Update app.py

app.py

@@ -1,63 +1,66 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    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 = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", 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 (nucleus sampling)",
-        ),
-    ],
+from groq import Groq
+import os
+
+# Initialize the Groq client
+client = Groq(
+    api_key=os.environ.get("GROQ_API_KEY"),
 )
 
+# Define the chat function
+def chat_with_federer(message, history):
+    # Construct the prompt
+    prompt = f"""You are a chatbot impersonating Roger Federer, the legendary tennis player. 
+    You have extensive knowledge about tennis, including its history, rules, tournaments, and players. 
+    Respond to the following message as Roger Federer would. After your main response, always include a new line with a short, funny "Did you know!" anecdote related to tennis. The anecdote should be no more than 15 words.
+
+    Human: {message}
+    Roger Federer:"""
+
+    # Get the full conversation history
+    full_history = "\n".join([f"Human: {h[0]}\nRoger Federer: {h[1]}" for h in history])
+    
+    # Combine history with the new prompt
+    full_prompt = full_history + "\n" + prompt if full_history else prompt
+
+    # Call the Groq API
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {
+                "role": "user",
+                "content": full_prompt,
+            }
+        ],
+        model="mixtral-8x7b-32768",
+        temperature=0.7,
+        max_tokens=1000,
+        top_p=1,
+        stream=False,
+    )
+
+    # Extract the response
+    response = chat_completion.choices[0].message.content
+
+    # Ensure the "Did you know!" part is on a new line
+    if "Did you know!" in response and not response.endswith("\n"):
+        response = response.replace("Did you know!", "\nDid you know!")
+
+    return response
+
+# Create the Gradio interface
+iface = gr.ChatInterface(
+    chat_with_federer,
+    title="🎾 Chat with the G.O.A.T. Roger Federer 🏆",
+    description="🌟 Serve up your questions to the tennis legend! 🎾 Get expert insights on Grand Slams, technique, and more. Let's rally some knowledge! 💬🏆",
+    theme="soft",
+    examples=[
+        "What's your favorite Grand Slam tournament and why?",
+        "Can you explain the difference between clay and grass courts?",
+        "What do you think about the current state of men's tennis?",
+        "Any tips for improving my backhand?",
+        "What was your most memorable match and why?",
+    ],
+)
 
-if __name__ == "__main__":
-    demo.launch()
+# Launch the interface
+iface.launch()