copy edits

Author: guimachiavelli

learn/chat/conversational_search.mdx

@@ -1,23 +1,29 @@
 ---
 title: What is conversational search?
-description: Conversational search is an AI-powered feature that allows users to ask questions in everyday language and receive answers based on the information in Meilisearch's indexes
+description: Conversational search allows people to make search queries using natural languages.
 ---
 
+Conversational search is an AI-powered search feature that allows users to ask questions in everyday language and receive answers based on the information in Meilisearch's indexes.
+
 ## When to use conversational vs traditional search
 
 Use conversational search when:
 
 - Users need easy-to-read answers to specific questions
-- You are handling informational-dense content, such as software documentation and knowledge bases
+- You are handling informational-dense content, such as knowledge bases
 - Natural language interaction improves user experience
 
 Use traditional search when:
 
 - Users need to browse multiple options, such as an ecommerce website
-- Approximative answers are not acceptable
+- Approximate answers are not acceptable
 - Your users need very quick responses
 
-## How conversational search usage differs from traditional search
+<Warning>
+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.
+</Warning>
+
+## Conversational search user workflow
 
 ### Traditional search workflow
 
@@ -46,10 +52,6 @@ Meilisearch's chat completions API consolidates RAG creation into a single proce
 
 Follow the [chat completions tutorial](/learn/chat/getting_started_with_chat) for information on how to implement a RAG with Meilisearch.
 
-<Warning>
-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.
-</Warning>
-
 ### Model Context Protocol (MCP)
 
 An alternative method is using a Model Context Protocol (MCP) server. MCPs are designed for broader uses that go beyond answering questions, but can be useful in contexts where having up-to-date data is more important than comprehensive answers.

learn/chat/getting_started_with_chat.mdx

@@ -3,7 +3,7 @@ title: Getting started with conversational search
 description: This article walks you through implementing Meilisearch's chat completions feature to create conversational search experiences in your application.
 ---
 
-To successfully implement a conversational search interface you must follow three steps: configure indexes for chat usage, create chat workspaces targeting different use-cases, and building a chat interface.
+To successfully implement a conversational search interface you must follow three steps: configure indexes for chat usage, create a chat workspaces, and build a chat interface.
 
 ## Prerequisites
 
@@ -21,7 +21,7 @@ First, enable the chat completions experimental feature:
 
 ```bash
 curl \
-  -X PATCH 'http://localhost:7700/experimental-features/' \
+  -X PATCH 'MEILISEARCH_URL/experimental-features/' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -38,19 +38,19 @@ Conversational search is still in early development. Conversational agents may o
 When Meilisearch runs with a master key on an instance created after v1.15.1, it automatically generates a "Default Chat API Key" with `chatCompletions` and `search` permissions on all indexes. Check if you have the key using:
 
 ```bash
-curl http://localhost:7700/keys \
+curl MEILISEARCH_URL/keys \
   -H "Authorization: Bearer MEILISEARCH_KEY"
 ```
 
-Look for the key with the description "Default Chat API Key" Use this key when querying the `/chats` endpoint.
+Look for the key with the description "Default Chat API Key".
 
 #### Troubleshooting: Missing default chat API key
 
 If your instance does not have a Default Chat API Key, create one manually:
 
 ```bash
 curl \
-  -X POST 'http://localhost:7700/keys' \
+  -X POST 'MEILISEARCH_URL/keys' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -68,7 +68,7 @@ After activating the `/chats` route and obtaining an API key with chat permissio
 
 ```bash
 curl \
-  -X PATCH 'http://localhost:7700/indexes/INDEX_NAME/settings' \
+  -X PATCH 'MEILISEARCH_URL/indexes/INDEX_NAME/settings' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -81,13 +81,14 @@ curl \
 ```
 
 - `description` gives the initial context of the conversation to the LLM. A good description improves relevance of the chat's answers
-- `documentTemplate` defines the document data Meilisearch sends to the AI provider. Consult the best [document template best practices](/learn/ai_powered_search/document_template_best_practices) article for more guidance
+- `documentTemplate` defines the document data Meilisearch sends to the AI provider. This template outputs all searchable fields in your documents, which may not be ideal if your documents have many fields. Consult the best [document template best practices](/learn/ai_powered_search/document_template_best_practices) article for more guidance
+- `documentTemplateMaxBytes` establishes a size limit for the document templates. Documents bigger than 400 bytes are truncated to ensure a good balance between speed and relevancy
 
 ## Configure a chat completions workspace
 
 The next step is to create a workspace. Chat completion workspaces are isolated configurations targeting different use cases. Each workspace can:
 
-- Use different embedding providers (openAi, azureOpenAi, mistral, gemini, vLlm)
+- Use different embedding providers (OpenAI, Azure OpenAI, Mistral, Gemini, vLLM)
 - Establish separate conversation contexts via baseline prompts
 - Access a specific set of indexes
 
