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    Using the API

    Features overviewClient SDKsBeta headersErrors
    Messages
    Create a Message
    Count tokens in a Message
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    Retrieve a Message Batch
    List Message Batches
    Cancel a Message Batch
    Delete a Message Batch
    Retrieve Message Batch results
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    Models
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    Messages
    Create a Message
    Count tokens in a Message
    Batches
    Create a Message Batch
    Retrieve a Message Batch
    List Message Batches
    Cancel a Message Batch
    Delete a Message Batch
    Retrieve Message Batch results
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    Completions
    Create a Text Completion

    Support & configuration

    Rate limitsService tiersVersionsIP addressesSupported regionsOpenAI SDK compatibility
    Console
    Retrieve Message Batch results
    messages.batches.results(strmessage_batch_id) -> MessageBatchIndividualResponse
    get/v1/messages/batches/{message_batch_id}/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
    message_batch_id: str

    ID of the Message Batch.

    ReturnsExpand Collapse
    class MessageBatchIndividualResponse: …

    This is a single line in the response .jsonl file and does not represent the response as a whole.

    custom_id: str

    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: MessageBatchResult

    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.

    Accepts one of the following:
    class MessageBatchSucceededResult: …
    message: Message
    id: str

    Unique object identifier.

    The format and length of IDs may change over time.

    content: List[ContentBlock]

    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)"}]
    
    Accepts one of the following:
    class TextBlock: …
    citations: Optional[List[TextCitation]]

    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.

    Accepts one of the following:
    class CitationCharLocation: …
    cited_text: str
    document_index: int
    minimum0
    document_title: Optional[str]
    end_char_index: int
    file_id: Optional[str]
    start_char_index: int
    minimum0
    type: Literal["char_location"]
    Accepts one of the following:
    "char_location"
    class CitationPageLocation: …
    cited_text: str
    document_index: int
    minimum0
    document_title: Optional[str]
    end_page_number: int
    file_id: Optional[str]
    start_page_number: int
    minimum1
    type: Literal["page_location"]
    Accepts one of the following:
    "page_location"
    class CitationContentBlockLocation: …
    cited_text: str
    document_index: int
    minimum0
    document_title: Optional[str]
    end_block_index: int
    file_id: Optional[str]
    start_block_index: int
    minimum0
    type: Literal["content_block_location"]
    Accepts one of the following:
    "content_block_location"
    class CitationsWebSearchResultLocation: …
    cited_text: str
    encrypted_index: str
    title: Optional[str]
    maxLength512
    type: Literal["web_search_result_location"]
    Accepts one of the following:
    "web_search_result_location"
    url: str
    class CitationsSearchResultLocation: …
    cited_text: str
    end_block_index: int
    search_result_index: int
    minimum0
    source: str
    start_block_index: int
    minimum0
    title: Optional[str]
    type: Literal["search_result_location"]
    Accepts one of the following:
    "search_result_location"
    text: str
    maxLength5000000
    minLength0
    type: Literal["text"]
    Accepts one of the following:
    "text"
    class ThinkingBlock: …
    signature: str
    thinking: str
    type: Literal["thinking"]
    Accepts one of the following:
    "thinking"
    class RedactedThinkingBlock: …
    data: str
    type: Literal["redacted_thinking"]
    Accepts one of the following:
    "redacted_thinking"
    class ToolUseBlock: …
    id: str
    input: Dict[str, object]
    name: str
    minLength1
    type: Literal["tool_use"]
    Accepts one of the following:
    "tool_use"
    class ServerToolUseBlock: …
    id: str
    input: Dict[str, object]
    name: Literal["web_search"]
    Accepts one of the following:
    "web_search"
    type: Literal["server_tool_use"]
    Accepts one of the following:
    "server_tool_use"
    class WebSearchToolResultBlock: …
    content: WebSearchToolResultBlockContent
    Accepts one of the following:
    class WebSearchToolResultError: …
    error_code: Literal["invalid_tool_input", "unavailable", "max_uses_exceeded", 2 more]
    Accepts one of the following:
    "invalid_tool_input"
    "unavailable"
    "max_uses_exceeded"
    "too_many_requests"
    "query_too_long"
    type: Literal["web_search_tool_result_error"]
    Accepts one of the following:
    "web_search_tool_result_error"
    UnionMember1 = List[WebSearchResultBlock]
    encrypted_content: str
    page_age: Optional[str]
    title: str
    type: Literal["web_search_result"]
    Accepts one of the following:
    "web_search_result"
    url: str
    tool_use_id: str
    type: Literal["web_search_tool_result"]
    Accepts one of the following:
    "web_search_tool_result"
    model: Model

    The model that will complete your prompt.

