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import chainlit as cl
from huggingface_hub import AsyncInferenceClient
#load model
API_TOKEN = "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"
headers = {"Authorization": f"Bearer {API_TOKEN}","Content-Type": "application/json"}
API_URL = "https://kfsb1xfskc2136wg.eu-west-1.aws.endpoints.huggingface.cloud"
client = AsyncInferenceClient(model=API_URL,token=API_TOKEN)
@cl.on_chat_start
async def main():
cl.user_session.set("history", [])
msg = cl.Message(content=f"Loading Chat please wait ...")
await msg.send()
# Let the user know that the system is ready
await msg.update(content=f"Chat has been loaded. You can now ask questions!")
return
@cl.on_message
async def main(message: str):
h = cl.user_session.get("history")
h.append("<|prompter|>"+message+"<|endoftext|><|assistant|>")
resp = ""
msg = cl.Message(content="")
async for token in await client.text_generation("".join(h), stream=True,max_new_tokens =250):
if token!="<|endoftext|>":
print(token, end="")
resp += token
await msg.stream_token(token)
h.append(resp+"<|endoftext|>")
cl.user_session.set("history",h)
print(h)
await msg.send()
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