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Update app.py
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app.py
CHANGED
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# from huggingface_hub import InferenceClient
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# import gradio as gr
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# client = InferenceClient(
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# "mistralai/Mixtral-8x7B-Instruct-v0.1"
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# )
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# def format_prompt(message, history):
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# prompt = "<s>"
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# for user_prompt, bot_response in history:
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# prompt += f"[INST] {user_prompt} [/INST]"
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# prompt += f" {bot_response}</s> "
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# prompt += f"[INST] {message} [/INST]"
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# return prompt
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# def generate(
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# prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
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# ):
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# temperature = float(temperature)
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# if temperature < 1e-2:
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# temperature = 1e-2
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# top_p = float(top_p)
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# generate_kwargs = dict(
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# temperature=temperature,
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# max_new_tokens=max_new_tokens,
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# top_p=top_p,
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# repetition_penalty=repetition_penalty,
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# do_sample=True,
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# seed=42,
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# )
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# formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
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# stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
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# output = ""
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# for response in stream:
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# output += response.token.text
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# yield output
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# return output
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# additional_inputs=[
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# gr.Textbox(
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# label="System Prompt",
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# max_lines=1,
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# interactive=True,
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# ),
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# gr.Slider(
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# label="Temperature",
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# value=0.9,
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# minimum=0.0,
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# maximum=1.0,
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# step=0.05,
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# interactive=True,
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# info="Higher values produce more diverse outputs",
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# ),
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# gr.Slider(
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# label="Max new tokens",
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# value=256,
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# minimum=0,
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# maximum=1048,
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# step=64,
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# interactive=True,
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# info="The maximum numbers of new tokens",
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# ),
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# gr.Slider(
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# label="Top-p (nucleus sampling)",
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# value=0.90,
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# minimum=0.0,
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# maximum=1,
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# step=0.05,
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# interactive=True,
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# info="Higher values sample more low-probability tokens",
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# ),
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# gr.Slider(
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# label="Repetition penalty",
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# value=1.2,
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# minimum=1.0,
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# maximum=2.0,
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# step=0.05,
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# interactive=True,
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# info="Penalize repeated tokens",
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# )
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# ]
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# examples=[["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", None, None, None, None, None, ],
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# ["Can you write a short story about a time-traveling detective who solves historical mysteries?", None, None, None, None, None,],
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# ["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", None, None, None, None, None,],
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# ["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", None, None, None, None, None,],
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# ["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, None, None,],
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# ["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", None, None, None, None, None,],
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# ]
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# gr.ChatInterface(
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# fn=generate,
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# chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
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# additional_inputs=additional_inputs,
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# title="Mixtral 46.7B",
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# examples=examples,
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# concurrency_limit=20,
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# ).launch(show_api= True)
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from huggingface_hub import InferenceClient
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import gradio as gr
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from PyPDF2 import PdfReader
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client = InferenceClient(
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"mistralai/Mixtral-8x7B-Instruct-v0.1"
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)
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def format_prompt(message, history):
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prompt = "<s>"
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for user_prompt, bot_response in history:
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prompt += f"[INST] {user_prompt} [/INST]"
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prompt += f" {bot_response}</s> "
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prompt += f"[INST] {message} [/INST]"
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return prompt
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def extract_text_from_pdf(pdf_file):
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text = ""
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pdf_reader = PdfReader(pdf_file)
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for page in pdf_reader.pages:
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text += page.extract_text()
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return text
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def
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temperature = float(temperature)
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if temperature < 1e-2:
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temperature = 1e-2
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)
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
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if pdf_text:
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formatted_prompt += pdf_text
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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@@ -153,13 +40,13 @@ def generate(prompt, history, system_prompt, temperature=0.9, max_new_tokens=256
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yield output
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return output
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additional_inputs=[
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gr.Textbox(
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label="System Prompt",
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max_lines=1,
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interactive=True,
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),
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gr.File("file", label="Upload PDF"),
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gr.Slider(
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label="Temperature",
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value=0.9,
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@@ -198,14 +85,13 @@ additional_inputs=[
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)
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]
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examples=[
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]
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gr.ChatInterface(
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fn=generate,
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from huggingface_hub import InferenceClient
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import gradio as gr
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client = InferenceClient(
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"mistralai/Mixtral-8x7B-Instruct-v0.1"
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)
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def format_prompt(message, history):
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prompt = "<s>"
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for user_prompt, bot_response in history:
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prompt += f"[INST] {user_prompt} [/INST]"
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prompt += f" {bot_response}</s> "
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prompt += f"[INST] {message} [/INST]"
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return prompt
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def generate(
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prompt, history, system_prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
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):
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temperature = float(temperature)
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if temperature < 1e-2:
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temperature = 1e-2
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)
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
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output = ""
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yield output
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return output
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additional_inputs=[
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gr.Textbox(
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label="System Prompt",
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max_lines=1,
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interactive=True,
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),
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gr.Slider(
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label="Temperature",
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value=0.9,
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)
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]
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examples=[["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", None, None, None, None, None, ],
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["Can you write a short story about a time-traveling detective who solves historical mysteries?", None, None, None, None, None,],
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["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", None, None, None, None, None,],
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["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", None, None, None, None, None,],
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["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, None, None,],
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["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", None, None, None, None, None,],
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]
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gr.ChatInterface(
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fn=generate,
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