autorag.data.qa.evolve package¶

Submodules¶

autorag.data.qa.evolve.llama_index_query_evolve module¶

async autorag.data.qa.evolve.llama_index_query_evolve.compress_ragas(row: Dict, llm: BaseLLM, lang: str = 'en') → Dict[source]¶

async autorag.data.qa.evolve.llama_index_query_evolve.conditional_evolve_ragas(row: Dict, llm: BaseLLM, lang: str = 'en') → Dict[source]¶

async autorag.data.qa.evolve.llama_index_query_evolve.llama_index_generate_base(row: Dict, llm: BaseLLM, messages: List[ChatMessage]) → Dict[source]¶

async autorag.data.qa.evolve.llama_index_query_evolve.reasoning_evolve_ragas(row: Dict, llm: BaseLLM, lang: str = 'en') → Dict[source]¶

autorag.data.qa.evolve.openai_query_evolve module¶

class autorag.data.qa.evolve.openai_query_evolve.Response(*, evolved_query: str)[source]¶

Bases: BaseModel

evolved_query: str¶

model_config: ClassVar[ConfigDict] = {}¶: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

async autorag.data.qa.evolve.openai_query_evolve.compress_ragas(row: Dict, client: AsyncOpenAI, model_name: str = 'gpt-4o-2024-08-06', lang: str = 'en') → Dict[source]¶

async autorag.data.qa.evolve.openai_query_evolve.conditional_evolve_ragas(row: Dict, client: AsyncOpenAI, model_name: str = 'gpt-4o-2024-08-06', lang: str = 'en') → Dict[source]¶

async autorag.data.qa.evolve.openai_query_evolve.query_evolve_openai_base(row: Dict, client: AsyncOpenAI, messages: List[ChatMessage], model_name: str = 'gpt-4o-2024-08-06')[source]¶: Evolve the original query to a new evolved query using OpenAI structured outputs.

async autorag.data.qa.evolve.openai_query_evolve.reasoning_evolve_ragas(row: Dict, client: AsyncOpenAI, model_name: str = 'gpt-4o-2024-08-06', lang: str = 'en') → Dict[source]¶

autorag.data.qa.evolve.prompt module¶

Module contents¶