Update app.py

app.py

@@ -8,143 +8,15 @@ from huggingface_hub import Repository, InferenceClient
 
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
 API_URL = "https://api-inference.huggingface.co/models/tiiuae/falcon-180B-chat"
-BOT_NAME = "Falcon"
+BOT_NAME = "Medic"
 
 STOP_SEQUENCES = ["\nUser:", "<|endoftext|>", " User:", "###"]
 
-EXAMPLES = [
-    ["Hey Falcon! Any recommendations for my holidays in Abu Dhabi?"],
-    ["What's the Everett interpretation of quantum mechanics?"],
-    ["Give me a list of the top 10 dive sites you would recommend around the world."],
-    ["Can you tell me more about deep-water soloing?"],
-    ["Can you write a short tweet about the release of our latest AI model, Falcon LLM?"]
-    ]
-
 client = InferenceClient(
     API_URL,
     headers={"Authorization": f"Bearer {HF_TOKEN}"},
 )
 
-# def format_prompt(message, history, system_prompt):
-#   prompt = ""
-#   if system_prompt:
-#     prompt += f"System: {system_prompt}\n"
-#   for user_prompt, bot_response in history:
-#     prompt += f"User: {user_prompt}\n"
-#     prompt += f"Falcon: {bot_response}\n" # Response already contains "Falcon: "
-#   prompt += f"""User: {message}
-# Falcon:"""
-#   return prompt
-
-# seed = 42
-
-# def generate(
-#     prompt, history, system_prompt="", 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)
-#     global seed
-#     generate_kwargs = dict(
-#         temperature=temperature,
-#         max_new_tokens=max_new_tokens,
-#         top_p=top_p,
-#         repetition_penalty=repetition_penalty,
-#         stop_sequences=STOP_SEQUENCES,
-#         do_sample=True,
-#         seed=seed,
-#     )
-#     seed = seed + 1
-#     formatted_prompt = format_prompt(prompt, history, system_prompt)
-
-#     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
-
-#         for stop_str in STOP_SEQUENCES:
-#             if output.endswith(stop_str):
-#                 output = output[:-len(stop_str)]
-#                 output = output.rstrip()
-#                 yield output
-#         yield output
-#     return output
-
-
-# additional_inputs=[
-#     gr.Textbox("", label="Optional system prompt"),
-#     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=8192,
-#         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",
-#     )
-# ]
-
-
-# with gr.Blocks() as demo:
-#     with gr.Row():
-#         with gr.Column(scale=0.4):
-#             gr.Image("better_banner.jpeg", elem_id="banner-image", show_label=False)
-#         with gr.Column():
-#             gr.Markdown(
-#                 """# Falcon-180B Demo
-
-#                 **Chat with [Falcon-180B-Chat](https://huggingface.co/tiiuae/falcon-180b-chat), brainstorm ideas, discuss your holiday plans, and more!**
-                
-#                 ✨ This demo is powered by [Falcon-180B](https://huggingface.co/tiiuae/falcon-180B) and finetuned on a mixture of [Ultrachat](https://huggingface.co/datasets/stingning/ultrachat), [Platypus](https://huggingface.co/datasets/garage-bAInd/Open-Platypus) and [Airoboros](https://huggingface.co/datasets/jondurbin/airoboros-2.1). [Falcon-180B](https://huggingface.co/tiiuae/falcon-180b) is a state-of-the-art large language model built by the [Technology Innovation Institute](https://www.tii.ae) in Abu Dhabi. It is trained on 3.5 trillion tokens (including [RefinedWeb](https://huggingface.co/datasets/tiiuae/falcon-refinedweb)) and available under the [Falcon-180B TII License](https://huggingface.co/spaces/tiiuae/falcon-180b-license/blob/main/LICENSE.txt). It currently holds the 🥇 1st place on the [🤗 Open LLM leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) for a pretrained model. 
-                
-#                 🧪 This is only a **first experimental preview**: we intend to provide increasingly capable versions of Falcon in the future, based on improved datasets and RLHF/RLAIF.
-                
-#                 👀 **Learn more about Falcon LLM:** [falconllm.tii.ae](https://falconllm.tii.ae/)
-                
-#                 ➡️️ **Intended Use**: this demo is intended to showcase an early finetuning of [Falcon-180B](https://huggingface.co/tiiuae/falcon-180b), to illustrate the impact (and limitations) of finetuning on a dataset of conversations and instructions. We encourage the community to further build upon the base model, and to create even better instruct/chat versions!
-                
-#                 ⚠️ **Limitations**: the model can and will produce factually incorrect information, hallucinating facts and actions. As it has not undergone any advanced tuning/alignment, it can produce problematic outputs, especially if prompted to do so. Finally, this demo is limited to a session length of about 1,000 words.
-#                 """
-#             )
-
-#     gr.ChatInterface(
-#         generate, 
-#         examples=EXAMPLES,
-#         additional_inputs=additional_inputs,
-#     ) 
-
-#demo.launch(show_api=True, share=True)
-#demo.queue(concurrency_count=100, api_open=False).launch(show_api=True)
-
 def query(system_prompt, user_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
     print(temperature, max_new_tokens, top_p, repetition_penalty)
     seed = 42
@@ -158,10 +30,6 @@ def query(system_prompt, user_prompt, temperature=0.9, max_new_tokens=256, top_p
         seed=seed,
     )
     prompt = f"System: {system_prompt}\nUser: {user_prompt}\nFalcon:"
-    print(prompt)
-    print('-----')
-    #output = client.text_generation(prompt, **generate_kwargs, details=True, return_full_text=False)
-    #print(output)
     stream = client.text_generation(prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
     for response in stream:
@@ -173,7 +41,6 @@ def query(system_prompt, user_prompt, temperature=0.9, max_new_tokens=256, top_p
                 output = output.rstrip()
                 #yield output
         #yield output
-    print(output)
     return output
 
 iface = gr.Interface(