mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-27 15:37:44 +00:00
Xu Yang
ed53af4c65
* fix several task & integrate deepseek R1 * fix CI --------- Co-authored-by: Xu Yang <xuyang1@microsoft.com>
111 lines
3.6 KiB
Python
111 lines
3.6 KiB
Python
from __future__ import annotations
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from pathlib import Path
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from pydantic import Field
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from rdagent.core.conf import ExtendedBaseSettings
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class LLMSettings(ExtendedBaseSettings):
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# backend
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backend: str = "rdagent.oai.backend.DeprecBackend"
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log_llm_chat_content: bool = True
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use_azure: bool = Field(default=False, deprecated=True)
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chat_use_azure: bool = False
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embedding_use_azure: bool = False
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chat_use_azure_token_provider: bool = False
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embedding_use_azure_token_provider: bool = False
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managed_identity_client_id: str | None = None
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max_retry: int = 10
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retry_wait_seconds: int = 1
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dump_chat_cache: bool = False
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use_chat_cache: bool = False
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dump_embedding_cache: bool = False
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use_embedding_cache: bool = False
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prompt_cache_path: str = str(Path.cwd() / "prompt_cache.db")
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max_past_message_include: int = 10
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# Behavior of returning answers to the same question when caching is enabled
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use_auto_chat_cache_seed_gen: bool = False
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"""
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`_create_chat_completion_inner_function` provides a feature to pass in a seed to affect the cache hash key
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We want to enable a auto seed generator to get different default seed for `_create_chat_completion_inner_function`
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if seed is not given.
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So the cache will only not miss you ask the same question on same round.
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"""
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init_chat_cache_seed: int = 42
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# Chat configs
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openai_api_key: str = "" # TODO: simplify the key design.
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chat_openai_api_key: str | None = None
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chat_openai_base_url: str | None = None #
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chat_azure_api_base: str = ""
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chat_azure_api_version: str = ""
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chat_model: str = "gpt-4-turbo"
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chat_max_tokens: int = 3000
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chat_temperature: float = 0.5
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chat_stream: bool = True
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chat_seed: int | None = None
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chat_frequency_penalty: float = 0.0
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chat_presence_penalty: float = 0.0
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chat_token_limit: int = (
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100000 # 100000 is the maximum limit of gpt4, which might increase in the future version of gpt
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)
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default_system_prompt: str = "You are an AI assistant who helps to answer user's questions."
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# Embedding configs
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embedding_openai_api_key: str = ""
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embedding_openai_base_url: str = ""
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embedding_azure_api_base: str = ""
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embedding_azure_api_version: str = ""
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embedding_model: str = ""
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embedding_max_str_num: int = 50
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# offline llama2 related config
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use_llama2: bool = False
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llama2_ckpt_dir: str = "Llama-2-7b-chat"
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llama2_tokenizer_path: str = "Llama-2-7b-chat/tokenizer.model"
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llams2_max_batch_size: int = 8
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# server served endpoints
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use_gcr_endpoint: bool = False
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gcr_endpoint_type: str = "llama2_70b" # or "llama3_70b", "phi2", "phi3_4k", "phi3_128k"
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llama2_70b_endpoint: str = ""
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llama2_70b_endpoint_key: str = ""
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llama2_70b_endpoint_deployment: str = ""
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llama3_70b_endpoint: str = ""
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llama3_70b_endpoint_key: str = ""
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llama3_70b_endpoint_deployment: str = ""
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phi2_endpoint: str = ""
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phi2_endpoint_key: str = ""
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phi2_endpoint_deployment: str = ""
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phi3_4k_endpoint: str = ""
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phi3_4k_endpoint_key: str = ""
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phi3_4k_endpoint_deployment: str = ""
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phi3_128k_endpoint: str = ""
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phi3_128k_endpoint_key: str = ""
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phi3_128k_endpoint_deployment: str = ""
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gcr_endpoint_temperature: float = 0.7
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gcr_endpoint_top_p: float = 0.9
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gcr_endpoint_do_sample: bool = False
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gcr_endpoint_max_token: int = 100
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chat_use_azure_deepseek: bool = False
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chat_azure_deepseek_endpoint: str = ""
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chat_azure_deepseek_key: str = ""
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chat_model_map: str = "{}"
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LLM_SETTINGS = LLMSettings()
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