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import gradio as gr
from huggingface_hub import InferenceClient
from openai import OpenAI
import anthropic
import os
hf_client = InferenceClient()
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
anthropic_client = anthropic.Anthropic(api_key=os.getenv("ANTHROPIC_API_KEY"))
MODEL_OPTIONS = {
"Mixtral-8x7B-Instruct-v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
"Qwen2-72B-Instruct": "Qwen/Qwen2-72B-Instruct",
"GPT-3.5-turbo": "gpt-3.5-turbo",
"GPT-4": "gpt-4",
"claude-3-5-sonnet": "claude-3-5-sonnet-20240620",
}
def generate_text(model_choice, messages):
full_response = ""
if "Mixtral" in model_choice or "Qwen" in model_choice:
prompt = "\n".join([f"Human: {m[0]}\nAI: {m[1] if m[1] else ''}" for m in messages])
prompt += f"\nHuman: {messages[-1][0]}\nAI:"
stream = hf_client.text_generation(
model=MODEL_OPTIONS[model_choice],
prompt=prompt,
max_new_tokens=1000,
temperature=0.7,
do_sample=True,
repetition_penalty=1.1,
stream=True
)
for response in stream:
full_response += response # This line is correct now
yield full_response
elif "GPT" in model_choice:
openai_messages = [{"role": "system", "content": "You are a helpful assistant."}]
for m in messages:
openai_messages.append({"role": "user", "content": m[0]})
if m[1]:
openai_messages.append({"role": "assistant", "content": m[1]})
stream = openai_client.chat.completions.create(
model=MODEL_OPTIONS[model_choice],
messages=openai_messages,
max_tokens=1000,
temperature=0.7,
stream=True
)
for chunk in stream:
if chunk.choices[0].delta.content:
full_response += chunk.choices[0].delta.content
yield full_response
elif "claude" in model_choice:
claude_messages = []
for msg in messages:
if msg[0]: # User message
claude_messages.append({"role": "user", "content": msg[0]})
if msg[1]: # AI response
claude_messages.append({"role": "assistant", "content": msg[1]})
if not claude_messages:
claude_messages = [{"role": "user", "content": "Hello"}]
with anthropic_client.messages.stream(
model=MODEL_OPTIONS[model_choice],
max_tokens=1024,
messages=claude_messages
) as stream:
for text in stream.text_stream:
full_response += text
yield full_response
else:
yield "Unsupported model"
def user(user_message, history):
history = history or []
return "", history + [[user_message, None]]
def bot(history, model_choice):
if not history:
return []
bot_message = generate_text(model_choice, history)
history[-1][1] = ""
for chunk in bot_message:
history[-1][1] = chunk
yield history
with gr.Blocks() as iface:
chatbot = gr.Chatbot()
msg = gr.Textbox()
clear = gr.Button("Clear")
model_dropdown = gr.Dropdown(
choices=list(MODEL_OPTIONS.keys()),
value="Mixtral-8x7B-Instruct-v0.1",
label="Select Model"
)
msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
bot, [chatbot, model_dropdown], chatbot
)
clear.click(lambda: None, None, chatbot, queue=False)
if __name__ == "__main__":
iface.launch(debug=True) |