
                     "conversation_id"
                 ],
                 "title": "ConversationDetails",
-                "description": "Model representing the details of a user conversation.\n\nAttributes:\n    conversation_id: The conversation ID (UUID).\n    created_at: When the conversation was created.\n    last_message_at: When the last message was sent.\n    message_count: Number of user messages in the conversation.\n    last_used_model: The last model used for the conversation.\n    last_used_provider: The provider of the last used model.\n\nExample:\n    ```python\n    conversation = ConversationDetails(\n        conversation_id=\"123e4567-e89b-12d3-a456-426614174000\"\n        created_at=\"2024-01-01T00:00:00Z\",\n        last_message_at=\"2024-01-01T00:05:00Z\",\n        message_count=5,\n        last_used_model=\"gemini/gemini-2.0-flash\",\n        last_used_provider=\"gemini\",\n    )\n    ```"
+                "description": "Model representing the details of a user conversation.\n\nAttributes:\n    conversation_id: The conversation ID (UUID).\n    created_at: When the conversation was created.\n    last_message_at: When the last message was sent.\n    message_count: Number of user messages in the conversation.\n    last_used_model: The last model used for the conversation.\n    last_used_provider: The provider of the last used model.\n    topic_summary: The topic summary for the conversation.\n\nExample:\n    ```python\n    conversation = ConversationDetails(\n        conversation_id=\"123e4567-e89b-12d3-a456-426614174000\"\n        created_at=\"2024-01-01T00:00:00Z\",\n        last_message_at=\"2024-01-01T00:05:00Z\",\n        message_count=5,\n        last_used_model=\"gemini/gemini-2.0-flash\",\n        last_used_provider=\"gemini\",\n        topic_summary=\"Openshift Microservices Deployment Strategies\",\n    )\n    ```"
             },
             "ConversationResponse": {
                 "properties": {
@@ -1604,7 +1652,7 @@
                     "conversations"
                 ],
                 "title": "ConversationsListResponse",
-                "description": "Model representing a response for listing conversations of a user.\n\nAttributes:\n    conversations: List of conversation details associated with the user.\n\nExample:\n    ```python\n    conversations_list = ConversationsListResponse(\n        conversations=[\n            ConversationDetails(\n                conversation_id=\"123e4567-e89b-12d3-a456-426614174000\",\n                created_at=\"2024-01-01T00:00:00Z\",\n                last_message_at=\"2024-01-01T00:05:00Z\",\n                message_count=5,\n                last_used_model=\"gemini/gemini-2.0-flash\",\n                last_used_provider=\"gemini\",\n            ),\n            ConversationDetails(\n                conversation_id=\"456e7890-e12b-34d5-a678-901234567890\"\n                created_at=\"2024-01-01T01:00:00Z\",\n                message_count=2,\n                last_used_model=\"gemini/gemini-2.0-flash\",\n                last_used_provider=\"gemini\",\n            )\n        ]\n    )\n    ```",
+                "description": "Model representing a response for listing conversations of a user.\n\nAttributes:\n    conversations: List of conversation details associated with the user.\n\nExample:\n    ```python\n    conversations_list = ConversationsListResponse(\n        conversations=[\n            ConversationDetails(\n                conversation_id=\"123e4567-e89b-12d3-a456-426614174000\",\n                created_at=\"2024-01-01T00:00:00Z\",\n                last_message_at=\"2024-01-01T00:05:00Z\",\n                message_count=5,\n                last_used_model=\"gemini/gemini-2.0-flash\",\n                last_used_provider=\"gemini\",\n                topic_summary=\"Openshift Microservices Deployment Strategies\",\n            ),\n            ConversationDetails(\n                conversation_id=\"456e7890-e12b-34d5-a678-901234567890\"\n                created_at=\"2024-01-01T01:00:00Z\",\n                message_count=2,\n                last_used_model=\"gemini/gemini-2.0-flash\",\n                last_used_provider=\"gemini\",\n                topic_summary=\"RHDH Purpose Summary\",\n            )\n        ]\n    )\n    ```",
                 "examples": [
                     {
                         "conversations": [
@@ -1614,14 +1662,16 @@
                                 "last_message_at": "2024-01-01T00:05:00Z",
                                 "last_used_model": "gemini/gemini-2.0-flash",
                                 "last_used_provider": "gemini",
-                                "message_count": 5
+                                "message_count": 5,
+                                "topic_summary": "Openshift Microservices Deployment Strategies"
                             },
                             {
                                 "conversation_id": "456e7890-e12b-34d5-a678-901234567890",
                                 "created_at": "2024-01-01T01:00:00Z",
                                 "last_used_model": "gemini/gemini-2.5-flash",
                                 "last_used_provider": "gemini",
-                                "message_count": 2
+                                "message_count": 2,
+                                "topic_summary": "RHDH Purpose Summary"
                             }
                         ]
                     }
@@ -1631,7 +1681,7 @@
                 "properties": {
                     "conversations": {
                         "items": {
-                            "type": "string"
+                            "$ref": "#/components/schemas/ConversationData"
                         },
                         "type": "array",
                         "title": "Conversations"
@@ -1642,7 +1692,7 @@
                     "conversations"
                 ],
                 "title": "ConversationsListResponseV2",
-                "description": "Model representing a response for listing conversations of a user.\n\nAttributes:\n    conversations: List of conversation IDs associated with the user."
+                "description": "Model representing a response for listing conversations of a user.\n\nAttributes:\n    conversations: List of conversation data associated with the user."
             },
             "CustomProfile": {
                 "properties": {

