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655e1e6312
* Add OpenAI function calls to settings screen for Azure models, and backend support in the Azure call for functions and function_calls
82 lines
3.9 KiB
Python
82 lines
3.9 KiB
Python
"""
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A list of all model APIs natively supported by ChainForge.
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"""
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from enum import Enum
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class LLM(str, Enum):
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""" OpenAI Chat """
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OpenAI_ChatGPT = "gpt-3.5-turbo"
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OpenAI_ChatGPT_16k = "gpt-3.5-turbo-16k"
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OpenAI_ChatGPT_16k_0613 = "gpt-3.5-turbo-16k-0613"
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OpenAI_ChatGPT_0301 = "gpt-3.5-turbo-0301"
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OpenAI_ChatGPT_0613 = "gpt-3.5-turbo-0613"
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OpenAI_GPT4 = "gpt-4"
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OpenAI_GPT4_0314 = "gpt-4-0314"
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OpenAI_GPT4_0613 = "gpt-4-0613"
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OpenAI_GPT4_32k = "gpt-4-32k"
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OpenAI_GPT4_32k_0314 = "gpt-4-32k-0314"
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OpenAI_GPT4_32k_0613 = "gpt-4-32k-0613"
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""" OpenAI Text Completions """
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OpenAI_Davinci003 = "text-davinci-003"
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OpenAI_Davinci002 = "text-davinci-002"
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""" Azure OpenAI Endpoints """
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Azure_OpenAI = "azure-openai"
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""" Dalai-served models (Alpaca and Llama) """
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Dalai_Alpaca_7B = "alpaca.7B"
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Dalai_Alpaca_13B = "alpaca.13B"
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Dalai_Llama_7B = "llama.7B"
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Dalai_Llama_13B = "llama.13B"
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Dalai_Llama_30B = "llama.30B"
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Dalai_Llama_65B = "llama.65B"
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""" Anthropic """
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# Our largest model, ideal for a wide range of more complex tasks. Using this model name
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# will automatically switch you to newer versions of claude-v1 as they are released.
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Claude_v1 = "claude-v1"
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# An earlier version of claude-v1
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Claude_v1_0 = "claude-v1.0"
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# An improved version of claude-v1. It is slightly improved at general helpfulness,
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# instruction following, coding, and other tasks. It is also considerably better with
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# non-English languages. This model also has the ability to role play (in harmless ways)
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# more consistently, and it defaults to writing somewhat longer and more thorough responses.
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Claude_v1_2 = "claude-v1.2"
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# A significantly improved version of claude-v1. Compared to claude-v1.2, it's more robust
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# against red-team inputs, better at precise instruction-following, better at code, and better
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# and non-English dialogue and writing.
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Claude_v1_3 = "claude-v1.3"
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# A smaller model with far lower latency, sampling at roughly 40 words/sec! Its output quality
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# is somewhat lower than claude-v1 models, particularly for complex tasks. However, it is much
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# less expensive and blazing fast. We believe that this model provides more than adequate performance
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# on a range of tasks including text classification, summarization, and lightweight chat applications,
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# as well as search result summarization. Using this model name will automatically switch you to newer
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# versions of claude-instant-v1 as they are released.
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Claude_v1_instant = "claude-instant-v1"
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""" Google models """
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PaLM2_Text_Bison = "text-bison-001" # it's really models/text-bison-001, but that's confusing
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PaLM2_Chat_Bison = "chat-bison-001"
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# LLM APIs often have rate limits, which control number of requests. E.g., OpenAI: https://platform.openai.com/account/rate-limits
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# For a basic organization in OpenAI, GPT3.5 is currently 3500 and GPT4 is 200 RPM (requests per minute).
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# For Anthropic evaluaton preview of Claude, can only send 1 request at a time (synchronously).
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# This 'cheap' version of controlling for rate limits is to wait a few seconds between batches of requests being sent off.
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# If a model is missing from below, it means we must send and receive only 1 request at a time (synchronous).
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# The following is only a guideline, and a bit on the conservative side.
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RATE_LIMITS = {
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LLM.OpenAI_ChatGPT: (30, 10), # max 30 requests a batch; wait 10 seconds between
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LLM.OpenAI_ChatGPT_0301: (30, 10),
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LLM.OpenAI_GPT4: (4, 15), # max 4 requests a batch; wait 15 seconds between
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LLM.OpenAI_GPT4_0314: (4, 15),
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LLM.OpenAI_GPT4_32k: (4, 15),
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LLM.OpenAI_GPT4_32k_0314: (4, 15),
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LLM.PaLM2_Text_Bison: (4, 10), # max 30 requests per minute; so do 4 per batch, 10 seconds between (conservative)
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LLM.PaLM2_Chat_Bison: (4, 10),
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} |