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llm_config.yaml
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# This configuration file defines the setup for how ChainLite calls various LLM APIs, and how it logs LLM inputs/outputs.
# To configure it:
# 1. Set directories containing the prompt files under the `prompt_dirs` section.
# 2. Adjust logging settings and optionally specify which prompts you would like to skip in the `prompt_logging` section.
# 3. Configure LLM endpoints under the `llm_endpoints` section, specifying the API base URL, version (if needed), API key (if needed),
# and the mapping of model names to their respective deployment identifiers. The name on the left-hand side of each mapping is "engine", the shorthand
# you can use in your code when calling llm_generation_chain(engine=...).
# The name on the right side-hand is the "model", the specific name that LiteLLM expects: https://docs.litellm.ai/docs/providers
# Note that "engine" names should be unique within this file, but "model" names do not have to be unique.
# 4. Follow the examples provided for Azure, OpenAI, Groq, Together, Mistral, and local models as needed, and remove unused llm endpoints.
prompt_dirs: # List of directories containing prompt files, relative to the location of this file
- "./" # Current directory
- "./tests/"
litellm_set_verbose: false # Verbose logging setting for LiteLLM
prompt_logging:
log_file: ./prompt_logs.jsonl # Path to the log file for prompt logs, relative to the location of this file
prompts_to_skip:
- tests/test.prompt # List of prompts to exclude from logging, relative to the location of this file
# Configuration for different LLM endpoints
llm_endpoints:
# Example configuration for OpenAI models via Azure API
- api_base: https://ovalopenairesource.openai.azure.com # Base URL for Azure OpenAI API
api_version: 2025-01-01-preview # API version for Azure OpenAI
api_key: AZURE_OPENAI_API_KEY_TEST # API key for Azure OpenAI
engine_map: # Mapping of model names to Azure deployment identifiers prepended by "azure/"
gpt-4o-azure: azure/gpt-4o-global
- api_base: https://ovaleastus.openai.azure.com
api_version: 2025-01-01-preview # API version for Azure OpenAI
api_key: AZURE_OPENAI_API_KEY_TEST_2 # API key for Azure OpenAI
engine_map:
o1-azure: azure/o1-2024-12-17
o3-mini-azure: azure/o3-mini
# Example of OpenAI models via openai.com
- api_base: https://api.openai.com/v1
api_key: OPENAI_API_KEY_TEST
engine_map: # OpenAI models don't need the "openai/" prefix
gpt-35-turbo: gpt-3.5-turbo-0125
gpt-35-turbo-instruct: gpt-3.5-turbo-instruct
gpt-4: gpt-4-turbo-2024-04-09
gpt-4o-mini: gpt-4o-mini
gpt-4o-openai: gpt-4o-2024-08-06 # you can specify which version of the model you want
gpt-4o: gpt-4o # you can leave it to OpenAI to select the latest model version for you
gpt-4o-another-one: gpt-4o # "model" names, which are on the right side-hand of a mapping, do not need to be unique
o1: o1
o3-mini: o3-mini
# Example of OpenAI fine-tuned model
- api_base: https://api.openai.com/v1
api_key: OPENAI_API_KEY
prompt_format: distilled
engine_map:
gpt-35-turbo-finetuned: ft:gpt-3.5-turbo-1106:<model_id>
# Example of Groq API (groq.com)
- api_base: https://api.groq.com/openai/v1
api_key: GROQ_API_KEY
engine_map: # Has limited model availability, but a very fast inference on custom hardware
llama-3-70b-instruct: groq/llama3-70b-8192
# Example of Together API (together.ai)
- api_key: TOGETHER_API_KEY
engine_map: # TODO non-instruct models don't work well because of LiteLLM's formatting issues, does not work with free accounts because of the 1 QPS limit
llama-2-70b: together_ai/togethercomputer/llama-2-70b
llama-3-70b-instruct: together_ai/meta-llama/Llama-3-70b-chat-hf
mixtral-8-7b: together_ai/mistralai/Mixtral-8x7B-v0.1
mixtral-8-7b-instruct: together_ai/mistralai/Mixtral-8x7B-Instruct-v0.1
mistral-7b: together_ai/mistralai/Mistral-7B-v0.1
# Example of Mistral API (mistral.ai)
- api_base: https://api.mistral.ai/v1 # https://docs.mistral.ai/platform/endpoints/
api_key: MISTRAL_API_KEY
engine_map:
mistral-large: mistral/mistral-large-latest
mistral-medium: mistral/mistral-medium-latest
mistral-small: mistral/mistral-small-latest
mistral-7b-instruct: mistral/open-mistral-7b
mixtral-8-7b-instruct: mistral/open-mixtral-8x7b
# Example of local distilled models served via HuggingFace's text-generation-inference (https://github.com/huggingface/text-generation-inference/)
# The name after huggingface/* does not matter and is unused
- api_base: http://127.0.0.1:5002
prompt_format: distilled
engine_map:
local_distilled: huggingface/local
# Example of local models served via HuggingFace's text-generation-inference (https://github.com/huggingface/text-generation-inference/)
# The name after huggingface/* does not matter and is unused
- api_base: http://127.0.0.1:5004
engine_map:
local_fewshot: huggingface/local