fix(chats): filter messages to include only relevant user and assistant content in chat retrieval

fix(message): change links type from HttpUrl to string for consistency
fix(agent): ensure links are converted to strings when structuring output

api/routers/chats.py

@@ -69,7 +69,18 @@ def get_user_chats(*, db: Session = Depends(get_db), user_id: uuid.UUID = Depend
 def get_single_chat_with_messages(*, chat_id: uuid.UUID, user_id: uuid.UUID = Depends(get_current_user), db: Session = Depends(get_db)):
     """Retrieves a specific chat with all its messages."""
     chat = get_chat_for_user(chat_id, user_id, db)
-    return chat
+    filtered_messages = [
+        msg for msg in chat.messages
+        if msg.role == 'user' or (msg.role == 'assistant' and msg.content)
+    ]
+
+    return ChatReadWithMessages(
+        id=chat.id,
+        title=chat.title,
+        created_at=chat.created_at,
+        updated_at=chat.updated_at,
+        messages=filtered_messages
+    )
 
 @router.patch("/{chat_id}", response_model=ChatReadSimple)
 def rename_chat(*, chat_id: uuid.UUID, chat_update: ChatUpdate, user_id: uuid.UUID = Depends(get_current_user), db: Session = Depends(get_db)):
@@ -117,7 +128,6 @@ async def post_message_and_get_response(
     final_answer = response["answer"]
     links = response["links"]
     updated_messages_from_agent = response["messages"]
-
     # 6. Isolate the messages that are new to this turn
     new_lc_messages = updated_messages_from_agent[initial_message_count - 1:]
 
@@ -137,5 +147,4 @@ async def post_message_and_get_response(
 
     # 9. Find the final AI message from the list of newly saved messages.
     final_ai_message = newly_created_db_messages[-1]
-    
     return final_ai_message

db/schemas/message.py

@@ -1,6 +1,6 @@
 import uuid
 from datetime import datetime
-from pydantic import BaseModel, Field, HttpUrl, computed_field
+from pydantic import BaseModel, Field, computed_field
 from typing import Optional
 
 # -------------------
@@ -17,7 +17,7 @@ class MessageRead(BaseModel):
     role: str
     created_at: datetime
 
-    links: Optional[list[HttpUrl]] = None
+    links: Optional[list[str]] = None
 
     raw_content: Optional[str] = Field(None, alias='content', exclude=True)
     answer: Optional[str] = Field(None, alias='answer', exclude=True)

workflow/agent.py

@@ -44,14 +44,14 @@ def agent(messages: list[BaseMessage], config: RunnableConfig):
 
     # Check if any tools other than search_memories were called
     other_tools_called = any(name != "search_memories" for name in tool_names_called)
-
+    
     if tool_calls_count > 0 and other_tools_called:
         # Structure the final output
         structured_output = (
             get_structued_output(llm_response.content).result().model_dump()
         )
         answer = structured_output["text"]
-        links = structured_output.get("links", [])
+        links = [str(link) for link in structured_output.get("links", [])]
     else:
         answer = llm_response.content