| similarity='dot_product' produces unbounded raw inner produc | console | warning | python, langchain, warning, similarity |
| persisted store is corrupt: {len(missing)} {what} id(s) pres | validation | critical | python, persistence, corruption, consistency, json |
| module {__name__!r} has no attribute {name!r} | exception | error | python, attributeerror, module-api, typo |
| side-car key {key!r} at {_crumb_path(entry)} is {type(key)._ | validation | error | python, json, serialization, data-loss |
| persisted store is corrupt: duplicate document ids in the si | validation | error | |
| {path} was written and committed, but syncing its parent dir | console | warning | io, durability, fsync, warning |
| TurboQuantVectorStore does not support max-marginal-relevanc | exception | error | |
| persisted store is corrupt: {len(extraneous)} {what} id(s) p | validation | critical | persistence, data-corruption, validation |
| Both metadata value and filter value must be strings for the | validation | error | python, filters, type-mismatch |
| turbovec: warning: {message} | console | warning | rust, logging, stderr, diagnostics |
| {} {detail}. | validation | error | io, file-format, version-mismatch |
| invalid TQ+ shift at coord {i}: {v} (must be finite and |shi | validation | error | validation, calibration, numeric-range |
| filter operator {op!r} not supported by TurboQuantVectorStor | exception | error | python, filters, llama-index, not-implemented |
| invalid TQ+ scale at coord {i}: {v} (must be finite and >= { | validation | error | validation, calibration, numeric-range |
| the v7 file at {} no longer matches this index's last sync ( | validation | error | concurrency, stale-state, v7 |
| namespace must not contain path separators ('/' or '\\') or | validation | error | |
| truncated file | validation | error | io, truncated-file, unexpected-eof |
| Please provide a list of Documents. | validation | error | |
| {src}: the newest commit (generation {newest}) is incomplete | console | warning | durability, crash-recovery, v7, warning |
| duplicate ids in v7 file | validation | error | rust, id-map, persistence, duplicate-keys, corruption |
| ids[{pos}] is {id_!r} of type {type(id_).__name__}; ids must | validation | error | |
| persisted store is inconsistent with its index: a {what} in | validation | critical | python, persistence, corruption, consistency |
| {param} must be one of {list(_VALID_MODES)}, got {value!r} | validation | error | validation, configuration, enum |
| TurboQuantVectorDb only supports search_type=SearchType.vect | validation | error | |
| side-car value at {_crumb_path(entry)} is {obj!r}, which JSO | validation | error | python, json, serialization, nan, infinity |
| {e} | panic | error | rust, panic, vector-search, invalid-input |
| TurboQuantVectorStore requires a pre-computed query_embeddin | validation | error | python, llama-index, vector-store, missing-embedding |
| persisted store is corrupt: the handle watermark next_u64={i | validation | critical | python, persistence, corruption, handle-allocation |
| embedder returned {vectors.shape[0]} vectors for {n_texts} t | validation | error | |
| embedding dimension {vectors.shape[1]} does not match index | validation | error | |
| metadatas[{i}] must be a dict, got {type(meta).__name__} | validation | error | |
| TurboQuantVectorStore.get(text_id) cannot return the origina | exception | error | python, llama-index, not-implemented, quantization |
| {prefix} {version}; this turbovec accepts versions {list(com | validation | error | python, validation, schema, versioning, persistence |
| file too large for this platform | validation | error | io, platform-limit, file-size |
| documents have empty embeddings (dim 0); check the embedder | validation | error | |
| expected 2D embedding batch, got {vectors.ndim}D | validation | error | |
| persisted store at {folder} was saved with distance={recorde | validation | error | |
| persisted dimensions={state.get('dimensions')} does not matc | validation | error | |
| embedding dim {vectors.shape[1]} does not match store dim {e | validation | error | |
| Document {doc.id!r} has no embedding. TurboQuantDocumentStor | validation | error | |
| duplicate id in batch: {k!r} | validation | error | python, validation, duplicates, batch |
| ID '{doc.id}' already exists in the document store. | exception | error | |
