add human readable result when there is not LLM studio working

backend/app/answer.py

@@ -0,0 +1,11 @@
+from typing import Any
+from typing_extensions import TypedDict
+from app.models.event_model import Event
+
+class Answer(TypedDict):
+  events: list[Event]
+  weather: str
+  pois: list[dict[str, Any]]
+  unesco_sites: list[str]
+  hotels_motels: list[str]
+  historic_places: list[str]

backend/app/api/lmstudio.py

@@ -4,13 +4,20 @@
 import json
 
 from app.config import LMSTUDIO_HOST, LMSTUDIO_ENDPOINT, LMSTUDIO_MODEL
+from app.query_str import generate_ai_style_response
+from app.answer import Answer
 
 class Message(TypedDict):
     role: Literal['user', 'assistant', 'system']
     content: str
 
-def lm_studio_request(messages: list[Message]) -> str:
+def lm_studio_request(message: Answer) -> str:
     full_url = f"http://{LMSTUDIO_HOST}/{LMSTUDIO_ENDPOINT}"
+
+    messages = [
+        { "role": "system", "content": "You are application assistant. Based on given JSON tell what person can visit. Answer in human way like chat assistant talking to a person." },
+        { "role": "user", "content": str(message) }
+    ]
 
     payload = {
         "model": LMSTUDIO_MODEL,
@@ -32,6 +39,5 @@ def lm_studio_request(messages: list[Message]) -> str:
         if response.status_code == 200:
             json_repsonse = response.json()
             return json_repsonse['choices'][0]['message']['content']
-    except:  # noqa: E722
-        return str(messages[1])
-    return str(messages[1])
+    finally:  # noqa: E722
+        return generate_ai_style_response(message["events"], message["weather"])

backend/app/query.py

@@ -9,6 +9,7 @@
     add_message,
     create_new_chat
 )
+from app.answer import Answer
 
 class QueryRequest(BaseModel):
     user_input: str
@@ -74,18 +75,17 @@ def run_query(query: QueryRequest):
         city=city,
     )
     weather_info = query_weather(weather_query)
-
-    if city and city.strip():  
-        unesco_sites = localdatasets.get_unesco_sites(city)
-        hotels_motels = localdatasets.get_hotels_motels(city)
-        historic_places = localdatasets.get_historical_places(city)
+
+    unesco_sites = localdatasets.get_unesco_sites(city)
+    hotels_motels = localdatasets.get_hotels_motels(city)
+    historic_places = localdatasets.get_historical_places(city)
 
     # TODO Implement ammenities keywords extraction in nlp
     amenity = keywords[0] if keywords else "cafe"  # Use first keyword as amenity type or default to "cafe"
     poi_results = overpass.get_poi_data(city, amenity)
 
     # Step 6: Return the compiled response
-    answer = {
+    answer: Answer = {
         "events": event_results,
         "weather": weather_info,
         "pois": poi_results,
@@ -95,10 +95,7 @@ def run_query(query: QueryRequest):
     }
 
     # Step 7: Post-process with LLM to get more human-like response
-    ans = lm_studio_request([
-        { "role": "system", "content": "You are application assistant. Based on given JSON tell what person can visit. Answer in human way like chat assistant talking to a person." },
-        { "role": "user", "content": str(answer) }
-    ])
+    ans = lm_studio_request(answer)
 
     add_message(
         InsertMessage(

backend/app/query_str.py

@@ -0,0 +1,27 @@
+from datetime import datetime
+
+from app.models.event_model import Event
+
+def generate_ai_style_response(events: list[Event], weather: str) -> str:
+  # Sort events by priority and pinned status
+  sorted_events = sorted(events, key=lambda x: (-x.pinned, -x.priority, x.date or datetime.max))
+
+  # Start the response with the weather
+  response = f"The weather for the day is expected to be: {weather}.\n\n"
+
+  # Check if there are any events
+  if not sorted_events:
+    response += "It seems like there are no events scheduled for now. Maybe take the opportunity to relax or explore something spontaneous!"
+  else:
+    response += "Here are some events you might enjoy:\n"
+    for event in sorted_events:
+      event_date = (
+        f" on {event.date.strftime('%A, %B %d at %I:%M %p')}" if event.date else ""
+      )
+      description = ""
+
+      if event.description:
+        description = f" - {description}"
+
+      response += f"- **{event.name}** at {event.location}{event_date}{description}\n"
+  return response.strip()