src/app/endpoints/conversations.py

@@ -214,6 +214,7 @@ async def get_conversations_list_endpoint_handler(
                     message_count=conv.message_count,
                     last_used_model=conv.last_used_model,
                     last_used_provider=conv.last_used_provider,
+                    topic_summary=conv.topic_summary,
                 )
                 for conv in user_conversations
             ]

src/app/endpoints/conversations_v2.py

@@ -83,6 +83,8 @@
         "conversations": [
             {
                 "conversation_id": "123e4567-e89b-12d3-a456-426614174000",
+                "topic_summary": "This is a topic summary",
+                "last_message_timestamp": "2024-01-01T00:00:00Z",
             }
         ]
     }
@@ -102,6 +104,8 @@ async def get_conversations_list_endpoint_handler(
 
     logger.info("Retrieving conversations for user %s", user_id)
 
+    skip_userid_check = auth[2]
+
     if configuration.conversation_cache is None:
         logger.warning("Converastion cache is not configured")
         raise HTTPException(
@@ -112,7 +116,7 @@ async def get_conversations_list_endpoint_handler(
             },
         )
 
-    conversations = configuration.conversation_cache.list(user_id, False)
+    conversations = configuration.conversation_cache.list(user_id, skip_userid_check)
     logger.info("Conversations for user %s: %s", user_id, len(conversations))
 
     return ConversationsListResponseV2(conversations=conversations)
@@ -132,6 +136,8 @@ async def get_conversation_endpoint_handler(
     user_id = auth[0]
     logger.info("Retrieving conversation %s for user %s", conversation_id, user_id)
 
+    skip_userid_check = auth[2]
+
     if configuration.conversation_cache is None:
         logger.warning("Converastion cache is not configured")
         raise HTTPException(
@@ -144,7 +150,9 @@ async def get_conversation_endpoint_handler(
 
     check_conversation_existence(user_id, conversation_id)
 
-    conversation = configuration.conversation_cache.get(user_id, conversation_id, False)
+    conversation = configuration.conversation_cache.get(
+        user_id, conversation_id, skip_userid_check
+    )
     chat_history = [transform_chat_message(entry) for entry in conversation]
 
     return ConversationResponse(
@@ -168,6 +176,8 @@ async def delete_conversation_endpoint_handler(
     user_id = auth[0]
     logger.info("Deleting conversation %s for user %s", conversation_id, user_id)
 
+    skip_userid_check = auth[2]
+
     if configuration.conversation_cache is None:
         logger.warning("Converastion cache is not configured")
         raise HTTPException(
@@ -181,7 +191,9 @@ async def delete_conversation_endpoint_handler(
     check_conversation_existence(user_id, conversation_id)
 
     logger.info("Deleting conversation %s for user %s", conversation_id, user_id)
-    deleted = configuration.conversation_cache.delete(user_id, conversation_id, False)
+    deleted = configuration.conversation_cache.delete(
+        user_id, conversation_id, skip_userid_check
+    )
 