| persisted store is corrupt: duplicate node handles in the si | validation | error | python, llama-index, persist, corruption, data-integrity |
| embedding dim {vectors.shape[1]} does not match index dim {s | validation | error | |
| persisted store is inconsistent with its index: side-car has | validation | critical | python, persistence, corruption, consistency |
| expected 2D embedding batch, got {vectors.ndim}D | validation | error | |
| haystack-ai is required to use turbovec.haystack. Install wi | exception | error | |
| Invalid filter syntax. See https://docs.haystack.deepset.ai/ | validation | error | |
| invalid input value at vector {vi}, coord {ci}: {v} (must be | panic | error | rust, panic, validation, vector-index, numeric |
| embedder returned a {qvec.ndim}D query embedding; expected a | validation | error | |
| query_embedding should be a non-empty list of floats. | validation | error | |
| agno is required to use turbovec.agno. Install with: pip ins | exception | error | dependency, import, installation |
| langchain-core is required to use turbovec.langchain. Instal | exception | error | |
| failed to embed {len(missing)} document(s): {ids} | validation | error | embedding, agno, validation |
| persisted store is corrupt: duplicate {what} handles in the | validation | error | python, persistence, corruption, data-integrity |
| missing one of {_STORE_FILENAME}/{_INDEX_FILENAME} under {fo | exception | error | |
| cannot sync a lazy index that has never seen an add or calib | validation | error | state-error, lazy-index, preconditions |
| embedder returned None instead of a query embedding | validation | error | |
| {} ids for {} rows | validation | error | rust, id-map, io-error, length-mismatch, data-integrity |
| node embedding dim {vectors.shape[1]} does not match index d | validation | error | python, dimension-mismatch, vector-store, embedding |
| llama-index-core is required to use turbovec.llama_index. In | exception | error | |
| {e} | panic | error | rust, panic, vector-search, invalid-input |
| embedder returned empty vectors (dim 0) for {n_texts} texts | validation | error | |
| No path to save to. Pass `folder_path=` here or set `path=` | validation | error | |
| filter must be a dict of metadata key/value pairs or a calla | validation | error | |
| TurboQuantVectorStore does not support query mode {query.mod | exception | error | python, llama-index, query-mode, not-implemented |
| namespace must be a non-empty name, got {namespace!r} | validation | error | |
| namespace must not contain ':' (a Windows drive-relative nam | validation | error | |
| query_embedding dim {qvec.shape[1]} does not match store dim | validation | error | |
| TurboQuantVectorDb not initialized — call create() before in | exception | error | lifecycle, state, agno |
| Both metadata value and filter value must be strings for the | validation | error | python, filters, type-mismatch, text-match |
| duplicate node_id {dup!r} appears multiple times in the inpu | validation | error | python, llama-index, vector-store, duplicate-id |
| nodes have empty embeddings (dim 0); check the embed model t | validation | error | python, embedding, empty-input, validation |
| expected 2D embedding batch, got {vectors.ndim}D | validation | error | |
| duplicate ids | validation | error | rust, id-map, duplicate-keys, io-error, validation |
| TurboQuantVectorDb has no index to save — call create() firs | exception | error | |
| Embedder.dimensions must be set. | validation | error | embedder, configuration, dimensions |
| TurboQuantVectorDb only supports search_type=SearchType.vect | validation | error | search-type, unsupported, configuration |
| texts, metadatas, and ids must all have the same length | validation | error | |
| fsspec filesystems are not supported yet; pass a local path. | exception | error | python, llama-index, persist, fsspec, unsupported-feature |
| TurboQuantVectorDb supports distance=Distance.cosine or dist | validation | error | distance-metric, unsupported, configuration |
| `embedder` is required; turbovec needs the embedder's `dimen | validation | error | constructor, validation, agno |
| expected 2D embedding batch, got {vectors.ndim}D | validation | error | python, numpy, shape-mismatch, embedding |
| filter condition {condition!r} not supported by TurboQuantVe | exception | error | python, llama-index, filters, not-implemented |
| bit_width must be 2, 3, or 4, got {bit_width} | validation | error | quantization, configuration, validation |