try to fix error (#3)

- try to fix error (a99672311687ee28958543c593c2498c2d62b0de)


Co-authored-by: Klara Sofia Varga <Klariiii@users.noreply.huggingface.co>

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-
 def respond(
     message,
     history: list[dict[str, str]],
@@ -11,33 +10,66 @@ def respond(
     top_p,
     hf_token: None,
 ):
-    """
-    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
-    """
+    from huggingface_hub import InferenceClient
+
     client = InferenceClient(model="Ana8413/model")
 
+    # Build the message history for the model
     messages = [{"role": "system", "content": system_message}]
-
     messages.extend(history)
-
     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,
-    ):
-        choices = message.choices
-        token = ""
-        if len(choices) and choices[0].delta.content:
-            token = choices[0].delta.content
-
-        response += token
-        yield response
+    # Use try/finally to safely iterate over the streaming generator
+    try:
+        for chunk in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+        ):
+            # Some chunks may not have choices or content
+            if chunk.choices and chunk.choices[0].delta.content:
+                token = chunk.choices[0].delta.content
+                response += token
+                yield response  # Yield incremental response for streaming
+    except Exception as e:
+        # Catch other possible exceptions from the generator
+        print(f"Stream error: {e}")
+        yield response  # Return whatever has been accumulated so far
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+chatbot = gr.ChatInterface(
+    respond,
+    type="messages",
+    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)",
+        ),
+    ],
+)
+
+with gr.Blocks() as demo:
+    #with gr.Sidebar():
+    #    gr.LoginButton()
+    chatbot.render()
+
+
+if __name__ == "__main__":
+    demo.launch(show_error=True)
+
+
 
 
 """