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Browse files- app.py +165 -0
- requirements.txt +71 -0
app.py
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import os
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import gradio as gr
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from text_generation import Client
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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API_URL = " https://api-inference.huggingface.co/models/BigCode/octocoder"
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theme = gr.themes.Monochrome(
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primary_hue="indigo",
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secondary_hue="blue",
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neutral_hue="slate",
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radius_size=gr.themes.sizes.radius_sm,
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font=[
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gr.themes.GoogleFont("Open Sans"),
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"ui-sans-serif",
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"system-ui",
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"sans-serif",
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],
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)
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client = Client(
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API_URL,
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headers={"Authorization": f"Bearer {HF_TOKEN}"},
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)
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def generate(query:str, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, ):
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if query.endswith("."):
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prompt = f"Question: {query}\n\nAnswer:"
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else:
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prompt = f"Question: {query}.\n\nAnswer:"
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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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stream = client.generate_stream(prompt, **generate_kwargs)
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output = ""
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previous_token = ""
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for response in stream:
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if response.token.text == "<|endoftext|>":
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return output
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else:
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output += response.token.text
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previous_token = response.token.text
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yield output
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return output
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def process_example(args):
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for x in generate(args):
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pass
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return x
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css = ".generating {visibility: hidden}"
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monospace_css = """
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#q-input textarea {
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font-family: monospace, 'Consolas', Courier, monospace;
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}
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"""
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description = """
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<div style="text-align: center;">
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<center><img src='https://raw.githubusercontent.com/bigcode-project/octopack/31f3320f098703c7910e43492c39366eeea68d83/banner.png' width='70%'/></center>
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<br>
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<h1><u> OctoCoder Demo </u></h1>
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</div>
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<br>
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<div style="text-align: center;">
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<p>This is a demo to demonstrate the capabilities of <a href="https://huggingface.co/bigcode/octocoder">OctoCoder</a> model by showing how it can be used to generate code by following the instructions provided in the input.</p>
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<p><strong>OctoCoder</strong> is an instruction tuned model with 15.5B parameters created by finetuning StarCoder on CommitPackFT & OASST</p>
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</div>
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"""
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disclaimer = """⚠️<b>Any use or sharing of this demo constitues your acceptance of the BigCode [OpenRAIL-M](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) License Agreement and the use restrictions included within.</b>\
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<br>**Intended Use**: this app and its [supporting model](https://huggingface.co/bigcode) are provided for demonstration purposes; not to serve as replacement for human expertise. For more details on the model's limitations in terms of factuality and biases, see the [model card.](https://huggingface.co/bigcode)"""
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examples = [['Please write a function in Python that performs bubble sort.']]
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with gr.Blocks(theme=theme, analytics_enabled=False, css=css) as demo:
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with gr.Column():
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gr.Markdown(description)
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with gr.Row():
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with gr.Column():
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with gr.Accordion("Settings", open=True):
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with gr.Row():
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column_1, column_2 = gr.Column(), gr.Column()
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with column_1:
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temperature = gr.Slider(
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label="Temperature",
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value=0.2,
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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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max_new_tokens = 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=8192,
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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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with column_2:
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top_p = 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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repetition_penalty = 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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with gr.Row():
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with gr.Column():
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instruction = gr.Textbox(
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placeholder="Enter your query here",
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lines=5,
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label="Input",
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elem_id="q-input",
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)
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submit = gr.Button("Generate", variant="primary")
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output = gr.Code(elem_id="q-output", lines=30, label="Output")
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gr.Markdown(disclaimer)
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gr.Examples(
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examples=examples,
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inputs=[instruction],
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cache_examples=False,
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fn=process_example,
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outputs=[output],
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)
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submit.click(
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generate,
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inputs=[instruction, temperature, max_new_tokens, top_p, repetition_penalty],
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outputs=[output],
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)
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demo.queue(concurrency_count=16).launch(debug=True)
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requirements.txt
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aiofiles==23.2.1
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aiohttp==3.8.5
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aiosignal==1.3.1
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altair==5.0.1
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annotated-types==0.5.0
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anyio==3.7.1
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async-timeout==4.0.2
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attrs==23.1.0
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certifi==2023.7.22
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charset-normalizer==3.2.0
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click==8.1.6
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contourpy==1.1.0
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cycler==0.11.0
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exceptiongroup==1.1.2
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fastapi==0.101.0
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ffmpy==0.3.1
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filelock==3.12.2
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fonttools==4.42.0
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frozenlist==1.4.0
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fsspec==2023.6.0
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gradio==3.39.0
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gradio_client==0.3.0
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h11==0.14.0
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httpcore==0.17.3
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httpx==0.24.1
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huggingface-hub==0.16.4
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idna==3.4
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importlib-resources==6.0.1
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Jinja2==3.1.2
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jsonschema==4.19.0
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jsonschema-specifications==2023.7.1
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kiwisolver==1.4.4
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linkify-it-py==2.0.2
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markdown-it-py==2.2.0
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MarkupSafe==2.1.3
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matplotlib==3.7.2
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mdit-py-plugins==0.3.3
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mdurl==0.1.2
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multidict==6.0.4
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numpy==1.24.4
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orjson==3.9.4
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packaging==23.1
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pandas==2.0.3
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Pillow==10.0.0
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pkgutil_resolve_name==1.3.10
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pydantic==1.10.12
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pydantic_core==2.4.0
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pydub==0.25.1
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pyparsing==3.0.9
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python-dateutil==2.8.2
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python-multipart==0.0.6
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pytz==2023.3
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PyYAML==6.0.1
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referencing==0.30.2
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requests==2.31.0
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rpds-py==0.9.2
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semantic-version==2.10.0
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six==1.16.0
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sniffio==1.3.0
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starlette==0.27.0
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text-generation==0.6.0
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toolz==0.12.0
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tqdm==4.66.0
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typing_extensions==4.7.1
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tzdata==2023.3
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uc-micro-py==1.0.2
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urllib3==2.0.4
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uvicorn==0.23.2
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websockets==11.0.3
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yarl==1.9.2
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zipp==3.16.2
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