Update app.py

app.py

@@ -1,7 +1,29 @@
 import streamlit as st
+import json
+from datetime import datetime
+from pathlib import Path
+from uuid import uuid4
+import os
+from huggingface_hub import CommitScheduler
+
+# Setup the directory for saving data
+JSON_DATASET_DIR = Path("feedback_dataset")
+JSON_DATASET_DIR.mkdir(parents=True, exist_ok=True)
+
+# Define a unique file name
+JSON_DATASET_PATH = JSON_DATASET_DIR / f"feedback-{uuid4()}.json"
+
+# Scheduler configuration for your dataset repo
+scheduler = CommitScheduler(
+    repo_id="Utsav2001/Feedback",  # Replace with your dataset repo
+    repo_type="dataset",
+    folder_path=JSON_DATASET_DIR,  # Local directory to sync
+    path_in_repo="data",  # Path in the dataset repository
+    token=os.getenv('hf_write')  # Ensure your HF write token is set
+)
 
 # Streamlit UI
-st.title("Feedback-enabled Chatbot")
+st.title("Feedback-enabled Chatbot with Hugging Face Integration")
 
 if "prompts" not in st.session_state:
     st.session_state.prompts = []
@@ -9,12 +31,36 @@ if "responses" not in st.session_state:
     st.session_state.responses = []
 if "show_feedback" not in st.session_state:
     st.session_state.show_feedback = False
+if "feedbacks" not in st.session_state:
+    st.session_state.feedbacks = []
+
+# Function to save data using Hugging Face CommitScheduler
+def save_feedback_to_hub(prompt, ai_response, feedback_type, feedback_comment):
+    try:
+        with scheduler.lock:
+            with JSON_DATASET_PATH.open("a") as f:
+                json.dump(
+                    {
+                        "prompt": prompt,
+                        "ai_response": ai_response,
+                        "feedback_type": feedback_type,
+                        "feedback_comment": feedback_comment,
+                        "datetime": datetime.now().isoformat(),
+                    },
+                    f,
+                )
+                f.write("\n")
+        # Push the changes to Hugging Face Hub
+        scheduler.push_to_hub()
+        return "Feedback saved successfully to Hugging Face Hub!"
+    except Exception as e:
+        return f"Error saving feedback: {e}"
 
 # User input section
 user_input = st.text_input("Enter your message:")
 if st.button("Get Response"):
-    # Generate AI response (replace with your model's logic)
-    ai_response = f"Response to: {user_input}"
+    # Simulate an AI response (replace with actual AI model logic)
+    ai_response = f"This is a response to: {user_input}"
     st.session_state.prompts.append(user_input)
     st.session_state.responses.append(ai_response)
     st.session_state.show_feedback = True
@@ -23,20 +69,27 @@ if st.button("Get Response"):
 # Feedback section
 if st.session_state.show_feedback and len(st.session_state.prompts) > 0 and len(st.session_state.responses) > 0:
     st.write("Provide feedback for the last interaction:")
-    
+
     col1, col2 = st.columns(2)
+    feedback_type = None
     with col1:
         if st.button("👍 Thumbs Up"):
-            st.session_state.feedback_value = "Positive"
+            feedback_type = "Positive"
             st.session_state.show_feedback_box = True
     with col2:
         if st.button("👎 Thumbs Down"):
-            st.session_state.feedback_value = "Negative"
+            feedback_type = "Negative"
             st.session_state.show_feedback_box = True
-    
+
     if "show_feedback_box" in st.session_state and st.session_state.show_feedback_box:
         feedback_comment = st.text_area("Your Feedback:")
         if st.button("Submit Feedback"):
-            st.success("Feedback submitted successfully!")
+            save_status = save_feedback_to_hub(
+                st.session_state.prompts[-1],
+                st.session_state.responses[-1],
+                feedback_type,
+                feedback_comment
+            )
+            st.success(save_status)
             st.session_state.show_feedback_box = False
             st.session_state.show_feedback = False