feat(g4f/models.py): add new providers and models, enhance existing configurations

@@ -7,6 +7,7 @@ from .Provider import (

7 7 AIChatFree,

8 8 Airforce,

9 9 Allyfy,

10 AmigoChat,

10 11 Bing,

11 12 Binjie,

12 13 Blackbox,

@@ -15,6 +16,9 @@ from .Provider import (

15 16 ChatGptEs,

16 17 ChatgptFree,

17 18 ChatHub,

19 ChatifyAI,

20 Cloudflare,

21 DarkAI,

18 22 DDG,

19 23 DeepInfra,

20 24 DeepInfraChat,

@@ -34,7 +38,27 @@ from .Provider import (

34 38 LiteIcoding,

35 39 MagickPen,

36 40 MetaAI,

37 Nexra,

41 NexraAnimagineXL,

42 NexraBing,

43 NexraBlackbox,

44 NexraChatGPT,

45 NexraChatGPT4o,

46 NexraChatGptV2,

47 NexraChatGptWeb,

48 NexraDallE,

49 NexraDallE2,

50 NexraDalleMini,

51 NexraEmi,

52 NexraFluxPro,

53 NexraGeminiPro,

54 NexraLLaMA31,

55 NexraMidjourney,

56 NexraProdiaAI,

57 NexraQwen,

58 NexraSD15,

59 NexraSD21,

60 NexraSDLora,

61 NexraSDTurbo,

38 62 OpenaiChat,

39 63 PerplexityLabs,

40 64 Pi,

@@ -85,9 +109,9 @@ default = Model(

85 109 LiteIcoding,

86 110 Airforce,

87 111 ChatHub,

88 Nexra,

89 112 ChatGptEs,

90 113 ChatHub,

114 AmigoChat,

91 115 ])

92 116 )

93 117

@@ -100,7 +124,7 @@ default = Model(

100 124 gpt_3 = Model(

101 125 name = 'gpt-3',

102 126 base_provider = 'OpenAI',

103 best_provider = Nexra

127 best_provider = NexraChatGPT

104 128 )

105 129

106 130 # gpt-3.5

@@ -108,7 +132,7 @@ gpt_35_turbo = Model(

108 132 name = 'gpt-3.5-turbo',

109 133 base_provider = 'OpenAI',

110 134 best_provider = IterListProvider([

111 Allyfy, Nexra, Airforce, Liaobots,

135 Allyfy, NexraChatGPT, Airforce, DarkAI, Liaobots,

112 136 ])

113 137 )

114 138

@@ -117,7 +141,7 @@ gpt_4o = Model(

117 141 name = 'gpt-4o',

118 142 base_provider = 'OpenAI',

119 143 best_provider = IterListProvider([

120 Liaobots, Nexra, ChatGptEs, Airforce,

144 NexraChatGPT4o, ChatGptEs, AmigoChat, DarkAI, Liaobots, Airforce,

121 145 OpenaiChat

122 146 ])

123 147 )

@@ -126,7 +150,7 @@ gpt_4o_mini = Model(

126 150 name = 'gpt-4o-mini',

127 151 base_provider = 'OpenAI',

128 152 best_provider = IterListProvider([

129 DDG, ChatGptEs, You, FreeNetfly, Pizzagpt, LiteIcoding, MagickPen, Liaobots, Airforce, ChatgptFree, Koala,

153

        DDG, ChatGptEs, You, FreeNetfly, Pizzagpt, LiteIcoding, MagickPen, AmigoChat, Liaobots, Airforce, ChatgptFree, Koala,

130 154 OpenaiChat, ChatGpt

131 155 ])

132 156 )

@@ -135,7 +159,7 @@ gpt_4_turbo = Model(

135 159 name = 'gpt-4-turbo',

136 160 base_provider = 'OpenAI',

137 161 best_provider = IterListProvider([

138 Nexra, Liaobots, Airforce, Bing

162 Liaobots, Airforce, Bing

139 163 ])

140 164 )

141 165

@@ -143,11 +167,24 @@ gpt_4 = Model(

143 167 name = 'gpt-4',

144 168 base_provider = 'OpenAI',

145 169 best_provider = IterListProvider([

146 Nexra, Binjie, Airforce, Chatgpt4Online, Bing, OpenaiChat,

170 NexraBing, NexraChatGPT, NexraChatGptV2, NexraChatGptWeb, Binjie, Airforce, Chatgpt4Online, Bing, OpenaiChat,

147 171 gpt_4_turbo.best_provider, gpt_4o.best_provider, gpt_4o_mini.best_provider

