diff options
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | g4f/Provider/Providers/Vercel.py | 110 | ||||
| -rw-r--r-- | g4f/__init__.py | 2 | ||||
| -rw-r--r-- | g4f/models.py | 5 | ||||
| -rw-r--r-- | setup.py | 2 |
5 files changed, 115 insertions, 5 deletions
@@ -35,6 +35,7 @@ dist/ *.egg-info build test.py +update.py # Emacs crap *~
\ No newline at end of file diff --git a/g4f/Provider/Providers/Vercel.py b/g4f/Provider/Providers/Vercel.py index 03d9be17..f9331bfc 100644 --- a/g4f/Provider/Providers/Vercel.py +++ b/g4f/Provider/Providers/Vercel.py @@ -42,6 +42,116 @@ vercel_models = {'anthropic:claude-instant-v1': {'id': 'anthropic:claude-instant 'id': 'huggingface:bigcode/santacoder', 'provider': 'huggingface', 'providerHumanName': 'HuggingFace', 'makerHumanName': 'BigCode', 'instructions': 'The model was trained on GitHub code. As such it is not an instruction model and commands like "Write a function that computes the square root." do not work well. You should phrase commands like they occur in source code such as comments (e.g. # the following function computes the sqrt) or write a function signature and docstring and let the model complete the function body.', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 0.95, 'range': [0.01, 0.99]}, 'topK': {'value': 4, 'range': [1, 500]}, 'repetitionPenalty': {'value': 1.03, 'range': [0.1, 2]}}, 'name': 'santacoder'}, 'cohere:command-medium-nightly': {'id': 'cohere:command-medium-nightly', 'provider': 'cohere', 'providerHumanName': 'Cohere', 'makerHumanName': 'Cohere', 'name': 'command-medium-nightly', 'parameters': {'temperature': {'value': 0.9, 'range': [0, 2]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0, 1]}, 'topK': {'value': 0, 'range': [0, 500]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'cohere:command-xlarge-nightly': {'id': 'cohere:command-xlarge-nightly', 'provider': 'cohere', 'providerHumanName': 'Cohere', 'makerHumanName': 'Cohere', 'name': 'command-xlarge-nightly', 'parameters': {'temperature': {'value': 0.9, 'range': [0, 2]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0, 1]}, 'topK': {'value': 0, 'range': [0, 500]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'openai:gpt-4': {'id': 'openai:gpt-4', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'name': 'gpt-4', 'minBillingTier': 'pro', 'parameters': {'temperature': {'value': 0.7, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'openai:code-cushman-001': {'id': 'openai:code-cushman-001', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}, 'name': 'code-cushman-001'}, 'openai:code-davinci-002': {'id': 'openai:code-davinci-002', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}, 'name': 'code-davinci-002'}, 'openai:gpt-3.5-turbo': {'id': 'openai:gpt-3.5-turbo', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'parameters': {'temperature': {'value': 0.7, 'range': [0, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'topK': {'value': 1, 'range': [1, 500]}, 'presencePenalty': {'value': 1, 'range': [0, 1]}, 'frequencyPenalty': {'value': 1, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}, 'name': 'gpt-3.5-turbo'}, 'openai:text-ada-001': {'id': 'openai:text-ada-001', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'name': 'text-ada-001', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'openai:text-babbage-001': {'id': 'openai:text-babbage-001', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'name': 'text-babbage-001', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'openai:text-curie-001': {'id': 'openai:text-curie-001', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'name': 'text-curie-001', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'openai:text-davinci-002': {'id': 'openai:text-davinci-002', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'name': 'text-davinci-002', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}, 'openai:text-davinci-003': {'id': 'openai:text-davinci-003', 'provider': 'openai', 'providerHumanName': 'OpenAI', 'makerHumanName': 'OpenAI', 'name': 'text-davinci-003', 'parameters': {'temperature': {'value': 0.5, 'range': [0.1, 1]}, 'maximumLength': {'value': 200, 'range': [50, 1024]}, 'topP': {'value': 1, 'range': [0.1, 1]}, 'presencePenalty': {'value': 0, 'range': [0, 1]}, 'frequencyPenalty': {'value': 0, 'range': [0, 1]}, 'stopSequences': {'value': [], 'range': []}}}} +# import requests +# import execjs +# import ubox +# import json +# import re + + +# html = requests.get('https://sdk.vercel.ai/').text +# paths_regex = r'static\/chunks.