mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-25 12:16:17 +03:00
Merge pull request #1213 from thatlukinhasguy1/main
Make the API use FastAPI instead of Flask
This commit is contained in:
Tekky
GitHub
commit
d5a499d064
@ -115,4 +115,4 @@ class Completion:
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return result if stream else ''.join(result)
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if version_check:
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check_pypi_version()
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check_pypi_version()
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@ -1,163 +1,137 @@
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import typing
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from .. import BaseProvider
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import g4f; g4f.debug.logging = True
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from fastapi import FastAPI, Response, Request
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from typing import List, Union, Any, Dict, AnyStr
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from ._tokenizer import tokenize
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from .. import BaseProvider
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import time
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import json
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import random
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import string
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import logging
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from typing import Union
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from loguru import logger
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from waitress import serve
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from ._logging import hook_logging
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from ._tokenizer import tokenize
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from flask_cors import CORS
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from werkzeug.serving import WSGIRequestHandler
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from werkzeug.exceptions import default_exceptions
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from werkzeug.middleware.proxy_fix import ProxyFix
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from flask import (
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Flask,
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jsonify,
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make_response,
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request,
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)
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import uvicorn
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import nest_asyncio
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import g4f
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class Api:
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__default_ip = '127.0.0.1'
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__default_port = 1337
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def __init__(self, engine: g4f, debug: bool = True, sentry: bool = False,
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list_ignored_providers:typing.List[typing.Union[str, BaseProvider]]=None) -> None:
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self.engine = engine
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self.debug = debug
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self.sentry = sentry
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self.list_ignored_providers = list_ignored_providers
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self.log_level = logging.DEBUG if debug else logging.WARN
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hook_logging(level=self.log_level, format='[%(asctime)s] %(levelname)s in %(module)s: %(message)s')
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self.logger = logging.getLogger('waitress')
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self.app = Flask(__name__)
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self.app.wsgi_app = ProxyFix(self.app.wsgi_app, x_port=1)
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self.app.after_request(self.__after_request)
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def run(self, bind_str, threads=8):
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host, port = self.__parse_bind(bind_str)
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list_ignored_providers: List[Union[str, BaseProvider]] = None) -> None:
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self.engine = engine
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self.debug = debug
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self.sentry = sentry
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self.list_ignored_providers = list_ignored_providers
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CORS(self.app, resources={r'/v1/*': {'supports_credentials': True, 'expose_headers': [
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'Content-Type',
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'Authorization',
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'X-Requested-With',
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'Accept',
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'Origin',
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'Access-Control-Request-Method',
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'Access-Control-Request-Headers',
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'Content-Disposition'], 'max_age': 600}})
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self.app = FastAPI()
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nest_asyncio.apply()
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self.app.route('/v1/models', methods=['GET'])(self.models)
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self.app.route('/v1/models/<model_id>', methods=['GET'])(self.model_info)
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JSONObject = Dict[AnyStr, Any]
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JSONArray = List[Any]
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JSONStructure = Union[JSONArray, JSONObject]
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self.app.route('/v1/chat/completions', methods=['POST'])(self.chat_completions)
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self.app.route('/v1/completions', methods=['POST'])(self.completions)
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@self.app.get("/")
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async def read_root():
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return Response(content=json.dumps({"info": "g4f API"}, indent=4), media_type="application/json")
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for ex in default_exceptions:
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self.app.register_error_handler(ex, self.__handle_error)
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@self.app.get("/v1")
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async def read_root_v1():
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return Response(content=json.dumps({"info": "Go to /v1/chat/completions or /v1/models."}, indent=4), media_type="application/json")
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if not self.debug:
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self.logger.warning(f'Serving on http://{host}:{port}')
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@self.app.get("/v1/models")
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async def models():
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model_list = [{
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'id': model,
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'object': 'model',
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'created': 0,
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'owned_by': 'g4f'} for model in g4f.Model.__all__()]
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WSGIRequestHandler.protocol_version = 'HTTP/1.1'
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serve(self.app, host=host, port=port, ident=None, threads=threads)
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def __handle_error(self, e: Exception):
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self.logger.error(e)
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return Response(content=json.dumps({
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'object': 'list',
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'data': model_list}, indent=4), media_type="application/json")
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return make_response(jsonify({
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'code': e.code,
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'message': str(e.original_exception if self.debug and hasattr(e, 'original_exception') else e.name)}), 500)
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@staticmethod
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def __after_request(resp):
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resp.headers['X-Server'] = f'g4f/{g4f.version}'
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return resp
