Understand first
New to this knowledge point
Complete the prerequisite concepts, read the principles and counterexamples, and then explain why in your own words.
Start with core principles →Understand → Implement → Debug → Design
Judge the end of transfer, model termination, output type and tool results separately to know which fragments can be previewed and which states can be delivered.
Knowledge content check2026-10-03 · Check the source of the original question2026-10-03
Select the starting point based on the current basis, or you can go deeper one by one. When you encounter an unfamiliar concept, go back to the core principles first; use the knowledge exercises to check your understanding when you are finished.
New to this knowledge point
Complete the prerequisite concepts, read the principles and counterexamples, and then explain why in your own words.
Start with core principles →Prepare to write the principles into code
Understand implementation steps and boundaries, complete small tasks, and check results against acceptance requirements.
Reading implementation and trade-offs →Need to handle failures and changes in conditions
Follow the continuous questioning to locate the failure premise, and then compare the migration cases to explain how the plan should be adjusted.
Continue to delve deeper into the problem →Need to design or review plans
Combine engineering deductions and senior self-evaluation standards to explain the applicable conditions, costs and alternatives of the plan.
Analyze engineering scenarios →LEARN · PRACTICE · REFLECT
First read along the principles, Q&A and migration cases. When you need to check your understanding, switch to reinforcement exercises or start personal recording.
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Core concept · Model-response lifecycle and completion semantics
Preparatory concepts:Request and response life cycle, Typed messages and streaming events
A build completion is a scoped protocol fact: it describes which response or content item reaches what boundary and cannot be expanded to a normal answer, a correct conclusion, or a tool business success. The parsable grammar only proves the current string form, and the termination event and content type help determine subsequent actions; when there is no final state evidence, it remains unknown to avoid disguising lack of information as failure or success.
A broken database connection does not prove remote rollback; a broken stream describes observation, not the remote generation outcome. Track trusted transport termination, generation status, content types such as text/refusal/call, and external action status. Queued or generating responses are not failures merely because they are nonterminal. These dimensions are application design, not universal vendor enums.
Client-side function calls transfer work to the application. The model proposes a call, the application executes it and returns results, and a later generation may answer the task. One response can therefore be complete while the task awaits tool results. Refusals can be typed normal-path results. Read filtering, incompleteness reasons, and refusal fields under the target protocol rather than inferring them solely from HTTP status.
A complete tool item permits validation and scheduling; a complete response establishes that round’s output set; a business receipt establishes an action’s effect. Early handling of complete items changes scheduling but cannot turn later missing events into observed events. Measure latency benefits separately. Not every API requires waiting for the entire response. Related units cover tool validation and duplicate effects; this unit identifies when particular evidence becomes available.
A preview saying “report complete” cannot override a later known-incomplete terminal status. Keep the preview and label incomplete delivery rather than exporting a partial report as final. Conversely, normal termination only makes content eligible for evaluation: empty output, missing answers, and factual errors remain contract failures.
Inspect terminal status and every typed output item, not only HTTP 200, text closure, or output_text. Distinguish prose, client tool calls, refusals, and known incompleteness; missing trusted termination leaves uncertainty. Streamed text is a preview. Assemble complete tool arguments by call identity before execution. Response completion does not establish tool-business completion, which needs separate receipts.
When the backend receives an HTTP 200, it simply means that the request entered the successful response path; errors may still occur later in the flow. The model sent a sentence "processed", which was just the content. The application at least separately records: whether the connection has completely read the termination information, why the model stopped, what types of output there are, and what the results of the business actions are. The "complete text" here means that the generation process is complete and content acceptance can be entered, and it cannot be used to conclude that the answer is factually correct.
Taking OpenAI Responses as an example, the response has a status field; completed differs from incomplete, failed, and other states; incomplete_details can explain the reason for the stop. Also traverse output: output_text, function call items and rejection content in normal messages are not the same result. output_text of the official SDK is a convenience attribute for text aggregation. When there is no text block, an empty string will be returned; an empty string cannot alone prove failure, and completed cannot alone prove that normal text can be obtained. Status and output definitions.
