154 lines
6.4 KiB
Python
154 lines
6.4 KiB
Python
import asyncio
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from typing import Any, Dict, List
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from pinecone import PineconeAsyncio
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from letta.constants import (
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PINECONE_CLOUD,
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PINECONE_EMBEDDING_MODEL,
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PINECONE_MAX_BATCH_SIZE,
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PINECONE_METRIC,
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PINECONE_REGION,
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PINECONE_TEXT_FIELD_NAME,
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)
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from letta.log import get_logger
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from letta.schemas.user import User
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from letta.settings import settings
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logger = get_logger(__name__)
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def should_use_pinecone(verbose: bool = False):
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if verbose:
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logger.info(
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"Pinecone check: enable_pinecone=%s, api_key=%s, agent_index=%s, source_index=%s",
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settings.enable_pinecone,
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bool(settings.pinecone_api_key),
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bool(settings.pinecone_agent_index),
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bool(settings.pinecone_source_index),
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)
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return settings.enable_pinecone and settings.pinecone_api_key and settings.pinecone_agent_index and settings.pinecone_source_index
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async def upsert_pinecone_indices():
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from pinecone import IndexEmbed, PineconeAsyncio
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for index_name in get_pinecone_indices():
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async with PineconeAsyncio(api_key=settings.pinecone_api_key) as pc:
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if not await pc.has_index(index_name):
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await pc.create_index_for_model(
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name=index_name,
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cloud=PINECONE_CLOUD,
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region=PINECONE_REGION,
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embed=IndexEmbed(model=PINECONE_EMBEDDING_MODEL, field_map={"text": PINECONE_TEXT_FIELD_NAME}, metric=PINECONE_METRIC),
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)
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def get_pinecone_indices() -> List[str]:
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return [settings.pinecone_agent_index, settings.pinecone_source_index]
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async def upsert_file_records_to_pinecone_index(file_id: str, source_id: str, chunks: List[str], actor: User):
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records = []
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for i, chunk in enumerate(chunks):
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record = {
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"_id": f"{file_id}_{i}",
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PINECONE_TEXT_FIELD_NAME: chunk,
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"file_id": file_id,
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"source_id": source_id,
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}
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records.append(record)
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return await upsert_records_to_pinecone_index(records, actor)
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async def delete_file_records_from_pinecone_index(file_id: str, actor: User):
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from pinecone.exceptions.exceptions import NotFoundException
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namespace = actor.organization_id
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try:
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async with PineconeAsyncio(api_key=settings.pinecone_api_key) as pc:
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description = await pc.describe_index(name=settings.pinecone_source_index)
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async with pc.IndexAsyncio(host=description.index.host) as dense_index:
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await dense_index.delete(
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filter={
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"file_id": {"$eq": file_id},
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},
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namespace=namespace,
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)
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except NotFoundException:
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logger.warning(f"Pinecone namespace {namespace} not found for {file_id} and {actor.organization_id}")
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async def delete_source_records_from_pinecone_index(source_id: str, actor: User):
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from pinecone.exceptions.exceptions import NotFoundException
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namespace = actor.organization_id
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try:
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async with PineconeAsyncio(api_key=settings.pinecone_api_key) as pc:
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description = await pc.describe_index(name=settings.pinecone_source_index)
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async with pc.IndexAsyncio(host=description.index.host) as dense_index:
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await dense_index.delete(filter={"source_id": {"$eq": source_id}}, namespace=namespace)
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except NotFoundException:
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logger.warning(f"Pinecone namespace {namespace} not found for {source_id} and {actor.organization_id}")
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async def upsert_records_to_pinecone_index(records: List[dict], actor: User):
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async with PineconeAsyncio(api_key=settings.pinecone_api_key) as pc:
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description = await pc.describe_index(name=settings.pinecone_source_index)
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async with pc.IndexAsyncio(host=description.index.host) as dense_index:
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# Process records in batches to avoid exceeding Pinecone limits
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batches = [records[i : i + PINECONE_MAX_BATCH_SIZE] for i in range(0, len(records), PINECONE_MAX_BATCH_SIZE)]
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await asyncio.gather(*[dense_index.upsert_records(actor.organization_id, batch) for batch in batches])
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async def search_pinecone_index(query: str, limit: int, filter: Dict[str, Any], actor: User) -> Dict[str, Any]:
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async with PineconeAsyncio(api_key=settings.pinecone_api_key) as pc:
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description = await pc.describe_index(name=settings.pinecone_source_index)
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async with pc.IndexAsyncio(host=description.index.host) as dense_index:
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namespace = actor.organization_id
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try:
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# Search the dense index with reranking
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search_results = await dense_index.search(
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namespace=namespace,
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query={
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"top_k": limit,
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"inputs": {"text": query},
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"filter": filter,
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},
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rerank={"model": "bge-reranker-v2-m3", "top_n": limit, "rank_fields": [PINECONE_TEXT_FIELD_NAME]},
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)
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return search_results
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except Exception as e:
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logger.warning(f"Failed to search Pinecone namespace {actor.organization_id}: {str(e)}")
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raise e
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async def list_pinecone_index_for_files(file_id: str, actor: User, limit: int = None, pagination_token: str = None) -> List[str]:
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from pinecone.exceptions.exceptions import NotFoundException
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namespace = actor.organization_id
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try:
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async with PineconeAsyncio(api_key=settings.pinecone_api_key) as pc:
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description = await pc.describe_index(name=settings.pinecone_source_index)
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async with pc.IndexAsyncio(host=description.index.host) as dense_index:
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kwargs = {"namespace": namespace, "prefix": file_id}
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if limit is not None:
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kwargs["limit"] = limit
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if pagination_token is not None:
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kwargs["pagination_token"] = pagination_token
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try:
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result = []
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async for ids in dense_index.list(**kwargs):
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result.extend(ids)
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return result
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except Exception as e:
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logger.warning(f"Failed to list Pinecone namespace {actor.organization_id}: {str(e)}")
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raise e
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except NotFoundException:
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logger.warning(f"Pinecone namespace {namespace} not found for {file_id} and {actor.organization_id}")
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