gradio app

README.md

@@ -1,8 +1,8 @@
 ---
 title: OpenChat 3.2
 emoji: 🏆
-colorFrom: yellow
-colorTo: red
+colorFrom: blue
+colorTo: indigo
 sdk: gradio
 sdk_version: 3.39.0
 app_file: app.py

app.py

@@ -0,0 +1,89 @@
+import os
+import gradio as gr
+import openai
+
+
+openai.api_base = os.environ.get("OPENAI_API_BASE")
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+MODEL_TYPE = os.environ.get("MODEL_TYPE")
+
+
+def make_prediction(history, max_tokens=None, temperature=None, top_p=None):
+    messages = []
+    for idx, (user, bot) in enumerate(history):
+        messages.append({"role": "user", "content": user})
+        if idx != len(history) - 1:
+            messages.append({"role": "assistant", "content": bot})
+
+    # print(messages)
+
+    completion = openai.ChatCompletion.create(model=MODEL_TYPE, messages=messages, max_tokens=max_tokens, temperature=temperature, top_p=top_p, stream=True)
+    for chunk in completion:
+        content = chunk["choices"][0]["delta"].get("content", "")
+        if content:
+            yield content
+
+
+def clear_chat(chat_history_state, chat_message):
+    chat_history_state = []
+    chat_message = ''
+    return chat_history_state, chat_message
+
+
+def user(message, history):
+    history = history or []
+    # Append the user's message to the conversation history
+    history.append([message, ""])
+    return "", history
+
+
+def chat(history, max_tokens, temperature, top_p):
+    history = history or []
+
+    prediction = make_prediction(
+        history,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p
+    )
+
+    for delta_text in prediction:
+        history[-1][1] += delta_text
+        # stream the response
+        yield history, history, ""
+
+
+start_message = ""
+
+with gr.Blocks() as demo:
+    with gr.Tab("Chatbot"):
+        gr.Markdown("# 💬 OpenChat 3.2 Playground 💬 ")
+        chatbot = gr.Chatbot().style(height=500)
+        with gr.Row():
+            message = gr.Textbox(
+                label="What do you want to chat about?",
+                placeholder="Ask me anything.",
+                lines=3,
+            )
+        with gr.Row():
+            submit = gr.Button(value="Send message", variant="secondary").style(full_width=True)
+            clear = gr.Button(value="New topic", variant="secondary").style(full_width=False)
+            stop = gr.Button(value="Stop", variant="secondary").style(full_width=False)
+        with gr.Row():
+            with gr.Column():
+                max_tokens = gr.Slider(32, 1024, label="Max Tokens", step=20, value=768)
+                temperature = gr.Slider(0.0, 1.0, label="Temperature", step=0.1, value=0.7)
+                top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=1.0)
+
+        chat_history_state = gr.State()
+        clear.click(clear_chat, inputs=[chat_history_state, message], outputs=[chat_history_state, message], queue=False)
+        clear.click(lambda: None, None, chatbot, queue=False)
+
+        submit_click_event = submit.click(
+            fn=user, inputs=[message, chat_history_state], outputs=[message, chat_history_state], queue=True
+        ).then(
+            fn=chat, inputs=[chat_history_state, max_tokens, temperature, top_p], outputs=[chat_history_state, chatbot, message], queue=True
+        )
+        stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_click_event], queue=False)
+
+demo.queue(max_size=128, concurrency_count=48).launch(debug=True, server_name="0.0.0.0", server_port=7860)