> ## Documentation Index
> Fetch the complete documentation index at: https://www.algolia.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Compact Context

> Summarize the older part of a conversation into a single user message via the caller's LLM.

**Required ACL:** `search`

Everything except the trailing `keepLastMessages` messages is summarized; the summary is
returned as a user-role message followed by the kept tail verbatim. Your provider runs the
summary, so the provider adds the cost to your account.

A conversation too large for the summarizer's context window is split into chunks that each fit,
summarized concurrently, then merged in a reduce pass - so payload size alone does not fail the
request. When the conversation still cannot be summarized (it needs more chunks than the server
allows, or the chunk summaries will not converge), the response is a `400`, not a `500`.

Two optional controls shape the output. `instructions` adds caller guidance inside the
server-owned prompt frame, so it steers the summary without the model echoing the wording back.
`targetTokensEstimate` sets a desired summary size, translated into word-count guidance.

The `compaction` block reports what happened: `compacted` is `false` when the payload passed
through untouched (nothing older than the kept tail), alongside chunk/pass counts and the
summarizer's own token usage.

## Usage

```cs C# theme={"system"}
// Initialize the client
var client = new AgentStudioClient(
  new AgentStudioConfig("ALGOLIA_APPLICATION_ID", "ALGOLIA_API_KEY")
);

// Call the API
var response = await client.CompactContextAsync(
  new ContextCompactRequest
  {
    ProviderID = "c2905529-b933-4b69-87ec-75f9829d5f59",
    Model = "gpt-4o-mini",
    Messages = new MessagesUnion(
      new List<MessageV4>
      {
        new MessageV4(new UserMessageV4 { Role = "user", Content = "Hello, how are you?" }),
      }
    ),
  }
);

// print the response
Console.WriteLine(response);
```

```dart Dart theme={"system"}
// Initialize the client
final client = AgentStudioClient(
    appId: 'ALGOLIA_APPLICATION_ID', apiKey: 'ALGOLIA_API_KEY');

// Call the API
final response = await client.compactContext(
  contextCompactRequest: ContextCompactRequest(
    providerID: "c2905529-b933-4b69-87ec-75f9829d5f59",
    model: "gpt-4o-mini",
    messages: [
      UserMessageV4(
        role: "user",
        content: "Hello, how are you?",
      ),
    ],
  ),
);

// print the response
print(response);
```

```go Go theme={"system"}
// Initialize the client
client, err := agentStudio.NewClient("ALGOLIA_APPLICATION_ID", "ALGOLIA_API_KEY")
if err != nil {
  // The client can fail to initialize if you pass an invalid parameter.
  panic(err)
}

// Call the API
response, err := client.CompactContext(client.NewApiCompactContextRequest(
  agentStudio.NewEmptyContextCompactRequest().
    SetProviderID("c2905529-b933-4b69-87ec-75f9829d5f59").
    SetModel("gpt-4o-mini").
    SetMessages(agentStudio.ArrayOfMessageV4AsMessagesUnion(
      []agentStudio.MessageV4{*agentStudio.UserMessageV4AsMessageV4(
        agentStudio.NewEmptyUserMessageV4().SetRole("user").SetContent("Hello, how are you?"))})),
))
if err != nil {
  // handle the eventual error
  panic(err)
}


// print the response
print(response)
```

```java Java theme={"system"}
// Initialize the client
AgentStudioClient client = new AgentStudioClient("ALGOLIA_APPLICATION_ID", "ALGOLIA_API_KEY");

// Call the API
ContextResponse response = client.compactContext(
  new ContextCompactRequest()
    .setProviderID("c2905529-b933-4b69-87ec-75f9829d5f59")
    .setModel("gpt-4o-mini")
    .setMessages(MessagesUnion.ofListOfMessageV4(Arrays.asList(new UserMessageV4().setRole("user").setContent("Hello, how are you?"))))
);

// print the response
System.out.println(response);
```

```js JavaScript theme={"system"}
