some more things

g4f/models.py

@@ -1,15 +1,15 @@
-from __future__  import annotations
+from __future__ import annotations
 from dataclasses import dataclass
-from .typing     import Union
-from .Provider   import BaseProvider, RetryProvider
-from .Provider   import (
+from .typing import Union
+from .Provider import BaseProvider, RetryProvider
+from .Provider import (
     ChatgptLogin,
-    ChatgptAi, 
-    ChatBase, 
-    Vercel, 
-    DeepAi, 
-    Aivvm, 
-    Bard, 
+    ChatgptAi,
+    ChatBase,
+    Vercel,
+    DeepAi,
+    Aivvm,
+    Bard,
     H2o,
     GptGo,
     Bing,
@@ -24,237 +24,241 @@ from .Provider   import (
     ChatgptDuo,
 )
 
+
 @dataclass(unsafe_hash=True)
 class Model:
     name: str
     base_provider: str
     best_provider: Union[type[BaseProvider], RetryProvider] = None
 
+
 # Config for HuggingChat, OpenAssistant
 # Works for Liaobots, H2o, OpenaiChat, Yqcloud, You
 default = Model(
-    name          = "",
-    base_provider = "",
-    best_provider = RetryProvider([
-        Bing,         # Not fully GPT 3 or 4
-        PerplexityAi, # Adds references to sources
-        Wewordle,     # Responds with markdown
-        Yqcloud,      # Answers short questions in chinese
-        ChatBase,     # Don't want to answer creatively
-        ChatgptDuo,   # Include search results
+    name="",
+    base_provider="",
+    best_provider=RetryProvider([
+        Bing,  # Not fully GPT 3 or 4
+        PerplexityAi,  # Adds references to sources
+        Wewordle,  # Responds with markdown
+        Yqcloud,  # Answers short questions in chinese
+        ChatBase,  # Don't want to answer creatively
+        ChatgptDuo,  # Include search results
         DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, AItianhuSpace, Aichat, Myshell, Aibn,
     ])
 )
 
 # GPT-3.5 / GPT-4
 gpt_35_turbo = Model(
-    name          = 'gpt-3.5-turbo',
-    base_provider = 'openai',
-    best_provider = RetryProvider([
+    name='gpt-3.5-turbo',
+    base_provider='openai',
+    best_provider=RetryProvider([
         DeepAi, ChatgptLogin, ChatgptAi, Aivvm, GptGo, AItianhu, Aichat, AItianhuSpace, Myshell, Aibn,
     ])
 )
 
 gpt_4 = Model(
-    name          = 'gpt-4',
-    base_provider = 'openai',
-    best_provider = RetryProvider([
+    name='gpt-4',
+    base_provider='openai',
+    best_provider=RetryProvider([
         Myshell, AItianhuSpace, Aivvm
     ])
 )
 
 # Bard
 palm = Model(
-    name          = 'palm',
-    base_provider = 'google',
-    best_provider = Bard)
+    name='palm',
+    base_provider='google',
+    best_provider=Bard)
 
 # H2o
 falcon_7b = Model(
-    name          = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
-    base_provider = 'huggingface',
-    best_provider = H2o)
+    name='h2oai/h2ogpt-gm-oasst1-en-2048-falcon-7b-v3',
+    base_provider='huggingface',
+    best_provider=H2o)
 
 falcon_40b = Model(
-    name          = 'h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
-    base_provider = 'huggingface',
-    best_provider = H2o)
+    name='h2oai/h2ogpt-gm-oasst1-en-2048-falcon-40b-v1',
+    base_provider='huggingface',
+    best_provider=H2o)
 
 llama_13b = Model(
-    name          = 'h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
-    base_provider = 'huggingface',
-    best_provider = H2o)
+    name='h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-13b',
+    base_provider='huggingface',
+    best_provider=H2o)
 
 # Vercel
 claude_instant_v1 = Model(
-    name          = 'claude-instant-v1',
-    base_provider = 'anthropic',
-    best_provider = Vercel)
+    name='claude-instant-v1',
+    base_provider='anthropic',
+    best_provider=Vercel)
 
 claude_v1 = Model(
-    name          = 'claude-v1',
-    base_provider = 'anthropic',
-    best_provider = Vercel)
+    name='claude-v1',
+    base_provider='anthropic',
+    best_provider=Vercel)
 
 claude_v2 = Model(
-    name          = 'claude-v2',
-    base_provider = 'anthropic',
-    best_provider = Vercel)
+    name='claude-v2',
+    base_provider='anthropic',
+    best_provider=Vercel)
 
 command_light_nightly = Model(
-    name          = 'command-light-nightly',
-    base_provider = 'cohere',
-    best_provider = Vercel)
+    name='command-light-nightly',
+    base_provider='cohere',
+    best_provider=Vercel)
 
 command_nightly = Model(
-    name          = 'command-nightly',
-    base_provider = 'cohere',
-    best_provider = Vercel)
+    name='command-nightly',
+    base_provider='cohere',
+    best_provider=Vercel)
 
