108 lines
4.3 KiB
Python
108 lines
4.3 KiB
Python
from typing import List, Optional
|
|
|
|
from letta.helpers.pinecone_utils import upsert_file_records_to_pinecone_index
|
|
from letta.log import get_logger
|
|
from letta.otel.tracing import log_event, trace_method
|
|
from letta.schemas.embedding_config import EmbeddingConfig
|
|
from letta.schemas.enums import VectorDBProvider
|
|
from letta.schemas.passage import Passage
|
|
from letta.schemas.user import User
|
|
from letta.services.file_processor.embedder.base_embedder import BaseEmbedder
|
|
|
|
try:
|
|
PINECONE_AVAILABLE = True
|
|
except ImportError:
|
|
PINECONE_AVAILABLE = False
|
|
|
|
logger = get_logger(__name__)
|
|
|
|
|
|
class PineconeEmbedder(BaseEmbedder):
|
|
"""Pinecone-based embedding generation"""
|
|
|
|
def __init__(self, embedding_config: Optional[EmbeddingConfig] = None):
|
|
super().__init__()
|
|
# set the vector db type for pinecone
|
|
self.vector_db_type = VectorDBProvider.PINECONE
|
|
|
|
if not PINECONE_AVAILABLE:
|
|
raise ImportError("Pinecone package is not installed. Install it with: pip install pinecone")
|
|
|
|
# set default embedding config if not provided
|
|
if embedding_config is None:
|
|
embedding_config = EmbeddingConfig.default_config(provider="pinecone")
|
|
|
|
self.embedding_config = embedding_config
|
|
|
|
@trace_method
|
|
async def generate_embedded_passages(self, file_id: str, source_id: str, chunks: List[str], actor: User) -> List[Passage]:
|
|
"""Generate embeddings and upsert to Pinecone, then return Passage objects"""
|
|
if not chunks:
|
|
return []
|
|
|
|
# Filter out empty or whitespace-only chunks
|
|
valid_chunks = [chunk for chunk in chunks if chunk and chunk.strip()]
|
|
|
|
if not valid_chunks:
|
|
logger.warning(f"No valid text chunks found for file {file_id}. PDF may contain only images without text layer.")
|
|
log_event(
|
|
"pinecone_embedder.no_valid_chunks",
|
|
{"file_id": file_id, "source_id": source_id, "total_chunks": len(chunks), "reason": "All chunks empty or whitespace-only"},
|
|
)
|
|
return []
|
|
|
|
if len(valid_chunks) < len(chunks):
|
|
logger.info(f"Filtered out {len(chunks) - len(valid_chunks)} empty chunks from {len(chunks)} total")
|
|
log_event(
|
|
"pinecone_embedder.chunks_filtered",
|
|
{
|
|
"file_id": file_id,
|
|
"original_chunks": len(chunks),
|
|
"valid_chunks": len(valid_chunks),
|
|
"filtered_chunks": len(chunks) - len(valid_chunks),
|
|
},
|
|
)
|
|
|
|
logger.info(f"Upserting {len(valid_chunks)} chunks to Pinecone using namespace {source_id}")
|
|
log_event(
|
|
"embedder.generation_started",
|
|
{
|
|
"total_chunks": len(valid_chunks),
|
|
"file_id": file_id,
|
|
"source_id": source_id,
|
|
},
|
|
)
|
|
|
|
# Upsert records to Pinecone using source_id as namespace
|
|
try:
|
|
await upsert_file_records_to_pinecone_index(file_id=file_id, source_id=source_id, chunks=valid_chunks, actor=actor)
|
|
logger.info(f"Successfully kicked off upserting {len(valid_chunks)} records to Pinecone")
|
|
log_event(
|
|
"embedder.upsert_started",
|
|
{"records_upserted": len(valid_chunks), "namespace": source_id, "file_id": file_id},
|
|
)
|
|
except Exception as e:
|
|
logger.error(f"Failed to upsert records to Pinecone: {str(e)}")
|
|
log_event("embedder.upsert_failed", {"error": str(e), "error_type": type(e).__name__})
|
|
raise
|
|
|
|
# Create Passage objects (without embeddings since Pinecone handles them)
|
|
passages = []
|
|
for i, text in enumerate(valid_chunks):
|
|
passage = Passage(
|
|
text=text,
|
|
file_id=file_id,
|
|
source_id=source_id,
|
|
embedding=None, # Pinecone handles embeddings internally
|
|
embedding_config=None, # None
|
|
organization_id=actor.organization_id,
|
|
)
|
|
passages.append(passage)
|
|
|
|
logger.info(f"Successfully created {len(passages)} passages")
|
|
log_event(
|
|
"embedder.generation_completed",
|
|
{"passages_created": len(passages), "total_chunks_processed": len(valid_chunks), "file_id": file_id, "source_id": source_id},
|
|
)
|
|
return passages
|