Recompile Conversation
Manually trigger system prompt recompilation for a conversation.
ParametersExpand Collapse
conversation_id: str
The conversation identifier. Can be a conversation ID ('conv-
If True, do not persist changes; still returns the compiled system prompt.
agent_id: Optional[str]
Agent ID for agent-direct mode with 'default' conversation. Use with conversation_id='default' in the URL path.
Configuration for conversation compaction / summarization.
Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle.
clip_chars: Optional[int]
The maximum length of the summary in characters. If none, no clipping is performed.
mode: Optional[Literal["all", "sliding_window", "self_compact_all", "self_compact_sliding_window"]]
The type of summarization technique use.
model: Optional[str]
Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults.
model_settings: Optional[CompactionSettingsModelSettings]
Optional model settings used to override defaults for the summarizer model.
class OpenAIModelSettings: …
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["openai"]]
The type of the provider.
reasoning: Optional[Reasoning]
The reasoning configuration for the model.
reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]
The reasoning effort to use when generating text reasoning models
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
strict: Optional[bool]
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
temperature: Optional[float]
The temperature of the model.
class CompactionSettingsModelSettingsSgLangModelSettings: …
SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["sglang"]]
The type of the provider.
reasoning: Optional[CompactionSettingsModelSettingsSgLangModelSettingsReasoning]
The reasoning configuration for the model.
reasoning_effort: Optional[Literal["none", "minimal", "low", 3 more]]
The reasoning effort to use when generating text reasoning models
response_format: Optional[CompactionSettingsModelSettingsSgLangModelSettingsResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
strict: Optional[bool]
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
temperature: Optional[float]
The temperature of the model.
tool_call_parser: Optional[str]
SGLang tool call parser name (for example 'glm47', 'qwen25', or 'hermes').
class AnthropicModelSettings: …
effort: Optional[Literal["low", "medium", "high", "max"]]
Effort level for supported Anthropic models (controls token spending). 'max' is only available on Opus 4.6. Not setting this gives similar performance to 'high'.
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["anthropic"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
strict: Optional[bool]
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
temperature: Optional[float]
The temperature of the model.
thinking: Optional[Thinking]
The thinking configuration for the model.
budget_tokens: Optional[int]
The maximum number of tokens the model can use for extended thinking.
type: Optional[Literal["enabled", "disabled"]]
The type of thinking to use.
verbosity: Optional[Literal["low", "medium", "high"]]
Soft control for how verbose model output should be, used for GPT-5 models.
class GoogleAIModelSettings: …
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["google_ai"]]
The type of the provider.
response_schema: Optional[ResponseSchema]
The response schema for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
thinking_config: Optional[ThinkingConfig]
The thinking configuration for the model.
include_thoughts: Optional[bool]
Whether to include thoughts in the model's response.
thinking_budget: Optional[int]
The thinking budget for the model.
class GoogleVertexModelSettings: …
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["google_vertex"]]
The type of the provider.
response_schema: Optional[ResponseSchema]
The response schema for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
thinking_config: Optional[ThinkingConfig]
The thinking configuration for the model.
include_thoughts: Optional[bool]
Whether to include thoughts in the model's response.
thinking_budget: Optional[int]
The thinking budget for the model.
class AzureModelSettings: …
Azure OpenAI model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["azure"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class XaiModelSettings: …
xAI model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["xai"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class CompactionSettingsModelSettingsZaiModelSettings: …
Z.ai (ZhipuAI) model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["zai"]]
The type of the provider.
response_format: Optional[CompactionSettingsModelSettingsZaiModelSettingsResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
thinking: Optional[CompactionSettingsModelSettingsZaiModelSettingsThinking]
The thinking configuration for GLM-4.5+ models.
clear_thinking: Optional[bool]
If False, preserved thinking is used (recommended for agents).
type: Optional[Literal["enabled", "disabled"]]
Whether thinking is enabled or disabled.
class GroqModelSettings: …
Groq model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["groq"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class DeepseekModelSettings: …
Deepseek model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["deepseek"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class TogetherModelSettings: …
Together AI model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["together"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class BedrockModelSettings: …
AWS Bedrock model configuration.
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["bedrock"]]
The type of the provider.
response_format: Optional[ResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class CompactionSettingsModelSettingsOpenRouterModelSettings: …
OpenRouter model configuration (OpenAI-compatible).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["openrouter"]]
The type of the provider.
response_format: Optional[CompactionSettingsModelSettingsOpenRouterModelSettingsResponseFormat]
The response format for the model.
class TextResponseFormat: …
Response format for plain text responses.
type: Optional[Literal["text"]]
The type of the response format.
class JsonSchemaResponseFormat: …
Response format for JSON schema-based responses.
json_schema: Dict[str, object]
The JSON schema of the response.
type: Optional[Literal["json_schema"]]
The type of the response format.
class JsonObjectResponseFormat: …
Response format for JSON object responses.
type: Optional[Literal["json_object"]]
The type of the response format.
temperature: Optional[float]
The temperature of the model.
class CompactionSettingsModelSettingsChatGptoAuthModelSettings: …
ChatGPT OAuth model configuration (uses ChatGPT backend API).
max_output_tokens: Optional[int]
The maximum number of tokens the model can generate.
parallel_tool_calls: Optional[bool]
Whether to enable parallel tool calling.
provider_type: Optional[Literal["chatgpt_oauth"]]
The type of the provider.
reasoning: Optional[CompactionSettingsModelSettingsChatGptoAuthModelSettingsReasoning]
The reasoning configuration for the model.
reasoning_effort: Optional[Literal["none", "low", "medium", 2 more]]
The reasoning effort level for GPT-5.x and o-series models.
temperature: Optional[float]
The temperature of the model.
prompt: Optional[str]
The prompt to use for summarization. If None, uses mode-specific default.
prompt_acknowledgement: Optional[bool]
Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs).
sliding_window_percentage: Optional[float]
The percentage of the context window to keep post-summarization (only used in sliding window modes).
ReturnsExpand Collapse
Recompile Conversation
import os
from letta_client import Letta
client = Letta(
api_key=os.environ.get("LETTA_API_KEY"), # This is the default and can be omitted
)
response = client.conversations.recompile(
conversation_id="default",
)
print(response)
"string"
Returns Examples
"string"