Create township_chatbot.py

township_chatbot.py

@@ -0,0 +1,48 @@
+import subprocess
+import gradio as gr
+
+def chat_with_ollama(user_message, chat_history):
+    """
+    Sends the full chat history + current user message to Ollama model,
+    captures the response, and appends it to the history.
+    """
+    # Prepare prompt by joining past conversation + current message
+    prompt = ""
+    for i, (user, bot) in enumerate(chat_history):
+        prompt += f"User: {user}\nAssistant: {bot}\n"
+    prompt += f"User: {user_message}\nAssistant:"
+
+    # Call Ollama CLI to get model response
+    try:
+        result = subprocess.run(
+            ["ollama", "run", "township_business_growth_coach", prompt],
+            capture_output=True,
+            text=True,
+            timeout=30
+        )
+        if result.returncode == 0:
+            bot_reply = result.stdout.strip()
+        else:
+            bot_reply = f"Error from Ollama: {result.stderr.strip()}"
+    except Exception as e:
+        bot_reply = f"Exception: {str(e)}"
+
+    # Update chat history
+    chat_history.append((user_message, bot_reply))
+
+    # Format output as list of dicts for chat UI
+    chat_formatted = [{"User": u, "Bot": b} for u, b in chat_history]
+
+    return chat_formatted, chat_history
+
+with gr.Blocks(title="Township Business Growth Coach Chatbot") as demo:
+    gr.Markdown("## 💬 Township Business Growth Coach Chatbot")
+    chatbox = gr.Chatbot(label="Chat History")
+    msg = gr.Textbox(placeholder="Ask your township business growth question here...")
+    state = gr.State([])  # stores history as list of (user, bot) tuples
+    submit = gr.Button("Send")
+
+    submit.click(chat_with_ollama, inputs=[msg, state], outputs=[chatbox, state])
+    msg.submit(chat_with_ollama, inputs=[msg, state], outputs=[chatbox, state])
+
+demo.launch(server_name="0.0.0.0", server_port=7860)