If the output is a function call executed by the application, the complete call should be received, handed over to the tool process, and then the result returned according to the interface; the end of the model response this time may mean that it is waiting for the tool, and the entire task has not yet been completed. If the output is a refusal, the corresponding description will be displayed, and the business JSON will not be parsed with the rejected content; if it is known to be incomplete, the truncation and reason will be indicated, and the missing parameters must not be invented on the model’s behalf. None of them equal a network failure.
Text increments are available for previews marked "Building". Tool parameters are accumulated separately according to the identity of the response and output items. Parallel calls cannot be combined into a string; seeing the right bracket or being able to do JSON.parse is just a grammatical phenomenon and does not prove that the model has ended the call. The parameter completion event and output item completion event of Responses express their respective boundaries, and the entire response also has its own termination information. The application can choose to wait for the trusted response to terminate before scheduling; if it is scheduled for low latency after the complete tool item is closed, the interface semantics and execution strategy must be clearly defined, and the tool results must be tracked independently. Any strategy does not execute unfinished parameters, nor does it regard parameter completion events as evidence of business success.
Disconnecting without reading the trusted termination information only means that the local server does not know the final status and cannot declare server failure or cancellation. When there is a response ID, the endpoint supports querying, and the response can be read, the original response can be read for verification; OpenAI's storage configuration will affect this path and does not extend the query capability to all interfaces. If the query is unavailable or the final status cannot be obtained, it will remain unknown and explain to the user that some of the content has not yet been confirmed; regeneration is a new response, not the result of making up the original response.
Claude Messages sends top-level changes and message_stop after the content block. The application also depends on stop_reason: natural end, tool request, quota truncation or server tool suspension have different follow-up actions. content_block_stop does not mean that the entire message is completed, and message_stop does not mean that the business is successful. Messages lifecycle definitions. Therefore, cross-interface adaptation should retain the original termination reason and then normalize it to a clear application state; the differences must not be erased by a generic done state.
Continue reading along with the premises and constraints of the problem. Understand the reference answers first, then try to put away the answers and explain the cause and effect and trade-offs in your own words.
Level 1Streaming tool parameters can be parsed into JSON, why can’t they be executed directly?
The main question separates the content from the life cycle. Here, a counterexample with complete syntax but lack of protocol boundaries is used to test understanding.
No. Parsability only shows that the current characters constitute a certain JSON value, and does not prove that the calling item is closed, has a complete identity, or that the subsequent status is acceptable. The SDK's incremental parsing objects may also be intermediate views. Accumulate the fragments of the specified call according to the identity of response/item/call, wait for the target interface to provide complete parameters and item boundaries, then verify and enter the schedule; arguments.done and output_item.done of Responses are different events. If the strategy of waiting for the response to terminate is adopted, then check the final status of the round. Don't rely on bracket counting to replace lifetime, and don't share a buffer with tool call parameters and ordinary text.
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Level 2The parameters are completed and the tool item is closed, but the connection is disconnected before the entire response is terminated. Can this round be recorded as success or failure?
The parent question determines the tool item boundary, and the child question joins the outer layer to terminate the evidence, indicating that the inner layer completion cannot push out the outer layer completion.
Neither can be derived from this trajectory alone. It can be confirmed that the parameter boundary of this call item has appeared, but the final state of the entire response is still unknown; there is no evidence whether there will be subsequent output, whether it is incomplete or failed. The conservative strategy for this question will suspend scheduling and check the original response. If the interface supports reading by ID and the object can be read, the original result can be queried; it cannot be assumed that it can still be queried under conditions such as disabling storage. Failure to find it does not mean that the remote end failed. Record known items and unknown responses, and the page states that the final status is unconfirmed, rather than deleting the complete item that has been received.
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Level 3If the application has started a read-only query after completing the tool item, and then the flow is cut off, should the query results be discarded and the model request reinitiated?
The parent question has not yet been scheduled, and the child question changes to the tool that has been started; at this time, the business facts that occur in parallel must be retained to verify the necessity of the hierarchical state.
