Upload chat.py

chat.py

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+import gradio as gr
+from openai import OpenAI
+
+# Point to the local server
+client = OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio")
+
+def chat(message, history):
+    """
+    Handles user input and sends it to the model.
+    """
+    # Append user message to history immediately 
+    history.append((message, None)) 
+
+    # Format messages for OpenAI API
+    messages = [{"role": "system", "content": "Always answer in rhymes."}]
+    for user_msg, assistant_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        # Only add assistant message if it exists
+        if assistant_msg:  
+            messages.append({"role": "assistant", "content": assistant_msg})
+
+    # Create chat completion
+    completion = client.chat.completions.create(
+        model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
+        messages=messages,
+        temperature=0.7,
+    )
+
+    # Check if choices is not empty
+    if completion.choices:
+        response = completion.choices[0].message.content
+        # Update the last message in history with the response
+        history[-1] = (message, response)  
+    else:
+        response = "No response received from the model."
+        # No need to update history here as the message is already added
+
+    return history, response
+
+# Create the Gradio interface using gr.Blocks
+# Create the Gradio interface using gr.Blocks
+with gr.Blocks() as iface:
+    chat_history = gr.Chatbot(label="Conversation History")
+    message_input = gr.Textbox(label="Your message")
+    send_button = gr.Button(value="Send")
+
+    # Connect components with the chat function within gr.Blocks context
+    # outputs から message_input を削除
+    send_button.click(
+        chat, inputs=[message_input, chat_history], outputs=[chat_history] 
+    )
+
+# Launch the Gradio interface
+iface.launch(share=False)