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decouple model list from hardcoded package variables

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Krrish Dholakia 2023-09-20 14:16:53 -07:00
parent 1ad9d7a98a
commit 93c41e8f6d
4 changed files with 43 additions and 86 deletions
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120
litellm/__init__.py
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@ -78,39 +78,43 @@ config_path = None
####### Secret Manager ##################### ####### Secret Manager #####################
secret_manager_client = None secret_manager_client = None
####### COMPLETION MODELS ################### ####### COMPLETION MODELS ###################
open_ai_chat_completion_models: List = [ open_ai_chat_completion_models: List = []
"gpt-4", open_ai_text_completion_models: List = []
"gpt-4-0613", cohere_models: List = []
"gpt-4-0314", anthropic_models: List = []
"gpt-4-32k", openrouter_models: List = []
"gpt-4-32k-0314", vertex_chat_models: List = []
"gpt-4-32k-0613", vertex_code_chat_models: List = []
################# vertex_text_models: List = []
"gpt-3.5-turbo", vertex_code_text_models: List = []
"gpt-3.5-turbo-0301", ai21_models: List = []
"gpt-3.5-turbo-0613", nlp_cloud_models: List = []
"gpt-3.5-turbo-16k", aleph_alpha_models: List = []
"gpt-3.5-turbo-16k-0613", for key, value in model_cost.items():
] if value.get('litellm_provider') == 'openai':
open_ai_text_completion_models: List = [ open_ai_chat_completion_models.append(key)
"gpt-3.5-turbo-instruct", elif value.get('litellm_provider') == 'text-completion-openai':
"text-davinci-003", open_ai_text_completion_models.append(key)
"text-curie-001", elif value.get('litellm_provider') == 'cohere':
"text-babbage-001", cohere_models.append(key)
"text-ada-001", elif value.get('litellm_provider') == 'anthropic':
"babbage-002", anthropic_models.append(key)
"davinci-002", elif value.get('litellm_provider') == 'openrouter':
] openrouter_models.append(key)
elif value.get('litellm_provider') == 'vertex_ai-text-models':
cohere_models: List = [ vertex_text_models.append(key)
"command-nightly", elif value.get('litellm_provider') == 'vertex_ai-code-text-models':
"command", vertex_code_text_models.append(key)
"command-light", elif value.get('litellm_provider') == 'vertex_ai-chat-models':
"command-medium-beta", vertex_chat_models.append(key)
"command-xlarge-beta", elif value.get('litellm_provider') == 'vertex_ai-code-chat-models':
] vertex_code_chat_models.append(key)
elif value.get('litellm_provider') == 'ai21':
anthropic_models: List = ["claude-2", "claude-instant-1", "claude-instant-1.2"] ai21_models.append(key)
elif value.get('litellm_provider') == 'nlp_cloud':
nlp_cloud_models.append(key)
elif value.get('litellm_provider') == 'aleph_alpha':
aleph_alpha_models.append(key)
# well supported replicate llms # well supported replicate llms
replicate_models: List = [ replicate_models: List = [
@ -128,44 +132,6 @@ replicate_models: List = [
"replit/replit-code-v1-3b:b84f4c074b807211cd75e3e8b1589b6399052125b4c27106e43d47189e8415ad", "replit/replit-code-v1-3b:b84f4c074b807211cd75e3e8b1589b6399052125b4c27106e43d47189e8415ad",
] ]
openrouter_models: List = [
"google/palm-2-codechat-bison",
"google/palm-2-chat-bison",
"openai/gpt-3.5-turbo",
"openai/gpt-3.5-turbo-16k",
"openai/gpt-4-32k",
"anthropic/claude-2",
"anthropic/claude-instant-v1",
"meta-llama/llama-2-13b-chat",
"meta-llama/llama-2-70b-chat",
]
vertex_chat_models: List = [
"chat-bison-32k",
"chat-bison",
"chat-bison@001",
]
vertex_code_chat_models: List = [
"codechat-bison",
"codechat-bison-32k",
"codechat-bison@001",
]
vertex_text_models: List = [
"text-bison",
"text-bison@001",
# "text-bison-32k",
]
vertex_code_text_models: List = [
"code-bison",
# "code-bison-32K",
"code-bison@001",
"code-gecko@001",
"code-gecko@latest",
]
huggingface_models: List = [ huggingface_models: List = [
"meta-llama/Llama-2-7b-hf", "meta-llama/Llama-2-7b-hf",
"meta-llama/Llama-2-7b-chat-hf", "meta-llama/Llama-2-7b-chat-hf",
@ -181,10 +147,6 @@ huggingface_models: List = [
"meta-llama/Llama-2-70b-chat", "meta-llama/Llama-2-70b-chat",
] # these have been tested on extensively. But by default all text2text-generation and text-generation models are supported by liteLLM. - https://docs.litellm.ai/docs/providers ] # these have been tested on extensively. But by default all text2text-generation and text-generation models are supported by liteLLM. - https://docs.litellm.ai/docs/providers
ai21_models: List = ["j2-ultra", "j2-mid", "j2-light"]
nlp_cloud_models: List = ["dolphin", "chatdolphin"]
together_ai_models: List = [ together_ai_models: List = [
# llama llms - chat # llama llms - chat
"togethercomputer/llama-2-70b-chat", "togethercomputer/llama-2-70b-chat",
@ -222,14 +184,6 @@ together_ai_models: List = [
] # supports all together ai models, just pass in the model id e.g. completion(model="together_computer/replit_code_3b",...) ] # supports all together ai models, just pass in the model id e.g. completion(model="together_computer/replit_code_3b",...)
aleph_alpha_models: List = [
"luminous-base",
"luminous-base-control",
"luminous-extended",
"luminous-extended-control",
"luminous-supreme",
"luminous-supreme-control"
]
baseten_models: List = ["qvv0xeq", "q841o8w", "31dxrj3"] # FALCON 7B # WizardLM # Mosaic ML baseten_models: List = ["qvv0xeq", "q841o8w", "31dxrj3"] # FALCON 7B # WizardLM # Mosaic ML

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5
litellm/tests/test_get_model_cost_map.py
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@ -5,6 +5,9 @@ sys.path.insert(
0, os.path.abspath("../..") 0, os.path.abspath("../..")
) # Adds the parent directory to the system path ) # Adds the parent directory to the system path
import time import time
from litellm import get_max_tokens from litellm import get_max_tokens, model_cost, open_ai_chat_completion_models
print(get_max_tokens("gpt-3.5-turbo")) print(get_max_tokens("gpt-3.5-turbo"))
print(model_cost)
print(open_ai_chat_completion_models)