Update app.py

app.py

@@ -44,38 +44,14 @@ KNOWN_MODELS = [
 
 def recommend_ai_model_via_gpt(description, dataset_description):
     combined_description = f"{description} Dataset: {dataset_description}"
-    messages = [
-        {"role": "user", "content": combined_description}
-    ]
-    response = openai.ChatCompletion.create(
-        model="gpt-4",
-        messages=messages
-    )
+    messages = [{"role": "user", "content": combined_description}]
+    response = openai.ChatCompletion.create(model="gpt-4", messages=messages)
     return response['choices'][0]['message']['content'].strip()
 
-    #except openai.APIError as e:
-    #    return f"Error: {e}"
-    #except openai.RateLimitError as e:
-    #    return f"Rate limit exceeded: {e}"
-    #except openai.APIConnectionError as e:
-    #    return f"Connection error: {e}"
-
-
 def explain_recommendation(model_name):
-    messages = [
-        {"role": "user", "content": f"Why would {model_name} be a suitable choice for the application?"}
-    ]
-    response = openai.ChatCompletion.create(
-        model="gpt-4",
-        messages=messages
-    )
+    messages = [{"role": "user", "content": f"Why would {model_name} be a suitable choice for the application?"}]
+    response = openai.ChatCompletion.create(model="gpt-4", messages=messages)
     return response['choices'][0]['message']['content'].strip()
-    #except openai.APIError as e:
-    #    return f"Error: {e}"
-    #except openai.RateLimitError as e:
-    #    return f"Rate limit exceeded: {e}"
-    #except openai.APIConnectionError as e:
-    #    return f"Connection error: {e}"
 
 # Streamlit UI
 st.image("./A8title2.png")
@@ -85,39 +61,18 @@ description = st.text_area("Describe your application:")
 
 if description:
     dataset_description = st.text_area("Describe the dataset you want to use for fine-tuning your model:")
-
     if dataset_description:
         if st.button("Recommend AI Model", key="recommend_model_button"):
             recommended_model = recommend_ai_model_via_gpt(description, dataset_description)
             st.subheader(f"Recommended: {recommended_model}")
-
-            recommendation_type = st.radio("What type of recommendation are you looking for?", ["Recommend Open-Source Model", "Recommend API Service"])
-
-if "rec_model_pressed" not in st.session_state:
-    st.session_state.rec_model_pressed = False
-
-if "feedback_submitted" not in st.session_state:
-    st.session_state.feedback_submitted = False
-
-if st.button("Recommend AI Model", key="another_unique_key"):
-    st.session_state.rec_model_pressed = True
-
-if st.session_state.rec_model_pressed:
-    if description and dataset_description:
-        combined_query = f"{description} Dataset: {dataset_description}"
-        recommended_model = recommend_ai_model_via_gpt(combined_query)
-        st.subheader(f"Recommended: {recommended_model}")
-        explanation = explain_recommendation(recommended_model)
-        st.write("Reason:", explanation)
-        
-        rating = st.slider("Rate the explanation from 1 (worst) to 5 (best):", 1, 5)
-        feedback = st.text_input("Any additional feedback?")
-
-        if st.button("Submit Feedback", key="submit_feedback_key"):
-            st.session_state.feedback_submitted = True
-
-        if st.session_state.feedback_submitted:
-            st.success("Thank you for your feedback!")
+            explanation = explain_recommendation(recommended_model)
+            st.write("Reason:", explanation)
+            rating = st.slider("Rate the explanation from 1 (worst) to 5 (best):", 1, 5)
+            feedback = st.text_input("Any additional feedback?")
+            if st.button("Submit Feedback", key="submit_feedback_key"):
+                st.session_state.feedback_submitted = True
+                if st.session_state.feedback_submitted:
+                    st.success("Thank you for your feedback!")
 
 else:
     st.warning("Please provide a description and dataset details.")