 gpt_neox_20b = Model(
-    name          = 'EleutherAI/gpt-neox-20b',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
+    name='EleutherAI/gpt-neox-20b',
+    base_provider='huggingface',
+    best_provider=Vercel)
 
 oasst_sft_1_pythia_12b = Model(
-    name          = 'OpenAssistant/oasst-sft-1-pythia-12b',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
+    name='OpenAssistant/oasst-sft-1-pythia-12b',
+    base_provider='huggingface',
+    best_provider=Vercel)
 
 oasst_sft_4_pythia_12b_epoch_35 = Model(
-    name          = 'OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
+    name='OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5',
+    base_provider='huggingface',
+    best_provider=Vercel)
 
 santacoder = Model(
-    name          = 'bigcode/santacoder',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
+    name='bigcode/santacoder',
+    base_provider='huggingface',
+    best_provider=Vercel)
 
 bloom = Model(
-    name          = 'bigscience/bloom',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
+    name='bigscience/bloom',
+    base_provider='huggingface',
+    best_provider=Vercel)
 
 flan_t5_xxl = Model(
-    name          = 'google/flan-t5-xxl',
-    base_provider = 'huggingface',
-    best_provider = Vercel)
+    name='google/flan-t5-xxl',
+    base_provider='huggingface',
+    best_provider=Vercel)
 
 code_davinci_002 = Model(
-    name          = 'code-davinci-002',
-    base_provider = 'openai',
-    best_provider = Vercel)
+    name='code-davinci-002',
+    base_provider='openai',
+    best_provider=Vercel)
 
 gpt_35_turbo_16k = Model(
-    name          = 'gpt-3.5-turbo-16k',
-    base_provider = 'openai',
-    best_provider = Aivvm)
+    name='gpt-3.5-turbo-16k',
+    base_provider='openai',
+    best_provider=Aivvm)
 
 gpt_35_turbo_16k_0613 = Model(
-    name          = 'gpt-3.5-turbo-16k-0613',
-    base_provider = 'openai')
+    name='gpt-3.5-turbo-16k-0613',
+    base_provider='openai')
 
 gpt_35_turbo_0613 = Model(
-    name          = 'gpt-3.5-turbo-0613',
-    base_provider = 'openai',
-    best_provider = RetryProvider([
+    name='gpt-3.5-turbo-0613',
+    base_provider='openai',
+    best_provider=RetryProvider([
         Aivvm, ChatgptLogin
     ])
 )
 
 gpt_4_0613 = Model(
-    name          = 'gpt-4-0613',
-    base_provider = 'openai',
-    best_provider = Aivvm)
+    name='gpt-4-0613',
+    base_provider='openai',
+    best_provider=Aivvm)
 
 gpt_4_32k = Model(
-    name          = 'gpt-4-32k',
-    base_provider = 'openai',
-    best_provider = Aivvm)
+    name='gpt-4-32k',
+    base_provider='openai',
+    best_provider=Aivvm)
 
 gpt_4_32k_0613 = Model(
-    name          = 'gpt-4-32k-0613',
-    base_provider = 'openai',
-    best_provider = Aivvm)
+    name='gpt-4-32k-0613',
+    base_provider='openai',
+    best_provider=Aivvm)
 
 text_ada_001 = Model(
-    name          = 'text-ada-001',
-    base_provider = 'openai',
-    best_provider = Vercel)
+    name='text-ada-001',
+    base_provider='openai',
+    best_provider=Vercel)
 
 text_babbage_001 = Model(
-    name          = 'text-babbage-001',
-    base_provider = 'openai',
-    best_provider = Vercel)
+    name='text-babbage-001',
+    base_provider='openai',
+    best_provider=Vercel)
 
 text_curie_001 = Model(
-    name          = 'text-curie-001',
-    base_provider = 'openai',
-    best_provider = Vercel)
+    name='text-curie-001',
+    base_provider='openai',
+    best_provider=Vercel)
 
 text_davinci_002 = Model(
-    name          = 'text-davinci-002',
-    base_provider = 'openai',
-    best_provider = Vercel)
+    name='text-davinci-002',
+    base_provider='openai',
+    best_provider=Vercel)
 
 text_davinci_003 = Model(
-    name          = 'text-davinci-003',
-    base_provider = 'openai',
-    best_provider = Vercel)
+    name='text-davinci-003',
+    base_provider='openai',
+    best_provider=Vercel)
 
 llama13b_v2_chat = Model(
-    name          = 'replicate:a16z-infra/llama13b-v2-chat',
-    base_provider = 'replicate',
-    best_provider = Vercel)
+    name='replicate:a16z-infra/llama13b-v2-chat',
+    base_provider='replicate',
+    best_provider=Vercel)
 
 llama7b_v2_chat = Model(
-    name          = 'replicate:a16z-infra/llama7b-v2-chat',
-    base_provider = 'replicate',
-    best_provider = Vercel)
+    name='replicate:a16z-infra/llama7b-v2-chat',
+    base_provider='replicate',
+    best_provider=Vercel)
 
