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XFEstudio/gpt4free

refactor: simplify model alias management and update providers

- Removed specific model aliases for various models (e.g., "gpt-4.1-mini", "phi-4", "grok-3-mini"). - Replaced the `get_model` method with a simplified approach using `get_alias` for alias resolution. - Updated model alias management in `PollinationsAI` to handle model aliases in `get_models` method. - Refined the logic for adding models to `text_models` and `vision_models` in `PollinationsAI`. - Replaced `deepseek-v3` and other model aliases with direct models in `PollinationsAI`. - Modified `Ollama` class to handle local models and improve model fetching with API key. - Changed the `create_async_generator` in `Ollama` to support local model handling and proxy use. - Updated `Azure` class to remove unused `extra_body` argument and streamline stream handling. - Updated model providers in `g4f/models.py` to remove certain providers (e.g., `PollinationsAI`) from `best_provider` lists for some models.

28c4c61f

hlohaus <983577+hlohaus@users.noreply.github.com>

提交于 2025-08-09 17:22

父提交 0c69ba8

代码差异

5 个文件 +87 -86

Modified g4f/Provider/PollinationsAI.py +15 -50

@@ -88,21 +88,8 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):

88 88 vision_models = [default_vision_model]

89 89 _models_loaded = False

90 90 model_aliases = {

91 "gpt-4.1-mini": "openai",

92 "gpt-4.1-nano": "openai-fast",

93 "gpt-4.1": "openai-large",

94 "o4-mini": "openai-reasoning",

95 "qwen-2.5-coder-32b": "qwen-coder",

96 "llama-3.3-70b": "llama",

97 91 "llama-4-scout": "llamascout",

98 "mistral-small-3.1-24b": "mistral",

99 "phi-4": "phi",

100 92 "deepseek-r1": "deepseek-reasoning",

101 "deepseek-v3-0324": "deepseek",

102 "deepseek-v3": "deepseek",

103 "grok-3-mini": "grok",

104 "grok-3-mini-high": "grok",

105 "gpt-4o-mini-audio": "openai-audio",

106 93 "sdxl-turbo": "turbo",

107 94 "gpt-image": "gptimage",

108 95 "flux-dev": "flux",

@@ -111,27 +98,11 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):

111 98 "flux": "flux",

112 99 "flux-kontext": "kontext",

113 100 }

114 swap_models = {value: key for key, value in model_aliases.items()}

115

116 @classmethod

117 def get_model(cls, model: str) -> str:

118 """Get the internal model name from the user-provided model name."""

119 if not model:

120 return cls.default_model

121

122 # Check if there's an alias for this model

123 if model in cls.model_aliases:

124 return cls.model_aliases[model]

125

126 # Check if the model exists directly in our model lists

127 if model in cls.text_models or model in cls.image_models or model in cls.audio_models:

128 return model

129

130 # If no match is found, raise an error

131 raise ModelNotFoundError(f"PollinationsAI: Model {model} not found")

132 101

133 102 @classmethod

134 103 def get_models(cls, **kwargs):

104 def get_alias(model: dict) -> str:

105

            return model.get("aliases", model.get("name")).replace("-instruct", "").replace("qwen-", "qwen").replace("qwen", "qwen-")

135 106 if not cls._models_loaded:

136 107 try:

137 108 # Update of image models

@@ -166,25 +137,19 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):

166 137 cls.audio_models.update({alias: {}})

167 138

168 139 cls.vision_models.extend([

169 cls.swap_models.get(model.get("name"), model.get("name"))

140 get_alias(model)

170 141 for model in models

171 if model.get("vision") and model not in cls.vision_models

142 if model.get("vision") and get_alias(model) not in cls.vision_models

172 143 ])

173 for alias, model in cls.model_aliases.items():

174 if model in cls.vision_models and alias not in cls.vision_models:

175 cls.vision_models.append(alias)

176 144

177 # Create a set of unique text models starting with default model

178 text_models = cls.text_models.copy()

179

180 # Add models from the API response

181 145 for model in models:

182 model_name = model.get("name")

183 if model_name and "input_modalities" in model and "text" in model["input_modalities"]:

184 text_models.append(cls.swap_models.get(model_name, model_name))

