## Modify Feedback For Step **patch** `/v1/steps/{step_id}/feedback` Modify feedback for a given step. ### Path Parameters - `step_id: string` The ID of the step in the format 'step-' ### Body Parameters - `feedback: optional "positive" or "negative"` Whether this feedback is positive or negative - `"positive"` - `"negative"` - `tags: optional array of string` Feedback tags to add to the step ### Returns - `Step object { id, agent_id, cache_write_tokens, 27 more }` - `id: string` The id of the step. Assigned by the database. - `agent_id: optional string` The ID of the agent that performed the step. - `cache_write_tokens: optional number` The number of input tokens written to cache (Anthropic only). None if not reported by provider. - `cached_input_tokens: optional number` The number of input tokens served from cache. None if not reported by provider. - `completion_tokens: optional number` The number of tokens generated by the agent during this step. - `completion_tokens_details: optional map[unknown]` Detailed completion token breakdown (e.g., reasoning_tokens). - `context_window_limit: optional number` The context window limit configured for this step. - `error_data: optional map[unknown]` Error details including message, traceback, and additional context - `error_type: optional string` The type/class of the error that occurred - `feedback: optional "positive" or "negative"` The feedback for this step. Must be either 'positive' or 'negative'. - `"positive"` - `"negative"` - `messages: optional array of InternalMessage` The messages generated during this step. Deprecated: use `GET /v1/steps/{step_id}/messages` endpoint instead - `id: string` The human-friendly ID of the Message - `role: MessageRole` The role of the participant. - `"assistant"` - `"user"` - `"tool"` - `"function"` - `"system"` - `"approval"` - `"summary"` - `agent_id: optional string` The unique identifier of the agent. - `approval_request_id: optional string` The id of the approval request if this message is associated with a tool call request. - `approvals: optional array of ApprovalReturn or object { status, func_response, stderr, 2 more }` The list of approvals for this message. - `ApprovalReturn object { approve, tool_call_id, reason, type }` - `approve: boolean` Whether the tool has been approved - `tool_call_id: string` The ID of the tool call that corresponds to this approval - `reason: optional string` An optional explanation for the provided approval status - `type: optional "approval"` The message type to be created. - `"approval"` - `LettaSchemasMessageToolReturnOutput object { status, func_response, stderr, 2 more }` - `status: "success" or "error"` The status of the tool call - `"success"` - `"error"` - `func_response: optional string or array of TextContent or ImageContent` The function response - either a string or list of content parts (text/image) - `string` - `array of TextContent or ImageContent` - `TextContent object { text, signature, type }` - `text: string` The text content of the message. - `signature: optional string` Stores a unique identifier for any reasoning associated with this text content. - `type: optional "text"` The type of the message. - `"text"` - `ImageContent object { source, type }` - `source: object { url, type } or object { data, media_type, detail, type } or object { file_id, data, detail, 2 more }` The source of the image. - `URL object { url, type }` - `url: string` The URL of the image. - `type: optional "url"` The source type for the image. - `"url"` - `Base64 object { data, media_type, detail, type }` - `data: string` The base64 encoded image data. - `media_type: string` The media type for the image. - `detail: optional string` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `type: optional "base64"` The source type for the image. - `"base64"` - `Letta object { file_id, data, detail, 2 more }` - `file_id: string` The unique identifier of the image file persisted in storage. - `data: optional string` The base64 encoded image data. - `detail: optional string` What level of detail to use when processing and understanding the image (low, high, or auto to let the model decide) - `media_type: optional string` The media type for the image. - `type: optional "letta"` The source type for the image. - `"letta"` - `type: optional "image"` The type of the message. - `"image"` - `stderr: optional array of string` Captured stderr from the tool invocation - `stdout: optional array of string` Captured stdout (e.g. prints, logs) from the tool invocation - `tool_call_id: optional unknown` The ID for the tool call - `approve: optional boolean` Whether tool call is approved. - `batch_item_id: optional string` The id of the