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feat: adding last_accessed_at field to the models and updating the retrievers to update the timestamp

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This commit is contained in:
chinu0609 2025-10-29 20:17:27 +05:30
parent 3372679f7b
commit 3f27c5592b
2 changed files with 44 additions and 32 deletions
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48
cognee/modules/retrieval/chunks_retriever.py
View file

@ -29,26 +29,34 @@ class ChunksRetriever(BaseRetriever):
self.top_k = top_k
async def get_context(self, query: str) -> Any:
"""Retrieves document chunks context based on the query."""
logger.info(
f"Starting chunk retrieval for query: '{query[:100]}{'...' if len(query) > 100 else ''}'"
)
vector_engine = get_vector_engine()
try:
found_chunks = await vector_engine.search("DocumentChunk_text", query, limit=self.top_k)
logger.info(f"Found {len(found_chunks)} chunks from vector search")
# NEW: Update access timestamps
await update_node_access_timestamps(found_chunks, "DocumentChunk")
except CollectionNotFoundError as error:
logger.error("DocumentChunk_text collection not found in vector database")
raise NoDataError("No data found in the system, please add data first.") from error
chunk_payloads = [result.payload for result in found_chunks]
logger.info(f"Returning {len(chunk_payloads)} chunk payloads")
return chunk_payloads
"""
Retrieves document chunks context based on the query.
Searches for document chunks relevant to the specified query using a vector engine.
Raises a NoDataError if no data is found in the system.
Parameters:
-----------
- query (str): The query string to search for relevant document chunks.
Returns:
--------
- Any: A list of document chunk payloads retrieved from the search.
"""
logger.info(
f"Starting chunk retrieval for query: '{query[:100]}{'...' if len(query) > 100 else ''}'"
)
vector_engine = get_vector_engine()
try:
found_chunks = await vector_engine.search("DocumentChunk_text", query, limit=self.top_k)
logger.info(f"Found {len(found_chunks)} chunks from vector search")
await update_node_access_timestamps(found_chunks, "DocumentChunk")
except CollectionNotFoundError as error:
logger.error("DocumentChunk_text collection not found in vector database")
raise NoDataError("No data found in the system, please add data first.") from error
chunk_payloads = [result.payload for result in found_chunks]
logger.info(f"Returning {len(chunk_payloads)} chunk payloads")
async def get_completion(
self, query: str, context: Optional[Any] = None, session_id: Optional[str] = None

28
cognee/modules/retrieval/summaries_retriever.py
View file

@ -48,19 +48,23 @@ class SummariesRetriever(BaseRetriever):
f"Starting summary retrieval for query: '{query[:100]}{'...' if len(query) > 100 else ''}'"
)
vector_engine = get_vector_engine()
try:
summaries_results = await vector_engine.search(
"TextSummary_text", query, limit=self.top_k
)
vector_engine = get_vector_engine()
try:
summaries_results = await vector_engine.search(
"TextSummary_text", query, limit=self.top_k
)
logger.info(f"Found {len(summaries_results)} summaries from vector search")
await update_node_access_timestamps(summaries_results, "TextSummary")
except CollectionNotFoundError as error:
raise NoDataError("No data found in the system, please add data first.") from error
return [summary.payload for summary in summaries_results]
except CollectionNotFoundError as error:
logger.error("TextSummary_text collection not found in vector database")
raise NoDataError("No data found in the system, please add data first.") from error
summary_payloads = [summary.payload for summary in summaries_results]
logger.info(f"Returning {len(summary_payloads)} summary payloads")
return summary_payloads
async def get_completion(
self, query: str, context: Optional[Any] = None, session_id: Optional[str] = None, **kwargs