> For the complete documentation index, see [llms.txt](https://docs.delphi.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.delphi.ai/advanced/actions/api-immortal-only/search.md). # Search Search for relevant data from your clone's digital mind. Supports semantic search, keyword/phrase matching, and optional scoping to specific content sources. Endpoint: `POST /v3/search/query` Request body: | Field | Type | Required | Description | | ------------ | --------- | -------- | ------------------------------------------------------------------------ | | `query` | string\[] | Yes | Semantic search strings (e.g. questions or topics) | | `keywords` | string\[] | No | Keyword or phrase strings for exact-match (BM25) boosting | | `content` | string\[] | No | Content descriptions to scope results to matching sources | | `contentIds` | string\[] | No | Direct content IDs to filter results to specific sources | | `limit` | number | No | Max chunks to return (1–50, default 10) | | `tag` | string | No | Access tier tag (e.g. `PUBLIC`, `PREMIUM`). Defaults to broadest access. | > **How search works:** `query` strings are used for semantic (meaning-based) search. `keywords` are routed through hybrid search for better exact-phrase matching via BM25. When both are provided, results are merged and deduplicated, keeping the highest-scoring passages. > **Content scoping:** Use `content` to describe the sources you want to search within (e.g. `["Series A fundraising podcast"]`). The API resolves these descriptions to matching content and restricts the chunk search to those sources. Alternatively, pass `contentIds` directly if you already know the content IDs. Example request: ```bash curl -X POST https://api.delphi.ai/v3/search/query \ -H "Content-Type: application/json" \ -H "x-api-key: YOUR_API_KEY" \ -d '{ "query": ["What is your advice on building a startup?"], "keywords": ["fundraising", "Series A"], "limit": 5 }' ``` Example response: ```json { "chunks": [ { "text": "When it comes to fundraising, the most important thing is to have a clear vision and a solid team. Investors want to see that you've thought deeply about the problem...", "sources": [ { "contentId": "c1a2b3c4-d5e6-7890-abcd-ef1234567890", "title": "Startup Fundraising Masterclass" } ], "createdTime": "2025-06-15T10:30:00.000Z", "editedTime": "2025-06-15T10:30:00.000Z" }, { "text": "For a Series A, you typically need to show strong product-market fit, a growing user base, and a path to revenue...", "sources": [ { "contentId": "c1a2b3c4-d5e6-7890-abcd-ef1234567890", "title": "Startup Fundraising Masterclass" } ], "createdTime": "2025-06-10T08:00:00.000Z", "editedTime": "2025-06-10T08:00:00.000Z" } ], "content": [ { "contentId": "c1a2b3c4-d5e6-7890-abcd-ef1234567890", "title": "Startup Fundraising Masterclass", "contentType": "podcast", "summary": "A deep dive into fundraising strategies for early-stage startups.", "metaData": {}, "createdTime": "2025-05-01T00:00:00.000Z", "editedTime": "2025-05-01T00:00:00.000Z" } ] } ``` Response fields: | Field | Type | Description | | ------------------------------ | --------- | ----------------------------------------------------------------- | | `chunks` | object\[] | Matching passages from the knowledge base | | `chunks[].text` | string | The passage text | | `chunks[].sources` | object\[] | Content sources this passage belongs to | | `chunks[].sources[].contentId` | string | Unique ID of the content source | | `chunks[].sources[].title` | string | Title of the content source | | `chunks[].createdTime` | string | When the passage was created | | `chunks[].editedTime` | string | When the passage was last updated | | `content` | object\[] | Deduplicated list of all content sources referenced by the chunks | > The `content` array includes full metadata for every content source that appears in the chunk results. Use this to display source cards, links, or attribution without making additional API calls. #### Example: scoped search Search only within specific content by providing descriptions: ```bash curl -X POST https://api.delphi.ai/v3/search/query \ -H "Content-Type: application/json" \ -H "x-api-key: YOUR_API_KEY" \ -d '{ "query": ["What do you think about AI?"], "content": ["podcast episode about artificial intelligence"], "limit": 3 }' ``` Or filter by known content IDs: ```bash curl -X POST https://api.delphi.ai/v3/search/query \ -H "Content-Type: application/json" \ -H "x-api-key: YOUR_API_KEY" \ -d '{ "query": ["What do you think about AI?"], "contentIds": ["c1a2b3c4-d5e6-7890-abcd-ef1234567890"], "limit": 3 }' ``` ### Search content sources Search for content sources (documents, articles, podcasts, etc.) in the knowledge base by title or description. Use this to discover what content is available before performing a chunk search. Endpoint: `POST /v3/search/content` Request body: | Field | Type | Required | Description | | ------- | --------- | -------- | ------------------------------------------------------------------------ | | `query` | string\[] | Yes | Content search strings (titles, descriptions, topics) | | `tag` | string | No | Access tier tag (e.g. `PUBLIC`, `PREMIUM`). Defaults to broadest access. | Example request: ```bash curl -X POST https://api.delphi.ai/v3/search/content \ -H "Content-Type: application/json" \ -H "x-api-key: YOUR_API_KEY" \ -d '{ "query": ["fundraising", "startup advice"] }' ``` Example response: ```json { "content": [ { "contentId": "c1a2b3c4-d5e6-7890-abcd-ef1234567890", "title": "Startup Fundraising Masterclass", "contentType": "podcast", "summary": "A deep dive into fundraising strategies for early-stage startups.", "metaData": {}, "createdTime": "2025-05-01T00:00:00.000Z", "editedTime": "2025-05-01T00:00:00.000Z" }, { "contentId": "d2b3c4d5-e6f7-8901-bcde-f12345678901", "title": "My Top 10 Startup Lessons", "contentType": "article", "summary": "Key lessons learned from building and scaling three companies.", "metaData": {}, "createdTime": "2025-04-15T00:00:00.000Z", "editedTime": "2025-04-15T00:00:00.000Z" } ] } ``` Content item fields: | Field | Type | Description | | ------------- | ------ | ----------------------------------------------------------- | | `contentId` | string | Unique identifier for the content source | | `title` | string | Title of the content | | `contentType` | string | Type of content (e.g. `podcast`, `article`, `pdf`, `video`) | | `summary` | string | Brief summary of the content (may be null) | | `metaData` | object | Additional metadata (varies by content type) | | `createdTime` | string | When the content was added | | `editedTime` | string | When the content was last updated | > Use content search to build a content catalog or let users browse available sources before diving into specific passages with `/v3/search/query`. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.delphi.ai/advanced/actions/api-immortal-only/search.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.