LLMBatchItem that this message is associated with - `content: optional array of TextContent or ImageContent or ToolCallContent or 5 more` The content of the message. - `TextContent object { text, signature, type }` - `ImageContent object { source, type }` - `ToolCallContent object { id, input, name, 2 more }` - `id: string` A unique identifier for this specific tool call instance. - `input: map[unknown]` The parameters being passed to the tool, structured as a dictionary of parameter names to values. - `name: string` The name of the tool being called. - `signature: optional string` Stores a unique identifier for any reasoning associated with this tool call. - `type: optional "tool_call"` Indicates this content represents a tool call event. - `"tool_call"` - `ToolReturnContent object { content, is_error, tool_call_id, type }` - `content: string` The content returned by the tool execution. - `is_error: boolean` Indicates whether the tool execution resulted in an error. - `tool_call_id: string` References the ID of the ToolCallContent that initiated this tool call. - `type: optional "tool_return"` Indicates this content represents a tool return event. - `"tool_return"` - `ReasoningContent object { is_native, reasoning, signature, type }` Sent via the Anthropic Messages API - `is_native: boolean` Whether the reasoning content was generated by a reasoner model that processed this step. - `reasoning: string` The intermediate reasoning or thought process content. - `signature: optional string` A unique identifier for this reasoning step. - `type: optional "reasoning"` Indicates this is a reasoning/intermediate step. - `"reasoning"` - `RedactedReasoningContent object { data, type }` Sent via the Anthropic Messages API - `data: string` The redacted or filtered intermediate reasoning content. - `type: optional "redacted_reasoning"` Indicates this is a redacted thinking step. - `"redacted_reasoning"` - `OmittedReasoningContent object { signature, type }` A placeholder for reasoning content we know is present, but isn't returned by the provider (e.g. OpenAI GPT-5 on ChatCompletions) - `signature: optional string` A unique identifier for this reasoning step. - `type: optional "omitted_reasoning"` Indicates this is an omitted reasoning step. - `"omitted_reasoning"` - `SummarizedReasoning object { id, summary, encrypted_content, type }` The style of reasoning content returned by the OpenAI Responses API - `id: string` The unique identifier for this reasoning step. - `summary: array of object { index, text }` Summaries of the reasoning content. - `index: number` The index of the summary part. - `text: string` The text of the summary part. - `encrypted_content: optional string` The encrypted reasoning content. - `type: optional "summarized_reasoning"` Indicates this is a summarized reasoning step. - `"summarized_reasoning"` - `conversation_id: optional string` The conversation this message belongs to - `created_at: optional string` The timestamp when the object was created. - `created_by_id: optional string` The id of the user that made this object. - `denial_reason: optional string` The reason the tool call request was denied. - `group_id: optional string` The multi-agent group that the message was sent in - `is_err: optional boolean` Whether this message is part of an error step. Used only for debugging purposes. - `last_updated_by_id: optional string` The id of the user that made this object. - `model: optional string` The model used to make the function call. - `name: optional string` For role user/assistant: the (optional) name of the participant. For role tool/function: the name of the function called. - `otid: optional string` The offline threading id associated with this message - `run_id: optional string` The id of the run that this message was created in. - `sender_id: optional string` The id of the sender of the message, can be an identity id or agent id - `step_id: optional string` The id of the step that this message was created in. - `tool_call_id: optional string` The ID of the tool call. Only applicable for role tool. - `tool_calls: optional array of object { id, function, type }` The list of tool calls requested. Only applicable for role assistant. - `id: string` - `function: object { arguments, name }` The function that the model called. - `arguments: string` - `name: string` - `type: "function"` - `"function"` - `tool_returns: optional array of object { status, func_response, stderr, 2 more }` Tool execution return information for prior tool calls - `status: "success" or "error"` The status of the tool call - `"success"` - `"error"` - `func_response: optional string or array of TextContent or ImageContent` The function