---
name: gdtest-long-names
description: >
  Test sidebar wrapping with long object names. Use when writing Python code that uses the gdtest_long_names package.
---

# gdtest_long_names

Test sidebar wrapping with long object names

## Installation

```bash
pip install gdtest-long-names
```

## API overview

### Document Stores

Backend storage systems for documents and embeddings.

- `BaseDocumentStore`: Abstract base class for document stores
- `DuckDBDocumentStore`: DuckDB-backed document store with vector search
- `PostgreSQLDocumentStore`: PostgreSQL-backed document store with pgvector

### DuckDBDocumentStore Methods

Methods for the DuckDBDocumentStore class

- `DuckDBDocumentStore.upsert_documents`
- `DuckDBDocumentStore.ingest_from_directory`
- `DuckDBDocumentStore.retrieve_by_similarity`
- `DuckDBDocumentStore.retrieve_by_bm25_score`
- `DuckDBDocumentStore.retrieve_hybrid_combination`
- `DuckDBDocumentStore.build_vector_index`
- `DuckDBDocumentStore.get_collection_size`

### Embedding Providers

Services for generating vector embeddings.

- `EmbeddingProvider`: Base class for embedding providers
- `OpenAIEmbeddingProvider`: OpenAI embedding provider using text-embedding models
- `CohereEmbeddingProvider`: Cohere embedding provider with input type support

### Chunker Strategies

Strategies for splitting documents into chunks.

- `BaseChunkerStrategy`: Abstract base class for document chunking strategies
- `MarkdownChunkerStrategy`: Markdown-aware chunking strategy that respects heading boundaries

### Data Types

Type definitions and result containers.

- `RetrievedDocumentChunk`: A document chunk returned from a retrieval query
- `DocumentMetadataConfig`: Configuration for document metadata extraction
- `EmbeddingVectorResult`: Result container for embedding vector operations

### Plain Text Names

Classes with long names containing no special characters.

- `documentstorewithvectorsearchcapabilities`: A store for documents supporting vector search
- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT`: All-uppercase embedding provider class
- `Chunkerstrategywithoverlapdetection`: Initial-cap chunker strategy class

### documentstorewithvectorsearchcapabilities Methods

Methods for the documentstorewithvectorsearchcapabilities class

- `documentstorewithvectorsearchcapabilities.insertdocumentswithembeddings`
- `documentstorewithvectorsearchcapabilities.searchbyvectorsimilarity`
- `documentstorewithvectorsearchcapabilities.rebuildvectorsearchindex`
- `documentstorewithvectorsearchcapabilities.deletedocumentsbyidentifier`
- `documentstorewithvectorsearchcapabilities.countdocumentsincollection`
- `documentstorewithvectorsearchcapabilities.exportcollectiontojsonlines`

### EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT Methods

Methods for the EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT class

- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT.GENERATEEMBEDDINGSFROMTEXTINPUT`
- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT.CALCULATETOKENCOUNTFORTEXTS`
- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT.RETRIEVEMODELCONFIGURATION`
- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT.VALIDATEINPUTTEXTLENGTHS`
- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT.EXPORTEMBEDDINGSTOFILE`
- `EMBEDDINGPROVIDERWITHBATCHPROCESSINGSUPPORT.RESETINTERNALBATCHCOUNTER`

### Chunkerstrategywithoverlapdetection Methods

Methods for the Chunkerstrategywithoverlapdetection class

- `Chunkerstrategywithoverlapdetection.splitcontentintochunks`
- `Chunkerstrategywithoverlapdetection.detectoverlapboundaries`
- `Chunkerstrategywithoverlapdetection.mergeundersizedfragments`
- `Chunkerstrategywithoverlapdetection.calculateoverlappercentage`
- `Chunkerstrategywithoverlapdetection.exportchunkswithoverlap`
- `Chunkerstrategywithoverlapdetection.resetinternalchunkcache`

## Resources

- [llms.txt](llms.txt) — Indexed API reference for LLMs
- [llms-full.txt](llms-full.txt) — Comprehensive documentation for LLMs