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def __parse_bind(self, bind_str):
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sections = bind_str.split(':', 2)
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if len(sections) < 2:
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@self.app.get("/v1/models/{model_name}")
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async def model_info(model_name: str):
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try:
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port = int(sections[0])
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return self.__default_ip, port
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except ValueError:
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return sections[0], self.__default_port
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model_info = (g4f.ModelUtils.convert[model_name])
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return sections[0], int(sections[1])
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async def home(self):
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return 'Hello world | https://127.0.0.1:1337/v1'
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async def chat_completions(self):
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model = request.json.get('model', 'gpt-3.5-turbo')
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stream = request.json.get('stream', False)
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messages = request.json.get('messages')
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logger.info(f'model: {model}, stream: {stream}, request: {messages[-1]["content"]}')
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return Response(content=json.dumps({
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'id': model_name,
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'object': 'model',
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'created': 0,
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'owned_by': model_info.base_provider
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}, indent=4), media_type="application/json")
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except:
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return Response(content=json.dumps({"error": "The model does not exist."}, indent=4), media_type="application/json")
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config = None
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proxy = None
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try:
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config = json.load(open("config.json","r",encoding="utf-8"))
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proxy = config["proxy"]
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except Exception:
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pass
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if proxy != None:
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response = self.engine.ChatCompletion.create(model=model,
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stream=stream, messages=messages,
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ignored=self.list_ignored_providers,
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proxy=proxy)
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else:
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response = self.engine.ChatCompletion.create(model=model,
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stream=stream, messages=messages,
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ignored=self.list_ignored_providers)
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completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
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completion_timestamp = int(time.time())
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if not stream:
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prompt_tokens, _ = tokenize(''.join([message['content'] for message in messages]))
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completion_tokens, _ = tokenize(response)
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return {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'message': {
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'role': 'assistant',
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'content': response,
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},
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'finish_reason': 'stop',
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}
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],
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'usage': {
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'prompt_tokens': prompt_tokens,
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'completion_tokens': completion_tokens,
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'total_tokens': prompt_tokens + completion_tokens,
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},
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@self.app.post("/v1/chat/completions")
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async def chat_completions(request: Request, item: JSONStructure = None):
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item_data = {
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'model': 'gpt-3.5-turbo',
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'stream': False,
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}
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def streaming():
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item_data.update(item or {})
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model = item_data.get('model')
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stream = item_data.get('stream')
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messages = item_data.get('messages')
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try:
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for chunk in response:
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completion_data = {
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response = g4f.ChatCompletion.create(model=model, stream=stream, messages=messages)
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except:
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return Response(content=json.dumps({"error": "An error occurred while generating the response."}, indent=4), media_type="application/json")
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completion_id = ''.join(random.choices(string.ascii_letters + string.digits, k=28))
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completion_timestamp = int(time.time())
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if not stream:
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prompt_tokens, _ = tokenize(''.join([message['content'] for message in messages]))
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completion_tokens, _ = tokenize(response)
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json_data = {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'message': {
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'role': 'assistant',
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'content': response,
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},
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'finish_reason': 'stop',
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}
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],
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'usage': {
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'prompt_tokens': prompt_tokens,
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'completion_tokens': completion_tokens,
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'total_tokens': prompt_tokens + completion_tokens,
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},
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}
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return Response(content=json.dumps(json_data, indent=4), media_type="application/json")
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def streaming():
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try:
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for chunk in response:
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completion_data = {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion.chunk',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'delta': {
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'content': chunk,
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},
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'finish_reason': None,
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}
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],
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}
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content = json.dumps(completion_data, separators=(',', ':'))
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yield f'data: {content}\n\n'
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time.sleep(0.03)
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end_completion_data = {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion.chunk',
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'created': completion_timestamp,