148 172 ])

149 173 )

150 174

175 # o1

176 o1 = Model(

177 name = 'o1',

178 base_provider = 'OpenAI',

179 best_provider = IterListProvider([AmigoChat])

180 )

181

182 o1_mini = Model(

183 name = 'o1-mini',

184 base_provider = 'OpenAI',

185 best_provider = IterListProvider([AmigoChat])

186 )

187

151 188

152 189 ### GigaChat ###

153 190 gigachat = Model(

@@ -165,6 +202,12 @@ meta = Model(

165 202 )

166 203

167 204 # llama 2

205 llama_2_7b = Model(

206 name = "llama-2-7b",

207 base_provider = "Meta Llama",

208 best_provider = Cloudflare

209 )

210

168 211 llama_2_13b = Model(

169 212 name = "llama-2-13b",

170 213 base_provider = "Meta Llama",

@@ -175,7 +218,7 @@ llama_2_13b = Model(

175 218 llama_3_8b = Model(

176 219 name = "llama-3-8b",

177 220 base_provider = "Meta Llama",

178 best_provider = IterListProvider([Airforce, DeepInfra, Replicate])

221 best_provider = IterListProvider([Cloudflare, Airforce, DeepInfra, Replicate])

179 222 )

180 223

181 224 llama_3_70b = Model(

@@ -194,40 +237,57 @@ llama_3 = Model(

194 237 llama_3_1_8b = Model(

195 238 name = "llama-3.1-8b",

196 239 base_provider = "Meta Llama",

197 best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Airforce, PerplexityLabs])

240 best_provider = IterListProvider([Blackbox, DeepInfraChat, ChatHub, Cloudflare, Airforce, PerplexityLabs])

198 241 )

199 242

200 243 llama_3_1_70b = Model(

201 244 name = "llama-3.1-70b",

202 245 base_provider = "Meta Llama",

203

    best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, Airforce, HuggingFace, PerplexityLabs])

246

    best_provider = IterListProvider([DDG, HuggingChat, Blackbox, FreeGpt, TeachAnything, Free2GPT, DeepInfraChat, DarkAI, Airforce, HuggingFace, PerplexityLabs])

204 247 )

205 248

206 249 llama_3_1_405b = Model(

207 250 name = "llama-3.1-405b",

208 251 base_provider = "Meta Llama",

209 best_provider = IterListProvider([DeepInfraChat, Blackbox, Airforce])

252 best_provider = IterListProvider([DeepInfraChat, Blackbox, AmigoChat, DarkAI, Airforce])

210 253 )

211 254

212 255 llama_3_1 = Model(

213 256 name = "llama-3.1",

214 257 base_provider = "Meta Llama",

215

    best_provider = IterListProvider([Nexra, llama_3_1_8b.best_provider, llama_3_1_70b.best_provider, llama_3_1_405b.best_provider,])

258

    best_provider = IterListProvider([NexraLLaMA31, ChatifyAI, llama_3_1_8b.best_provider, llama_3_1_70b.best_provider, llama_3_1_405b.best_provider,])

216 259 )

217 260

218 261 # llama 3.2

262 llama_3_2_1b = Model(

263 name = "llama-3.2-1b",

264 base_provider = "Meta Llama",

265 best_provider = IterListProvider([Cloudflare])

266 )

267

268 llama_3_2_3b = Model(

269 name = "llama-3.2-3b",

270 base_provider = "Meta Llama",

271 best_provider = IterListProvider([Cloudflare])

272 )

273

219 274 llama_3_2_11b = Model(

220 275 name = "llama-3.2-11b",

221 276 base_provider = "Meta Llama",

222 best_provider = IterListProvider([HuggingChat, HuggingFace])

277 best_provider = IterListProvider([Cloudflare, HuggingChat, HuggingFace])

223 278 )

224 279

225 280 llama_3_2_90b = Model(

226 281 name = "llama-3.2-90b",

227 282 base_provider = "Meta Llama",

228 best_provider = IterListProvider([Airforce])

283 best_provider = IterListProvider([AmigoChat, Airforce])

229 284 )

