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Artificial intelligence · llms.txt file breakdown
Voyage AI Documentation organizes Voyage AI content, including Guides: GET STARTED, Guides: CAPABILITIES, Guides: GUIDES, Guides: DEPLOYMENT ON VPC and 3 additional sections.
The actual file
The saved llms.txt text, displayed as source. The file belongs to its publisher; the live endpoint may change.
Complete saved Markdown shown below.
# Voyage AI Documentation
> Voyage AI provides cutting-edge embedding models for retrieval-augmented generation (RAG).
## Guides: GET STARTED
- [Introduction](https://docs.voyageai.com/docs/introduction.md)
- [API Key and Python Client](https://docs.voyageai.com/docs/api-key-and-installation.md)
- [Quickstart Tutorial](https://docs.voyageai.com/docs/quickstart-tutorial.md)
## Guides: CAPABILITIES
- [Text Embeddings](https://docs.voyageai.com/docs/embeddings.md)
- [Contextualized Chunk Embeddings](https://docs.voyageai.com/docs/contextualized-chunk-embeddings.md)
- [Multimodal Embeddings](https://docs.voyageai.com/docs/multimodal-embeddings.md)
- [Rerankers](https://docs.voyageai.com/docs/reranker.md)
## Guides: GUIDES
- [Tokenization](https://docs.voyageai.com/docs/tokenization.md)
- [Flexible Dimensions and Quantization](https://docs.voyageai.com/docs/flexible-dimensions-and-quantization.md)
- [Batch Inference](https://docs.voyageai.com/docs/batch-inference.md)
- [Error Codes](https://docs.voyageai.com/docs/error-codes.md)
- [Rate Limits](https://docs.voyageai.com/docs/rate-limits.md)
- [Pricing](https://docs.voyageai.com/docs/pricing.md)
- [Organizations and Projects](https://docs.voyageai.com/docs/organizations-and-projects.md)
- [Service Level Objectives](https://docs.voyageai.com/docs/service-level-objectives.md)
## Guides: DEPLOYMENT ON VPC
- AWS Marketplace Model Package
- [MongoDB Voyage AI Models in AWS](https://docs.voyageai.com/docs/aws-marketplace-mongodb-voyage.md): Deploy MongoDB Voyage AI models using AWS Marketplace
- [Voyage AI Models in AWS](https://docs.voyageai.com/docs/aws-marketplace-voyage.md): Deploy Voyage AI models using AWS Marketplace
- Azure Marketplace Managed Application
- [MongoDB Voyage AI Models in Azure](https://docs.voyageai.com/docs/azure-marketplace-mongodb-voyage.md): Deploy MongoDB Voyage AI models using Azure Marketplace
- [Voyage AI Models in Azure](https://docs.voyageai.com/docs/azure-marketplace-voyage.md): Deploy Voyage AI models using Azure Marketplace
## Guides: Community
- [Integrations](https://docs.voyageai.com/docs/integrations-and-other-libraries.md)
- [Community SDKs](https://docs.voyageai.com/docs/community-sdks.md)
## Guides: HELP
- [FAQ](https://docs.voyageai.com/docs/faq.md)
- [Contact Email](https://docs.voyageai.com/docs/contact-email.md)
- [Discord](https://docs.voyageai.com/docs/discord.md)
## API Reference: Voyage API
- Inference
- [Text embedding models](https://docs.voyageai.com/reference/embeddings-api.md): The Voyage text embedding endpoint receives as input a string (or a list of strings) and other arguments such as the preferred model name, and returns a response containing a list of embeddings.
- [Contextualized chunk embedding models](https://docs.voyageai.com/reference/contextualized-embeddings-api.md): The Voyage contextualized chunk embedding endpoint accepts document chunks—in addition to queries and full documents—and returns a response containing contextualized chunk vector embeddings. These…
- [Multimodal embedding models](https://docs.voyageai.com/reference/multimodal-embeddings-api.md): The Voyage multimodal embedding endpoint returns vector representations for a given list of multimodal inputs consisting of text, images, or an interleaving of both modalities. <blockquote…
- [Rerankers](https://docs.voyageai.com/reference/reranker-api.md): Voyage reranker endpoint receives as input a query, a list of documents, and other arguments such as the model name, and returns a response containing the reranking results.
