voice + code evaluation

app.py

@@ -11,16 +11,13 @@ import requests
 # Set up OpenAI client
 client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
-# Set up ElevenLabs API key
-ELEVENLABS_API_KEY = OpenAI(api_key=os.getenv("VOICE_API_KEY"))
-
 # Check if GPU is available
 device = "cuda" if torch.cuda.is_available() else "cpu"
 print(f"Using device: {device}")
 
 # Load metadata and embeddings (ensure these files are in your working directory or update paths)
-metadata_path = 'question_metadata.csv'  # Update this path if needed
-embeddings_path = 'question_dataset_embeddings.npy'  # Update this path if needed
+metadata_path = 'question_metadata.csv'
+embeddings_path = 'question_dataset_embeddings.npy'
 
 metadata = pd.read_csv(metadata_path)
 embeddings = np.load(embeddings_path)
@@ -41,68 +38,73 @@ st.title("Real-World Programming Question Mock Interview")
 if "messages" not in st.session_state:
     st.session_state.messages = []
 
-if "follow_up_mode" not in st.session_state:
-    st.session_state.follow_up_mode = False  # Tracks whether we're in follow-up mode
-
 if "generated_question" not in st.session_state:
-    st.session_state.generated_question = None  # Stores the generated question for persistence
-
-if "debug_logs" not in st.session_state:
-    st.session_state.debug_logs = []  # Stores debug logs for toggling
+    st.session_state.generated_question = None
 
 if "code_output" not in st.session_state:
-    st.session_state.code_output = None  # Stores the output of executed Python code
-
-# Function to find the top 1 most similar question based on user input
-def find_top_question(query):
-    query_embedding = model.encode(query, convert_to_tensor=True, device=device).cpu().numpy()
-    query_embedding = query_embedding.reshape(1, -1)  # Reshape to (1, n_features)
-    similarities = cosine_similarity(query_embedding, embeddings).flatten()
-    top_index = similarities.argsort()[-1]
-    top_result = metadata.iloc[top_index].copy()
-    top_result['similarity_score'] = similarities[top_index]
-    return top_result
-
-# Function to generate response using OpenAI API with debugging logs
-def generate_response(messages):
-    debug_log_entry = {"messages": messages}
-    st.session_state.debug_logs.append(debug_log_entry)  # Store debug log
-    
-    response = client.chat.completions.create(
-        model="o1-mini",
-        messages=messages,
-    )
-    
-    return response.choices[0].message.content
-
-# Function to generate audio using ElevenLabs API
-def generate_audio(text):
-    url = "https://api.elevenlabs.io/v1/text-to-speech"
-    headers = {
-        "xi-api-key": ELEVENLABS_API_KEY,
-        "content-type": "application/json"
-    }
-    payload = {
-        "text": text,
-        "voice_id": "21m00tcm4tlvdq8ikwam",  # Default voice ID; replace with desired voice ID.
-        "voice_settings": {
-            "similarity_boost": 0.85,
-            "stability": 0.5
-        }
-    }
-    
-    response = requests.post(url, headers=headers, json=payload)
-    
-    if response.status_code == 200:
-        audio_file_path = f"assistant_response.mp3"
-        with open(audio_file_path, "wb") as audio_file:
-            audio_file.write(response.content)
-        return audio_file_path
+    st.session_state.code_output = ""
+
+if "evaluation_output" not in st.session_state:
+    st.session_state.evaluation_output = ""
+
+# Sidebar layout for Generated Question and Code Box
+st.sidebar.markdown("## Generated Question")
+if st.session_state.generated_question:
+    st.sidebar.markdown(st.session_state.generated_question)
+else:
+    st.sidebar.markdown("_No question generated yet._")
+
+st.sidebar.markdown("---")
+st.sidebar.markdown("## Code Box")
+
+code_input = st.sidebar.text_area(
+    label="Write your Python code here:",
+    height=200,
+    placeholder="Enter your code...",
+)
+
+col1, col2 = st.sidebar.columns(2)
+
+# Button to run code and display output
+if col1.button("Run Code"):
+    try:
+        exec_globals = {}
+        exec(code_input, exec_globals)
+        st.session_state.code_output = exec_globals.get("output", "Code executed successfully.")
+    except Exception as e:
+        st.session_state.code_output = f"Error: {str(e)}"
+
+# Button to evaluate code using OpenAI API
+if col2.button("Evaluate Code"):
+    if not st.session_state.generated_question:
+        st.sidebar.error("Generate a question first!")
     else:
-        st.error(f"Error generating audio: {response.status_code} - {response.text}")
-        return None
-
-# User input form for generating a new question
+        try:
+            evaluation_prompt = (
+                f"Question: {st.session_state.generated_question}\n\n"
+                f"Code:\n{code_input}\n\n"
+                f"Evaluate this code's correctness, efficiency, and style."
+            )
+            response = client.chat.completions.create(
+                model="gpt-4",
+                messages=[{"role": "user", "content": evaluation_prompt}],
+            )
+            evaluation_response = response.choices[0].message.content
+            st.session_state.evaluation_output = evaluation_response
+
+            # Add evaluation output to follow-up conversation
+            st.session_state.messages.append({"role": "assistant", "content": evaluation_response})
+        except Exception as e:
+            st.sidebar.error(f"Error during evaluation: {str(e)}")
+
+# Display outputs below the main app content
+st.subheader("Code Output")
+st.text(st.session_state.code_output)
+
+st.subheader("Evaluation Output")
+st.text(st.session_state.evaluation_output)
+
+# Main app logic for generating questions and follow-up conversation remains unchanged.
 with st.form(key="input_form"):
     company = st.text_input("Company", value="Google")
     difficulty = st.selectbox("Difficulty", ["Easy", "Medium", "Hard"], index=1)
@@ -111,10 +113,17 @@ with st.form(key="input_form"):
     generate_button = st.form_submit_button(label="Generate")
 