185

186 # Convert to list and update text_models

187 cls.text_models = list(dict.fromkeys(text_models))

146 alias = get_alias(model)

147 if alias not in cls.text_models:

148 cls.text_models.append(alias)

149 if alias != model.get("name"):

150 cls.model_aliases[alias] = model.get("name")

151 elif model.get("name") not in cls.text_models:

152 cls.text_models.append(model.get("name"))

188 153

189 154 cls._models_loaded = True

190 155

@@ -259,10 +224,10 @@ class PollinationsAI(AsyncGeneratorProvider, ProviderModelMixin):

259 224 has_audio = True

260 225 break

261 226 model = cls.default_audio_model if has_audio else model

262 try:

263 model = cls.get_model(model) if model else None

264 except ModelNotFoundError:

265 pass

227 elif cls._models_loaded or cls.get_models():

228 if model in cls.model_aliases:

229 model = cls.model_aliases[model]

230 debug.log(f"Using model: {model}")

266 231 if model in cls.image_models:

267 232 async for chunk in cls._generate_image(

268 233 model="gptimage" if model == "transparent" else model,

Modified g4f/Provider/local/Ollama.py +49 -9

@@ -1,22 +1,35 @@

1 1 from __future__ import annotations

2 2

3 import json

3 4 import requests

4 5 import os

5 6

6 7 from ..needs_auth.OpenaiAPI import OpenaiAPI

8 from ...requests import StreamSession, raise_for_status

9 from ...providers.response import Usage, Reasoning

7 10 from ...typing import AsyncResult, Messages

8 11

9 12 class Ollama(OpenaiAPI):

10 13 label = "Ollama"

11 14 url = "https://ollama.com"

12 login_url = None

15 login_url = "https://ollama.com/settings/keys"

16 api_endpoint = "https://ollama.com/api/chat"

13 17 needs_auth = False

14 18 working = True

15 active_by_default = False

19 active_by_default = True

20 local_models: list[str] = []

21 model_aliases = {

22 "gpt-oss-120b": "gpt-oss:120b",

23 "gpt-oss-20b": "gpt-oss:20b"

24 }

16 25

17 26 @classmethod

18 def get_models(cls, api_base: str = None, **kwargs):

27 def get_models(cls, api_key: str = None, api_base: str = None, **kwargs):

19 28 if not cls.models:

29 cls.models = []

30 if api_key:

                models = requests.get("https://ollama.com/api/tags", {"headers": {"Authorization": f"Bearer {api_key}"}}).json()["models"]

32 cls.models = [model["name"] for model in models]

20 33 if api_base is None:

21 34 host = os.getenv("OLLAMA_HOST", "127.0.0.1")

22 35 port = os.getenv("OLLAMA_PORT", "11434")

@@ -26,23 +39,50 @@ class Ollama(OpenaiAPI):

26 39 try:

27 40 models = requests.get(url).json()["models"]

28 41 except requests.exceptions.RequestException as e:

29 return cls.fallback_models

30 cls.models = [model["name"] for model in models]

42 return cls.models

43 cls.local_models = [model["name"] for model in models]

44 cls.models = cls.models + cls.local_models

31 45 cls.default_model = next(iter(cls.models), None)

32 46 return cls.models

33 47

34 48 @classmethod

35 def create_async_generator(

49 async def create_async_generator(

36 50 cls,

37 51 model: str,

38 52 messages: Messages,

53 api_key: str = None,

39 54 api_base: str = None,

55 proxy: str = None,

40 56 **kwargs

41 57 ) -> AsyncResult:

42 58 if api_base is None:

43 59 host = os.getenv("OLLAMA_HOST", "localhost")

44 60 port = os.getenv("OLLAMA_PORT", "11434")

45 61 api_base: str = f"http://{host}:{port}/v1"

46 return super().create_async_generator(

47 model, messages, api_base=api_base, **kwargs

48 )

62 if model in cls.local_models or not api_key:

63 for chunk in super().create_async_generator(

64 model, messages, api_base=api_base, proxy=proxy, **kwargs

65 ):

66 yield chunk

67 else:

68 async with StreamSession(headers={"Authorization": f"Bearer {api_key}"}, proxy=proxy) as session:

69 async with session.post(cls.api_endpoint, json={

70 "model": model,

71 "messages": messages,

72 }) as response:

