> For the complete documentation index, see [llms.txt](https://api.docs.blockbrain.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://api.docs.blockbrain.ai/getting-started/knowledge-management/create-a-database.md).
# Create a Database
[Document Databases](/concepts/knowledge-base.md) store and serve the source materials that knowledge workflows rely on: files, email contents, and structured documents. In this stack, documents are linked to conversations (data rooms) and Insights via short-lived references, enabling retrieval, processing, and indexing while preserving provenance and access controls.
**Each database can have:**
* **Folders**: Can be used for organization by project, topic, or knowledge domain. Fine-granular access can be provided to specific users.
* **Documents**: Main entities of different types like PDFs, Word/Office docs, emails, spreadsheets, structured JSON/XML, images that will be indexed, chunked and vectorized for RAG.
* Documents can be uploaded manually, by API or imported through the provided web crawler.
## Create a new Knowledgebase / Database
## POST /knowledge\_base
> Create Knowledgebase
```json
{"openapi":"3.1.0","info":{"title":"Blockbrain Knowledge Bots","version":"0.2.6"},"security":[{"HTTPBearer":[]}],"components":{"securitySchemes":{"HTTPBearer":{"type":"http","scheme":"bearer"}},"schemas":{"KnowledgeBaseCreate":{"properties":{"name":{"type":"string","title":"Name"},"description":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Description"},"is_public":{"type":"boolean","title":"Is Public","default":false},"embeddingModel":{"$ref":"#/components/schemas/EmbeddingModel","default":"azure-ada-002"},"chunkSize":{"anyOf":[{"type":"integer","maximum":30000,"minimum":0},{"type":"null"}],"title":"Chunksize","default":1200},"chunkOverlap":{"anyOf":[{"type":"integer","maximum":12000,"minimum":0},{"type":"null"}],"title":"Chunkoverlap","default":200},"markedLanguages":{"items":{"type":"string"},"type":"array","maxItems":3,"title":"Markedlanguages","default":[]},"enableExtractTable":{"anyOf":[{"type":"boolean"},{"type":"null"}],"title":"Enableextracttable","default":false},"enableExtractImage":{"anyOf":[{"type":"boolean"},{"type":"null"}],"title":"Enableextractimage","default":true},"enableConvertImage":{"anyOf":[{"type":"boolean"},{"type":"null"}],"title":"Enableconvertimage","default":false},"useContextualChunking":{"anyOf":[{"type":"boolean"},{"type":"null"}],"title":"Usecontextualchunking","default":false},"enableMultiplePdfPagesPerChunk":{"type":"boolean","title":"Enablemultiplepdfpagesperchunk","default":false}},"type":"object","required":["name","description"],"title":"KnowledgeBaseCreate"},"EmbeddingModel":{"type":"string","enum":["azure-ada-002","azure-emb-3-large","openai-ada-002","openai-emb-3-small","openai-emb-3-large","sagemaker-bge","vertex-ai-embedding-english-text-4","vertex-ai-embedding-multilingual-text-2","gemini-embedding-001"],"title":"EmbeddingModel"},"CommonResponseDTO":{"properties":{"code":{"anyOf":[{"type":"integer"},{"type":"null"}],"title":"Code"},"key":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Key"},"body":{"anyOf":[{"type":"string"},{"type":"null"}],"title":"Body"}},"type":"object","title":"CommonResponseDTO"},"HTTPValidationError":{"properties":{"detail":{"items":{"$ref":"#/components/schemas/ValidationError"},"type":"array","title":"Detail"}},"type":"object","title":"HTTPValidationError"},"ValidationError":{"properties":{"loc":{"items":{"anyOf":[{"type":"string"},{"type":"integer"}]},"type":"array","title":"Location"},"msg":{"type":"string","title":"Message"},"type":{"type":"string","title":"Error Type"}},"type":"object","required":["loc","msg","type"],"title":"ValidationError"}}},"paths":{"/knowledge_base":{"post":{"tags":["knowledge_base"],"summary":"Create Knowledgebase","operationId":"create_knowledgebase_knowledge_base_post","requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/KnowledgeBaseCreate"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/CommonResponseDTO"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}}}}
```
The response contains a `body` property that contains the `_id` of the created Knowledgebase. This id will can be used for altering the DB, creating folders and uploading documents.
## Next Step
Now that you have created a Knowledgebase, you can [Create Folders](/getting-started/knowledge-management/create-a-database/create-folders.md) and [Upload Documents to DBs](/getting-started/knowledge-management/upload-documents-to-dbs.md).
## Supported File-Types
Every standard file-type is already being supported by our indexing and vectorization pipelines. Still, we are constantly adding more compatibility.
---
# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://api.docs.blockbrain.ai/getting-started/knowledge-management/create-a-database.md?ask=
```
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