Crea una risposta del modello
Usa CometAPI POST /v1/responses per creare risposte del modello Multimodal e cronologia delle conversazioni con strumenti integrati e Function Calling.
gpt-6-astra. Gli esempi mostrano anche la ricerca web, le chiamate a funzioni personalizzate, l’output strutturato, il ragionamento e Streaming.
Prosegui una conversazione
Per una conversazione solo testuale, conserva i messaggi utente e le risposte testuali dell’assistente, quindi aggiungi il messaggio utente successivo:response.output_text è una proprietà pratica dell’SDK che combina il testo dell’assistente della risposta. Le conversazioni con Function Calling richiedono anche gli elementi delle chiamate degli strumenti e dei risultati, come descritto di seguito.
Usa la ricerca web
Aggiungi uno strumentoweb_search per cercare informazioni e includere citazioni delle fonti:
web_search_call restituiti e le annotazioni URL del messaggio quando l’applicazione necessita di risultati di ricerca o citazioni. Gli altri strumenti integrati richiedono una configurazione specifica; consulta la guida agli strumenti OpenAI.
Chiamare funzioni personalizzate
Definisci gli argomenti della funzione e consenti al modello di richiedere la funzione:function_call. Il relativo campo arguments è una stringa codificata in JSON. Esegui la funzione, quindi costruisci la richiesta successiva a partire dall’input originale e dagli elementi di output restituiti senza i relativi campi id dell’elemento di risposta. Mantieni name, arguments e call_id della funzione e aggiungi un elemento function_call_output con il valore call_id corrispondente e il risultato in output.
Richiedere output strutturato
Usatext.format per richiedere JSON conforme a uno schema:
Configurare il ragionamento
Impostareasoning.effort per selezionare il livello di impegno di ragionamento del modello:
low per le attività generali e high per l’esempio di ragionamento. max_output_tokens include sia i token di ragionamento sia i token di output visibili.
Trasmettere le risposte in streaming
Impostastream su true per ricevere eventi inviati dal server:
response.created, response.in_progress e response.completed. Il testo arriva negli eventi response.output_text.delta. Gli eventi di strumenti e ragionamento dipendono dalla richiesta, quindi gestisci gli eventi in base al relativo type anziché presumere che ogni risposta abbia la stessa sequenza.
Autorizzazioni
Bearer token authentication. Use your CometAPI key.
Corpo
Model ID to use for this request. See the Models page for current options.
"gpt-6-astra"
Text, image, or file inputs to the model, used to generate a response. Can be a simple string for text-only input, or an array of input items for multimodal content (images, files) and multi-turn conversations.
A system (or developer) message inserted into the model's context. When used with previous_response_id, instructions from the previous response are not carried over — this makes it easy to swap system messages between turns.
Whether to run the model response in the background. Background responses do not return output directly — you retrieve the result later via the response ID.
Context management configuration for this request. Controls how the model manages context when the conversation exceeds the context window.
The conversation this response belongs to. Items from the conversation are prepended to input for context. Input and output items are automatically added to the conversation after the response completes. Cannot be used with previous_response_id.
Additional output data to include in the response. Use this to request extra information that is not included by default.
web_search_call.action.sources, code_interpreter_call.outputs, computer_call_output.output.image_url, file_search_call.results, message.input_image.image_url, message.output_text.logprobs, reasoning.encrypted_content An upper bound for the number of tokens that can be generated for a response, including visible output tokens and reasoning tokens.
The maximum number of total calls to built-in tools that can be processed in a response. This limit applies across all built-in tool calls, not per individual tool. Any further tool call attempts by the model will be ignored.
Set of up to 16 key-value pairs that can be attached to the response. Useful for storing additional information in a structured format. Keys have a maximum length of 64 characters; values have a maximum length of 512 characters.
Whether to allow the model to run tool calls in parallel.
An ID for a stored response that is accessible to the selected model and request context. Cannot be combined with conversation. The conversation-history example sends prior input and output items explicitly.
Reference to a prompt template and its variables.
A key used to cache responses for similar requests, helping optimize cache hit rates. Replaces the deprecated user field for caching purposes.
Legacy prompt-cache retention setting. Refer to the selected model documentation for prompt_cache_options and supported retention settings.
in_memory, 24h Reasoning configuration for the selected model.
A stable identifier for your end-users, used to help detect policy violations. Should be a hashed username or email — do not send identifying information directly.
64Specifies the processing tier for the request. When set, the response will include the actual service_tier used.
auto: Uses the tier configured in project settings (default behavior).default: Standard pricing and performance.flex: Flexible processing with potential cost savings.priority: Priority processing with faster response times.
auto, default, flex, priority Request response storage for later retrieval, when supported by the selected model and request context.
If set to true, the response data will be streamed to the client as it is generated using server-sent events (SSE). Events include response.created, response.output_text.delta, response.completed, and more.
Options for streaming responses. Only set this when stream is true.
Sampling temperature. Omit this field for GPT-6 Astra.
0 <= x <= 2Configuration for text output. Use this to request structured JSON output via JSON mode or JSON Schema.
Controls how the model selects which tool(s) to call.
auto(default): The model decides whether and which tools to call.none: The model will not call any tools.required: The model must call at least one tool.- An object specifying a particular tool to use.
Tools available to the model. This page demonstrates web_search and custom function tools. Other tool types require their own configuration; see the official tool reference.
Number of token alternatives to include for models supporting log probabilities. Requires message.output_text.logprobs in include. Omit for GPT-6 Astra.
0 <= x <= 20Nucleus sampling threshold. Omit this field for GPT-6 Astra. For sampling overrides, adjust either top_p or temperature.
0 <= x <= 1The truncation strategy for handling inputs that exceed the model's context window.
auto: The model truncates the input by dropping items from the beginning of the conversation to fit.disabled(default): The request fails with a 400 error if the input exceeds the context window.
auto, disabled Deprecated. Use safety_identifier and prompt_cache_key instead. A stable identifier for your end-user.
Risposta
The generated Response object.
Unique identifier for the response.
"resp_example"
The object type, always response.
response "response"
Unix timestamp (in seconds) of when the response was created.
1788763707
The status of the response.
completed, in_progress, failed, cancelled, queued, incomplete "completed"
Whether the response was run in the background.
false
Unix timestamp of when the response was completed, or null if still in progress.
1788763711
Error information if the response failed, or null on success.
Details about why the response is incomplete, if applicable.
The system instructions used for this response.
The maximum output token limit that was applied.
The model used for the response.
"gpt-6-astra"
An array of output items generated by the model. Each item can be a message, function call, or other output type.
Whether parallel tool calls were enabled.
The ID of the previous response, if this is a multi-turn conversation.
The reasoning configuration that was used.
The service tier actually used to process the request.
Whether the response was stored.
The temperature value used.
The text configuration used.
The tool choice setting used.
The tools that were available for this response.
The top_p value used.
The truncation strategy used.
Token usage statistics for this response.
The user identifier, if provided.
The metadata attached to this response.
Content filter results applied to the response, if any.
The frequency penalty applied to the request.
Maximum number of tool calls allowed, if set.
The presence penalty applied to the request.
Cache key for prompt caching, if applicable.
Prompt cache retention policy, if applicable.
Safety system identifier for the response, if applicable.
Number of top log probabilities returned per token position.