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ToolExecutionResult object { status, agent_state, func_return, 3 more }
Representation of an agent’s state. This is the state of the agent at a given time, and is persisted in the DB backend. The state has all the information needed to recreate a persisted agent.
Deprecated: Use model field instead. The LLM configuration used by the agent.
model_endpoint_type: "openai" or "anthropic" or "google_ai" or 27 more
The endpoint type for the model.
enable_reasoner: optional boolean
Whether or not the model should use extended thinking if it is a ‘reasoning’ style model
frequency_penalty: optional number
Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim. From OpenAI: Number between -2.0 and 2.0.
max_reasoning_tokens: optional number
Configurable thinking budget for extended thinking. Used for enable_reasoner and also for Google Vertex models like Gemini 2.5 Flash. Minimum value is 1024 when used with enable_reasoner.
max_tokens: optional number
The maximum number of tokens to generate. If not set, the model will use its default value.
Deprecatedparallel_tool_calls: optional boolean
Deprecated: Use model_settings to configure parallel tool calls instead. If set to True, enables parallel tool calling. Defaults to False.
put_inner_thoughts_in_kwargs: optional boolean
Puts ‘inner_thoughts’ as a kwarg in the function call if this is set to True. This helps with function calling performance and also the generation of inner thoughts.
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
return_logprobs: optional boolean
Whether to return log probabilities of the output tokens. Useful for RL training.
return_token_ids: optional boolean
Whether to return token IDs for all LLM generations via SGLang native endpoint. Required for multi-turn RL training with loss masking. Only works with SGLang provider.
strict: optional boolean
Enable strict mode for tool calling. When true, tool schemas include strict: true and additionalProperties: false, guaranteeing tool outputs match JSON schemas.
temperature: optional number
The temperature to use when generating text with the model. A higher temperature will result in more random text.
tool_call_parser: optional string
SGLang tool call parser name (e.g. ‘glm47’, ‘qwen25’, ‘hermes’). Used by the SGLang native adapter to parse tool calls from raw model output.
Deprecatedmemory: object { blocks, agent_type, file_blocks, 2 more }
Deprecated: Use blocks field instead. The in-context memory of the agent.
file_blocks: optional array of object { file_id, is_open, source_id, 20 more }
Special blocks representing the agent’s in-context memory of an attached file
Deprecatedsources: array of object { id, embedding_config, name, 8 more }
Deprecated: Use folders field instead. The sources used by the agent.
embedding_config: EmbeddingConfig { embedding_dim, embedding_endpoint_type, embedding_model, 7 more }
The tools used by the agent.
default_requires_approval: optional boolean
Default value for whether or not executing this tool requires approval.
enable_parallel_execution: optional boolean
If set to True, then this tool will potentially be executed concurrently with other tools. Default False.
return_char_limit: optional number
The maximum number of characters in the response.
compaction_settings: optional object { clip_chars, mode, model, 4 more }
Configuration for conversation compaction / summarization.
Per-model settings (temperature, max tokens, etc.) are derived from the default configuration for that handle.
clip_chars: optional number
The maximum length of the summary in characters. If none, no clipping is performed.
model: optional string
Model handle to use for sliding_window/all summarization (format: provider/model-name). If None, uses lightweight provider-specific defaults.
model_settings: optional OpenAIModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 4 more } or object { max_output_tokens, parallel_tool_calls, provider_type, 5 more } or AnthropicModelSettings { effort, max_output_tokens, parallel_tool_calls, 6 more } or 14 more
Optional model settings used to override defaults for the summarizer model.
OpenAIModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 4 more }
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Sglang object { max_output_tokens, parallel_tool_calls, provider_type, 5 more }
SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
AnthropicModelSettings object { effort, max_output_tokens, parallel_tool_calls, 6 more }
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
strict: optional boolean
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
GoogleAIModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
response_schema: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
GoogleVertexModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
response_schema: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
AzureModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Azure OpenAI model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
XaiModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
xAI model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Moonshot object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
Moonshot/Kimi model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Zai object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
Z.ai (ZhipuAI) model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
MoonshotCoding object { effort, max_output_tokens, parallel_tool_calls, 6 more }
Kimi Code model configuration (Anthropic-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
strict: optional boolean
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
GroqModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Groq model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
DeepseekModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Deepseek model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
TogetherModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Together AI model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
BedrockModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
AWS Bedrock model configuration.
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Baseten object { max_output_tokens, parallel_tool_calls, provider_type, temperature }
Baseten model configuration (OpenAI-compatible).
Openrouter object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
OpenRouter model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
embedding: optional string
The embedding model handle used by the agent (format: provider/model-name).