 if generate_button:
-    st.session_state.messages = []
-    st.session_state.follow_up_mode = False
-    
     query = f"{company} {difficulty} {topic}"
+    
+    def find_top_question(query):
+        query_embedding = model.encode(query, convert_to_tensor=True, device=device).cpu().numpy()
+        query_embedding = query_embedding.reshape(1, -1)
+        similarities = cosine_similarity(query_embedding, embeddings).flatten()
+        top_index = similarities.argsort()[-1]
+        top_result = metadata.iloc[top_index].copy()
+        top_result['similarity_score'] = similarities[top_index]
+        return top_result
+    
     top_question = find_top_question(query)
     
     detailed_prompt = (
@@ -127,68 +136,29 @@ if generate_button:
         f"\nPlease create a real-world interview question based on this information."
     )
     
-    response_text = generate_response([{"role": "assistant", "content": question_generation_prompt}, {"role": "user", "content": detailed_prompt}])
+    response_text = client.chat.completions.create(
+        model="gpt-4",
+        messages=[{"role": "assistant", "content": question_generation_prompt}, {"role": "user", "content": detailed_prompt}],
+    ).choices[0].message.content
     
     st.session_state.generated_question = response_text
 
-    st.session_state.messages.append({"role": "assistant", "content": response_text})
-    
-    st.session_state.follow_up_mode = True
-
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
-if st.session_state.follow_up_mode:
-    if user_input := st.chat_input("Continue your conversation or ask follow-up questions here:"):
-        with st.chat_message("user"):
-            st.markdown(user_input)
-        
-        st.session_state.messages.append({"role": "user", "content": user_input})
-
-        assistant_response_text = generate_response(
-            [{"role": "assistant", "content": technical_interviewer_prompt}] + st.session_state.messages
-        )
-
-        assistant_audio_path = generate_audio(assistant_response_text)
-
-        with st.chat_message("assistant"):
-            st.markdown(assistant_response_text)
-            if assistant_audio_path:
-                audio_bytes = open(assistant_audio_path, "rb").read()
-                st.audio(audio_bytes, format="audio/mp3")
-        
-        st.session_state.messages.append({"role": "assistant", "content": assistant_response_text})
-
-# Left Sidebar: Generated Question and Code Box
-with st.sidebar:
-    # Top Half: Generated Question
-    st.markdown("## Generated Question")
-    if st.session_state.generated_question:
-        st.markdown(st.session_state.generated_question)
-    else:
-        st.markdown("_No question generated yet._")
-
-    # Divider between sections
-    st.markdown("---")
-
-    # Bottom Half: Python Code Box
-    st.markdown("## Python Code Interpreter")
+if user_input := st.chat_input("Continue your conversation or ask follow-up questions here:"):
+    with st.chat_message("user"):
+        st.markdown(user_input)
     
-    code_input = st.text_area("Write your Python code here:")
+    assistant_response_text = client.chat.completions.create(
+        model="gpt-4",
+        messages=[{"role": "assistant", "content": technical_interviewer_prompt}] + [{"role": msg["role"], "content": msg["content"]} for msg in st.session_state.messages],
+    ).choices[0].message.content
     
-    col1, col2 = st.columns(2)
+    with st.chat_message("assistant"):
+        st.markdown(assistant_response_text)
     
-    with col1:
-        if st.button("Run Code"):
-            try:
-                exec_globals = {}
-                exec(code_input, exec_globals)  # Execute user-provided code safely within its own scope.
-                output_key_values = {k: v for k, v in exec_globals.items() if k != "__builtins__"}
-                if output_key_values:
-                    output_strs = [f"{key}: {value}" for key, value in output_key_values.items()]
-                    output_display_strs = "\n".join(output_strs)
-                    output_display_strs += "\nCode executed successfully!"
-                    print(output_display_strs)
-
-            except Exception as e:
+    # Append to session state messages for persistence
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    st.session_state.messages.append({"role": "assistant", "content": assistant_response_text})