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import gradio as gr
import os
import cohere
from huggingface_hub import InferenceClient
# Retrieve API keys from environment variables
HF_API_KEY = os.getenv("HF_API_KEY")
COHERE_API_KEY = os.getenv("COHERE_API_KEY")
# Initialize clients
hf_model = "meta-llama/Llama-3.2-3B-Instruct" # Change to preferred HF model
hf_client = InferenceClient(model=hf_model, token=HF_API_KEY)
cohere_client = cohere.Client(COHERE_API_KEY)
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
use_cohere, # Checkbox input
):
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
# 🔹 **Switch API based on checkbox**
if use_cohere:
response = cohere_client.chat(
model="command-r-plus",
message=message,
chat_history=[{"user_name": "User", "text": h[0]} for h in history if h[0]] +
[{"user_name": "Assistant", "text": h[1]} for h in history if h[1]],
temperature=temperature,
max_tokens=max_tokens,
p=top_p,
)
return response.text # Cohere returns full response
else:
response = ""
for message in hf_client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
token = message.choices[0].delta.content
response += token
yield response # Hugging Face supports streaming
# 🔥 **Gradio UI with Checkbox**
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(
minimum=0.1,
maximum=1.0,
value=0.95,
step=0.05,
label="Top-p (nucleus sampling)",
),
gr.Checkbox(label="Use Cohere API", value=False), # Checkbox to toggle API
],
)
if __name__ == "__main__":
demo.launch()
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