KeyArgo
/
private-gpt
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Reuse existing stored index during ingestion (#1220)

This commit is contained in:
Iván Martínez 2023-11-12 22:14:38 +01:00 committed by GitHub
parent aa70d3d9f0
commit f394ca61bb
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 21 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

29
private_gpt/server/ingest/ingest_service.py
View File

@ -133,14 +133,27 @@ class IngestService:
document.excluded_embed_metadata_keys = ["doc_id"]
# We don't want the LLM to receive these metadata in the context
document.excluded_llm_metadata_keys = ["file_name", "doc_id", "page_label"]
# create vectorStore index
VectorStoreIndex.from_documents(
documents,
storage_context=self.storage_context,
service_context=self.ingest_service_context,
store_nodes_override=True, # Force store nodes in index and document stores
show_progress=True,
)
try:
# Load the index from storage and insert new documents,
index = load_index_from_storage(
storage_context=self.storage_context,
service_context=self.ingest_service_context,
store_nodes_override=True, # Force store nodes in index and document stores
show_progress=True,
)
for doc in documents:
index.insert(doc)
except ValueError:
# Or create a new one if there is none
VectorStoreIndex.from_documents(
documents,
storage_context=self.storage_context,
service_context=self.ingest_service_context,
store_nodes_override=True, # Force store nodes in index and document stores
show_progress=True,
)
# persist the index and nodes
self.storage_context.persist(persist_dir=local_data_path)
return [