230 285

286 llama_3_2 = Model(

287 name = "llama-3.2",

288 base_provider = "Meta Llama",

289

    best_provider = IterListProvider([llama_3_2_1b.best_provider, llama_3_2_3b.best_provider, llama_3_2_11b.best_provider, llama_3_2_90b.best_provider])

290 )

231 291 # llamaguard

232 292 llamaguard_7b = Model(

233 293 name = "llamaguard-7b",

@@ -246,7 +306,7 @@ llamaguard_2_8b = Model(

246 306 mistral_7b = Model(

247 307 name = "mistral-7b",

248 308 base_provider = "Mistral",

249 best_provider = IterListProvider([DeepInfraChat, Airforce, HuggingFace, DeepInfra])

309 best_provider = IterListProvider([DeepInfraChat, Cloudflare, Airforce, DeepInfra])

250 310 )

251 311

252 312 mixtral_8x7b = Model(

@@ -289,6 +349,12 @@ hermes_3 = Model(

289 349

290 350

291 351 ### Microsoft ###

352 phi_2 = Model(

353 name = "phi-2",

354 base_provider = "Microsoft",

355 best_provider = Cloudflare

356 )

357

292 358 phi_3_medium_4k = Model(

293 359 name = "phi-3-medium-4k",

294 360 base_provider = "Microsoft",

@@ -306,7 +372,7 @@ phi_3_5_mini = Model(

306 372 gemini_pro = Model(

307 373 name = 'gemini-pro',

308 374 base_provider = 'Google DeepMind',

309

    best_provider = IterListProvider([GeminiPro, LiteIcoding, Blackbox, AIChatFree, GPROChat, Nexra, Liaobots, Airforce])

375

    best_provider = IterListProvider([GeminiPro, LiteIcoding, Blackbox, AIChatFree, GPROChat, NexraGeminiPro, AmigoChat, Liaobots, Airforce])

310 376 )

311 377

312 378 gemini_flash = Model(

@@ -343,6 +409,12 @@ gemma_2b = Model(

343 409 ])

344 410 )

345 411

412 gemma_7b = Model(

413 name = 'gemma-7b',

414 base_provider = 'Google',

415 best_provider = IterListProvider([Cloudflare])

416 )

417

346 418 # gemma 2

347 419 gemma_2_27b = Model(

348 420 name = 'gemma-2-27b',

@@ -407,7 +479,7 @@ claude_3 = Model(

407 479 claude_3_5_sonnet = Model(

408 480 name = 'claude-3.5-sonnet',

409 481 base_provider = 'Anthropic',

410 best_provider = IterListProvider([Blackbox, Airforce, Liaobots])

482 best_provider = IterListProvider([Blackbox, Airforce, AmigoChat, Liaobots])

411 483 )

412 484

413 485 claude_3_5 = Model(

@@ -430,10 +502,16 @@ reka_core = Model(

430 502

431 503

432 504 ### Blackbox AI ###

433 blackbox = Model(

434 name = 'blackbox',

505 blackboxai = Model(

506 name = 'blackboxai',

435 507 base_provider = 'Blackbox AI',

436 best_provider = Blackbox

508 best_provider = IterListProvider([Blackbox, NexraBlackbox])

509 )

510

511 blackboxai_pro = Model(

512 name = 'blackboxai-pro',

513 base_provider = 'Blackbox AI',

514 best_provider = IterListProvider([Blackbox])

437 515 )

438 516

439 517

@@ -463,16 +541,22 @@ sparkdesk_v1_1 = Model(

463 541

464 542 ### Qwen ###

465 543 # qwen 1

544 qwen_1_5_0_5b = Model(

545 name = 'qwen-1.5-0.5b',

546 base_provider = 'Qwen',

547 best_provider = Cloudflare

548 )

549

466 550 qwen_1_5_7b = Model(

467 551 name = 'qwen-1.5-7b',

468 552 base_provider = 'Qwen',

469 best_provider = Airforce

553 best_provider = IterListProvider([Cloudflare, Airforce])

470 554 )

471 555

472 556 qwen_1_5_14b = Model(

473 557 name = 'qwen-1.5-14b',

474 558 base_provider = 'Qwen',

475 best_provider = IterListProvider([FreeChatgpt, Airforce])

559 best_provider = IterListProvider([FreeChatgpt, Cloudflare, Airforce])

476 560 )

477 561

478 562 qwen_1_5_72b = Model(

@@ -487,6 +571,12 @@ qwen_1_5_110b = Model(

487 571 best_provider = Airforce

488 572 )