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@ -165,63 +139,24 @@ class Api:
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'choices': [
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{
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'index': 0,
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'delta': {
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'content': chunk,
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},
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'finish_reason': None,
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'delta': {},
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'finish_reason': 'stop',
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}
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],
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}
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content = json.dumps(completion_data, separators=(',', ':'))
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content = json.dumps(end_completion_data, separators=(',', ':'))
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yield f'data: {content}\n\n'
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time.sleep(0.03)
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end_completion_data = {
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'id': f'chatcmpl-{completion_id}',
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'object': 'chat.completion.chunk',
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'created': completion_timestamp,
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'model': model,
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'choices': [
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{
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'index': 0,
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'delta': {},
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'finish_reason': 'stop',
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}
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],
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}
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content = json.dumps(end_completion_data, separators=(',', ':'))
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yield f'data: {content}\n\n'
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logger.success(f'model: {model}, stream: {stream}')
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except GeneratorExit:
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pass
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except GeneratorExit:
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pass
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return self.app.response_class(streaming(), mimetype='text/event-stream')
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async def completions(self):
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return 'not working yet', 500
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async def model_info(self, model_name):
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model_info = (g4f.ModelUtils.convert[model_name])
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return jsonify({
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'id' : model_name,
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'object' : 'model',
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'created' : 0,
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'owned_by' : model_info.base_provider
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})
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async def models(self):
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model_list = [{
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'id' : model,
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'object' : 'model',
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'created' : 0,
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'owned_by' : 'g4f'} for model in g4f.Model.__all__()]
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return jsonify({
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'object': 'list',
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'data': model_list})
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return Response(content=json.dumps(streaming(), indent=4), media_type="application/json")
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@self.app.post("/v1/completions")
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async def completions():
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return Response(content=json.dumps({'info': 'Not working yet.'}, indent=4), media_type="application/json")
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def run(self, ip):
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split_ip = ip.split(":")
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uvicorn.run(app=self.app, host=split_ip[0], port=int(split_ip[1]), use_colors=False)
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@ -3,4 +3,4 @@ import g4f.api
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if __name__ == "__main__":
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print(f'Starting server... [g4f v-{g4f.version}]')
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g4f.api.Api(g4f).run('127.0.0.1:1337', 8)
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g4f.api.Api(engine = g4f, debug = True).run(ip = "127.0.0.1:1337")
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@ -7,11 +7,9 @@ from g4f import Provider
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from g4f.api import Api
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from g4f.gui.run import gui_parser, run_gui_args
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def run_gui(args):
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print("Running GUI...")
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def main():
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IgnoredProviders = Enum("ignore_providers", {key: key for key in Provider.__all__})
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parser = argparse.ArgumentParser(description="Run gpt4free")
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@ -19,22 +17,19 @@ def main():
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api_parser=subparsers.add_parser("api")
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api_parser.add_argument("--bind", default="127.0.0.1:1337", help="The bind string.")
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api_parser.add_argument("--debug", type=bool, default=False, help="Enable verbose logging")
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api_parser.add_argument("--num-threads", type=int, default=8, help="The number of threads.")
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api_parser.add_argument("--ignored-providers", nargs="+", choices=[provider.name for provider in IgnoredProviders],
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default=[], help="List of providers to ignore when processing request.")
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subparsers.add_parser("gui", parents=[gui_parser()], add_help=False)
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args = parser.parse_args()
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if args.mode == "api":
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controller=Api(g4f, debug=args.debug)
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controller.list_ignored_providers=args.ignored_providers
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controller.run(args.bind, args.num_threads)
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controller=Api(engine=g4f, debug=args.debug, list_ignored_providers=args.ignored_providers)
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controller.run(args.bind)
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elif args.mode == "gui":
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run_gui_args(args)
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else:
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parser.print_help()
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exit(1)
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if __name__ == "__main__":
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main()
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@ -6,8 +6,6 @@ certifi
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browser_cookie3
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websockets
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js2py
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flask[async]
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flask-cors
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typing-extensions
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PyExecJS
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duckduckgo-search
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@ -20,3 +18,5 @@ pillow
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platformdirs
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numpy
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asgiref
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fastapi
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uvicorn
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