Update app.py

app.py

@@ -1,37 +1,76 @@
-def respond(message, history):
-    print("Query received:", message)
-    print("Chat history:", history)
+import gradio as gr
+import gspread
+from google.oauth2.service_account import Credentials
+from huggingface_hub import InferenceClient
+
+# Google Sheets Configuration
+SERVICE_ACCOUNT_FILE = "sheet-integration-agent@bold-physics-445007-g4.iam.gserviceaccount.com.json"
+SPREADSHEET_ID = "1LHgb4eYDM2ImFY3e3h4kPUnDh6oRHpVz2PA29lQ3Xxg"
+
+# Authenticate and connect to Google Sheets
+scopes = ["https://www.googleapis.com/auth/spreadsheets"]
+credentials = Credentials.from_service_account_file(SERVICE_ACCOUNT_FILE, scopes=scopes)
+client = gspread.authorize(credentials)
+worksheet = client.open_by_key(SPREADSHEET_ID).sheet1
 
-    # Ensure history is a list of dictionaries
-    if not history:
-        history = []
+# Hugging Face Model Configuration
+model_name = "HuggingFaceH4/zephyr-7b-beta"
+hf_client = InferenceClient(model_name)
 
+def get_apartment_data(query):
+    """
+    Fetch apartment data based on the user query from Google Sheets.
+    """
+    rows = worksheet.get_all_records()
+    results = []
+    for row in rows:
+        if query.lower() in row.get("district", "").lower() or query.lower() in row.get("developer", "").lower():
+            results.append(row)
+    if results:
+        return "\n".join([str(result) for result in results])
+    return "No matching apartments found for your query."
+
+def respond(message, history):
+    """
+    Respond to user messages using Hugging Face and Google Sheets data.
+    """
     try:
-        # Check for specific keywords to invoke Google Sheets query
-        if "bostandyk" in message.lower() or "developer" in message.lower():
-            response = get_apartment_data(message)
-        else:
-            # Process the query using the model
-            messages = [{"role": "system", "content": "You are a helpful assistant."}]
-            for entry in history:
-                messages.append({"role": entry["role"], "content": entry["content"]})
-
-            messages.append({"role": "user", "content": message})
-
-            # Generate response from model
-            model_response = client.chat_completion(
-                messages=messages,
-                max_tokens=512,
-                temperature=0.7,
-                top_p=0.95,
-            )
-            response = model_response["choices"][0]["message"]["content"]
-
-        # Append the interaction to the history
-        history.append({"role": "user", "content": message})
+        # Check if the query relates to apartments
+        if "apartment" in message.lower() or "district" in message.lower():
+            sheet_response = get_apartment_data(message)
+            history.append({"role": "assistant", "content": sheet_response})
+            return history
+
+        # Default response from the Hugging Face model
+        messages = [{"role": "system", "content": "You are a friendly real estate assistant."}]
+        for user_message, bot_response in history:
+            if user_message:
+                messages.append({"role": "user", "content": user_message})
+            if bot_response:
+                messages.append({"role": "assistant", "content": bot_response})
+
+        messages.append({"role": "user", "content": message})
+
+        response = ""
+        for chunk in hf_client.chat_completion(messages, stream=True):
+            token = chunk.choices[0].delta.content
+            response += token
+
         history.append({"role": "assistant", "content": response})
         return history
 
     except Exception as e:
-        print(f"Error processing query: {e}")
-        return [{"role": "assistant", "content": "An error occurred while processing your query."}]
+        error_message = f"An error occurred: {str(e)}"
+        history.append({"role": "assistant", "content": error_message})
+        return history
+
+# Gradio Interface
+chat_interface = gr.ChatInterface(
+    respond,
+    chatbot=gr.Chatbot(),
+    title="Real Estate Chatbot",
+    description="Ask about available apartments or districts in our database.",
+)
+
+if __name__ == "__main__":
+    chat_interface.launch()