Update app.py

app.py

@@ -1,85 +1,116 @@
-# import gradio as gr
 # from huggingface_hub import InferenceClient
+# import gradio as gr
 
-# """
-# 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 respond(
-#     message,
-#     history: list[tuple[str, str]],
-#     system_message,
-#     max_tokens,
-#     temperature,
-#     top_p,
-# ):
-#     messages = [{"role": "system", "content": system_message}]
+# client = InferenceClient(
+#     "mistralai/Mistral-7B-Instruct-v0.3"
+# )
 
-#     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.append({"role": "user", "content": message})
+# 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
 
-#     response = ""
+# 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)
 
-#     for message in client.chat_completion(
-#         messages,
-#         max_tokens=max_tokens,
-#         stream=True,
+#     generate_kwargs = dict(
 #         temperature=temperature,
+#         max_new_tokens=max_new_tokens,
 #         top_p=top_p,
-#     ):
-#         token = message.choices[0].delta.content
-
-#         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=[
-#         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()
-from huggingface_hub import InferenceClient
+#         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
 
-client = InferenceClient(
-    "mistralai/Mistral-7B-Instruct-v0.3"
-)
-
+# Initialize the client with your desired model
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Define the system prompt as an AI Dermatologist
 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
-
+    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]"
+    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
+
+# Function to generate responses with the AI Dermatologist context
 def generate(
-    prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
+    prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0
 ):
     temperature = float(temperature)
     if temperature < 1e-2:
@@ -97,7 +128,9 @@ def generate(
 
     formatted_prompt = format_prompt(prompt, history)
 
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    stream = client.text_generation(
+        formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False
+    )
     output = ""
 
     for response in stream:
@@ -105,8 +138,8 @@ def generate(
         yield output
     return output
 
-
-additional_inputs=[
+# Customizable input controls for the chatbot interface
+additional_inputs = [
     gr.Slider(
         label="Temperature",
         value=0.9,
@@ -145,13 +178,13 @@ additional_inputs=[
     )
 ]
 
-
+# Define the chatbot interface with the starting system message as AI Dermatologist
 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"""
+    title="AI Dermatologist"
 ).launch(show_api=False)
 
-
-gr.load("models/Bhaskar2611/Capstone").launch()
+# Load your model after launching the interface
+gr.load("models/Bhaskar2611/Capstone").launch()