+?\.js' +# separator_regex = r'"\]\)<\/script><script>self\.__next_f\.push\(\[.,"' + +# paths = re.findall(paths_regex, html) +# for i in range(len(paths)): +# paths[i] = re.sub(separator_regex, "", paths[i]) +# paths = list(set(paths)) +# print(paths) + +# scripts = [] +# threads = [] + +# print(f"Downloading and parsing scripts...") +# def download_thread(path): +# script_url = f"{self.base_url}/_next/{path}" +# script = self.session.get(script_url).text +# scripts.append(script) + +# for path in paths: +# thread = threading.Thread(target=download_thread, args=(path,), daemon=True) +# thread.start() +# threads.append(thread) + +# for thread in threads: +# thread.join() + +# for script in scripts: +# models_regex = r'let .="\\n\\nHuman:\",r=(.+?),.=' +# matches = re.findall(models_regex, script) + +# if matches: +# models_str = matches[0] +# stop_sequences_regex = r'(?<=stopSequences:{value:\[)\D(?<!\])' +# models_str = re.sub(stop_sequences_regex, re.escape('"\\n\\nHuman:"'), models_str) + +# context = quickjs.Context() +# json_str = context.eval(f"({models_str})").json() +# #return json.loads(json_str) + +# quit() +# headers = { +# 'authority': 'sdk.vercel.ai', +# 'accept': '*/*', +# 'accept-language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3', +# 'content-type': 'application/json', +# 'origin': 'https://sdk.vercel.ai', +# 'referer': 'https://sdk.vercel.ai/', +# 'sec-ch-ua': '"Not.A/Brand";v="8", "Chromium";v="114", "Google Chrome";v="114"', +# 'sec-ch-ua-mobile': '?0', +# 'sec-ch-ua-platform': '"macOS"', +# 'sec-fetch-dest': 'empty', +# 'sec-fetch-mode': 'cors', +# 'sec-fetch-site': 'same-origin', +# 'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/114.0.0.0 Safari/537.36' +# } + +# response = requests.get('https://sdk.vercel.ai/openai.jpeg', headers=headers) + +# data = (json.loads(ubox.b64dec(response.text))) + +# script = 'globalThis={data: "sentinel"};a=()=>{return (%s)(%s)}' % (data['c'], data['a']) + +# token_data = execjs.compile(script).call('a') +# print(token_data) + +# token = { +# 'r': token_data, +# 't': data["t"] +# } + +# botToken = ubox.b64enc(json.dumps(token, separators=(',', ':'))) +# print(botToken) + +# import requests + +# headers['custom-encoding'] = botToken + +# json_data = { +# 'messages': [ +# { +# 'role': 'user', +# 'content': 'hello', +# }, +# ], +# 'playgroundId': ubox.uuid4(), +# 'chatIndex': 0, +# 'model': 'openai:gpt-3.5-turbo', +# 'temperature': 0.7, +# 'maxTokens': 500, +# 'topK': 1, +# 'topP': 1, +# 'frequencyPenalty': 1, +# 'presencePenalty': 1, +# 'stopSequences': [] +# } + +# response = requests.post('https://sdk.vercel.ai/api/generate', +# headers=headers, json=json_data, stream=True) + +# for token in response.iter_content(chunk_size=2046): +# print(token) + def _create_completion(model: str, messages: list, stream: bool, **kwargs): return # conversation = 'This is a conversation between a human and a language model, respond to the last message accordingly, referring to the past history of messages if needed.\n' diff --git a/g4f/__init__.py b/g4f/__init__.py index e5d3d4bf..d04d2c78 100644 --- a/g4f/__init__.py +++ b/g4f/__init__.py @@ -6,7 +6,7 @@ logging = False class ChatCompletion: @staticmethod - def create(model: models.Model | str, messages: list, provider: Provider.Provider = None, stream: bool = False, auth: str = False, **kwargs): + def create(model: models.Model or str, messages: list, provider: Provider.Provider = None, stream: bool = False, auth: str = False, **kwargs): kwargs['auth'] = auth if provider and provider.working == False: return f'{provider.__name__} is not working' diff --git a/g4f/models.py b/g4f/models.py index 3a049614..27336244 100644 --- a/g4f/models.py +++ b/g4f/models.py @@ -7,13 +7,12 @@ from dataclasses import dataclass class Model: name: str base_provider: str - best_provider: ModuleType | None - + best_provider: ModuleType or None gpt_35_turbo = Model( name="gpt-3.5-turbo", base_provider="openai", - best_provider=Provider.Forefront, + best_provider=Provider.GetGpt, ) gpt_4 = Model( @@ -10,7 +10,7 @@ with codecs.open(os.path.join(here, "README.md"), encoding="utf-8") as fh: with open('requirements.txt') as f: required = f.read().splitlines() -VERSION = '0.0.1.4' +VERSION = '0.0.1.9' DESCRIPTION = 'The official gpt4free repository | various collection of powerful language models' # Setting up |