 
 class ModelUtils:
     convert: dict[str, Model] = {
         # gpt-3.5 / gpt-4
-        'gpt-3.5-turbo'          : gpt_35_turbo,
-        'gpt-3.5-turbo-16k'      : gpt_35_turbo_16k,
-        'gpt-4'                  : gpt_4,
-        'gpt-4-0613'             : gpt_4_0613,
-        'gpt-3.5-turbo-16k-0613' : gpt_35_turbo_16k_0613,
-        
+        'gpt-3.5-turbo': gpt_35_turbo,
+        'gpt-3.5-turbo-16k': gpt_35_turbo_16k,
+        'gpt-3.5-turbo-16k-0613': gpt_35_turbo_16k_0613,
+        'gpt-4': gpt_4,
+        'gpt-4-0613': gpt_4_0613,
+        'gpt-4-32k': gpt_4_32k,
+        'gpt-4-32k-0613': gpt_4_32k_0613,
+
         # Bard
-        'palm2'       : palm,
-        'palm'        : palm,
-        'google'      : palm,
-        'google-bard' : palm,
-        'google-palm' : palm,
-        'bard'        : palm,
-        
+        'palm2': palm,
+        'palm': palm,
+        'google': palm,
+        'google-bard': palm,
+        'google-palm': palm,
+        'bard': palm,
+
         # H2o
-        'falcon-40b' : falcon_40b,
-        'falcon-7b'  : falcon_7b,
-        'llama-13b'  : llama_13b,
-        
+        'falcon-40b': falcon_40b,
+        'falcon-7b': falcon_7b,
+        'llama-13b': llama_13b,
+
         # Vercel
-        'claude-instant-v1' : claude_instant_v1,
-        'claude-v1'         : claude_v1,
-        'claude-v2'         : claude_v2,
-        'command-nightly'   : command_nightly,
-        'gpt-neox-20b'      : gpt_neox_20b,
-        'santacoder'        : santacoder,
-        'bloom'             : bloom,
-        'flan-t5-xxl'       : flan_t5_xxl,
-        'code-davinci-002'  : code_davinci_002,
-        'text-ada-001'      : text_ada_001,
-        'text-babbage-001'  : text_babbage_001,
-        'text-curie-001'    : text_curie_001,
-        'text-davinci-002'  : text_davinci_002,
-        'text-davinci-003'  : text_davinci_003,
-        'llama13b-v2-chat'  : llama13b_v2_chat,
-        'llama7b-v2-chat'   : llama7b_v2_chat,
-        
-        'oasst-sft-1-pythia-12b'           : oasst_sft_1_pythia_12b,
-        'oasst-sft-4-pythia-12b-epoch-3.5' : oasst_sft_4_pythia_12b_epoch_35,
-        'command-light-nightly'            : command_light_nightly,
+        'claude-instant-v1': claude_instant_v1,
+        'claude-v1': claude_v1,
+        'claude-v2': claude_v2,
+        'command-nightly': command_nightly,
+        'gpt-neox-20b': gpt_neox_20b,
+        'santacoder': santacoder,
+        'bloom': bloom,
+        'flan-t5-xxl': flan_t5_xxl,
+        'code-davinci-002': code_davinci_002,
+        'text-ada-001': text_ada_001,
+        'text-babbage-001': text_babbage_001,
+        'text-curie-001': text_curie_001,
+        'text-davinci-002': text_davinci_002,
+        'text-davinci-003': text_davinci_003,
+        'llama13b-v2-chat': llama13b_v2_chat,
+        'llama7b-v2-chat': llama7b_v2_chat,
+
+        'oasst-sft-1-pythia-12b': oasst_sft_1_pythia_12b,
+        'oasst-sft-4-pythia-12b-epoch-3.5': oasst_sft_4_pythia_12b_epoch_35,
+        'command-light-nightly': command_light_nightly,
     }

testing/test_chat_completion.py

@@ -7,19 +7,20 @@ import g4f, asyncio
 
 print("create:", end=" ", flush=True)
 for response in g4f.ChatCompletion.create(
-    model=g4f.models.gpt_4,
-    provider=g4f.Provider.Vercel,
-    messages=[{"role": "user", "content": "hello!"}],
+    model=g4f.models.gpt_4_32k_0613,
+    provider=g4f.Provider.Aivvm,
+    messages=[{"role": "user", "content": "send a bunch of emojis. i want to test something"}],
+    temperature=0.0,
+    stream=True
 ):
     print(response, end="", flush=True)
 print()
 
 async def run_async():
     response = await g4f.ChatCompletion.create_async(
-        model=g4f.models.gpt_4_32k_0613,
+        model=g4f.models.gpt_35_turbo_16k_0613,
         provider=g4f.Provider.Aivvm,
         messages=[{"role": "user", "content": "hello!"}],
-        temperature=0.0
     )
     print("create_async:", response)