# ---------------------------------------------------------------------------- # # Welcome to Baml! To use this generated code, please run the following: # # $ pip install baml # # ---------------------------------------------------------------------------- # This file was generated by BAML: please do not edit it. Instead, edit the # BAML files and re-generate this code using: baml-cli generate # baml-cli is available with the baml package. import typing import typing_extensions from . import stream_types, types from .runtime import DoNotUseDirectlyCallManager, BamlCallOptions class LlmResponseParser: __options: DoNotUseDirectlyCallManager def __init__(self, options: DoNotUseDirectlyCallManager): self.__options = options def FilterItems( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["types.Verdict"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="FilterItems", llm_response=llm_response, mode="request") return typing.cast(typing.List["types.Verdict"], __result__) def FilterScoreItems( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["types.RankedItem"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="FilterScoreItems", llm_response=llm_response, mode="request") return typing.cast(typing.List["types.RankedItem"], __result__) def GenerateOutline( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> types.EpisodeOutline: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="GenerateOutline", llm_response=llm_response, mode="request") return typing.cast(types.EpisodeOutline, __result__) def GenerateScriptSegment( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["types.ScriptLine"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="GenerateScriptSegment", llm_response=llm_response, mode="request") return typing.cast(typing.List["types.ScriptLine"], __result__) def ScoreItems( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["types.ScoredItem"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ScoreItems", llm_response=llm_response, mode="request") return typing.cast(typing.List["types.ScoredItem"], __result__) class LlmStreamParser: __options: DoNotUseDirectlyCallManager def __init__(self, options: DoNotUseDirectlyCallManager): self.__options = options def FilterItems( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["stream_types.Verdict"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="FilterItems", llm_response=llm_response, mode="stream") return typing.cast(typing.List["stream_types.Verdict"], __result__) def FilterScoreItems( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["stream_types.RankedItem"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="FilterScoreItems", llm_response=llm_response, mode="stream") return typing.cast(typing.List["stream_types.RankedItem"], __result__) def GenerateOutline( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> stream_types.EpisodeOutline: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="GenerateOutline", llm_response=llm_response, mode="stream") return typing.cast(stream_types.EpisodeOutline, __result__) def GenerateScriptSegment( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["stream_types.ScriptLine"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="GenerateScriptSegment", llm_response=llm_response, mode="stream") return typing.cast(typing.List["stream_types.ScriptLine"], __result__) def ScoreItems( self, llm_response: str, baml_options: BamlCallOptions = {}, ) -> typing.List["stream_types.ScoredItem"]: __result__ = self.__options.merge_options(baml_options).parse_response(function_name="ScoreItems", llm_response=llm_response, mode="stream") return typing.cast(typing.List["stream_types.ScoredItem"], __result__)