73 await raise_for_status(response)

74 last_data = {}

75 async for chunk in response.iter_lines():

76 data = json.loads(chunk)

77 last_data = data

78 thinking = data.get("message", {}).get("thinking", "")

79 if thinking:

80 yield Reasoning(thinking)

81 content = data.get("message", {}).get("content", "")

82 if content:

83 yield content

84 yield Usage(

85 prompt_tokens=last_data.get("prompt_eval_count", 0),

86 completion_tokens=last_data.get("eval_count", 0),

87 total_tokens=last_data.get("prompt_eval_count", 0) + last_data.get("eval_count", 0),

88 )

Modified g4f/Provider/needs_auth/Azure.py +10 -10

@@ -63,7 +63,6 @@ class Azure(OpenaiTemplate):

63 63 messages: Messages,

64 64 stream: bool = True,

65 65 media: MediaListType = None,

66 extra_body: dict = None,

67 66 api_key: str = None,

68 67 api_endpoint: str = None,

69 68 **kwargs

@@ -118,17 +117,19 @@ class Azure(OpenaiTemplate):

118 117 async with session.post(api_endpoint, data=form, json=data) as response:

119 118 data = await response.json()

120 119 await raise_for_status(response, data)

121

                    async for chunk in save_response_media(data["data"][0]["b64_json"], prompt, content_type=f"image/{output_format}"):

120 async for chunk in save_response_media(

121 data["data"][0]["b64_json"],

122 prompt,

123 content_type=f"image/{output_format.replace('jpg', 'jpeg')}"

124 ):

122 125 yield chunk

123 126 return

124 if extra_body is None:

125 if model in cls.model_extra_body:

126 extra_body = cls.model_extra_body[model]

127 stream = False

128 else:

129 extra_body = {}

127 if model in cls.model_extra_body:

128 for key, value in cls.model_extra_body[model].items():

129 kwargs.setdefault(key, value)

130 stream = False

130 131 if stream:

131 extra_body.setdefault("stream_options", {"include_usage": True})

132 kwargs.setdefault("stream_options", {"include_usage": True})

132 133 try:

133 134 async for chunk in super().create_async_generator(

134 135 model=model,

@@ -137,7 +138,6 @@ class Azure(OpenaiTemplate):

137 138 media=media,

138 139 api_key=api_key,

139 140 api_endpoint=api_endpoint,

140 extra_body=extra_body,

141 141 **kwargs

142 142 ):

143 143 yield chunk

Modified g4f/Provider/template/OpenaiTemplate.py +5 -3

@@ -80,7 +80,7 @@ class OpenaiTemplate(AsyncGeneratorProvider, ProviderModelMixin, RaiseErrorMixin

80 80 headers: dict = None,

81 81 impersonate: str = None,

82 82 download_media: bool = True,

        extra_parameters: list[str] = ["tools", "parallel_tool_calls", "tool_choice", "reasoning_effort", "logit_bias", "modalities", "audio"],

        extra_parameters: list[str] = ["tools", "parallel_tool_calls", "tool_choice", "reasoning_effort", "logit_bias", "modalities", "audio", "stream_options"],

84 84 extra_body: dict = None,

85 85 **kwargs

86 86 ) -> AsyncResult:

@@ -88,6 +88,7 @@ class OpenaiTemplate(AsyncGeneratorProvider, ProviderModelMixin, RaiseErrorMixin

88 88 api_key = cls.api_key

89 89 if cls.needs_auth and api_key is None:

90 90 raise MissingAuthError('Add a "api_key"')

91 print(cls.get_headers(stream, api_key, headers))

91 92 async with StreamSession(

92 93 proxy=proxy,

93 94 headers=cls.get_headers(stream, api_key, headers),

@@ -135,9 +136,10 @@ class OpenaiTemplate(AsyncGeneratorProvider, ProviderModelMixin, RaiseErrorMixin

135 136 **extra_body

136 137 )

137 138 if api_endpoint is None:

138 api_endpoint = cls.api_endpoint

139 if api_endpoint is None:

139 if api_base:

140 140 api_endpoint = f"{api_base.rstrip('/')}/chat/completions"

141 if api_endpoint is None:

