Retrieve Message Batch results
Streams the results of a Message Batch as a .jsonl file.
Each line in the file is a JSON object containing the result of a single request in the Message Batch. Results are not guaranteed to be in the same order as requests. Use the custom_id field to match results to requests.
Learn more about the Message Batches API in our user guide
ParametersExpand Collapse
ID of the Message Batch.
ReturnsExpand Collapse
type MessageBatchIndividualResponse struct{…}This is a single line in the response .jsonl file and does not represent the response as a whole.
This is a single line in the response .jsonl file and does not represent the response as a whole.
CustomID stringDeveloper-provided ID created for each request in a Message Batch. Useful for matching results to requests, as results may be given out of request order.
Developer-provided ID created for each request in a Message Batch. Useful for matching results to requests, as results may be given out of request order.
Must be unique for each request within the Message Batch.
Result MessageBatchResultUnionProcessing result for this request.
Processing result for this request.
Contains a Message output if processing was successful, an error response if processing failed, or the reason why processing was not attempted, such as cancellation or expiration.
type MessageBatchSucceededResult struct{…}
Message Message
ID stringUnique object identifier.
Unique object identifier.
The format and length of IDs may change over time.
Container ContainerInformation about the container used in the request (for the code execution tool)
Information about the container used in the request (for the code execution tool)
Identifier for the container used in this request
The time at which the container will expire.
Content []ContentBlockUnionContent generated by the model.
Content generated by the model.
This is an array of content blocks, each of which has a type that determines its shape.
Example:
[{"type": "text", "text": "Hi, I'm Claude."}]
If the request input messages ended with an assistant turn, then the response content will continue directly from that last turn. You can use this to constrain the model's output.
For example, if the input messages were:
[
{"role": "user", "content": "What's the Greek name for Sun? (A) Sol (B) Helios (C) Sun"},
{"role": "assistant", "content": "The best answer is ("}
]
Then the response content might be:
[{"type": "text", "text": "B)"}]
type TextBlock struct{…}
Citations []TextCitationUnionCitations supporting the text block.
Citations supporting the text block.
The type of citation returned will depend on the type of document being cited. Citing a PDF results in page_location, plain text results in char_location, and content document results in content_block_location.
type CitationCharLocation struct{…}
type CitationPageLocation struct{…}
type CitationContentBlockLocation struct{…}
type CitationsWebSearchResultLocation struct{…}
type CitationsSearchResultLocation struct{…}
type ThinkingBlock struct{…}
type RedactedThinkingBlock struct{…}
type ToolUseBlock struct{…}
Caller ToolUseBlockCallerUnionTool invocation directly from the model.
Tool invocation directly from the model.
type DirectCaller struct{…}Tool invocation directly from the model.
Tool invocation directly from the model.
type ServerToolCaller struct{…}Tool invocation generated by a server-side tool.
Tool invocation generated by a server-side tool.
type ServerToolCaller20260120 struct{…}
type ServerToolUseBlock struct{…}
Caller ServerToolUseBlockCallerUnionTool invocation directly from the model.
Tool invocation directly from the model.
type DirectCaller struct{…}Tool invocation directly from the model.
Tool invocation directly from the model.
type ServerToolCaller struct{…}Tool invocation generated by a server-side tool.
Tool invocation generated by a server-side tool.
type ServerToolCaller20260120 struct{…}
Name ServerToolUseBlockName
type WebSearchToolResultBlock struct{…}
Caller WebSearchToolResultBlockCallerUnionTool invocation directly from the model.
Tool invocation directly from the model.
type DirectCaller struct{…}Tool invocation directly from the model.
Tool invocation directly from the model.
type ServerToolCaller struct{…}Tool invocation generated by a server-side tool.
Tool invocation generated by a server-side tool.
type ServerToolCaller20260120 struct{…}
type WebSearchToolResultError struct{…}
ErrorCode WebSearchToolResultErrorCode
type WebSearchToolResultBlockContentArray []WebSearchResultBlock
type WebFetchToolResultBlock struct{…}
Caller WebFetchToolResultBlockCallerUnionTool invocation directly from the model.
Tool invocation directly from the model.
type DirectCaller struct{…}Tool invocation directly from the model.
Tool invocation directly from the model.
type ServerToolCaller struct{…}Tool invocation generated by a server-side tool.
Tool invocation generated by a server-side tool.
type ServerToolCaller20260120 struct{…}
Content WebFetchToolResultBlockContentUnion
type WebFetchToolResultErrorBlock struct{…}
ErrorCode WebFetchToolResultErrorCode
type WebFetchBlock struct{…}
Content DocumentBlock
Citations CitationsConfigCitation configuration for the document
Citation configuration for the document
Source DocumentBlockSourceUnion
type Base64PDFSource struct{…}
type PlainTextSource struct{…}
The title of the document
ISO 8601 timestamp when the content was retrieved
Fetched content URL
type CodeExecutionToolResultBlock struct{…}
Code execution result with encrypted stdout for PFC + web_search results.
Code execution result with encrypted stdout for PFC + web_search results.
type CodeExecutionToolResultError struct{…}
ErrorCode CodeExecutionToolResultErrorCode
type CodeExecutionResultBlock struct{…}
Content []CodeExecutionOutputBlock
type EncryptedCodeExecutionResultBlock struct{…}Code execution result with encrypted stdout for PFC + web_search results.
Code execution result with encrypted stdout for PFC + web_search results.
