added

app.py

@@ -1,12 +1,23 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-
+from model import *
 """
 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 evaluate_response(problem):
+#     problem=b'what is angle x if angle y is 60 degree and angle z in 60 degree of a traingle'
+    problem=problem.decode('utf-8')
+    results, answers = [[],[]]
+    messages = [{"role": "user", "content": problem  }] 
+    query_prompt = tokenizer.apply_chat_template(messages, tokenize=False)
+    raw_output = pipeline(query_prompt, max_new_tokens=2048, do_sample=True, temperature=0.9, return_full_text=False)
 
+    raw_output = raw_output[0]['generated_text']
+#     result_output, code_output = process_output(raw_output)
+    return raw_output
+    
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -42,22 +53,30 @@ def respond(
 """
 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)",
-        ),
-    ],
-)
+# demo = gr.ChatInterface(
+#     evaluate_response,
+#     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)",
+#         ),
+#     ],
+# )
 
+demo = gr.Interface(
+        fn=evaluate_response,
+        inputs=[gr.Textbox(label="Question")],
+        outputs=gr.Textbox(label="Answer"),
+        title="Question and Answer Interface",
+        description="Enter a question."
+    )
 
+  
 if __name__ == "__main__":
     demo.launch()