142 api_endpoint = cls.api_endpoint

141 143 async with session.post(api_endpoint, json=data, ssl=cls.ssl) as response:

142 144 async for chunk in read_response(response, stream, prompt, cls.get_dict(), download_media):

143 145 yield chunk

Modified g4f/models.py +8 -14

@@ -214,7 +214,7 @@ gpt_4o_mini = Model(

214 214 )

215 215

216 216 gpt_4o_mini_audio = AudioModel(

217 name = 'gpt-4o-mini-audio',

217 name = 'gpt-4o-mini-audio-preview',

218 218 base_provider = 'OpenAI',

219 219 best_provider = PollinationsAI

220 220 )

@@ -255,7 +255,7 @@ o3_mini_high = Model(

255 255 o4_mini = Model(

256 256 name = 'o4-mini',

257 257 base_provider = 'OpenAI',

258 best_provider = IterListProvider([PollinationsAI, OpenaiChat])

258 best_provider = OpenaiChat

259 259 )

260 260

261 261 o4_mini_high = Model(

@@ -274,7 +274,7 @@ gpt_4_1 = Model(

274 274 gpt_4_1_mini = Model(

275 275 name = 'gpt-4.1-mini',

276 276 base_provider = 'OpenAI',

277 best_provider = IterListProvider([Blackbox, OIVSCodeSer0501, PollinationsAI])

277 best_provider = IterListProvider([Blackbox, OIVSCodeSer0501])

278 278 )

279 279

280 280 gpt_4_1_nano = Model(

@@ -390,7 +390,7 @@ llama_3_2_90b = Model(

390 390 llama_3_3_70b = Model(

391 391 name = "llama-3.3-70b",

392 392 base_provider = "Meta Llama",

393 best_provider = IterListProvider([DeepInfraChat, LambdaChat, PollinationsAI, Together, HuggingChat, HuggingFace])

393 best_provider = IterListProvider([DeepInfraChat, LambdaChat, Together, HuggingChat, HuggingFace])

394 394 )

395 395

396 396 # llama-4

@@ -456,7 +456,7 @@ phi_3_5_mini = Model(

456 456 phi_4 = Model(

457 457 name = "phi-4",

458 458 base_provider = "Microsoft",

459 best_provider = IterListProvider([DeepInfraChat, PollinationsAI, HuggingSpace])

459 best_provider = IterListProvider([DeepInfraChat, HuggingSpace])

460 460 )

461 461

462 462 phi_4_multimodal = VisionModel(

@@ -753,7 +753,7 @@ qwq_32b = Model(

753 753 deepseek_v3 = Model(

754 754 name = 'deepseek-v3',

755 755 base_provider = 'DeepSeek',

756 best_provider = IterListProvider([DeepInfraChat, PollinationsAI, Together])

756 best_provider = IterListProvider([DeepInfraChat, Together])

757 757 )

758 758

759 759 # deepseek-r1

@@ -810,7 +810,7 @@ deepseek_prover_v2_671b = Model(

810 810 deepseek_v3_0324 = Model(

811 811 name = 'deepseek-v3-0324',

812 812 base_provider = 'DeepSeek',

813 best_provider = IterListProvider([DeepInfraChat, LambdaChat, PollinationsAI])

813 best_provider = IterListProvider([DeepInfraChat, LambdaChat])

814 814 )

815 815

816 816 deepseek_v3_0324_turbo = Model(

@@ -823,7 +823,7 @@ deepseek_v3_0324_turbo = Model(

823 823 deepseek_r1_0528 = Model(

824 824 name = 'deepseek-r1-0528',

825 825 base_provider = 'DeepSeek',

826 best_provider = IterListProvider([DeepInfraChat, LambdaChat])

826 best_provider = IterListProvider([DeepInfraChat, LambdaChat, PollinationsAI])

827 827 )

828 828

829 829 deepseek_r1_0528_turbo = Model(

@@ -852,12 +852,6 @@ grok_3 = Model(

852 852 best_provider = Grok

853 853 )

854 854

855 grok_3_mini = Model(

856 name = 'grok-3-mini',

857 base_provider = 'x.ai',

858 best_provider = PollinationsAI

859 )

860

861 855 grok_3_r1 = Model(

862 856 name = 'grok-3-r1',

863 857 base_provider = 'x.ai',