Pash1986 commited on
Commit
3c111c9
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1 Parent(s): d880a07

Update app.py

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Files changed (1) hide show
  1. app.py +6 -3
app.py CHANGED
@@ -42,14 +42,17 @@ def get_restaurants(search, location, meters):
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  restaurant_docs = list(trips_collection.aggregate([vectorQuery, {"$project": {"_id": 0, "embedding": 0}}]))
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- chat_response = openai_client.chat.completions.create(
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  model="gpt-4o",
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  messages=[
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  {"role": "system", "content": "You are a helpful restaurant assistant. Answer shortly and quickly. You will get a context if the context is not relevant to the user query please address that and not provide by default the restaurants as is."},
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  {"role": "user", "content": f"Find me the 2 best restaurant and why based on {search} and {restaurant_docs}. Shortly explain trades offs and why I should go to each one. You can mention the third option as a possible alternative in one sentence."}
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- ]
 
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  )
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  trips_collection.delete_many({"searchTrip": newTrip})
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  if len(restaurant_docs) == 0:
@@ -112,7 +115,7 @@ if st.button("Get Restaurants"):
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  location_value = location['value']
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  result, iframe, pre_agg, vectorQuery = get_restaurants(search, location_value, meters)
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  if result:
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- st.markdown(result)
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  st.markdown(iframe, unsafe_allow_html=True)
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  st.json(pre_agg)
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  st.json(vectorQuery)
 
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  restaurant_docs = list(trips_collection.aggregate([vectorQuery, {"$project": {"_id": 0, "embedding": 0}}]))
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+ stream_response = openai_client.chat.completions.create(
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  model="gpt-4o",
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  messages=[
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  {"role": "system", "content": "You are a helpful restaurant assistant. Answer shortly and quickly. You will get a context if the context is not relevant to the user query please address that and not provide by default the restaurants as is."},
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  {"role": "user", "content": f"Find me the 2 best restaurant and why based on {search} and {restaurant_docs}. Shortly explain trades offs and why I should go to each one. You can mention the third option as a possible alternative in one sentence."}
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+ ],
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+ stream=True
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  )
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+ chat_response = st.write_stream(stream_response)
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+
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  trips_collection.delete_many({"searchTrip": newTrip})
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  if len(restaurant_docs) == 0:
 
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  location_value = location['value']
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  result, iframe, pre_agg, vectorQuery = get_restaurants(search, location_value, meters)
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  if result:
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+
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  st.markdown(iframe, unsafe_allow_html=True)
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  st.json(pre_agg)
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  st.json(vectorQuery)