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Alejandro Rodriguez Salamanca
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7a5ca50
1
Parent(s):
c9c672b
Use new chat-ui template
Browse files- Dockerfile +1 -0
- README.md +4 -4
- app.py +0 -143
- requirements.txt +0 -2
Dockerfile
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FROM ghcr.io/huggingface/chat-ui-db:sha-28351df
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README.md
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---
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title: C4AI Command
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emoji: 🌟
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colorFrom: purple
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colorTo: red
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sdk:
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app_file: app.py
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pinned: false
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license: other
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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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---
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title: C4AI Command Models
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emoji: 🌟
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colorFrom: purple
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colorTo: red
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sdk: docker
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pinned: false
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license: other
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app_port: 3000
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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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import cohere
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import os
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import re
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import uuid
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import secrets
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cohere_api_key = os.getenv("COHERE_API_KEY")
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co = cohere.Client(cohere_api_key, client_name="huggingface-rp")
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def trigger_example(example):
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chat, updated_history = generate_response(example)
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return chat, updated_history
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def generate_response(user_message, cid, token, history=None):
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if not token:
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raise gr.Error("Error loading.")
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if history is None:
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history = []
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if cid == "" or None:
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cid = str(uuid.uuid4())
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print(f"cid: {cid} prompt:{user_message}")
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history.append(user_message)
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stream = co.chat_stream(message=user_message, conversation_id=cid, model='command-r-plus', connectors=[], temperature=0.3)
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output = ""
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for idx, response in enumerate(stream):
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if response.event_type == "text-generation":
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output += response.text
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if idx == 0:
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history.append(" " + output)
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else:
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history[-1] = output
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chat = [
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(history[i].strip(), history[i + 1].strip())
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for i in range(0, len(history) - 1, 2)
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]
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yield chat, history, cid
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return chat, history, cid
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def clear_chat():
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return [], [], str(uuid.uuid4())
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examples = [
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"What are 8 good questions to get to know a stranger?",
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"Create a list of 10 unusual excuses people might use to get out of a work meeting",
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"Write a python code to reverse a string",
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"Explain the relativity theory in French",
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"Como sair de um helicóptero que caiu na água?",
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"Formally introduce the transformer architecture with notation.",
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"¿Cómo le explicarías el aprendizaje automático a un extraterrestre?",
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"Summarize recent news about the North American tech job market",
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"Explain gravity to a chicken.",
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"Is the world discrete or analog?",
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"What is the memory cost in a typical implementation of an all-gather operation?",
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"Give me a brief history of the golden era of Cantopop.",
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"Descrivi il processo di creazione di un capolavoro, come se fossi un artista del Rinascimento a Firenze.",
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"Explique-moi le sens de la vie selon un grand auteur littéraire.",
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"Give me an example of an endangered species and let me know what I can do to help preserve it"
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]
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custom_css = """
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#logo-img {
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border: none !important;
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}
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#chat-message {
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font-size: 14px;
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min-height: 300px;
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}
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"""
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with gr.Blocks(analytics_enabled=False, css=custom_css) as demo:
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cid = gr.State("")
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token = gr.State(value=None)
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with gr.Row():
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with gr.Column(scale=1):
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gr.Image("logoplus.png", elem_id="logo-img", show_label=False, show_share_button=False, show_download_button=False)
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with gr.Column(scale=3):
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gr.Markdown("""C4AI Command R+ is a research open weights release of a 104B billion parameter with highly advanced Retrieval Augmented Generation (RAG) capabilities, tool Use to automate sophisticated tasks, and is multilingual in 10 languages: English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, and Chinese. Command R+ is optimized for a variety of use cases including reasoning, summarization, and question answering.
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<br/><br/>
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**Model**: [c4ai-command-r-plus](https://huggingface.co/CohereForAI/c4ai-command-r-plus)
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<br/>
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**Developed by**: [Cohere](https://cohere.com/) and [Cohere for AI](https://cohere.com/research)
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<br/>
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**License**: [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license), requires also adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy)
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"""
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)
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with gr.Column():
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with gr.Row():
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chatbot = gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True)
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with gr.Row():
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user_message = gr.Textbox(lines=1, placeholder="Ask anything ...", label="Input", show_label=False)
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with gr.Row():
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submit_button = gr.Button("Submit")
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clear_button = gr.Button("Clear chat")
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history = gr.State([])
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user_message.submit(fn=generate_response, inputs=[user_message, cid, token, history], outputs=[chatbot, history, cid], concurrency_limit=32)
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submit_button.click(fn=generate_response, inputs=[user_message, cid, token, history], outputs=[chatbot, history, cid], concurrency_limit=32)
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clear_button.click(fn=clear_chat, inputs=None, outputs=[chatbot, history, cid], concurrency_limit=32)
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user_message.submit(lambda x: gr.update(value=""), None, [user_message], queue=False)
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submit_button.click(lambda x: gr.update(value=""), None, [user_message], queue=False)
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clear_button.click(lambda x: gr.update(value=""), None, [user_message], queue=False)
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with gr.Row():
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gr.Examples(
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examples=examples,
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inputs=user_message,
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cache_examples=False,
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fn=trigger_example,
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outputs=[chatbot],
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examples_per_page=100
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)
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demo.load(lambda: secrets.token_hex(16), None, token)
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if __name__ == "__main__":
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# demo.launch(debug=True)
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try:
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demo.queue(api_open=False, max_size=40).launch(show_api=False)
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except Exception as e:
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print(f"Error: {e}")
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requirements.txt
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gradio==4.1.0
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cohere
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