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feat(memory): add perceptual memory retrieval service with BM25+embedding fusion

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Eternity
2026-04-01 17:19:03 +08:00
parent 75bb96d4e7
commit 9cbe9d5edc
13 changed files with 1042 additions and 409 deletions
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70
api/app/repositories/neo4j/create_indexes.py
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@@ -1,17 +1,17 @@
import asyncio
from app.repositories.neo4j.neo4j_connector import Neo4jConnector
async def create_fulltext_indexes():
"""Create full-text indexes for keyword search with BM25 scoring."""
connector = Neo4jConnector()
try:
# 创建 Statements 索引
await connector.execute_query("""
CREATE FULLTEXT INDEX statementsFulltext IF NOT EXISTS FOR (s:Statement) ON EACH [s.statement]
OPTIONS { indexConfig: { `fulltext.analyzer`: 'cjk' } }
""")
""")
# # 创建 Dialogues 索引
# await connector.execute_query("""
# CREATE FULLTEXT INDEX dialoguesFulltext IF NOT EXISTS FOR (d:Dialogue) ON EACH [d.content]
@@ -21,27 +21,35 @@ async def create_fulltext_indexes():
await connector.execute_query("""
CREATE FULLTEXT INDEX entitiesFulltext IF NOT EXISTS FOR (e:ExtractedEntity) ON EACH [e.name]
OPTIONS { indexConfig: { `fulltext.analyzer`: 'cjk' } }
""")
""")
# 创建 Chunks 索引
await connector.execute_query("""
CREATE FULLTEXT INDEX chunksFulltext IF NOT EXISTS FOR (c:Chunk) ON EACH [c.content]
OPTIONS { indexConfig: { `fulltext.analyzer`: 'cjk' } }
""")
""")
# 创建 MemorySummary 索引
await connector.execute_query("""
CREATE FULLTEXT INDEX summariesFulltext IF NOT EXISTS FOR (m:MemorySummary) ON EACH [m.content]
OPTIONS { indexConfig: { `fulltext.analyzer`: 'cjk' } }
""")
""")
# 创建 Community 索引
await connector.execute_query("""
CREATE FULLTEXT INDEX communitiesFulltext IF NOT EXISTS FOR (c:Community) ON EACH [c.name, c.summary]
OPTIONS { indexConfig: { `fulltext.analyzer`: 'cjk' } }
""")
# 创建 Perceptual 感知记忆索引
await connector.execute_query("""
CREATE FULLTEXT INDEX perceptualFulltext IF NOT EXISTS FOR (p:Perceptual) ON EACH [p.summary, p.topic, p.domain]
OPTIONS { indexConfig: { `fulltext.analyzer`: 'cjk' } }
""")
finally:
await connector.close()
async def create_vector_indexes():
"""Create vector indexes for fast embedding similarity search.
@@ -50,8 +58,7 @@ async def create_vector_indexes():
"""
connector = Neo4jConnector()
try:
# Statement embedding index
await connector.execute_query("""
CREATE VECTOR INDEX statement_embedding_index IF NOT EXISTS
@@ -62,8 +69,7 @@ async def create_vector_indexes():
`vector.similarity_function`: 'cosine'
}}
""")
# Chunk embedding index
await connector.execute_query("""
CREATE VECTOR INDEX chunk_embedding_index IF NOT EXISTS
@@ -75,7 +81,6 @@ async def create_vector_indexes():
}}
""")
# Entity name embedding index
await connector.execute_query("""
CREATE VECTOR INDEX entity_embedding_index IF NOT EXISTS
@@ -86,8 +91,7 @@ async def create_vector_indexes():
`vector.similarity_function`: 'cosine'
}}
""")
# Memory summary embedding index
await connector.execute_query("""
CREATE VECTOR INDEX summary_embedding_index IF NOT EXISTS
@@ -98,7 +102,7 @@ async def create_vector_indexes():
`vector.similarity_function`: 'cosine'
}}
""")
# Community summary embedding index
await connector.execute_query("""
CREATE VECTOR INDEX community_summary_embedding_index IF NOT EXISTS
@@ -108,8 +112,8 @@ async def create_vector_indexes():
`vector.dimensions`: 1024,
`vector.similarity_function`: 'cosine'
}}
""")
""")
# Dialogue embedding index (optional)
await connector.execute_query("""
CREATE VECTOR INDEX dialogue_embedding_index IF NOT EXISTS
@@ -120,15 +124,27 @@ async def create_vector_indexes():
`vector.similarity_function`: 'cosine'
}}
""")
# Perceptual summary embedding index
await connector.execute_query("""
CREATE VECTOR INDEX perceptual_summary_embedding_index IF NOT EXISTS
FOR (p:Perceptual)
ON p.summary_embedding
OPTIONS {indexConfig: {
`vector.dimensions`: 1024,
`vector.similarity_function`: 'cosine'
}}
""")
finally:
await connector.close()
async def create_unique_constraints():
"""Create uniqueness constraints for core node identifiers.
Ensures concurrent MERGE operations remain safe and prevents duplicates.
"""
connector = Neo4jConnector()
try:
try:
# Dialogue.id unique
await connector.execute_query(
"""
@@ -136,7 +152,7 @@ async def create_unique_constraints():
FOR (d:Dialogue) REQUIRE d.id IS UNIQUE
"""
)
# Statement.id unique
await connector.execute_query(
"""
@@ -144,7 +160,7 @@ async def create_unique_constraints():
FOR (s:Statement) REQUIRE s.id IS UNIQUE
"""
)
# Chunk.id unique
await connector.execute_query(
"""
@@ -152,13 +168,13 @@ async def create_unique_constraints():
FOR (c:Chunk) REQUIRE c.id IS UNIQUE
"""
)
finally:
await connector.close()
async def create_all_indexes():
"""Create all indexes and constraints in one go."""
await create_fulltext_indexes()
await create_vector_indexes()
await create_unique_constraints()
print("✓ All indexes and constraints created successfully!")