Update app.py

app.py

@@ -1,96 +1,3 @@
-# from huggingface_hub import InferenceClient
-# import gradio as gr
-
-# client = InferenceClient(
-#     "mistralai/Mistral-7B-Instruct-v0.3"
-# )
-
-
-# def format_prompt(message, history):
-#   prompt = "<s>"
-#   for user_prompt, bot_response in history:
-#     prompt += f"[INST] {user_prompt} [/INST]"
-#     prompt += f" {bot_response}</s> "
-#   prompt += f"[INST] {message} [/INST]"
-#   return prompt
-
-# def generate(
-#     prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
-# ):
-#     temperature = float(temperature)
-#     if temperature < 1e-2:
-#         temperature = 1e-2
-#     top_p = float(top_p)
-
-#     generate_kwargs = dict(
-#         temperature=temperature,
-#         max_new_tokens=max_new_tokens,
-#         top_p=top_p,
-#         repetition_penalty=repetition_penalty,
-#         do_sample=True,
-#         seed=42,
-#     )
-
-#     formatted_prompt = format_prompt(prompt, history)
-
-#     stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-#     output = ""
-
-#     for response in stream:
-#         output += response.token.text
-#         yield output
-#     return output
-
-
-# additional_inputs=[
-#     gr.Slider(
-#         label="Temperature",
-#         value=0.9,
-#         minimum=0.0,
-#         maximum=1.0,
-#         step=0.05,
-#         interactive=True,
-#         info="Higher values produce more diverse outputs",
-#     ),
-#     gr.Slider(
-#         label="Max new tokens",
-#         value=256,
-#         minimum=0,
-#         maximum=1048,
-#         step=64,
-#         interactive=True,
-#         info="The maximum numbers of new tokens",
-#     ),
-#     gr.Slider(
-#         label="Top-p (nucleus sampling)",
-#         value=0.90,
-#         minimum=0.0,
-#         maximum=1,
-#         step=0.05,
-#         interactive=True,
-#         info="Higher values sample more low-probability tokens",
-#     ),
-#     gr.Slider(
-#         label="Repetition penalty",
-#         value=1.2,
-#         minimum=1.0,
-#         maximum=2.0,
-#         step=0.05,
-#         interactive=True,
-#         info="Penalize repeated tokens",
-#     )
-# ]
-
-
-# gr.ChatInterface(
-#     fn=generate,
-#     chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, layout="panel"),
-#     additional_inputs=additional_inputs,
-#     title="""AI Dermatologist"""
-# ).launch(show_api=False)
-
-
-# gr.load("models/Bhaskar2611/Capstone").launch()
 import gradio as gr
 from huggingface_hub import InferenceClient
 
@@ -101,7 +8,7 @@ client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 def format_prompt(message, history):
     prompt = "<s>"
     # Start the conversation with a system message
-    prompt += "[INST] You are an AI Dermatologist designed to assist users with skin and hair care.[/INST]"
+    prompt += "[INST] You are an AI Dermatologist designed to assist users with skin and hair care by providing text.[/INST]"
     for user_prompt, bot_response in history:
         prompt += f"[INST] {user_prompt} [/INST]"
         prompt += f" {bot_response}</s> "