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# You can find this code for Chainlit python streaming here (https://docs.chainlit.io/concepts/streaming/python) | |
# OpenAI Chat completion | |
import os | |
from openai import AsyncOpenAI # importing openai for API usage | |
import chainlit as cl # importing chainlit for our app | |
from chainlit.prompt import Prompt, PromptMessage # importing prompt tools | |
from chainlit.playground.providers import ChatOpenAI # importing ChatOpenAI tools | |
from dotenv import load_dotenv | |
import requests | |
load_dotenv() | |
prompt_template = """\ | |
<|begin_of_text|><|start_header_id|>system<|end_header_id|> | |
Gen-Z-ify<|eot_id|><|start_header_id|>user<|end_header_id|> | |
{english}<|eot_id|><|start_header_id|>assistant<|end_header_id|> | |
""" | |
API_URL = "https://nc7q281oard1b1ar.us-east-1.aws.endpoints.huggingface.cloud" | |
# marks a function that should be run each time the chatbot receives a message from a user | |
async def main(message: cl.Message): | |
headers = { | |
"Accept" : "application/json", | |
"Authorization": f"Bearer {os.environ['HF_TOKEN']}", | |
"Content-Type": "application/json" | |
} | |
def query(payload): | |
response = requests.post(API_URL, headers=headers, json=payload) | |
return response.json() | |
formatted_prompt = prompt_template.format(english=message.content) | |
print(formatted_prompt) | |
output = query({ | |
"inputs": formatted_prompt, | |
"parameters": { | |
"return_full_text": False, | |
"clean_up_tokenization_spaces": False | |
} | |
}) | |
msg = cl.Message(content=output[0]["generated_text"]) | |
# Send and close the message stream | |
await msg.send() | |