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Copy file name to clipboardExpand all lines: learn/chat/conversational_search.mdx
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Follow the [chat completions tutorial](/learn/chat/getting_started_with_chat) for information on how to implement a RAG with Meilisearch.
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<Warning>
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Conversational search is still in early development. Conversational agents may occasionally hallucinate innacurate and misleading information, so it is important to closely monitor it in production environments.
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Conversational search is still in early development. Conversational agents may occasionally hallucinate inaccurate and misleading information, so it is important to closely monitor it in production environments.
Copy file name to clipboardExpand all lines: learn/chat/getting_started_with_chat.mdx
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```
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<Warning>
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Conversational search is still in early development. Conversational agents may occasionally hallucinate innacurate and misleading information, so it is important to closely monitor it in production environments.
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Conversational search is still in early development. Conversational agents may occasionally hallucinate inaccurate and misleading information, so it is important to closely monitor it in production environments.
Copy file name to clipboardExpand all lines: reference/api/chats.mdx
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</Note>
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<Warning>
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Conversational search is still in early development. Conversational agents may occasionally hallucinate innacurate and misleading information, so it is important to closely monitor it in production environments.
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Conversational search is still in early development. Conversational agents may occasionally hallucinate inaccurate and misleading information, so it is important to closely monitor it in production environments.
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</Warning>
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## Authorization
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When implementing conversational search, use an API key with access to both the `search` and `chatCompletions` actions such as the default chat API key. You may also use tenant tokens instead of an API key, provided you generate the tokens with access to the required actions.
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When implementing conversational search, use an API key with access to both the `search` and `chatCompletions` actions such as the default chat API key. You may also use tenant tokens instead of an API key, provided you generate the tokens with a key that has access to the required actions.
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Chat queries only search indexes its API key can access. The default chat API key has access to all indexes. To limit chat access to specific indexes, you must either create a new key, or [generate a tenant token](/learn/security/generate_tenant_token_sdk) from the default chat API key.
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Chat queries only search the indexes its API key can access. The default chat API key has access to all indexes. To limit access, you must either create a new key, or [generate a tenant token](/learn/security/generate_tenant_token_sdk) from the default chat API key.
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## Chat workspace object
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## Chat workspaces
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Workspaces are groups of chat settings tailored towards specific use cases. You must configure at least on workspace to use chat completions.
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### Chat workspace object
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```json
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{
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|**`workspace_uid`** * | String |`uid` of the requested index |
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### Example
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```sh
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curl \
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-X GET 'MEILISEARCH_URL/chats/WORKSPACE_UID'
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```
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#### Response: `200 Ok`
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```json
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{
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"uid": "WORKSPACE_UID"
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}
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```
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## Chat workspace settings
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### Chat workspace settings object
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```json
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-`prompts.QParam`: Description of expected user input and the desired output. Example: "Users will ask about Meilisearch. Provide short and direct keyword-style queries."
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-`prompts.IndexUidParam`: Instructions describing each index the agent has access to and how to use them. Example: "If user asks about code or API or parameters, use the index called `documentation`."
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### List chat workspaces
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<RouteHighlightermethod="GET"path="/chats" />
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List all chat workspaces. Results can be paginated by using the `offset` and `limit` query parameters.
Create a chat completion using Meilisearch's OpenAI-compatible interface. The endpoint searches relevant indexes and generates responses based on the retrieved content.
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Create a chat completions stream using Meilisearch's OpenAI-compatible interface. This endpoint searches relevant indexes and generates responses based on the retrieved content.
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