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https://github.com/xtekky/gpt4free.git
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b8a3db526c
* Update backend.py change to the model that received from user interactive from the web interface model selection. * Update index.html added Llama2 as a provider selection and also include the model selection for Llama2: llama2-70b, llama2-13b, llama2-7b * Update requirements.txt add asgiref to enable async for Flask in api. "RuntimeError: Install Flask with the 'async' extra in order to use async views"
75 lines
2.2 KiB
Python
75 lines
2.2 KiB
Python
import g4f
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from flask import request
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from .internet import search
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from .config import special_instructions
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from .provider import get_provider
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g4f.logging = True
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class Backend_Api:
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def __init__(self, app) -> None:
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self.app = app
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self.routes = {
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'/backend-api/v2/models': {
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'function': self.models,
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'methods' : ['GET']
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},
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'/backend-api/v2/conversation': {
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'function': self._conversation,
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'methods': ['POST']
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},
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'/backend-api/v2/gen.set.summarize:title': {
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'function': self._gen_title,
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'methods': ['POST']
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},
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'/backend-api/v2/error': {
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'function': self.error,
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'methods': ['POST']
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}
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}
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def error(self):
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print(request.json)
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return 'ok', 200
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def models(self):
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return g4f._all_models
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def _gen_title(self):
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return {
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'title': ''
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}
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def _conversation(self):
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try:
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#jailbreak = request.json['jailbreak']
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#internet_access = request.json['meta']['content']['internet_access']
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#conversation = request.json['meta']['content']['conversation']
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prompt = request.json['meta']['content']['parts']
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model = request.json['model']
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provider = request.json.get('provider').split('g4f.Provider.')[1]
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messages = prompt
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print(messages)
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def stream():
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yield from g4f.ChatCompletion.create(
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model=model,
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provider=get_provider(provider),
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messages=messages,
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stream=True,
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) if provider else g4f.ChatCompletion.create(
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model=model, messages=messages, stream=True
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)
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return self.app.response_class(stream(), mimetype='text/event-stream')
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except Exception as e:
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return {
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'code' : 'G4F_ERROR',
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'_action': '_ask',
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'success': False,
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'error' : f'an error occurred {str(e)}'}, 400
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