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| import gradio as gr | |
| import cohere | |
| import os | |
| import re | |
| import uuid | |
| import secrets | |
| cohere_api_key = os.getenv("COHERE_API_KEY") | |
| co = cohere.Client(cohere_api_key, client_name="huggingface-rp") | |
| def trigger_example(example): | |
| chat, updated_history = generate_response(example) | |
| return chat, updated_history | |
| def generate_response(user_message, cid, token, history=None): | |
| if not token: | |
| raise gr.Error("Error loading.") | |
| if history is None: | |
| history = [] | |
| if cid == "" or None: | |
| cid = str(uuid.uuid4()) | |
| print(f"cid: {cid} prompt:{user_message}") | |
| history.append(user_message) | |
| stream = co.chat_stream(message=user_message, conversation_id=cid, model='command-r-plus', connectors=[], temperature=0.3) | |
| output = "" | |
| for idx, response in enumerate(stream): | |
| if response.event_type == "text-generation": | |
| output += response.text | |
| if idx == 0: | |
| history.append(" " + output) | |
| else: | |
| history[-1] = output | |
| chat = [ | |
| (history[i].strip(), history[i + 1].strip()) | |
| for i in range(0, len(history) - 1, 2) | |
| ] | |
| yield chat, history, cid | |
| return chat, history, cid | |
| def clear_chat(): | |
| return [], [], str(uuid.uuid4()) | |
| examples = [ | |
| "What are 8 good questions to get to know a stranger?", | |
| "Create a list of 10 unusual excuses people might use to get out of a work meeting", | |
| "Write a python code to reverse a string", | |
| "Explain the relativity theory in French", | |
| "Como sair de um helicóptero que caiu na água?", | |
| "Formally introduce the transformer architecture with notation.", | |
| "¿Cómo le explicarías el aprendizaje automático a un extraterrestre?", | |
| "Summarize recent news about the North American tech job market", | |
| "Explain gravity to a chicken.", | |
| "Is the world discrete or analog?", | |
| "What is the memory cost in a typical implementation of an all-gather operation?", | |
| "Give me a brief history of the golden era of Cantopop.", | |
| "Descrivi il processo di creazione di un capolavoro, come se fossi un artista del Rinascimento a Firenze.", | |
| "Explique-moi le sens de la vie selon un grand auteur littéraire.", | |
| "Give me an example of an endangered species and let me know what I can do to help preserve it" | |
| ] | |
| custom_css = """ | |
| #logo-img { | |
| border: none !important; | |
| } | |
| #chat-message { | |
| font-size: 14px; | |
| min-height: 300px; | |
| } | |
| """ | |
| with gr.Blocks(analytics_enabled=False, css=custom_css) as demo: | |
| cid = gr.State("") | |
| token = gr.State(value=None) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| gr.Image("logoplus.png", elem_id="logo-img", show_label=False, show_share_button=False, show_download_button=False) | |
| with gr.Column(scale=3): | |
| 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. | |
| <br/><br/> | |
| **Model**: [c4ai-command-r-plus](https://huggingface.co/CohereForAI/c4ai-command-r-plus) | |
| <br/> | |
| **Developed by**: [Cohere](https://cohere.com/) and [Cohere for AI](https://cohere.com/research) | |
| <br/> | |
| **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) | |
| """ | |
| ) | |
| with gr.Column(): | |
| with gr.Row(): | |
| chatbot = gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True) | |
| with gr.Row(): | |
| user_message = gr.Textbox(lines=1, placeholder="Ask anything ...", label="Input", show_label=False) | |
| with gr.Row(): | |
| submit_button = gr.Button("Submit") | |
| clear_button = gr.Button("Clear chat") | |
| history = gr.State([]) | |
| user_message.submit(fn=generate_response, inputs=[user_message, cid, token, history], outputs=[chatbot, history, cid], concurrency_limit=32) | |
| submit_button.click(fn=generate_response, inputs=[user_message, cid, token, history], outputs=[chatbot, history, cid], concurrency_limit=32) | |
| clear_button.click(fn=clear_chat, inputs=None, outputs=[chatbot, history, cid], concurrency_limit=32) | |
| user_message.submit(lambda x: gr.update(value=""), None, [user_message], queue=False) | |
| submit_button.click(lambda x: gr.update(value=""), None, [user_message], queue=False) | |
| clear_button.click(lambda x: gr.update(value=""), None, [user_message], queue=False) | |
| with gr.Row(): | |
| gr.Examples( | |
| examples=examples, | |
| inputs=user_message, | |
| cache_examples=False, | |
| fn=trigger_example, | |
| outputs=[chatbot], | |
| examples_per_page=100 | |
| ) | |
| demo.load(lambda: secrets.token_hex(16), None, token) | |
| if __name__ == "__main__": | |
| # demo.launch(debug=True) | |
| try: | |
| demo.queue(api_open=False, max_size=40).launch(show_api=False) | |
| except Exception as e: | |
| print(f"Error: {e}") |