wip

app.py

@@ -7,23 +7,23 @@ For more information on `huggingface_hub` Inference API support, please check th
 """
 client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+
 @spaces.GPU
 def respond(
     message,
-    history: list[tuple[str, str]],
-    system_message,
+    task_type,
     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 = [{"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 = []
     messages.append({"role": "user", "content": message})
 
     response = ""
@@ -40,13 +40,52 @@ def respond(
         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=[
+# 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)",
+#         ),
+#     ],
+# )
+task_types = [
+    "extractive question answering",
+    "multiple-choice question answering",
+    "question generation",
+    "question answering without choices",
+    "yes-no question answering",
+    "coreference resolution",
+    "paraphrase generation",
+    "paraphrase identification",
+    "sentence completion",
+    "sentiment",
+    "summarization",
+    "text generation",
+    "topic classification",
+    "word sense disambiguation",
+    "textual entailment",
+    "natural language inference",
+]
+
+demo = gr.Interface(
+    fn=respond,
+    inputs=[
         gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Dropdown(task_types, label="Task type"),
+    ],
+    outputs=gr.Textbox(label="Response"),
+    additional_inputs=[
         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(
@@ -57,8 +96,10 @@ demo = gr.ChatInterface(
             label="Top-p (nucleus sampling)",
         ),
     ],
+    title="Zephyr Chatbot",
+    description="A chatbot that uses the Hugging Face Zephyr model.",
 )
 
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()