- Files
- [Upload file](https://docs.voyageai.com/reference/upload-file.md): Upload a file that can be used with the Batch API. The Batch API only supports `.jsonl` files with a specific required format.
- [List files](https://docs.voyageai.com/reference/list-files.md): Returns a list of files that can be optionally limited to a set of results (e.g., `limit`, `after`), ordered (e.g., `order`), and filtered (e.g., `purpose`).
- [Retrieve file](https://docs.voyageai.com/reference/retrieve-file.md): Returns information about a specific file.
- [Delete file](https://docs.voyageai.com/reference/delete-file.md): Delete a file.
- [Retrieve file content](https://docs.voyageai.com/reference/retrieve-file-content.md): Returns the contents of the specified file.
- [Bulk delete files](https://docs.voyageai.com/reference/bulk-delete-files.md): Delete one or more files at once.
- Batch
- [Create batch](https://docs.voyageai.com/reference/create-batch.md): Creates and executes a batch.
- [List batches](https://docs.voyageai.com/reference/list-batches.md): List organization batches.
- [Retrieve batch](https://docs.voyageai.com/reference/retrieve-batch.md): Returns a batch.
- [Cancel batch](https://docs.voyageai.com/reference/cancel-batch.md): Cancels a batch that is currently in progress. You can only cancel batches that are in `validating` or `in_progress` status. The batch status will change to `cancelling` for up to 10 minutes before…
Measured from the saved file
Size measures the captured UTF-8 text, not compressed transfer size. Tokens are counted with a named tokenizer; other models can count differently. Neither measure establishes context compatibility or answer quality.
Voyage AI provides cutting-edge embedding models for retrieval-augmented generation (RAG).
Context architecture
7 H2 sections organize 38 parsed Markdown links. 38 links point to .md or .markdown paths; 0 link occurrences use another hostname. Linked destinations have not been recursively validated.
| H2 section | Links | UTF-8 bytes | Tokens |
|---|---|---|---|
| Guides: GET STARTEDLine 5 | 3 | 235 | 63 |
| Guides: CAPABILITIESLine 10 | 4 | 311 | 95 |
| Guides: GUIDESLine 16 | 8 | 613 | 166 |
| Guides: DEPLOYMENT ON VPCLine 26 | 4 | 673 | 164 |
| Guides: CommunityLine 34 | 2 | 155 | 44 |
| Guides: HELPLine 38 | 3 | 170 | 52 |
| API Reference: Voyage APILine 43 | 14 | 2615 | 612 |
Link counts exclude parsed fenced and inline code and resolve relative destinations against the final endpoint. Section sizes cover the text below each H2 until the next H2.
Embedded material
Embedded example text and links to further documentation are counted separately. A code block does not establish that a sample runs or that an authentication flow succeeds.
Publisher prioritization
No H2 section named “Optional” was detected in this file.
The community proposal uses Optional by convention for secondary links that can be skipped for a shorter context. This label does not establish that everything outside it is critical, or that the material inside it is deprecated.
Machine-readable routes
No MCP or Model Context Protocol term was detected in the captured file. 0 links have MCP-related labels or paths. 0 fenced lines match mcpServers, mcp_servers or an mcp add command.
These are text and link observations. No MCP server connection, authentication or tool call was tested.
Index and bundle
Not found at checked URLs
A verified text response establishes a companion at the checked URL. It does not prove the bundle contains all product documentation, that generation is automated, or that it fits an assistant’s context window.
Change evidence
This capture establishes a baseline. Update frequency cannot be determined from one observation.
File changes can reveal documentation edits or navigation changes. They do not by themselves measure product release velocity, accuracy, agent adoption or AI visibility.
e08f4e2a9ce0562deaaa7f2bc7033f2490adedcd27981d02e971de049b40f9f2Counts use a deterministic parser, not a spec-compliance grade. Unusual Markdown and indented code can fall outside its recognized patterns. See the llms.txt proposal and tokenizer implementation.