Recompile Conversation

client.conversations.recompile(, ?, ?): ConversationRecompileResponse

POST/v1/conversations/{conversation_id}/recompile

Manually trigger system prompt recompilation for a conversation.

ParametersExpand Collapse

conversationID: string

The conversation identifier. Can be a conversation ID (‘conv-’), ‘default’ for agent-direct mode (with agent_id parameter), or an agent ID (‘agent-’) for backwards compatibility (deprecated).

minLength1

maxLength42

params: ConversationRecompileParams { dry_run, agent_id, compaction_settings }

dry_run?: boolean

Query param: If True, do not persist changes; still returns the compiled system prompt.

agent_id?: string | null

Body param: Agent ID for agent-direct mode with ‘default’ conversation. Use with conversation_id=‘default’ in the URL path.

compaction_settings?: CompactionSettings | null

Body param: Configuration for conversation compaction / summarization.

Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle.

clip_chars?: number | null

The maximum length of the summary in characters. If none, no clipping is performed.

mode?: "all" | "sliding_window" | "self_compact_all" | "self_compact_sliding_window"

The type of summarization technique use.

One of the following:

"all"

"sliding_window"

"self_compact_all"

"self_compact_sliding_window"

model?: string | null

Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults.

model_settings?: OpenAIModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 4 more } | SgLangModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 5 more } | AnthropicModelSettings { effort, max_output_tokens, parallel_tool_calls, 6 more } | 14 more | null

Optional model settings used to override defaults for the summarizer model.

One of the following:

OpenAIModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 4 more }

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "openai"

The type of the provider.

reasoning?: Reasoning { reasoning_effort }

The reasoning configuration for the model.

reasoning_effort?: "none" | "minimal" | "low" | 3 more

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

strict?: boolean

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature?: number

The temperature of the model.

SgLangModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 5 more }

SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "sglang"

The type of the provider.

reasoning?: Reasoning { reasoning_effort }

The reasoning configuration for the model.

reasoning_effort?: "none" | "minimal" | "low" | 3 more

The reasoning effort to use when generating text reasoning models

One of the following:

"none"

"minimal"

"low"

"medium"

"high"

"xhigh"

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

strict?: boolean

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature?: number

The temperature of the model.

tool_call_parser?: string | null

SGLang tool call parser name (for example ‘glm47’, ‘qwen25’, or ‘hermes’).

AnthropicModelSettings { effort, max_output_tokens, parallel_tool_calls, 6 more }

effort?: "low" | "medium" | "high" | 2 more | null

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "anthropic"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

strict?: boolean

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature?: number

The temperature of the model.

thinking?: Thinking { budget_tokens, type }

The thinking configuration for the model.

budget_tokens?: number

The maximum number of tokens the model can use for extended thinking.

type?: "enabled" | "disabled"

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity?: "low" | "medium" | "high" | null

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

GoogleAIModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 3 more }

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "google_ai"

The type of the provider.

response_schema?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response schema for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

thinking_config?: ThinkingConfig { include_thoughts, thinking_budget }

The thinking configuration for the model.

include_thoughts?: boolean

Whether to include thoughts in the model’s response.

thinking_budget?: number

The thinking budget for the model.

GoogleVertexModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 3 more }

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "google_vertex"

The type of the provider.

response_schema?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response schema for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

thinking_config?: ThinkingConfig { include_thoughts, thinking_budget }

The thinking configuration for the model.

include_thoughts?: boolean

Whether to include thoughts in the model’s response.

thinking_budget?: number

The thinking budget for the model.

AzureModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

Azure OpenAI model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "azure"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

XaiModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

xAI model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "xai"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

MoonshotModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 3 more }

Moonshot/Kimi model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "moonshot"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

strict?: boolean

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature?: number

The temperature of the model.

ZaiModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 3 more }

Z.ai (ZhipuAI) model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "zai"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

thinking?: Thinking { clear_thinking, type }

The thinking configuration for GLM-4.5+ models.

clear_thinking?: boolean

If False, preserved thinking is used (recommended for agents).

type?: "enabled" | "disabled"

Whether thinking is enabled or disabled.

One of the following:

"enabled"

"disabled"

MoonshotCodingModelSettings { effort, max_output_tokens, parallel_tool_calls, 6 more }

Kimi Code model configuration (Anthropic-compatible).

effort?: "low" | "medium" | "high" | 2 more | null

Effort level for supported Anthropic models (controls token spending). ‘xhigh’ and ‘max’ are available on Opus 4.6+. Not setting this gives similar performance to ‘high’.

One of the following:

"low"

"medium"

"high"

"xhigh"

"max"

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "moonshot_coding"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

strict?: boolean

Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.

temperature?: number

The temperature of the model.

thinking?: Thinking { budget_tokens, type }

The thinking configuration for the model.

budget_tokens?: number

The maximum number of tokens the model can use for extended thinking.

type?: "enabled" | "disabled"

The type of thinking to use.

One of the following:

"enabled"

"disabled"

verbosity?: "low" | "medium" | "high" | null

Soft control for how verbose model output should be, used for GPT-5 models.

One of the following:

"low"

"medium"

"high"

GroqModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

Groq model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "groq"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

DeepseekModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

Deepseek model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "deepseek"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

TogetherModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

Together AI model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "together"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

BedrockModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

AWS Bedrock model configuration.

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "bedrock"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

BasetenModelSettings { max_output_tokens, parallel_tool_calls, provider_type, temperature }

Baseten model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "baseten"

The type of the provider.

temperature?: number

The temperature of the model.

OpenRouterModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

OpenRouter model configuration (OpenAI-compatible).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "openrouter"

The type of the provider.

response_format?: TextResponseFormat { type } | JsonSchemaResponseFormat { json_schema, type } | JsonObjectResponseFormat { type } | null

The response format for the model.

One of the following:

TextResponseFormat { type }

Response format for plain text responses.

type?: "text"

The type of the response format.

JsonSchemaResponseFormat { json_schema, type }

Response format for JSON schema-based responses.

json_schema: Record<string, unknown>

The JSON schema of the response.

type?: "json_schema"

The type of the response format.

JsonObjectResponseFormat { type }

Response format for JSON object responses.

type?: "json_object"

The type of the response format.

temperature?: number

The temperature of the model.

ChatGptoAuthModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 2 more }

ChatGPT OAuth model configuration (uses ChatGPT backend API).

max_output_tokens?: number

The maximum number of tokens the model can generate.

parallel_tool_calls?: boolean

Whether to enable parallel tool calling.

provider_type?: "chatgpt_oauth"

The type of the provider.

reasoning?: Reasoning { reasoning_effort }

The reasoning configuration for the model.

reasoning_effort?: "none" | "low" | "medium" | 2 more

The reasoning effort level for GPT-5.x and o-series models.

One of the following:

"none"

"low"

"medium"

"high"

"xhigh"

temperature?: number

The temperature of the model.

prompt?: string | null

The prompt to use for summarization. If None, uses mode-specific default.

prompt_acknowledgement?: boolean

Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs).

sliding_window_percentage?: number

The percentage of the context window to keep post-summarization (only used in sliding window modes).

ReturnsExpand Collapse

ConversationRecompileResponse = string

Recompile Conversation

import Letta from '@letta-ai/letta-client';

const client = new Letta({
  apiKey: process.env['LETTA_API_KEY'], // This is the default and can be omitted
});

const response = await client.conversations.recompile('default');

console.log(response);

"string"

Returns Examples

"string"