open orca preview

fix tabs
add start message
fix clear chat
setup queue
setup api vars from env
use .get for env
debug env vars
fix import

app.py

@@ -0,0 +1,107 @@
+import os
+import re
+import logging
+import gradio as gr
+import openai
+
+print(os.environ)
+openai.api_base = os.environ.get("OPENAI_API_BASE")
+openai.api_key = os.environ.get("OPENAI_API_KEY")
+
+def make_prediction(prompt, max_tokens=None, temperature=None, top_p=None, top_k=None, repetition_penalty=None):
+    completion = openai.Completion.create(model="Open-Orca/OpenOrcaxOpenChat-Preview2-13B", prompt=prompt, max_tokens=max_tokens, temperature=temperature, top_p=top_p, top_k=top_k, repetition_penalty=repetition_penalty, stream=True)
+    for chunk in completion:
+        yield chunk["choices"][0]["text"]
+
+def delay_typer(words, delay=0.8):
+    tokens = re.findall(r'\s*\S+\s*', words)
+    for s in tokens:
+        yield s
+        sleep(delay)
+
+
+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, system_message, max_tokens, temperature, top_p, top_k, repetition_penalty):
+    history = history or []
+
+    messages = system_message.strip() + "\n" + \
+               "\n".join(["\n".join(["User: "+item[0]+"<|end_of_turn|>", "Assistant: "+item[1]+"<|end_of_turn|>"])
+                          for item in history])
+    # strip the last `<|end_of_turn|>` from the messages
+    messages = messages.rstrip("<|end_of_turn|>")
+    # remove last space from assistant, some models output a ZWSP if you leave a space
+    messages = messages.rstrip()
+
+    prediction = make_prediction(
+        messages,
+        max_tokens=max_tokens,
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+        repetition_penalty=repetition_penalty,
+    )
+    for tokens in prediction:
+        tokens = re.findall(r'\s*\S+\s*', tokens)
+        for s in tokens:
+            answer = s
+            history[-1][1] += answer
+            # stream the response
+            yield history, history, ""
+
+
+start_message = ""
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown(f"""
+                    ### Brought to you by OpenChat x OpenOrca
+                    """)
+    with gr.Tab("Chatbot"):
+        gr.Markdown("# 🐋 OpenChat x OpenOrca-Preview2 GGML Playground Space! 🐋")
+        chatbot = gr.Chatbot()
+        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(20, 1000, label="Max Tokens", step=20, value=300)
+                temperature = gr.Slider(0.2, 2.0, label="Temperature", step=0.1, value=0.8)
+                top_p = gr.Slider(0.0, 1.0, label="Top P", step=0.05, value=0.95)
+                top_k = gr.Slider(0, 100, label="Top K", step=1, value=40)
+                repetition_penalty = gr.Slider(0.0, 2.0, label="Repetition Penalty", step=0.1, value=1.1)
+
+        system_msg = gr.Textbox(
+            start_message, label="System Message", interactive=True, visible=True, placeholder="system prompt, useful for RP", lines=5)
+
+        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, system_msg, max_tokens, temperature, top_p, top_k, repetition_penalty], outputs=[chatbot, chat_history_state, message], queue=True
+        )
+        stop.click(fn=None, inputs=None, outputs=None, cancels=[submit_click_event], queue=False)
+
+demo.queue(max_size=48, concurrency_count=16).launch(debug=True, server_name="0.0.0.0", server_port=7860)

requirements.txt

@@ -0,0 +1,2 @@
+requests
+openai