Update app.py

app.py

@@ -1,68 +1,61 @@
 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
-"""
+# Connect to Hugging Face model
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
+# Example Q&A pairs about Resilient Coders
+rc_qa_examples = [
+    ("What is Resilient Coders?", "Resilient Coders is a nonprofit that trains young people of color for careers in tech."),
+    ("Is the bootcamp free?", "Yes, the bootcamp is completely free and includes a stipend."),
+    ("How long is the program?", "It usually runs for about 14 to 20 weeks."),
+    ("Do I need to know how to code?", "No prior experience is required. We train participants from the ground up."),
+    ("Is it remote or in-person?", "The program may be remote, in-person, or hybrid depending on the cohort."),
+]
+
+# Main response function
+def respond(message, history, system_message, max_tokens, temperature, top_p):
+    # Format prompt
     messages = [{"role": "system", "content": system_message}]
-
-    # Add a few-shot context to guide the chatbot
-    rc_qa_examples = [
-        ("What is Resilient Coders?", "Resilient Coders is a nonprofit that trains young people of color for careers in tech."),
-        ("Is the bootcamp free?", "Yes, the bootcamp is completely free and includes a stipend."),
-        ("How long is the program?", "It usually runs for about 14 to 20 weeks."),
-        ("Do I need to know how to code?", "No prior experience is required. We train participants from the ground up."),
-        ("Is it remote or in-person?", "The program may be remote, in-person, or hybrid depending on the cohort."),
-    ]
+    
     for q, a in rc_qa_examples:
         messages.append({"role": "user", "content": q})
         messages.append({"role": "assistant", "content": a})
-
-    # Add conversation history
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    # Append current user message
+    
+    for user_msg, bot_reply in history:
+        if user_msg:
+            messages.append({"role": "user", "content": user_msg})
+        if bot_reply:
+            messages.append({"role": "assistant", "content": bot_reply})
+    
     messages.append({"role": "user", "content": message})
 
     # Stream response
     response = ""
-    for message in client.chat_completion(
-        messages,
+    for chunk in client.chat_completion(
+        messages=messages,
         max_tokens=max_tokens,
-        stream=True,
         temperature=temperature,
         top_p=top_p,
+        stream=True
     ):
-        token = message.choices[0].delta.content
-        response += token
-        yield response
-
+        delta = chunk.choices[0].delta.content
+        if delta:
+            response += delta
+            yield response
 
+# Gradio UI
 demo = gr.ChatInterface(
-    respond,
+    fn=respond,
     additional_inputs=[
-        gr.Textbox(value="You are a helpful assistant that only answers questions about the Resilient Coders bootcamp. If the question is unrelated, politely decline.", 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)"),
+        gr.Textbox(value="You are a helpful assistant who only answers questions about Resilient Coders.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max tokens"),
+        gr.Slider(minimum=0.1, maximum=2.0, 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"),
     ],
+    title="Resilient Coders FAQ Chatbot",
+    description="Ask anything about the Resilient Coders bootcamp!"
 )
 
-
 if __name__ == "__main__":
     demo.launch()