response - either a string or list of content parts (text/image) - `string` - `array of TextContent or ImageContent` - `TextContent object { text, signature, type }` - `ImageContent object { source, type }` - `stderr: optional array of string` Captured stderr from the tool invocation - `stdout: optional array of string` Captured stdout (e.g. prints, logs) from the tool invocation - `tool_call_id: optional unknown` The ID for the tool call - `updated_at: optional string` The timestamp when the object was last updated. - `model: optional string` The name of the model used for this step. - `model_endpoint: optional string` The model endpoint url used for this step. - `model_handle: optional string` The model handle (e.g., 'openai/gpt-4o-mini') used for this step. - `origin: optional string` The surface that this agent step was initiated from. - `project_id: optional string` The project that the agent that executed this step belongs to (cloud only). - `prompt_tokens: optional number` The number of tokens in the prompt during this step. - `prompt_tokens_details: optional map[unknown]` Detailed prompt token breakdown (e.g., cached_tokens, cache_read_tokens, cache_creation_tokens). - `provider_category: optional string` The category of the provider used for this step. - `provider_id: optional string` The unique identifier of the provider that was configured for this step - `provider_name: optional string` The name of the provider used for this step. - `reasoning_tokens: optional number` The number of reasoning/thinking tokens generated. None if not reported by provider. - `request_id: optional string` The API request log ID from cloud-api for correlating steps with API requests. - `run_id: optional string` The unique identifier of the run that this step belongs to. Only included for async calls. - `status: optional "pending" or "success" or "failed" or "cancelled"` Status of a step execution - `"pending"` - `"success"` - `"failed"` - `"cancelled"` - `stop_reason: optional StopReasonType` The stop reason associated with the step. - `"end_turn"` - `"error"` - `"llm_api_error"` - `"invalid_llm_response"` - `"invalid_tool_call"` - `"max_steps"` - `"max_tokens_exceeded"` - `"no_tool_call"` - `"tool_rule"` - `"cancelled"` - `"insufficient_credits"` - `"requires_approval"` - `"context_window_overflow_in_system_prompt"` - `tags: optional array of string` Metadata tags. - `tid: optional string` The unique identifier of the transaction that processed this step. - `total_tokens: optional number` The total number of tokens processed by the agent during this step. - `trace_id: optional string` The trace id of the agent step. ### Example ```http curl https://api.letta.com/v1/steps/$STEP_ID/feedback \ -X PATCH \ -H 'Content-Type: application/json' \ -H "Authorization: Bearer $LETTA_API_KEY" \ -d '{}' ``` #### Response ```json { "id": "id", "agent_id": "agent_id", "cache_write_tokens": 0, "cached_input_tokens": 0, "completion_tokens": 0, "completion_tokens_details": { "foo": "bar" }, "context_window_limit": 0, "error_data": { "foo": "bar" }, "error_type": "error_type", "feedback": "positive", "messages": [ { "id": "message-123e4567-e89b-12d3-a456-426614174000", "role": "assistant", "agent_id": "agent_id", "approval_request_id": "approval_request_id", "approvals": [ { "approve": true, "tool_call_id": "tool_call_id", "reason": "reason", "type": "approval" } ], "approve": true, "batch_item_id": "batch_item_id", "content": [ { "text": "text", "signature": "signature", "type": "text" } ], "conversation_id": "conversation_id", "created_at": "2019-12-27T18:11:19.117Z", "created_by_id": "created_by_id", "denial_reason": "denial_reason", "group_id": "group_id", "is_err": true, "last_updated_by_id": "last_updated_by_id", "model": "model", "name": "name", "otid": "otid", "run_id": "run_id", "sender_id": "sender_id", "step_id": "step_id", "tool_call_id": "tool_call_id", "tool_calls": [ { "id": "id", "function": { "arguments": "arguments", "name": "name" }, "type": "function" } ], "tool_returns": [ { "status": "success", "func_response": "string", "stderr": [ "string" ], "stdout": [ "string" ], "tool_call_id": {} } ], "updated_at": "2019-12-27T18:11:19.117Z" } ], "model": "model", "model_endpoint": "model_endpoint", "model_handle": "model_handle", "origin": "origin", "project_id": "project_id", "prompt_tokens": 0, "prompt_tokens_details": { "foo": "bar" }, "provider_category": "provider_category", "provider_id": "provider_id", "provider_name": "provider_name", "reasoning_tokens": 0, "request_id": "request_id", "run_id": "run_id", "status": "pending", "stop_reason": "end_turn", "tags": [ "string" ], "tid": "tid", "total_tokens": 0, "trace_id": "trace_id" } ```