    See models for additional details and options.

    Accepts one of the following:
    UnionMember0 = Literal["claude-3-7-sonnet-latest", "claude-3-7-sonnet-20250219", "claude-3-5-haiku-latest", 15 more]

    The model that will complete your prompt.

    See models for additional details and options.

    • claude-3-7-sonnet-latest - Deprecated: Will reach end-of-life on February 19th, 2026. Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.
    • claude-3-7-sonnet-20250219 - Deprecated: Will reach end-of-life on February 19th, 2026. Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.
    • claude-3-5-haiku-latest - Fastest and most compact model for near-instant responsiveness
    • claude-3-5-haiku-20241022 - Our fastest model
    • claude-haiku-4-5 - Hybrid model, capable of near-instant responses and extended thinking
    • claude-haiku-4-5-20251001 - Hybrid model, capable of near-instant responses and extended thinking
    • claude-sonnet-4-20250514 - High-performance model with extended thinking
    • claude-sonnet-4-0 - High-performance model with extended thinking
    • claude-4-sonnet-20250514 - High-performance model with extended thinking
    • claude-sonnet-4-5 - Our best model for real-world agents and coding
    • claude-sonnet-4-5-20250929 - Our best model for real-world agents and coding
    • claude-opus-4-0 - Our most capable model
    • claude-opus-4-20250514 - Our most capable model
    • claude-4-opus-20250514 - Our most capable model
    • claude-opus-4-1-20250805 - Our most capable model
    • claude-3-opus-latest - Deprecated: Will reach end-of-life on January 5th, 2026. Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.
    • claude-3-opus-20240229 - Deprecated: Will reach end-of-life on January 5th, 2026. Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.
    • claude-3-haiku-20240307 - Our previous most fast and cost-effective
    Accepts one of the following:
    "claude-3-7-sonnet-latest"

    High-performance model with early extended thinking

    "claude-3-7-sonnet-20250219"

    High-performance model with early extended thinking

    "claude-3-5-haiku-latest"

    Fastest and most compact model for near-instant responsiveness

    "claude-3-5-haiku-20241022"

    Our fastest model

    "claude-haiku-4-5"

    Hybrid model, capable of near-instant responses and extended thinking

    "claude-haiku-4-5-20251001"

    Hybrid model, capable of near-instant responses and extended thinking

    "claude-sonnet-4-20250514"

    High-performance model with extended thinking

    "claude-sonnet-4-0"

    High-performance model with extended thinking

    "claude-4-sonnet-20250514"

    High-performance model with extended thinking

    "claude-sonnet-4-5"

    Our best model for real-world agents and coding

    "claude-sonnet-4-5-20250929"

    Our best model for real-world agents and coding

    "claude-opus-4-0"

    Our most capable model

    "claude-opus-4-20250514"

    Our most capable model

    "claude-4-opus-20250514"

    Our most capable model

    "claude-opus-4-1-20250805"

    Our most capable model

    "claude-3-opus-latest"

    Excels at writing and complex tasks

    "claude-3-opus-20240229"

    Excels at writing and complex tasks

    "claude-3-haiku-20240307"

    Our previous most fast and cost-effective

    UnionMember1 = str
    role: Literal["assistant"]

    Conversational role of the generated message.

    This will always be "assistant".

    Accepts one of the following:
    "assistant"
    stop_reason: Optional[StopReason]

    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 requested max_tokens or the model's maximum
    • "stop_sequence": one of your provided custom stop_sequences was 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.

    Accepts one of the following:
    "end_turn"
    "max_tokens"
    "stop_sequence"
    "tool_use"
    "pause_turn"
    "refusal"
    stop_sequence: Optional[str]

    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: Literal["message"]

    Object type.

    For Messages, this is always "message".

