create_index_for_model: OK in 8.2s
kind: {'vector_type': None, 'dimension': None, 'metric': None} | embed: {'model': 'llama-text-embed-v2', 'metric': 'cosine', 'dimension': None, 'vector_type': None, 'field_map': {'text': 'chunk_text'}, 'read_parameters': {'truncate': 'END', 'dimension': 1024, 'input_type': 'query'}, 'write_parameters': {'truncate': 'END', 'dimension': 1024, 'input_type': 'passage'}}
upsert_records: sent 5 records
search: {'result': {'hits': [{'id_': '1310a29021ebb2d0', 'score_': 0.22077985107898712, 'fields': {'section': 'access-key', 'url': 'https://webcrawlerapi.com/docs/access-key'}}, {'id_': 'eb683453302b013f', 'score_': 0.20973217487335205, 'fields': {'section': 'access-key', 'url': 'https://webcrawlerapi.com/docs/access-key'}}]}, 'usage': {'read_units': 1, 'embed_total_tokens': 9, 'rerank_units': None}, 'response_info': {'raw_headers': {'date': 'Fri, 06 Nov 2026 00:53:29 GMT', 'content-type': 'application/json', 'content-length': '387', 'connection': 'keep-alive', 'x-pinecone-max-indexed-lsn': '1', 'x-pi
documents.upsert on the legacy index: ApiError: [400 INVALID_ARGUMENT] This index is not served by the documents API. Use the vectors API: POST /vectors/upsert and POST /query with pre-computed vectors, and /vectors/fetch, /vectors/update, /vectors/delete or /vectors/list. If the index is configured for integrated inference, use the records API to upsert and search text: POST /records/namespaces/{namespace}/upsert or /records/namespaces/{namespace}/search. To use the documents API, create an index with a document schema.
deleted kb-legacy | indexes now: ['kb-docs-byo', 'kb-docs']