Update app.py

app.py

@@ -42,54 +42,34 @@ KNOWN_MODELS = [
     "Attention Mechanisms", "Named Entity Recognition", "Text Summarization"
 ]
 
-def recommend_ai_model_via_gpt(description, dataset_description):
-    combined_description = f"{description} Dataset: {dataset_description}"
-    messages = [{"role": "user", "content": combined_description}]
+def recommend_ai_model_via_gpt(description):
+    messages = [{"role": "user", "content": description}]
     response = openai.ChatCompletion.create(model="gpt-4", messages=messages)
     return response['choices'][0]['message']['content'].strip()
 
 def explain_recommendation(model_name):
-    messages = [{"role": "user", "content": f"Why would {model_name} be a suitable choice for the application?"}]
+    messages = [{"role": "user", "content": f"Why is {model_name} the best choice for my application?"}]
     response = openai.ChatCompletion.create(model="gpt-4", messages=messages)
     return response['choices'][0]['message']['content'].strip()
 
 # Streamlit UI
-if 'show_dataset_description' not in st.session_state:
-    st.session_state.show_dataset_description = False
-
 st.image("./A8title.png")
 st.title('Discover the best model for your GenAI App')
 
-# Inserting blank space
-st.write("")
-st.write("")
 st.write("")
 
-st.markdown("<h4 style='font-size:20px;'>Outline below your app's functionality:</h4>", unsafe_allow_html=True)
+st.markdown("<h4 style='font-size:20px;'>Outline Your Application's Functionality:</h4>", unsafe_allow_html=True)
 description = st.text_area("", key="app_description")
 
 if description:
-    if st.button("Next", key="next_to_dataset"):
-        st.session_state.show_dataset_description = True
-
-if 'show_dataset_description' in st.session_state and st.session_state.show_dataset_description:
-    st.write("")
-    st.write("")
-    st.write("")
-    st.markdown("<h4 style='font-size:20px;'>Detail your dataset for fine-tuning this model:</h4>", unsafe_allow_html=True)
-    dataset_description = st.text_area("", key="dataset_description")
-    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}")
-            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 of your application.")
+    if st.button("Recommend AI Model", key="recommend_model_button"):
+        recommended_model = recommend_ai_model_via_gpt(description)
+        st.subheader(f"Recommended: {recommended_model}")
+        explanation = explain_recommendation(recommended_model)
+        st.write("Explanation:", 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!")