Update app.py

app.py

@@ -1,9 +1,42 @@
-import streamlit as st
+import gradio as gr
 import requests
+import os
 
-def generate_more_factors(problem_statement, user_factors):
-    # 1. Prepare prompt text
-    factors_text = "\n".join([f"- {factor}" for factor in user_factors if factor.strip() != ""])
+# Maximum number of factor textboxes allowed
+MAX_FACTORS = 10
+
+def add_factor(num_factors):
+    """
+    Increase the number of visible factor rows.
+    
+    Inputs:
+    1. num_factors: current number of visible factor rows
+    
+    Outputs:
+    1. Updated number of visible rows
+    2. Updated visibility for each factor textbox (list of gr.update objects)
+    """
+    new_num = num_factors + 1 if num_factors < MAX_FACTORS else num_factors
+    # Prepare update list for each textbox: show textbox if its index is less than new_num, hide otherwise.
+    updates = [gr.update(visible=True) if i < new_num else gr.update(visible=False) for i in range(MAX_FACTORS)]
+    return new_num, *updates
+
+def generate_factors(problem_statement, *factors):
+    """
+    Call the Hugging Face inference API to generate additional factors.
+    
+    Inputs:
+    1. problem_statement: The problem statement provided by the user.
+    2. factors: A list of factor inputs (only non-empty ones will be used).
+    
+    Output:
+    1. A string containing additional factor suggestions.
+    """
+    # Filter out empty or whitespace-only factor entries
+    factor_list = [f for f in factors if f and f.strip() != ""]
+    
+    # Prepare the prompt text for the LLM
+    factors_text = "\n".join([f"- {factor}" for factor in factor_list])
     prompt = (
         f"You are an expert problem solver. Given the following problem statement:\n"
         f"{problem_statement}\n\n"
@@ -12,18 +45,18 @@ def generate_more_factors(problem_statement, user_factors):
         f"Please suggest additional factors that would complete a MECE (Mutually Exclusive, Collectively Exhaustive) "
         f"set of factors responsible for solving the problem. Provide your suggestions as a bullet list."
     )
-
-    # 2. Call Hugging Face inference API (using a sample model; replace as needed)
+    
+    # Call the Hugging Face inference API (using GPT-2 as an example; change the model as needed)
     API_URL = "https://api-inference.huggingface.co/models/gpt2"
-    token = st.secrets.get("HF_API_TOKEN", "")
+    token = os.environ.get("HF_API_TOKEN", "")
     headers = {"Authorization": f"Bearer {token}"} if token else {}
-
+    
     response = requests.post(API_URL, headers=headers, json={"inputs": prompt})
     if response.status_code == 200:
         result = response.json()
         if isinstance(result, list) and result and "generated_text" in result[0]:
             generated = result[0]["generated_text"]
-            # Remove the prompt from the generated output
+            # Remove the prompt portion from the response to return only the suggestions.
             suggestions = generated[len(prompt):].strip()
             return suggestions
         else:
@@ -31,59 +64,45 @@ def generate_more_factors(problem_statement, user_factors):
     else:
         return f"Error: {response.status_code} - {response.text}"
 
-def main():
-    st.title("Problem Statement and Factor Guess")
-    st.write("Enter your problem statement and factors. The UI is organized into four horizontal levels:")
-
-    # Initialize session state variables
-    if "factor_rows" not in st.session_state:
-        st.session_state.factor_rows = [""]
-    if "llm_suggestions" not in st.session_state:
-        st.session_state.llm_suggestions = None
-
-    # Create four columns for the four levels
-    col1, col2, col3, col4 = st.columns(4)
-
-    # Level 1: Problem Statement (Left-most column)
-    with col1:
-        st.header("Level 1: Problem Statement")
-        problem_statement = st.text_input("Enter your problem statement:")
-
-    # Level 2: User-Provided Factors
-    with col2:
-        st.header("Level 2: Your Factors")
-        factor_inputs = []
-        for i in range(len(st.session_state.factor_rows)):
-            key = f"factor_{i}"
-            value = st.text_input(f"Factor {i+1}", value=st.session_state.factor_rows[i], key=key)
-            factor_inputs.append(value)
-            st.session_state.factor_rows[i] = value
-
-        if st.button("Add Factor Row", key="add_row"):
-            st.session_state.factor_rows.append("")
-            try:
-                st.experimental_rerun()
-            except AttributeError:
-                st.write("Row added. Please refresh the page to see the new row.")
-
-    # Level 3: Generate More Factors Button
-    with col3:
-        st.header("Level 3: Generate More Factors")
-        if st.button("Generate More Factors", key="generate_factors"):
-            if not problem_statement.strip():
-                st.error("Please enter a problem statement before generating factors.")
-            else:
-                with st.spinner("Generating more factors..."):
-                    suggestions = generate_more_factors(problem_statement, factor_inputs)
-                st.session_state.llm_suggestions = suggestions
-
-    # Level 4: LLM Suggestions Display
-    with col4:
-        st.header("Level 4: LLM Suggestions")
-        if st.session_state.llm_suggestions:
-            st.write(st.session_state.llm_suggestions)
-        else:
-            st.write("LLM suggestions will appear here after you click 'Generate More Factors'.")
+with gr.Blocks() as demo:
+    # State variable to keep track of the current number of factor rows visible.
+    num_factors_state = gr.State(value=1)
+    
+    # Define the layout with 4 columns for 4 levels.
+    with gr.Row():
+        # Level 1: Problem Statement
+        with gr.Column():
+            problem_statement = gr.Textbox(label="Level 1: Problem Statement", placeholder="Enter your problem statement here")
+        
+        # Level 2: Factor inputs and an Add Factor Row button
+        with gr.Column():
+            factor_textboxes = []
+            # Pre-create MAX_FACTORS textboxes. Only the first 'num_factors_state' will be visible.
+            for i in range(MAX_FACTORS):
+                tb = gr.Textbox(label=f"Factor {i+1}", visible=(i == 0), placeholder="Enter a factor")
+                factor_textboxes.append(tb)
+            add_factor_btn = gr.Button("Add Factor Row")
+        
+        # Level 3: Generate More Factors button
+        with gr.Column():
+            generate_btn = gr.Button("Generate More Factors")
+        
+        # Level 4: LLM suggestions display
+        with gr.Column():
+            llm_output = gr.Textbox(label="Level 4: LLM Suggestions", interactive=False, placeholder="LLM suggestions will appear here")
+    
+    # When Add Factor Row is clicked, update the state and the visibility of each factor textbox.
+    add_factor_btn.click(
+        fn=add_factor,
+        inputs=num_factors_state,
+        outputs=[num_factors_state] + factor_textboxes
+    )
+    
+    # When Generate More Factors is clicked, call the LLM generation function.
+    generate_btn.click(
+        fn=generate_factors,
+        inputs=[problem_statement] + factor_textboxes,
+        outputs=llm_output
+    )
 
-if __name__ == "__main__":
-    main()
+demo.launch()