Content []CodeExecutionOutputBlock
type BashCodeExecutionToolResultBlock struct{…}
Content BashCodeExecutionToolResultBlockContentUnion
type BashCodeExecutionToolResultError struct{…}
ErrorCode BashCodeExecutionToolResultErrorCode
type BashCodeExecutionResultBlock struct{…}
Content []BashCodeExecutionOutputBlock
type TextEditorCodeExecutionToolResultBlock struct{…}
Content TextEditorCodeExecutionToolResultBlockContentUnion
type TextEditorCodeExecutionToolResultError struct{…}
type TextEditorCodeExecutionViewResultBlock struct{…}
FileType TextEditorCodeExecutionViewResultBlockFileType
type TextEditorCodeExecutionCreateResultBlock struct{…}
type TextEditorCodeExecutionStrReplaceResultBlock struct{…}
type ToolSearchToolResultBlock struct{…}
Content ToolSearchToolResultBlockContentUnion
type ToolSearchToolResultError struct{…}
ErrorCode ToolSearchToolResultErrorCode
type ToolSearchToolSearchResultBlock struct{…}
ToolReferences []ToolReferenceBlock
type ContainerUploadBlock struct{…}Response model for a file uploaded to the container.
Response model for a file uploaded to the container.
Model ModelThe model that will complete your prompt.
The model that will complete your prompt.
See models for additional details and options.
type Model stringThe model that will complete your prompt.
The model that will complete your prompt.
See models for additional details and options.
Most intelligent model for building agents and coding
Frontier intelligence at scale — built for coding, agents, and enterprise workflows
Premium model combining maximum intelligence with practical performance
Premium model combining maximum intelligence with practical performance
High-performance model with early extended thinking
High-performance model with early extended thinking
Fastest and most compact model for near-instant responsiveness
Our fastest model
Hybrid model, capable of near-instant responses and extended thinking
Hybrid model, capable of near-instant responses and extended thinking
High-performance model with extended thinking
High-performance model with extended thinking
High-performance model with extended thinking
Our best model for real-world agents and coding
Our best model for real-world agents and coding
Our most capable model
Our most capable model
Our most capable model
Our most capable model
Excels at writing and complex tasks
Excels at writing and complex tasks
Our previous most fast and cost-effective
Role AssistantConversational role of the generated message.
Conversational role of the generated message.
This will always be "assistant".
StopReason StopReasonThe reason that we stopped.
The reason that we stopped.
This may be one the following values:
"end_turn": the model reached a natural stopping point"max_tokens": we exceeded the requestedmax_tokensor the model's maximum"stop_sequence": one of your provided customstop_sequenceswas generated"tool_use": the model invoked one or more tools"pause_turn": we paused a long-running turn. You may provide the response back as-is in a subsequent request to let the model continue."refusal": when streaming classifiers intervene to handle potential policy violations
In non-streaming mode this value is always non-null. In streaming mode, it is null in the message_start event and non-null otherwise.
StopSequence stringWhich custom stop sequence was generated, if any.
Which custom stop sequence was generated, if any.
This value will be a non-null string if one of your custom stop sequences was generated.
Type MessageObject type.
Object type.
For Messages, this is always "message".
Usage UsageBilling and rate-limit usage.
Billing and rate-limit usage.
Anthropic's API bills and rate-limits by token counts, as tokens represent the underlying cost to our systems.
Under the hood, the API transforms requests into a format suitable for the model. The model's output then goes through a parsing stage before becoming an API response. As a result, the token counts in usage will not match one-to-one with the exact visible content of an API request or response.
For example, output_tokens will be non-zero, even for an empty string response from Claude.
Total input tokens in a request is the summation of input_tokens, cache_creation_input_tokens, and cache_read_input_tokens.
CacheCreation CacheCreationBreakdown of cached tokens by TTL
Breakdown of cached tokens by TTL
The number of input tokens used to create the 1 hour cache entry.
The number of input tokens used to create the 5 minute cache entry.
The number of input tokens used to create the cache entry.
The number of input tokens read from the cache.
The geographic region where inference was performed for this request.
The number of input tokens which were used.
The number of output tokens which were used.
ServerToolUse ServerToolUsageThe number of server tool requests.
The number of server tool requests.
The number of web fetch tool requests.
The number of web search tool requests.
ServiceTier UsageServiceTierIf the request used the priority, standard, or batch tier.
If the request used the priority, standard, or batch tier.
type MessageBatchErroredResult struct{…}
Error ErrorResponse
Error ErrorObjectUnion
type InvalidRequestError struct{…}
type AuthenticationError struct{…}
type BillingError struct{…}
type PermissionError struct{…}
type NotFoundError struct{…}
type RateLimitError struct{…}
type GatewayTimeoutError struct{…}
type APIErrorObject struct{…}
type OverloadedError struct{…}
type MessageBatchCanceledResult struct{…}
type MessageBatchExpiredResult struct{…}
package main
import (
"context"
"fmt"
"github.com/anthropics/anthropic-sdk-go"
"github.com/anthropics/anthropic-sdk-go/option"
)
func main() {
client := anthropic.NewClient(
option.WithAPIKey("my-anthropic-api-key"),
)
stream := client.Messages.Batches.ResultsStreaming(context.TODO(), "message_batch_id")
if stream.Err() != nil {
panic(err.Error())
}
fmt.Printf("%+v\n", messageBatchIndividualResponse.CustomID)
}