@@ -99,7 +100,7 @@ Create a workspace setting your LLM provider as its `source`:
 
 ```bash OpenAI
 curl \
-  -X PATCH 'http://localhost:7700/chats/WORKSPACE_NAME/settings' \
+  -X PATCH 'MEILISEARCH_URL/chats/WORKSPACE_NAME/settings' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -114,7 +115,7 @@ curl \
 
 ```bash Azure OpenAI
 curl \
-  -X PATCH 'http://localhost:7700/chats/WORKSPACE_NAME/settings' \
+  -X PATCH 'MEILISEARCH_URL/chats/WORKSPACE_NAME/settings' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -129,7 +130,7 @@ curl \
 
 ```bash Mistral
 curl \
-  -X PATCH 'http://localhost:7700/chats/WORKSPACE_NAME/settings' \
+  -X PATCH 'MEILISEARCH_URL/chats/WORKSPACE_NAME/settings' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -143,7 +144,7 @@ curl \
 
 ```bash Gemini
 curl \
-  -X PATCH 'http://localhost:7700/chats/WORKSPACE_NAME/settings' \
+  -X PATCH 'MEILISEARCH_URL/chats/WORKSPACE_NAME/settings' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -157,7 +158,7 @@ curl \
 
 ```bash vLLM
 curl \
-  -X PATCH 'http://localhost:7700/chats/WORKSPACE_NAME/settings' \
+  -X PATCH 'MEILISEARCH_URL/chats/WORKSPACE_NAME/settings' \
   -H 'Authorization: Bearer MEILISEARCH_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -173,17 +174,17 @@ curl \
 
 Which fields are mandatory will depend on your chosen provider `source`. In most cases, you will have to provide an `apiKey` to access the provider.
 
-`baseUrl` indicates the URL Meilisearch queries when users submit questions to your chat interface.
+`baseUrl` indicates the URL Meilisearch queries when users submit questions to your chat interface. This is only mandatory for Azure OpenAI and vLLM sources.
 
-`prompts.system` gives the conversational search bot the baseline context of your users and their questions. The `prompts` object accepts a few other fields that provide more information to improve how the agent uses the information it finds via Meilisearch. In real-life scenarios filling these fields would improve the quality of conversational search results.
+`prompts.system` gives the conversational search bot the baseline context of your users and their questions. [The `prompts` object accepts a few other fields](/reference/api/chats#prompts) that provide more information to improve how the agent uses the information it finds via Meilisearch. In real-life scenarios filling these fields would improve the quality of conversational search results.
 
 ## Send your first chat completions request
 
 You have finished configuring your conversational search agent. To test everything is working as expected, send a streaming `curl` query to the chat completions API route:
 
 ```bash
 curl -N \
-  -X POST 'http://localhost:7700/chats/WORKSPACE_NAME/chat/completions' \
+  -X POST 'MEILISEARCH_URL/chats/WORKSPACE_NAME/chat/completions' \
   -H 'Authorization: Bearer MEILISEARCH_API_KEY' \
   -H 'Content-Type: application/json' \
   --data-binary '{
@@ -243,7 +244,7 @@ Integrating Meiliearch and the OpenAI SDK with JavaScript would look lik this:
 import OpenAI from 'openai';
 
 const client = new OpenAI({
-  baseURL: 'http://localhost:7700/chats/WORKSPACE_NAME',
+  baseURL: 'MEILISEARCH_URL/chats/WORKSPACE_NAME',
   apiKey: 'PROVIDER_API_KEY',
 });
 
@@ -287,7 +288,7 @@ Take particular note of the last lines, which output the streamed responses to t
 
 - Use either the master key or the "Default Chat API Key"
 - Don't use search or admin API keys for chat endpoints
-- Find your chat key: `curl http://localhost:7700/keys -H "Authorization: Bearer MEILISEARCH_KEY"`
+- Find your chat key: `curl MEILISEARCH_URL/keys -H "Authorization: Bearer MEILISEARCH_KEY"`
 
 #### "Socket connection closed unexpectedly"
 
@@ -298,14 +299,14 @@ Take particular note of the last lines, which output the streamed responses to t
 1. Check workspace configuration:
 
    ```bash
-   curl http://localhost:7700/chats/WORKSPACE_NAME/settings \
+   curl MEILISEARCH_URL/chats/WORKSPACE_NAME/settings \
      -H "Authorization: Bearer MEILISEARCH_KEY"
    ```
 
 2. Update with valid API key:
 
    ```bash
-   curl -X PATCH http://localhost:7700/chats/WORKSPACE_NAME/settings \
+   curl -X PATCH MEILISEARCH_URL/chats/WORKSPACE_NAME/settings \
      -H "Authorization: Bearer MEILISEARCH_KEY" \
      -H "Content-Type: application/json" \
      -d '{"apiKey": "your-valid-api-key"}'