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Récupérer les résultats d'un lot de messages

beta.messages.batches.results(message_batch_id, **kwargs) -> JSONLDecoder[BetaMessageBatchIndividualResponse]
GET/v1/messages/batches/{message_batch_id}/results

Diffuse en streaming les résultats d'un lot de messages sous forme de fichier .jsonl.

Chaque ligne du fichier est un objet JSON contenant le résultat d'une requête unique du lot de messages. L'ordre des résultats n'est pas garanti identique à celui des requêtes. Utilisez le champ custom_id pour faire correspondre les résultats aux requêtes.

Pour en savoir plus sur l'API Message Batches, consultez notre guide de l'utilisateur.

Parameters
message_batch_id: str⁠Path parameter

ID of the Message Batch.

betas: Optional[List[AnthropicBetaParam]]⁠Header parameter

Optional header to specify the beta version(s) you want to use.

One of the following:
str
"message-batches-2024-09-24"
"prompt-caching-2024-07-31"
"computer-use-2024-10-22"
"computer-use-2025-01-24"
"pdfs-2024-09-25"
"token-counting-2024-11-01"
"token-efficient-tools-2025-02-19"
"output-128k-2025-02-19"
"files-api-2025-04-14"
"mcp-client-2025-04-04"
"mcp-client-2025-11-20"
"dev-full-thinking-2025-05-14"
"interleaved-thinking-2025-05-14"
"code-execution-2025-05-22"
"extended-cache-ttl-2025-04-11"
"context-1m-2025-08-07"
"context-management-2025-06-27"
"model-context-window-exceeded-2025-08-26"
"skills-2025-10-02"
"fast-mode-2026-02-01"
"output-300k-2026-03-24"
"user-profiles-2026-03-24"
"user-profiles-2026-08-18"
"user-profiles-2026-09-04"
"advisor-tool-2026-03-01"
"managed-agents-2026-04-01"
"cache-diagnosis-2026-04-07"
"dreaming-2026-04-21"
"thinking-token-count-2026-05-13"
"server-side-fallback-2026-06-01"
"server-side-fallback-2026-07-01"
"fallback-credit-2026-06-01"
"fallback-credit-2026-07-01"
"agent-memory-2026-07-22"
"mid-conversation-tool-changes-2026-07-01"
"compact-2026-01-12"
"computer-use-2025-11-24"
"mcp-tunnels-2026-06-22"
"structured-outputs-2025-11-13"
"task-budgets-2026-03-13"
"thinking-display-updates-2026-08-18"
"ce-user-management-2026-07-13"
"mid-conversation-output-config-2026-07-01"
"thinking-binding-controls-2026-08-01"
"mid-conversation-system-clear-at-2026-08-21"
"compact-2026-09-04"
"inline-tools-2026-09-15"
"mcp-client-2026-09-15"
"ce-plugins-2026-09-01"
"spend-limit-reads-2026-09-26"
workspace_id: Optional[str]⁠Header parameter

Optional header to select the Workspace for this request. The value is a Workspace ID (for example, wrkspc_011CZkZaBF1tNoB5wlCeusgy).

Only needed for credentials that can act on more than one Workspace. A credential that belongs to a specific Workspace may omit it; if sent, it must match that Workspace.

Returns
class BetaMessageBatchIndividualResponse: custom_id; result

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: BetaMessageBatchResult

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.

One of the following:
Récupérer les résultats d'un lot de messages
import os
from anthropic import Anthropic

client = Anthropic(
    api_key=os.environ.get(
        "ANTHROPIC_API_KEY"
    ),  # This is the default and can be omitted
)
for batch in client.beta.messages.batches.results(
    message_batch_id="message_batch_id",
):
    print(batch)