// Initialize the client
const client = agentStudioClient('ALGOLIA_APPLICATION_ID', 'ALGOLIA_API_KEY');

// Call the API
const response = await client.compactContext({
  providerID: 'c2905529-b933-4b69-87ec-75f9829d5f59',
  model: 'gpt-4o-mini',
  messages: [{ role: 'user', content: 'Hello, how are you?' }],
});


// print the response
console.log(response);
```

```kotlin Kotlin theme={"system"}
// Initialize the client
val client = AgentStudioClient(appId = "ALGOLIA_APPLICATION_ID", apiKey = "ALGOLIA_API_KEY")

// Call the API
var response =
  client.compactContext(
    contextCompactRequest =
      ContextCompactRequest(
        providerID = "c2905529-b933-4b69-87ec-75f9829d5f59",
        model = "gpt-4o-mini",
        messages =
          MessagesUnion.ofListOfMessageV4(
            listOf(UserMessageV4(role = "user", content = "Hello, how are you?"))
          ),
      )
  )


// print the response
println(response)
```

```php PHP theme={"system"}
// Initialize the client
$client = AgentStudioClient::create('ALGOLIA_APPLICATION_ID', 'ALGOLIA_API_KEY');

// Call the API
$response = $client->compactContext(
    ['providerID' => 'c2905529-b933-4b69-87ec-75f9829d5f59',
        'model' => 'gpt-4o-mini',
        'messages' => [
            ['role' => 'user',
                'content' => 'Hello, how are you?',
            ],
        ],
    ],
);


// print the response
var_dump($response);
```

```python Python theme={"system"}
# Initialize the client
# In an asynchronous context, you can use AgentStudioClient instead, which exposes the exact same methods.
client = AgentStudioClientSync("ALGOLIA_APPLICATION_ID", "ALGOLIA_API_KEY")

# Call the API
response = client.compact_context(
    context_compact_request={
        "providerID": "c2905529-b933-4b69-87ec-75f9829d5f59",
        "model": "gpt-4o-mini",
        "messages": [
            {
                "role": "user",
                "content": "Hello, how are you?",
            },
        ],
    },
)


# print the response
print(response)
```

```ruby Ruby theme={"system"}
# Initialize the client
client = Algolia::AgentStudioClient.create("ALGOLIA_APPLICATION_ID", "ALGOLIA_API_KEY")

# Call the API
response = client.compact_context(
  Algolia::AgentStudio::ContextCompactRequest.new(
    provider_id: "c2905529-b933-4b69-87ec-75f9829d5f59",
    model: "gpt-4o-mini",
    messages: [Algolia::AgentStudio::UserMessageV4.new(role: "user", content: "Hello, how are you?")]
  )
)


# print the response
puts(response)
```

```scala Scala theme={"system"}
// Initialize the client
val client = AgentStudioClient(appId = "ALGOLIA_APPLICATION_ID", apiKey = "ALGOLIA_API_KEY")

// Call the API
val response = Await.result(
  client.compactContext(
    contextCompactRequest = ContextCompactRequest(
      providerID = "c2905529-b933-4b69-87ec-75f9829d5f59",
      model = "gpt-4o-mini",
      messages = MessagesUnion(
        Seq(
          UserMessageV4(
            role = "user",
            content = "Hello, how are you?"
          )
        )
      )
    )
  ),
  Duration(100, "sec")
)

// print the response
println(response)
```

```swift Swift theme={"system"}
// Initialize the client
let client = try AgentStudioClient(appID: "ALGOLIA_APPLICATION_ID", apiKey: "ALGOLIA_API_KEY")

// Call the API
let response = try await client.compactContext(contextCompactRequest: ContextCompactRequest(
    providerID: "c2905529-b933-4b69-87ec-75f9829d5f59",
    model: "gpt-4o-mini",
    messages: MessagesUnion.arrayOfMessageV4([MessageV4.userMessageV4(UserMessageV4(
        role: "user",
        content: "Hello, how are you?"
    ))])
))

// print the response
print(response)
```

> [card] [See the full API reference](https://www.algolia.com/doc/rest-api/agent-studio/compact-context.md)
>
> For more details about input parameters
> and response fields.