""" Copyright 2024, Zep Software, Inc. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ from enum import Enum from pydantic import BaseModel, Field from graphiti_core.edges import EntityEdge from graphiti_core.nodes import CommunityNode, EntityNode, EpisodicNode from graphiti_core.search.search_utils import ( DEFAULT_MIN_SCORE, DEFAULT_MMR_LAMBDA, MAX_SEARCH_DEPTH, ) DEFAULT_SEARCH_LIMIT = 10 class EdgeSearchMethod(Enum): cosine_similarity = 'cosine_similarity' bm25 = 'bm25' bfs = 'breadth_first_search' class NodeSearchMethod(Enum): cosine_similarity = 'cosine_similarity' bm25 = 'bm25' bfs = 'breadth_first_search' class EpisodeSearchMethod(Enum): bm25 = 'bm25' class CommunitySearchMethod(Enum): cosine_similarity = 'cosine_similarity' bm25 = 'bm25' class EdgeReranker(Enum): rrf = 'reciprocal_rank_fusion' node_distance = 'node_distance' episode_mentions = 'episode_mentions' mmr = 'mmr' cross_encoder = 'cross_encoder' class NodeReranker(Enum): rrf = 'reciprocal_rank_fusion' node_distance = 'node_distance' episode_mentions = 'episode_mentions' mmr = 'mmr' cross_encoder = 'cross_encoder' class EpisodeReranker(Enum): rrf = 'reciprocal_rank_fusion' cross_encoder = 'cross_encoder' class CommunityReranker(Enum): rrf = 'reciprocal_rank_fusion' mmr = 'mmr' cross_encoder = 'cross_encoder' class EdgeSearchConfig(BaseModel): search_methods: list[EdgeSearchMethod] reranker: EdgeReranker = Field(default=EdgeReranker.rrf) sim_min_score: float = Field(default=DEFAULT_MIN_SCORE) mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA) bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH) class NodeSearchConfig(BaseModel): search_methods: list[NodeSearchMethod] reranker: NodeReranker = Field(default=NodeReranker.rrf) sim_min_score: float = Field(default=DEFAULT_MIN_SCORE) mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA) bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH) class EpisodeSearchConfig(BaseModel): search_methods: list[EpisodeSearchMethod] reranker: EpisodeReranker = Field(default=EpisodeReranker.rrf) sim_min_score: float = Field(default=DEFAULT_MIN_SCORE) mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA) bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH) class CommunitySearchConfig(BaseModel): search_methods: list[CommunitySearchMethod] reranker: CommunityReranker = Field(default=CommunityReranker.rrf) sim_min_score: float = Field(default=DEFAULT_MIN_SCORE) mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA) bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH) class SearchConfig(BaseModel): edge_config: EdgeSearchConfig | None = Field(default=None) node_config: NodeSearchConfig | None = Field(default=None) episode_config: EpisodeSearchConfig | None = Field(default=None) community_config: CommunitySearchConfig | None = Field(default=None) limit: int = Field(default=DEFAULT_SEARCH_LIMIT) reranker_min_score: float = Field(default=0) class SearchResults(BaseModel): edges: list[EntityEdge] = Field(default_factory=list) edge_reranker_scores: list[float] = Field(default_factory=list) nodes: list[EntityNode] = Field(default_factory=list) node_reranker_scores: list[float] = Field(default_factory=list) episodes: list[EpisodicNode] = Field(default_factory=list) episode_reranker_scores: list[float] = Field(default_factory=list) communities: list[CommunityNode] = Field(default_factory=list) community_reranker_scores: list[float] = Field(default_factory=list)