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import gradio as gr
import cohere
import os
import re
import uuid
from functools import partial
cohere_api_key = os.getenv("COHERE_API_KEY")
co = cohere.Client(cohere_api_key)
def trigger_example(example):
chat, updated_history = generate_response(example)
return chat, updated_history
def generate_response(user_message, history=None):
global cid
if history is None:
history = []
history.append(user_message)
stream = co.chat_stream(message=user_message, conversation_id=cid, model='command-r', 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
return chat, history
def clear_chat():
global cid
cid = str(uuid.uuid4())
return [], []
examples = [
"What are some good questions to get to know a stranger?",
"Create a list of 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"
]
title = """<h1 align="center">Cohere for AI Command R</h1>"""
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:
#gr.HTML(title)
with gr.Row():
with gr.Column(scale=1):
gr.Image("logo2.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 large language model with open weights optimized for various use cases
including reasoning, summarization, and question answering. Command R is capable of multilingual generation
evaluated in 10 languages and highly performant RAG capabilities.
<br/><br/>
**Model**: [c4ai-command-r-v01](https://huggingface.co/CohereForAI/c4ai-command-r-v01)
<br/>
**Developed by**: [Cohere](https://cohere.com/) and [Cohere for AI](https://cohere.com/research)
<br/>
**License**: CC-BY-NC, 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)
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([])
cid = str(uuid.uuid4())
user_message.submit(fn=generate_response, inputs=[user_message, history], outputs=[chatbot, history], concurrency_limit=32)
submit_button.click(fn=generate_response, inputs=[user_message, history], outputs=[chatbot, history], concurrency_limit=32)
clear_button.click(fn=clear_chat, inputs=None, outputs=[chatbot, history], concurrency_limit=32)
with gr.Row():
gr.Examples(
examples=examples,
inputs=[user_message],
cache_examples=False,
fn=trigger_example,
outputs=[chatbot],
)
if __name__ == "__main__":
demo.launch(debug=True) |