ceb60a3d33
* cross encoder reranker * update reranker * add openai reranker * format * mypy * update * updates * MyPy typing * bump version
105 lines
3 KiB
Python
105 lines
3 KiB
Python
"""
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Copyright 2024, Zep Software, Inc.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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"""
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from enum import Enum
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from pydantic import BaseModel, Field
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from graphiti_core.edges import EntityEdge
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from graphiti_core.nodes import CommunityNode, EntityNode
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from graphiti_core.search.search_utils import (
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DEFAULT_MIN_SCORE,
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DEFAULT_MMR_LAMBDA,
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MAX_SEARCH_DEPTH,
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)
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DEFAULT_SEARCH_LIMIT = 10
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class EdgeSearchMethod(Enum):
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cosine_similarity = 'cosine_similarity'
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bm25 = 'bm25'
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bfs = 'breadth_first_search'
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class NodeSearchMethod(Enum):
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cosine_similarity = 'cosine_similarity'
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bm25 = 'bm25'
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bfs = 'breadth_first_search'
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class CommunitySearchMethod(Enum):
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cosine_similarity = 'cosine_similarity'
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bm25 = 'bm25'
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class EdgeReranker(Enum):
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rrf = 'reciprocal_rank_fusion'
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node_distance = 'node_distance'
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episode_mentions = 'episode_mentions'
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mmr = 'mmr'
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cross_encoder = 'cross_encoder'
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class NodeReranker(Enum):
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rrf = 'reciprocal_rank_fusion'
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node_distance = 'node_distance'
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episode_mentions = 'episode_mentions'
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mmr = 'mmr'
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cross_encoder = 'cross_encoder'
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class CommunityReranker(Enum):
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rrf = 'reciprocal_rank_fusion'
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mmr = 'mmr'
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cross_encoder = 'cross_encoder'
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class EdgeSearchConfig(BaseModel):
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search_methods: list[EdgeSearchMethod]
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reranker: EdgeReranker = Field(default=EdgeReranker.rrf)
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sim_min_score: float = Field(default=DEFAULT_MIN_SCORE)
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mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA)
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bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH)
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class NodeSearchConfig(BaseModel):
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search_methods: list[NodeSearchMethod]
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reranker: NodeReranker = Field(default=NodeReranker.rrf)
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sim_min_score: float = Field(default=DEFAULT_MIN_SCORE)
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mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA)
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bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH)
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class CommunitySearchConfig(BaseModel):
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search_methods: list[CommunitySearchMethod]
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reranker: CommunityReranker = Field(default=CommunityReranker.rrf)
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sim_min_score: float = Field(default=DEFAULT_MIN_SCORE)
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mmr_lambda: float = Field(default=DEFAULT_MMR_LAMBDA)
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bfs_max_depth: int = Field(default=MAX_SEARCH_DEPTH)
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class SearchConfig(BaseModel):
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edge_config: EdgeSearchConfig | None = Field(default=None)
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node_config: NodeSearchConfig | None = Field(default=None)
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community_config: CommunitySearchConfig | None = Field(default=None)
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limit: int = Field(default=DEFAULT_SEARCH_LIMIT)
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class SearchResults(BaseModel):
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edges: list[EntityEdge]
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nodes: list[EntityNode]
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communities: list[CommunityNode]
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