489 573

574 qwen_1_5_1_8b = Model(

575 name = 'qwen-1.5-1.8b',

576 base_provider = 'Qwen',

577 best_provider = Airforce

578 )

579

490 580 # qwen 2

491 581 qwen_2_72b = Model(

492 582 name = 'qwen-2-72b',

@@ -497,7 +587,7 @@ qwen_2_72b = Model(

497 587 qwen = Model(

498 588 name = 'qwen',

499 589 base_provider = 'Qwen',

500

    best_provider = IterListProvider([Nexra, qwen_1_5_14b.best_provider, qwen_1_5_72b.best_provider, qwen_1_5_110b.best_provider, qwen_2_72b.best_provider])

590

    best_provider = IterListProvider([NexraQwen, qwen_1_5_0_5b.best_provider, qwen_1_5_14b.best_provider, qwen_1_5_72b.best_provider, qwen_1_5_110b.best_provider, qwen_1_5_1_8b.best_provider, qwen_2_72b.best_provider])

501 591 )

502 592

503 593

@@ -514,14 +604,6 @@ glm_4_9b = Model(

514 604 best_provider = FreeChatgpt

515 605 )

516 606

517 glm_4 = Model(

518 name = 'glm-4',

519 base_provider = 'Zhipu AI',

520 best_provider = IterListProvider([

521 glm_3_6b.best_provider, glm_4_9b.best_provider

522 ])

523 )

524

525 607

526 608 ### 01-ai ###

527 609 yi_1_5_9b = Model(

@@ -602,6 +684,12 @@ lzlv_70b = Model(

602 684

603 685

604 686 ### OpenChat ###

687 openchat_3_5 = Model(

688 name = 'openchat-3.5',

689 base_provider = 'OpenChat',

690 best_provider = Cloudflare

691 )

692

605 693 openchat_3_6_8b = Model(

606 694 name = 'openchat-3.6-8b',

607 695 base_provider = 'OpenChat',

@@ -669,16 +757,71 @@ cosmosrp = Model(

669 757 )

670 758

671 759

760 ### TheBloke ###

761 german_7b = Model(

762 name = 'german-7b',

763 base_provider = 'TheBloke',

764 best_provider = IterListProvider([Cloudflare])

765 )

766

767

768 ### Tinyllama ###

769 tinyllama_1_1b = Model(

770 name = 'tinyllama-1.1b',

771 base_provider = 'Tinyllama',

772 best_provider = IterListProvider([Cloudflare])

773 )

774

775

776 ### Fblgit ###

777 cybertron_7b = Model(

778 name = 'cybertron-7b',

779 base_provider = 'Fblgit',

780 best_provider = IterListProvider([Cloudflare])

781 )

782

783

672 784

673 785 #############

674 786 ### Image ###

675 787 #############

676 788

677 789 ### Stability AI ###

790 sdxl_lora = Model(

791 name = 'sdxl-lora',

792 base_provider = 'Stability AI',

793 best_provider = IterListProvider([NexraSDLora])

794

795 )

796

797 sdxl_turbo = Model(

798 name = 'sdxl-turbo',

799 base_provider = 'Stability AI',

800 best_provider = IterListProvider([NexraSDTurbo])

801

802 )

803

678 804 sdxl = Model(

679 805 name = 'sdxl',

680 806 base_provider = 'Stability AI',

681 best_provider = IterListProvider([ReplicateHome, Nexra, DeepInfraImage])

807 best_provider = IterListProvider([

808 ReplicateHome, NexraSD21, DeepInfraImage,

809 sdxl_lora.best_provider, sdxl_turbo.best_provider,

810 ])

811

812 )

813

814 sd_1_5 = Model(

815 name = 'sd-1.5',

816 base_provider = 'Stability AI',

817 best_provider = IterListProvider([NexraSD15])

818

819 )

820

821 sd_2_1 = Model(

822 name = 'sd-2.1',

823 base_provider = 'Stability AI',

824 best_provider = IterListProvider([NexraSD21])

682 825

683 826 )

684 827

@@ -689,6 +832,13 @@ sd_3 = Model(

689 832

690 833 )

691 834

835 sd = Model(

836 name = 'sd',

837 base_provider = 'Stability AI',

838 best_provider = IterListProvider([sd_1_5.best_provider, sd_2_1.best_provider, sd_3.best_provider])

839

840 )