Deprecatedembedding_config: optional EmbeddingConfig { embedding_dim, embedding_endpoint_type, embedding_model, 7 more }
enable_sleeptime: optional boolean
If set to True, memory management will move to a background agent thread.
identities: optional array of object { id, agent_ids, block_ids, 5 more }
Deprecatedidentity_ids: optional array of string
Deprecated: Use identities field instead. The ids of the identities associated with this agent.
last_run_completion: optional string
The timestamp when the agent last completed a run.
managed_group: optional object { id, agent_ids, description, 15 more }
The multi-agent group that this agent manages
max_message_buffer_length: optional number
The desired maximum length of messages in the context window of the convo agent. This is a best effort, and may be off slightly due to user/assistant interleaving.
max_files_open: optional number
Maximum number of files that can be open at once for this agent. Setting this too high may exceed the context window, which will break the agent.
message_buffer_autoclear: optional boolean
If set to True, the agent will not remember previous messages (though the agent will still retain state via core memory blocks and archival/recall memory). Not recommended unless you have an advanced use case.
model_settings: optional OpenAIModelSettings { max_output_tokens, parallel_tool_calls, provider_type, 4 more } or object { max_output_tokens, parallel_tool_calls, provider_type, 5 more } or AnthropicModelSettings { effort, max_output_tokens, parallel_tool_calls, 6 more } or 14 more
The model settings used by the agent.
OpenAIModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 4 more }
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Sglang object { max_output_tokens, parallel_tool_calls, provider_type, 5 more }
SGLang model configuration (OpenAI-compatible runtime with SGLang-specific parsing).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
AnthropicModelSettings object { effort, max_output_tokens, parallel_tool_calls, 6 more }
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
strict: optional boolean
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
GoogleAIModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
response_schema: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
GoogleVertexModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
response_schema: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
AzureModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Azure OpenAI model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
XaiModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
xAI model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Moonshot object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
Moonshot/Kimi model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Zai object { max_output_tokens, parallel_tool_calls, provider_type, 3 more }
Z.ai (ZhipuAI) model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
MoonshotCoding object { effort, max_output_tokens, parallel_tool_calls, 6 more }
Kimi Code model configuration (Anthropic-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
strict: optional boolean
Enable strict mode for tool calling. When true, tool outputs are guaranteed to match JSON schemas.
GroqModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Groq model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
DeepseekModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Deepseek model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
TogetherModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
Together AI model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
BedrockModelSettings object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
AWS Bedrock model configuration.
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Baseten object { max_output_tokens, parallel_tool_calls, provider_type, temperature }
Baseten model configuration (OpenAI-compatible).
Openrouter object { max_output_tokens, parallel_tool_calls, provider_type, 2 more }
OpenRouter model configuration (OpenAI-compatible).
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Deprecatedmulti_agent_group: optional object { id, agent_ids, description, 15 more }
Deprecated: Use managed_group field instead. The multi-agent group that this agent manages.
max_message_buffer_length: optional number
The desired maximum length of messages in the context window of the convo agent. This is a best effort, and may be off slightly due to user/assistant interleaving.
A message representing a request for approval to call a tool (generated by the LLM to trigger tool execution).
Args: id (str): The ID of the message date (datetime): The date the message was created in ISO format name (Optional[str]): The name of the sender of the message tool_call (ToolCall): The tool call
Deprecatedtool_call: ToolCall { arguments, name, tool_call_id } or ToolCallDelta { arguments, name, tool_call_id }
The tool call that has been requested by the llm to run
otid: optional string
The offline threading id (OTID). Set by the client to deduplicate requests. Used for idempotency in background streaming mode — each message in a request must have a unique OTID. Retries of the same request should reuse the same OTIDs.
tool_calls: optional array of ToolCall { arguments, name, tool_call_id } or ToolCallDelta { arguments, name, tool_call_id }
The tool calls that have been requested by the llm to run, which are pending approval
array of ToolCall { arguments, name, tool_call_id }
per_file_view_window_char_limit: optional number
The per-file view window character limit for this agent. Setting this too high may exceed the context window, which will break the agent.
response_format: optional TextResponseFormat { type } or JsonSchemaResponseFormat { json_schema, type } or JsonObjectResponseFormat { type }
Deprecatedtool_exec_environment_variables: optional array of AgentEnvironmentVariable { agent_id, key, value, 7 more }
Deprecated: use secrets field instead.
tool_rules: optional array of ChildToolRule { children, tool_name, child_arg_nodes, 2 more } or InitToolRule { tool_name, args, prompt_template, type } or TerminalToolRule { tool_name, prompt_template, type } or 6 more
The list of tool rules.
ChildToolRule object { children, tool_name, child_arg_nodes, 2 more }
InitToolRule object { tool_name, args, prompt_template, type }
Represents the initial tool rule configuration.
args: optional map[unknown]
Optional prefilled arguments for this tool. When present, these values will override any LLM-provided arguments with the same keys during invocation. Keys must match the tool’s parameter names and values must satisfy the tool’s JSON schema. Supports partial prefill; non-overlapping parameters are left to the model.
ConditionalToolRule object { child_output_mapping, tool_name, default_child, 3 more }
MaxCountPerStepToolRule object { max_count_limit, tool_name, prompt_template, type }
ParentToolRule object { children, tool_name, prompt_template, type }
A ToolRule that only allows a child tool to be called if the parent has been called.