    Accepts one of the following:
    "message"
    usage: 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.

    cache_creation: Optional[CacheCreation]

    Breakdown of cached tokens by TTL

    ephemeral_1h_input_tokens: int

    The number of input tokens used to create the 1 hour cache entry.

    minimum0
    ephemeral_5m_input_tokens: int

    The number of input tokens used to create the 5 minute cache entry.

    minimum0
    cache_creation_input_tokens: Optional[int]

    The number of input tokens used to create the cache entry.

    minimum0
    cache_read_input_tokens: Optional[int]

    The number of input tokens read from the cache.

    minimum0
    input_tokens: int

    The number of input tokens which were used.

    minimum0
    output_tokens: int

    The number of output tokens which were used.

    minimum0
    server_tool_use: Optional[ServerToolUsage]

    The number of server tool requests.

    web_search_requests: int

    The number of web search tool requests.

    minimum0
    service_tier: Optional[Literal["standard", "priority", "batch"]]

    If the request used the priority, standard, or batch tier.

    Accepts one of the following:
    "standard"
    "priority"
    "batch"
    type: Literal["succeeded"]
    Accepts one of the following:
    "succeeded"
    class MessageBatchErroredResult: …
    error: ErrorResponse
    error: ErrorObject
    Accepts one of the following:
    class InvalidRequestError: …
    message: str
    type: Literal["invalid_request_error"]
    Accepts one of the following:
    "invalid_request_error"
    class AuthenticationError: …
    message: str
    type: Literal["authentication_error"]
    Accepts one of the following:
    "authentication_error"
    class BillingError: …
    message: str
    type: Literal["billing_error"]
    Accepts one of the following:
    "billing_error"
    class PermissionError: …
    message: str
    type: Literal["permission_error"]
    Accepts one of the following:
    "permission_error"
    class NotFoundError: …
    message: str
    type: Literal["not_found_error"]
    Accepts one of the following:
    "not_found_error"
    class RateLimitError: …
    message: str
    type: Literal["rate_limit_error"]
    Accepts one of the following:
    "rate_limit_error"
    class GatewayTimeoutError: …
    message: str
    type: Literal["timeout_error"]
    Accepts one of the following:
    "timeout_error"
    class APIErrorObject: …
    message: str
    type: Literal["api_error"]
    Accepts one of the following:
    "api_error"
    class OverloadedError: …
    message: str
    type: Literal["overloaded_error"]
    Accepts one of the following:
    "overloaded_error"
    request_id: Optional[str]
    type: Literal["error"]
    Accepts one of the following:
    "error"
    type: Literal["errored"]
    Accepts one of the following:
    "errored"
    class MessageBatchCanceledResult: …
    type: Literal["canceled"]
    Accepts one of the following:
    "canceled"
    class MessageBatchExpiredResult: …
    type: Literal["expired"]
    Accepts one of the following:
    "expired"
    Retrieve Message Batch results
    Python
    from anthropic import Anthropic
    
    client = Anthropic(
        api_key="my-anthropic-api-key",
    )
    message_batch_individual_response = client.messages.batches.results(
        "message_batch_id",
    )
    print(message_batch_individual_response.custom_id)
    Returns Examples
    © 2025 ANTHROPIC PBC

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    Products

    • Claude
    • Claude Code
    • Max plan
    • Team plan
    • Enterprise plan
    • Download app
    • Pricing
    • Log in

    Features

    • Claude and Slack
    • Claude in Excel

    Models

    • Opus
    • Sonnet
    • Haiku

    Solutions

    • AI agents
    • Code modernization
    • Coding
    • Customer support
    • Education
    • Financial services
    • Government
    • Life sciences

    Claude Developer Platform

    • Overview
    • Developer docs
    • Pricing
    • Amazon Bedrock
    • Google Cloud’s Vertex AI
    • Console login

    Learn

    • Blog
    • Catalog
    • Courses
    • Use cases
    • Connectors
    • Customer stories
    • Engineering at Anthropic
    • Events
    • Powered by Claude
    • Service partners
    • Startups program

    Company

    • Anthropic
    • Careers
    • Economic Futures
    • Research
    • News
    • Responsible Scaling Policy
    • Security and compliance
    • Transparency

    Help and security

    • Availability
    • Status
    • Support center

    Terms and policies

    • Privacy policy
    • Responsible disclosure policy
    • Terms of service: Commercial
    • Terms of service: Consumer
    • Usage policy
    © 2025 ANTHROPIC PBC