Use def in FastAPI dashboard calls.

src/codegate/dashboard/dashboard.py

@@ -5,9 +5,8 @@
 from fastapi import APIRouter
 
 from codegate.dashboard.post_processing import (
-    match_conversations,
     parse_get_alert_conversation,
-    parse_get_prompt_with_output,
+    parse_messages_in_conversations,
 )
 from codegate.dashboard.request_models import AlertConversation, Conversation
 from codegate.db.connection import DbReader
@@ -19,31 +18,19 @@
 
 
 @dashboard_router.get("/dashboard/messages")
-async def get_messages() -> List[Conversation]:
+def get_messages() -> List[Conversation]:
     """
     Get all the messages from the database and return them as a list of conversations.
     """
-    prompts_outputs = await db_reader.get_prompts_with_output()
+    prompts_outputs = asyncio.run(db_reader.get_prompts_with_output())
 
-    # Parse the prompts and outputs in parallel
-    async with asyncio.TaskGroup() as tg:
-        tasks = [tg.create_task(parse_get_prompt_with_output(row)) for row in prompts_outputs]
-    partial_conversations = [task.result() for task in tasks]
-
-    conversations = await match_conversations(partial_conversations)
-    return conversations
+    return asyncio.run(parse_messages_in_conversations(prompts_outputs))
 
 
 @dashboard_router.get("/dashboard/alerts")
-async def get_alerts() -> List[AlertConversation]:
+def get_alerts() -> List[AlertConversation]:
     """
     Get all the messages from the database and return them as a list of conversations.
     """
-    alerts_prompt_output = await db_reader.get_alerts_with_prompt_and_output()
-
-    # Parse the prompts and outputs in parallel
-    async with asyncio.TaskGroup() as tg:
-        tasks = [tg.create_task(parse_get_alert_conversation(row)) for row in alerts_prompt_output]
-    alert_conversations = [task.result() for task in tasks if task.result() is not None]
-
-    return alert_conversations
+    alerts_prompt_output = asyncio.run(db_reader.get_alerts_with_prompt_and_output())
+    return asyncio.run(parse_get_alert_conversation(alerts_prompt_output))

src/codegate/dashboard/post_processing.py

@@ -200,7 +200,23 @@ async def match_conversations(
     return conversations
 
 
-async def parse_get_alert_conversation(
+async def parse_messages_in_conversations(
+    prompts_outputs: List[GetPromptWithOutputsRow],
+) -> List[Conversation]:
+    """
+    Get all the messages from the database and return them as a list of conversations.
+    """
+
+    # Parse the prompts and outputs in parallel
+    async with asyncio.TaskGroup() as tg:
+        tasks = [tg.create_task(parse_get_prompt_with_output(row)) for row in prompts_outputs]
+    partial_conversations = [task.result() for task in tasks]
+
+    conversations = await match_conversations(partial_conversations)
+    return conversations
+
+
+async def parse_row_alert_conversation(
     row: GetAlertsWithPromptAndOutputRow,
 ) -> Optional[AlertConversation]:
     """
@@ -220,12 +236,33 @@ async def parse_get_alert_conversation(
         conversation_timestamp=row.timestamp,
     )
     code_snippet = json.loads(row.code_snippet) if row.code_snippet else None
+    trigger_string = None
+    if row.trigger_string:
+        try:
+            trigger_string = json.loads(row.trigger_string)
+        except Exception:
+            trigger_string = row.trigger_string
+
     return AlertConversation(
         conversation=conversation,
         alert_id=row.id,
         code_snippet=code_snippet,
-        trigger_string=row.trigger_string,
+        trigger_string=trigger_string,
         trigger_type=row.trigger_type,
         trigger_category=row.trigger_category,
         timestamp=row.timestamp,
     )
+
+
+async def parse_get_alert_conversation(
+    alerts_conversations: List[GetAlertsWithPromptAndOutputRow],
+) -> List[AlertConversation]:
+    """
+    Parse a list of rows from the get_alerts_with_prompt_and_output query and return a list of
+    AlertConversation
+
+    The rows contain the raw request and output strings from the pipeline.
+    """
+    async with asyncio.TaskGroup() as tg:
+        tasks = [tg.create_task(parse_row_alert_conversation(row)) for row in alerts_conversations]
+    return [task.result() for task in tasks if task.result() is not None]

src/codegate/dashboard/request_models.py

@@ -1,5 +1,5 @@
 import datetime
-from typing import List, Optional
+from typing import List, Optional, Union
 
 from pydantic import BaseModel
 
@@ -57,7 +57,7 @@ class AlertConversation(BaseModel):
     conversation: Conversation
     alert_id: str
     code_snippet: Optional[CodeSnippet]
-    trigger_string: Optional[str]
+    trigger_string: Optional[Union[str, dict]]
     trigger_type: str
     trigger_category: Optional[str]
     timestamp: datetime.datetime

src/codegate/pipeline/codegate_context_retriever/codegate.py

@@ -88,6 +88,10 @@ async def process(
         # Look for matches in vector DB using list of packages as filter
         searched_objects = await self.get_objects_from_search(last_user_message_str, packages)
 
+        logger.info(
+            f"Found {len(searched_objects)} matches in the database",
+            searched_objects=searched_objects,
+        )
         # If matches are found, add the matched content to context
         if len(searched_objects) > 0:
             # Remove searched objects that are not in packages. This is needed

src/codegate/pipeline/system_prompt/codegate.py

@@ -56,6 +56,4 @@ async def process(
             context.add_alert(self.name, trigger_string=prepended_message)
             request_system_message["content"] = prepended_message
 
-        return PipelineResult(
-            request=new_request,
-        )
+        return PipelineResult(request=new_request, context=context)