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[Docs](https://cherrry.com/docs) | [Blog](https://cherrry.com/blog)\n\n## Installation + API keys\n\n### npm package\n\nInstall the package from npm with your favorite package manager\n\n```js\nnpm install @cherrry-ai/cherrry-js\n```\n\n### API Keys\n\nFrom https://cherrry.com/dashboard/api to get your API Keys\n\n#### Private Key\n\nPrivate keys start with `ch_prv`\n\n**keep it secret and never use it client-side**. It has service role privilages: it can read + write data.\n\n#### Public Key\n\nPublic keys start with `ch_pub`\n\nThey're intended to be use client-side and have read-only privilages.\n\n### Initalize\n\n```js\nconst CherrryClient = require(\"@cherrry-ai/cherrry-js\");\n```\n\nor\n\n```js\nimport CherrryClient from \"@cherrry-ai/cherrry-js\";\n```\n\ninitialize the client\n\n```js\nconst client = new CherrryClient(api_key);\n```\n\n## Concepts\n\n### Table\n\nA table is a collection of documents.\n\n### Document\n\nA document is respresented as a JSON object literal with three fields: `text`, `image`, and `metadata`.\nThese fields are also JSON object literals, where the keys can be strings with any contents, and their values are also strings.\n\n`text` and `image` are semantically searchable each by their type respectively. Each document must have either a `text` or `image` field. It can also have both fields.\n`metadata` is used to store additional information and for filtering (feature in progress), it is an optional field.\n\n## Basic Functions\n\n### Create Table\n\n```js\nvar { data, error } = await client.create_table(\"example_table\");\n```\n\n### Insert a Doc\n\nDocuments must be of the following form\n\n```js\n{\n    \"text\": {\n        \"a name for your text\": \"your desired text in a string\"\n    },\n    \"image\": {\n        \"a name for your image\": \"a url to your downloadable image\"\n    },\n    \"metadata\": {\n        \"key\": \"value\"\n    }\n}\n```\n\nfor example:\n\n```js\nvar { data, error } = await client.from(\"recipes\").insert({\n    text: {\n        name: \"Octopus Cherry Pie\"\n    },\n    image: {\n        preview: \"https://i.imgur.com/lFC8p0L.jpeg\"\n    },\n    data: {\n        author_name: \"Davy Jones\",\n        author_email: \"octo@pus.com\"\n    }\n});\n```\n\n### Search\n\n```js\nvar { data, error } = await client\n    .from(\"blogs\")\n    .search({ prompt: \"sea creature desert\", size: 1, search_type: \"image\" });\n```\n\n### Get Doc by ID\n\nThe ID of documents are returned in the responses of `/search` or `/doc`\n\n```js\nvar { data, error } = await client.from(\"blogs\").doc(\"1234\");\n```\n\n### Delete a Doc\n\n```js\nvar { success, error } = await client.from(\"blogs\").delete(\"1234\");\n```\n","readmeFilename":"README.md","keywords":["cherrry","cherry","search","api","ai","ml","neural","semantic","vector","engine"]}