     if deleted:
         return ConversationDeleteResponse(
@@ -215,7 +227,8 @@ def check_conversation_existence(user_id: str, conversation_id: str) -> None:
     if configuration.conversation_cache is None:
         return
     conversations = configuration.conversation_cache.list(user_id, False)
-    if conversation_id not in conversations:
+    conversation_ids = [conv.conversation_id for conv in conversations]
+    if conversation_id not in conversation_ids:
         logger.error("No conversation found for conversation ID %s", conversation_id)
         raise HTTPException(
             status_code=status.HTTP_404_NOT_FOUND,

src/app/endpoints/query.py

@@ -46,6 +46,8 @@
 from utils.endpoints import (
     check_configuration_loaded,
     get_agent,
+    get_topic_summary_system_prompt,
+    get_temp_agent,
     get_system_prompt,
     store_conversation_into_cache,
     validate_conversation_ownership,
@@ -98,7 +100,11 @@ def is_transcripts_enabled() -> bool:
 
 
 def persist_user_conversation_details(
-    user_id: str, conversation_id: str, model: str, provider_id: str
+    user_id: str,
+    conversation_id: str,
+    model: str,
+    provider_id: str,
+    topic_summary: Optional[str],
 ) -> None:
     """Associate conversation to user in the database."""
     with get_session() as session:
@@ -112,6 +118,7 @@ def persist_user_conversation_details(
                 user_id=user_id,
                 last_used_model=model,
                 last_used_provider=provider_id,
+                topic_summary=topic_summary,
                 message_count=1,
             )
             session.add(conversation)
@@ -169,9 +176,42 @@ def evaluate_model_hints(
     return model_id, provider_id
 
 
+async def get_topic_summary(
+    question: str, client: AsyncLlamaStackClient, model_id: str
+) -> str:
+    """Get a topic summary for a question.
+
+    Args:
+        question: The question to be validated.
+        client: The AsyncLlamaStackClient to use for the request.
+        model_id: The ID of the model to use.
+    Returns:
+        str: The topic summary for the question.
+    """
+    topic_summary_system_prompt = get_topic_summary_system_prompt(configuration)
+    agent, session_id, _ = await get_temp_agent(
+        client, model_id, topic_summary_system_prompt
+    )
+    response = await agent.create_turn(
+        messages=[UserMessage(role="user", content=question)],
+        session_id=session_id,
+        stream=False,
+        toolgroups=None,
+    )
+    response = cast(Turn, response)
+    return (
+        interleaved_content_as_str(response.output_message.content)
+        if (
+            getattr(response, "output_message", None) is not None
+            and getattr(response.output_message, "content", None) is not None
+        )
+        else ""
+    )
+
+
 @router.post("/query", responses=query_response)
 @authorize(Action.QUERY)
-async def query_endpoint_handler(
+async def query_endpoint_handler(  # pylint: disable=R0914
     request: Request,
     query_request: QueryRequest,
     auth: Annotated[AuthTuple, Depends(auth_dependency)],
@@ -200,7 +240,7 @@ async def query_endpoint_handler(
     # log Llama Stack configuration
     logger.info("Llama stack config: %s", configuration.llama_stack_configuration)
 
-    user_id, _, _, token = auth
+    user_id, _, _skip_userid_check, token = auth
 
     user_conversation: UserConversation | None = None
     if query_request.conversation_id:
@@ -251,6 +291,16 @@ async def query_endpoint_handler(
         # Update metrics for the LLM call
         metrics.llm_calls_total.labels(provider_id, model_id).inc()
 
+        # Get the initial topic summary for the conversation
+        topic_summary = None
+        with get_session() as session:
+            existing_conversation = (
+                session.query(UserConversation).filter_by(id=conversation_id).first()
+            )
+            if not existing_conversation:
+                topic_summary = await get_topic_summary(
+                    query_request.query, client, model_id
+                )
         # Convert RAG chunks to dictionary format once for reuse
         logger.info("Processing RAG chunks...")
         rag_chunks_dict = [chunk.model_dump() for chunk in summary.rag_chunks]
@@ -278,6 +328,7 @@ async def query_endpoint_handler(
             conversation_id=conversation_id,
             model=model_id,
             provider_id=provider_id,
+            topic_summary=topic_summary,
         )
 
         store_conversation_into_cache(
@@ -288,6 +339,8 @@ async def query_endpoint_handler(
             model_id,
             query_request.query,
             summary.llm_response,
+            _skip_userid_check,
+            topic_summary,
         )
 
         # Convert tool calls to response format