Update app.py

app.py

@@ -1,162 +1,127 @@
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 import gradio as gr
+from openai import OpenAI
 import os
-import requests
-import time
-
-css = """
-.gradio-container {
-    background-color: #1e1e2f;
-    color: white;
-    max-width: 800px !important;
-    margin: auto;
-    padding-top: 50px;
-}
-h1 {
-    text-align: center;
-    font-size: 2em;
-    margin-bottom: 20px;
-}
+
+css = '''
+.gradio-container{max-width: 1000px !important}
+h1{text-align:center}
 footer {
-    visibility: hidden;
-}
-select {
-    background-color: #2a2a40;
-    color: white;
-    padding: 6px 10px;
-    border-radius: 8px;
-    border: 1px solid #444;
-    width: 300px;
-}
-option {
-    background-color: #2a2a40;
-    color: white;
+    visibility: hidden
 }
-"""
+'''
 
 ACCESS_TOKEN = os.getenv("HF_TOKEN")
-API_URL = "https://api.deepinfra.com/v1/openai/chat/completions"
 
-HEADERS = {
-    "Content-Type": "application/json",
-    "Authorization": f"Bearer {ACCESS_TOKEN}",
-}
+client = OpenAI(
+    base_url="https://api.deepinfra.com/v1/openai/chat/completions",
+    api_key=ACCESS_TOKEN,
+)
 
-# Define system prompts for each model.
-PROMPTS = {
-    "Elon Ma (Official)": (
-        "You are Elon Ma, a Chinese car salesman selling the Edision Model S.\n"
-        "Respond in broken English, overhyping the car, never mentioning Tesla."
-    ),
-    "Cole (Community)": (
-        "You are Cole, a Gen Z troll who sells Edision Model S cars.\n"
-        "You type like you're on TikTok, casually roasting the user."
-    ),
-    "Mr. Shortreed (Official)": (
-        "You are Mr. Shortreed, a serious teacher explaining the Edision Model S.\n"
-        "You use formal, educational language."
-    )
-}
+SYSTEM_PROMPT = """From now on respond as a sale man for a car that is a ripoff of a tesla called an edision model s, Respond in broken english
+The company is Edision Motors and you never mention tesla and the car is made of cardborard and ducktape but you dont mention it
+When you understand say "Ready"
+Your name is Elon Ma and your Chinese
+There is also evil donald ducks and mr long reeds trying to vandlize the cars calling them nazi cars or "sawasticars"
+.
+"""
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    # Apply the structured system prompt
+    system_message = SYSTEM_PROMPT
 
-def stream_response(message, history, character):
-    """
-    Calls the API and yields partial responses for streaming.
-    """
-    system_message = PROMPTS.get(character, "")
-    # Build messages using a list of dictionaries.
     messages = [{"role": "system", "content": system_message}]
-    for msg in history:
-        messages.append(msg)
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
     messages.append({"role": "user", "content": message})
+
+    response = ""
     
-    payload = {
-        "model": "mistralai/Mistral-Small-24B-Instruct-2501",
-        "messages": messages,
-        "max_tokens": 512,
-        "temperature": 0.7,
-        "top_p": 0.95,
-    }
-    
-    try:
-        response = requests.post(API_URL, headers=HEADERS, json=payload)
-        response.raise_for_status()
-        data = response.json()
-        if "choices" not in data:
-            # Yield the full response data for debugging.
-            yield f"Error: API returned an unexpected response: {data}"
-            return
-        content = data["choices"][0]["message"]["content"]
+    for message in client.chat.completions.create(
+        model="mistralai/Mistral-Small-24B-Instruct-2501",
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+        messages=messages,
+    ):
+        token = message.choices[0].delta.content
         
-        stream_response = ""
-        # Simulate streaming by yielding token-by-token.
-        for token in content.split():
-            stream_response += token + " "
-            time.sleep(0.02)
-            yield stream_response.strip()
-    except Exception as e:
-        yield f"Error: {str(e)}"
-
-def chat(user_message, history, character):
-    """
-    Appends the user message to the conversation history, then streams the assistant's reply.
-    """
-    # Ensure history is a list.
-    history = history or []
-    history = history.copy()
-    # Append the user's message.
-    history.append({"role": "user", "content": user_message})
-    
-    full_response = ""
-    for partial in stream_response(user_message, history, character):
-        full_response = partial
-        # Yield the conversation updated with the current assistant response.
-        yield history + [{"role": "assistant", "content": full_response}]
-    # Append the final assistant message.
-    history.append({"role": "assistant", "content": full_response})
-    return history
-
-def clean_choice(choice):
-    """
-    Extract the key for PROMPTS from the dropdown choice.
-    """
-    if "Elon" in choice:
-        return "Elon Ma (Official)"
-    if "Cole" in choice:
-        return "Cole (Community)"
-    if "Shortreed" in choice:
-        return "Mr. Shortreed (Official)"
-    return "Elon Ma (Official)"
-
-with gr.Blocks(css=css) as demo:
-    # Header with QClone Public label.
-    gr.HTML("<h1>QClone <span style='background-color:#3b82f6;color:white;font-size:0.75em;padding:2px 6px;border-radius:5px;margin-left:8px;'>Public</span></h1>")
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            # Dropdown for model selection (smaller width).
-            model_dropdown = gr.Dropdown(
-                choices=[
-                    "Elon Ma (Official) 🟡 - Broken English salesman",
-                    "Cole (Community) 🔵 - Gen Z slang troll",
-                    "Mr. Shortreed (Official) 🟡 - Serious teacher vibes"
-                ],
-                value="Elon Ma (Official) 🟡 - Broken English salesman",
-                label="Model"
-            )
-        with gr.Column(scale=3):
-            # Chatbot component to display conversation.
-            chatbot = gr.Chatbot(label="QClone Chat")
-    
-    # Textbox for user input.
-    msg = gr.Textbox(label="Your Message", placeholder="Type your message here...")
-    # State to hold conversation history.
-    state = gr.State([])
-
-    # When user submits text, update chat.
-    msg.submit(
-        fn=lambda user_message, history, choice: chat(user_message, history, clean_choice(choice)),
-        inputs=[msg, state, model_dropdown],
-        outputs=[chatbot, state],
-        show_progress=True
-    )
-    
-demo.launch(show_api=False)
+        response += token
+        yield response
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-P",
+        ),
+    ],
+    css=css
+)
+
+if __name__ == "__main__":
+    demo.launch()
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