841

692 842

693 843 ### Playground ###

694 844 playground_v2_5 = Model(

@@ -707,10 +857,17 @@ flux = Model(

707 857

708 858 )

709 859

860 flux_pro = Model(

861 name = 'flux-pro',

862 base_provider = 'Flux AI',

863 best_provider = IterListProvider([NexraFluxPro, AmigoChat])

864

865 )

866

710 867 flux_realism = Model(

711 868 name = 'flux-realism',

712 869 base_provider = 'Flux AI',

713 best_provider = IterListProvider([Airforce])

870 best_provider = IterListProvider([Airforce, AmigoChat])

714 871

715 872 )

716 873

@@ -757,31 +914,48 @@ flux_schnell = Model(

757 914 )

758 915

759 916

760 ### ###

917 ### OpenAI ###

761 918 dalle_2 = Model(

762 919 name = 'dalle-2',

763 base_provider = '',

764 best_provider = IterListProvider([Nexra])

920 base_provider = 'OpenAI',

921 best_provider = IterListProvider([NexraDallE2])

765 922

766 923 )

767 924 dalle_3 = Model(

768 925 name = 'dalle-3',

769 base_provider = '',

926 base_provider = 'OpenAI',

770 927 best_provider = IterListProvider([Airforce])

771 928

772 929 )

773 930

774 931 dalle = Model(

775 932 name = 'dalle',

776 base_provider = '',

777 best_provider = IterListProvider([Nexra, dalle_2.best_provider, dalle_3.best_provider])

933 base_provider = 'OpenAI',

934 best_provider = IterListProvider([NexraDallE, dalle_2.best_provider, dalle_3.best_provider])

778 935

779 936 )

780 937

781 938 dalle_mini = Model(

782 939 name = 'dalle-mini',

783 base_provider = '',

784 best_provider = IterListProvider([Nexra])

940 base_provider = 'OpenAI',

941 best_provider = IterListProvider([NexraDalleMini])

942

943 )

944

945

946 ### Cagliostro Research Lab ###

947 animagine_xl = Model(

948 name = 'animagine-xl',

949 base_provider = 'Cagliostro Research Lab',

950 best_provider = IterListProvider([NexraAnimagineXL])

951

952 )

953

954 ### Midjourney ###

955 midjourney = Model(

956 name = 'midjourney',

957 base_provider = 'Midjourney',

958 best_provider = IterListProvider([NexraMidjourney])

785 959

786 960 )

787 961

@@ -789,7 +963,7 @@ dalle_mini = Model(

789 963 emi = Model(

790 964 name = 'emi',

791 965 base_provider = '',

792 best_provider = IterListProvider([Nexra])

966 best_provider = IterListProvider([NexraEmi])

793 967

794 968 )

795 969

@@ -800,13 +974,6 @@ any_dark = Model(

800 974

801 975 )

802 976

803 prodia = Model(

804 name = 'prodia',

805 base_provider = '',

806 best_provider = IterListProvider([Nexra])

807

808 )

809

810 977 class ModelUtils:

811 978 """

812 979 Utility class for mapping string identifiers to Model instances.

@@ -832,12 +999,17 @@ class ModelUtils:

832 999 'gpt-4o-mini': gpt_4o_mini,

833 1000 'gpt-4': gpt_4,

834 1001 'gpt-4-turbo': gpt_4_turbo,

1002

1003 # o1

1004 'o1': o1,

1005 'o1-mini': o1_mini,

835 1006

836 1007

837 1008 ### Meta ###

838 1009 "meta-ai": meta,

839 1010

840 1011 # llama-2

1012 'llama-2-7b': llama_2_7b,

841 1013 'llama-2-13b': llama_2_13b,

842 1014

843 1015 # llama-3

@@ -852,6 +1024,9 @@ class ModelUtils:

852 1024 'llama-3.1-405b': llama_3_1_405b,

853 1025

854 1026 # llama-3.2

1027 'llama-3.2': llama_3_2,

1028 'llama-3.2-1b': llama_3_2_1b,

1029 'llama-3.2-3b': llama_3_2_3b,

855 1030 'llama-3.2-11b': llama_3_2_11b,

856 1031 'llama-3.2-90b': llama_3_2_90b,

857 1032

@@ -875,6 +1050,7 @@ class ModelUtils:

