Update app.py

app.py

@@ -7,7 +7,62 @@ For more information on `huggingface_hub` Inference API support, please check th
 """
 client = InferenceClient("meta-llama/Meta-Llama-3-8B",token=os.getenv('HF_API_TOKEN'))
 
-## None type 
+# ## None type 
+# def respond(
+#     message: str,
+#     history: list[tuple[str, str]],  # This will not be used
+#     system_message: str,
+#     max_tokens: int,
+#     temperature: float,
+#     top_p: float,
+# ):
+#     messages = [{"role": "system", "content": system_message}]
+    
+#     # Append only the latest user message
+#     messages.append({"role": "user", "content": message})
+
+#     response = ""
+
+#     try:
+#         # Generate response from the model
+#         for message in client.chat_completion(
+#             messages,
+#             max_tokens=max_tokens,
+#             stream=True,
+#             temperature=temperature,
+#             top_p=top_p,
+#         ):
+#             if message.choices[0].delta.content is not None:
+#                 token = message.choices[0].delta.content
+#                 response += token
+#             yield response
+#     except Exception as e:
+#         yield f"An error occurred: {e}"
+
+# """
+# 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)",
+#         ),
+#     ],
+# )
+
+# if __name__ == "__main__":
+#     demo.launch()
+
+
+####19
 def respond(
     message: str,
     history: list[tuple[str, str]],  # This will not be used
@@ -16,32 +71,26 @@ def respond(
     temperature: float,
     top_p: float,
 ):
-    messages = [{"role": "system", "content": system_message}]
-    
-    # Append only the latest user message
-    messages.append({"role": "user", "content": message})
+    # Combine the system message and user input into a single prompt
+    prompt = f"{system_message}\n{message}"
 
     response = ""
 
     try:
-        # Generate response from the model
-        for message in client.chat_completion(
-            messages,
-            max_tokens=max_tokens,
-            stream=True,
+        # Generate response from the model using text generation method
+        for message in client.text_generation(
+            prompt=prompt,
+            max_new_tokens=max_tokens,
             temperature=temperature,
             top_p=top_p,
         ):
-            if message.choices[0].delta.content is not None:
-                token = message.choices[0].delta.content
-                response += token
+            if message.token is not None:
+                response += message.token
             yield response
     except Exception as e:
         yield f"An error occurred: {e}"
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Define the Gradio interface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
@@ -61,7 +110,6 @@ demo = gr.ChatInterface(
 if __name__ == "__main__":
     demo.launch()
 
-
 # import os
 # import gradio as gr
 # from huggingface_hub import InferenceClient