Update app.py

app.py

@@ -25,122 +25,136 @@ client = InferenceClient(
     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!**
+# 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 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.
+#                 🧪 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/)
+#                 👀 **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!
+#                 ➡️️ **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.
-                """
-            )
+#                 ⚠️ **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,
-    ) 
+#     gr.ChatInterface(
+#         generate, 
+#         examples=EXAMPLES,
+#         additional_inputs=additional_inputs,
+#     ) 
 
-demo.launch(show_api=True, share=True)
+#demo.launch(show_api=True, share=True)
 #demo.queue(concurrency_count=100, api_open=False).launch(show_api=True)
+
+def query(text):
+    print(text)
+    return text
+
+iface = gr.Interface(
+    transcribe,
+    inputs=["text"],
+    outputs="text",
+)
+
+
+iface.queue()
+iface.launch()