875 1050

876 1051

877 1052 ### Microsoft ###

1053 'phi-2': phi_2,

878 1054 'phi_3_medium-4k': phi_3_medium_4k,

879 1055 'phi-3.5-mini': phi_3_5_mini,

880 1056

@@ -888,6 +1064,7 @@ class ModelUtils:

888 1064 'gemma-2b': gemma_2b,

889 1065 'gemma-2b-9b': gemma_2b_9b,

890 1066 'gemma-2b-27b': gemma_2b_27b,

1067 'gemma-7b': gemma_7b,

891 1068

892 1069 # gemma-2

893 1070 'gemma-2': gemma_2,

@@ -914,7 +1091,8 @@ class ModelUtils:

914 1091

915 1092

916 1093 ### Blackbox AI ###

917 'blackbox': blackbox,

1094 'blackboxai': blackboxai,

1095 'blackboxai-pro': blackboxai_pro,

918 1096

919 1097

920 1098 ### CohereForAI ###

@@ -935,17 +1113,18 @@ class ModelUtils:

935 1113

936 1114 ### Qwen ###

937 1115 'qwen': qwen,

1116 'qwen-1.5-0.5b': qwen_1_5_0_5b,

938 1117 'qwen-1.5-7b': qwen_1_5_7b,

939 1118 'qwen-1.5-14b': qwen_1_5_14b,

940 1119 'qwen-1.5-72b': qwen_1_5_72b,

941 1120 'qwen-1.5-110b': qwen_1_5_110b,

1121 'qwen-1.5-1.8b': qwen_1_5_1_8b,

942 1122 'qwen-2-72b': qwen_2_72b,

943 1123

944 1124

945 1125 ### Zhipu AI ###

946 1126 'glm-3-6b': glm_3_6b,

947 1127 'glm-4-9b': glm_4_9b,

948 'glm-4': glm_4,

949 1128

950 1129

951 1130 ### 01-ai ###

@@ -983,6 +1162,7 @@ class ModelUtils:

983 1162

984 1163

985 1164 ### OpenChat ###

1165 'openchat-3.5': openchat_3_5,

986 1166 'openchat-3.6-8b': openchat_3_6_8b,

987 1167

988 1168

@@ -1012,6 +1192,18 @@ class ModelUtils:

1012 1192 'cosmosrp': cosmosrp,

1013 1193

1014 1194

1195 ### TheBloke ###

1196 'german-7b': german_7b,

1197

1198

1199 ### Tinyllama ###

1200 'tinyllama-1.1b': tinyllama_1_1b,

1201

1202

1203 ### Fblgit ###

1204 'cybertron-7b': cybertron_7b,

1205

1206

1015 1207

1016 1208 #############

1017 1209 ### Image ###

@@ -1019,6 +1211,11 @@ class ModelUtils:

1019 1211

1020 1212 ### Stability AI ###

1021 1213 'sdxl': sdxl,

1214 'sdxl-lora': sdxl_lora,

1215 'sdxl-turbo': sdxl_turbo,

1216 'sd': sd,

1217 'sd-1.5': sd_1_5,

1218 'sd-2.1': sd_2_1,

1022 1219 'sd-3': sd_3,

1023 1220

1024 1221

@@ -1028,6 +1225,7 @@ class ModelUtils:

1028 1225

1029 1226 ### Flux AI ###

1030 1227 'flux': flux,

1228 'flux-pro': flux_pro,

1031 1229 'flux-realism': flux_realism,

1032 1230 'flux-anime': flux_anime,

1033 1231 'flux-3d': flux_3d,

@@ -1037,14 +1235,24 @@ class ModelUtils:

1037 1235 'flux-schnell': flux_schnell,

1038 1236

1039 1237

1040 ### ###

1238 ### OpenAI ###

1041 1239 'dalle': dalle,

1042 1240 'dalle-2': dalle_2,

1043 1241 'dalle-3': dalle_3,

1044 1242 'dalle-mini': dalle_mini,

1243

1244

1245 ### Cagliostro Research Lab ###

1246 'animagine-xl': animagine_xl,

1247

1248

1249 ### Midjourney ###

1250 'midjourney': midjourney,

1251

1252

1253 ### Other ###

1045 1254 'emi': emi,

1046 1255 'any-dark': any_dark,

1047 'prodia': prodia,

1048 1256 }

1049 1257

1050 1258 _all_models = list(ModelUtils.convert.keys())

gpt4free

feat(g4f/models.py): add new providers and models, enhance existing configurations

代码差异