XThomasBU commited on
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f8f58b3
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1 Parent(s): 9b3fb08

Update app.py

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  1. app.py +0 -54
app.py CHANGED
@@ -37,57 +37,6 @@ print(authorization_url, state)
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  # and then handling the redirect back to your application to exchange the code for a token.
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- from flask import Flask, request, redirect
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- import base64
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- import requests
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-
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- app = Flask(__name__)
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-
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- @app.route('/login/callback')
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- def login_callback():
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- # Retrieve the authorization code and state from the callback URL
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- code = request.args.get('code')
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- state = request.args.get('state')
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-
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- # You should verify the state here (compare it to the one you stored before redirecting the user)
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- # For simplicity, this step is not shown
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-
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- # Exchange the code for tokens
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- token_url = 'https://huggingface.co/oauth/token'
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- credentials = f"{OAUTH_CLIENT_ID}:{OAUTH_CLIENT_SECRET}"
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- basic_auth_header = base64.b64encode(credentials.encode('utf-8')).decode('utf-8')
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-
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- headers = {
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- 'Authorization': f'Basic {basic_auth_header}',
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- 'Content-Type': 'application/x-www-form-urlencoded'
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- }
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-
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- data = {
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- 'grant_type': 'authorization_code',
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- 'code': code,
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- 'redirect_uri': redirect_uri,
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- 'client_id': OAUTH_CLIENT_ID
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- }
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-
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- response = requests.post(token_url, headers=headers, data=data)
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-
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- if response.ok:
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- tokens = response.json()
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- access_token = tokens['access_token']
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- id_token = tokens.get('id_token')
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-
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- # Now you can use the access_token (and id_token) to access protected resources or identify the user
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- # For example, fetch user info from the userinfo endpoint if needed
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-
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- return "Login successful" # Redirect to another page or show a message
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- else:
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- return "Error exchanging code for tokens", 400
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-
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-
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- login_callback()
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-
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-
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-
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  # Instantiate the LLM
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  llm = HuggingFaceHub(
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  model_kwargs={"max_length": 500},
@@ -151,6 +100,3 @@ async def on_message(message: cl.Message):
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  await msg.stream_token(chunk)
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  await msg.send()
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-
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- if __name__ == '__main__':
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- app.run(debug=True)
 
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  # and then handling the redirect back to your application to exchange the code for a token.
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  # Instantiate the LLM
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  llm = HuggingFaceHub(
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  model_kwargs={"max_length": 500},
 
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  await msg.stream_token(chunk)
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  await msg.send()