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Parent(s):
EuroLLM chat Space creation
Browse files- .gitattributes +35 -0
- README.md +13 -0
- app.py +61 -0
- requirements.txt +2 -0
.gitattributes
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README.md
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---
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title: Eurollm Chat
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emoji: 👀
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colorFrom: indigo
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colorTo: red
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sdk: gradio
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sdk_version: 5.7.1
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app_file: app.py
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pinned: false
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short_description: HF space to interact with EuroLLM 9B Model
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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from huggingface_hub import InferenceClient, get_inference_endpoint
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from openai import OpenAI
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import os
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MODEL_URL_MAP = {"EuroLLM-9B-Instruct": os.getenv('ENDPOINT_URL_9B'),
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}
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def respond(
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message,
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history: list[tuple[str, str]],
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system_message,
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max_tokens,
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temperature,
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model
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):
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client = OpenAI(
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base_url=MODEL_URL_MAP.get(model),
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api_key=os.getenv('AUTH_TOKEN')
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)
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messages = [{"role": "system", "content": system_message}]
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for val in history:
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if val[0]:
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messages.append({"role": "user", "content": val[0]})
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if val[1]:
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messages.append({"role": "assistant", "content": val[1]})
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messages.append({"role": "user", "content": message})
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response = ""
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try:
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chat_completion = client.chat.completions.create(
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model=model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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stream=True,
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)
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for message in chat_completion:
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token = message.choices[0].delta.content
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response += token
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yield response
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except Exception:
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yield response
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demo = gr.ChatInterface(
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respond,
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additional_inputs=[
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gr.Textbox(value="", label="System Prompt"),
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gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.0, maximum=4.0, value=0.0, step=0.1, label="Temperature"),
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gr.Dropdown(["EuroLLM-9B-Instruct"], label="Model Name", value="EuroLLM-9B-Instruct")
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],
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)
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if __name__ == "__main__":
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demo.launch()
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requirements.txt
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huggingface_hub==0.25.2
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openai
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