Update app.py

app.py

@@ -1,28 +1,7 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-from textblob import TextBlob
-import json
-import os
-import time
-import logging
 
-# Set up logging
-logging.basicConfig(level=logging.INFO)
-
-# Get the API token from the environment variable
-api_token = os.getenv('HUGGINGFACEHUB_API_TOKEN')
-
-client = InferenceClient(
-    model="Futuresony/future_ai_12_10_2024.gguf",
-    token=api_token
-)
-
-# Directory to store interactions and feedback
-DATA_DIR = "data"
-INTERACTIONS_FILE = os.path.join(DATA_DIR, "interactions.json")
-
-# Ensure the data directory exists
-os.makedirs(DATA_DIR, exist_ok=True)
+client = InferenceClient("Futuresony/future_ai_12_10_2024.gguf")
 
 def format_alpaca_prompt(user_input, system_prompt, history):
     """Formats input in Alpaca/LLaMA style"""
@@ -37,116 +16,23 @@ def format_alpaca_prompt(user_input, system_prompt, history):
 """
     return prompt
 
-def analyze_sentiment(message):
-    """Analyze the sentiment of the user's message"""
-    blob = TextBlob(message)
-    sentiment = blob.sentiment.polarity
-    return sentiment
-
-def save_interaction(user_input, chatbot_response, feedback=None):
-    """Save the interaction and feedback to a file"""
-    interaction = {
-        "user_input": user_input,
-        "chatbot_response": chatbot_response,
-        "feedback": feedback,
-        "timestamp": time.strftime("%Y-%m-%d %H:%M:%S")
-    }
-    if os.path.exists(INTERACTIONS_FILE):
-        with open(INTERACTIONS_FILE, "r") as file:
-            interactions = json.load(file)
-    else:
-        interactions = []
-
-    interactions.append(interaction)
-
-    with open(INTERACTIONS_FILE, "w") as file:
-        json.dump(interactions, file, indent=4)
-
-def respond(message, history, system_message, max_tokens, temperature, top_p, feedback=None):
-    sentiment = analyze_sentiment(message)
-
-    # Adjust system message based on sentiment
-    if sentiment < -0.2:
-        system_message = "You are a sympathetic Chatbot."
-    elif sentiment > 0.2:
-        system_message = "You are an enthusiastic Chatbot."
-    else:
-        system_message = "You are a friendly Chatbot."
-
+def respond(message, history, system_message, max_tokens, temperature, top_p):
     formatted_prompt = format_alpaca_prompt(message, system_message, history)
 
-    # Retry mechanism
-    max_retries = 3
-    for attempt in range(max_retries):
-        try:
-            response = client.text_generation(
-                formatted_prompt,
-                max_new_tokens=max_tokens,
-                temperature=temperature,
-                top_p=top_p,
-            )
-            break  # Exit the loop if the request is successful
-        except Exception as e:
-            logging.error(f"Attempt {attempt + 1} failed: {e}")
-            if attempt < max_retries - 1:
-                time.sleep(2 ** attempt)  # Exponential backoff
-            else:
-                raise e
+    response = client.text_generation(
+        formatted_prompt,
+        max_new_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+    )
 
     # ✅ Extract only the response
     cleaned_response = response.split("### Response:")[-1].strip()
-
+    
     history.append((message, cleaned_response))  # ✅ Update history with the new message and response
-
-    save_interaction(message, cleaned_response, feedback)  # ✅ Save the interaction and feedback
-
+    
     yield cleaned_response  # ✅ Output only the answer
 
-def collect_feedback(response, feedback):
-    """Collect user feedback on the chatbot's response"""
-    save_interaction(response, feedback=feedback)
-
-def view_interactions():
-    if os.path.exists(INTERACTIONS_FILE):
-        with open(INTERACTIONS_FILE, "r") as file:
-            interactions = json.load(file)
-            return json.dumps(interactions, indent=4)
-    else:
-        return "No interactions found."
-
-def download_interactions():
-    """Provide the interactions file for download"""
-    if os.path.exists(INTERACTIONS_FILE):
-        return INTERACTIONS_FILE
-    else:
-        return None
-
-# Create a Gradio interface to display interactions
-view_interface = gr.Interface(
-    fn=view_interactions,
-    inputs=[],
-    outputs="text",
-    title="View Interactions"
-)
-
-# Create a Gradio interface for downloading interactions
-download_interface = gr.Interface(
-    fn=download_interactions,
-    inputs=[],
-    outputs=gr.File(label="Download Interactions"),
-    title="Download Interactions"
-)
-
-feedback_interface = gr.Interface(
-    fn=collect_feedback,
-    inputs=[
-        gr.Textbox(label="Response"),
-        gr.Radio(choices=["Good", "Bad"], label="Feedback"),
-    ],
-    outputs="text",
-    title="Feedback Interface"
-)
-
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -157,9 +43,5 @@ demo = gr.ChatInterface(
     ],
 )
 
-# Launch all interfaces
 if __name__ == "__main__":
-    demo.launch()
-    feedback_interface.launch()
-    view_interface.launch()
-    download_interface.launch()
+    demo.launch()