There is no need to invalidate the query fact just because the channel is disconnected. Keep two records of "response final status unknown" and "query execution status". If the query is successful, its call association and results will be saved. If it is not completed, continue to observe the status of the query itself. The new model request has a new response identity, and the old response will not be naturally restored; first check whether the old output can be restored, and then decide whether to start a new round based on a clear strategy. The write operation retry algorithm is not discussed here; the key is that the observation channel, generation status, and tool results do not pretend to be evidence of each other. During verification, mark the interruption point and query completion point on the same track. You cannot use failed to clear all statuses.
Level 1Why might there still be no deliverable normal answer after receiving a completion mark for a model?
Change the output type when evidence of termination is available, explaining why transmission and generation complete are not sufficient to determine delivery.
The completion mark first indicates that the generation has reached the termination boundary defined by the interface, and then checks the output type and task contract. The completed output of Responses can contain client function calls or rejections, and an empty output_text aggregate does not mean failure. Calling means handing over control to the tool process; rejection should enter the corresponding product state; normal text still needs to be accepted. Only when the results truly meet the delivery conditions of this task can the task be said to be completed. The model’s claim that something is “processed” cannot override the absence of tool results, nor can it be input as normal structured data if it is rejected.
Level 1What will be lost by switching OpenAI Responses to Claude Messages and only unifying it to the done Boolean value?
The constraint changes from one interface to several: the abstraction must preserve meaning rather than merely standardize field names.
The stop reason, content item closure, and execution position will be lost. Responses uses status and typed output, and Claude Messages uses content block and stop_reason; Claude's content_block_stop is just the end of a block, and message_stop needs to be judged in conjunction with the reason. end_turn, tool_use, max_tokens and pause_turn respectively point to different actions. The pause of the server tool cannot be directly handed over to the client to rerun the tool. The adaptation layer can unify the status of "preview/pending tool/rejection/incomplete/final state unknown" of the application, but retain the original fields; when encountering unrecognized events or reasons, it should not default to success, and should be recorded and processed according to the compatibility policy.
First find out the conditions for change, and then determine which premises in the original plan still hold true. The following cases are teaching deductions to facilitate the transfer of principles to new problems.
Changing conditions:Users can read the generated draft and change it to another system that requires a complete JSON document before it can be imported; failed content cannot be input into the downstream as a draft.
Extended question:The JSON text has been closed, but the final status is incomplete, or a refusal has been received. Can it be delivered directly?
You cannot deliver on closure alone. First check the termination status and typed content of the specified interface; incomplete means that the complete generation of this round has not been obtained, and refusal takes the rejection path. Even if structured output is configured, it cannot be assumed that it conforms to the business schema. Keep the diagnosis and preview, but prevent automatic import; if it is regenerated, a new response will be generated and re-accepted, and the text will not be supplemented by itself. Only the complete target content has been confirmed before structural and business verification. The independent acceptance of some chapters is another contract that needs to be clearly stated, and overall failure cannot be temporarily interpreted as overall completion.
The principles that remain unchanged:Display rights and consumption rights can be different. Delivery must have completion evidence that complies with the target artifact contract. Legal grammar cannot replace it.
Changing conditions:The application originally executed the custom function and switched to the server-side tool round of Claude Messages; the execution location and stop reason changed.
Extended question:When message_stop is received and stop_reason is pause_turn, should the local tool with the same name be executed once and then be declared complete?
Should not. pause_turn means that the server tool loop is paused, and its document processing is to add the received assistant content to the session and request continuation; continue within budget and turn limits, rather than translating the server tool items into custom local functions. The server may have generated tool results, identified and retained by type, and it cannot be assumed that there is no action just because it has not been executed locally. message_stop confirms the end of the message, but does not prove that the task has received a final reply; the output after continuing the round is still accepted according to the stop reason and task conditions.
The principles that remain unchanged:The termination boundary belongs to the specific interface and execution layer; after the execution position changes, the end of a generation must still be separated from the completion of the task.
Written based on the OpenAI and Claude official documents and OpenAI official SDK source code read on 2026-10-03. The event trajectory is a teaching hypothesis, and no real model has been run, and no new production experience, manufacturer consistency guarantee or tool execution effect has been added. New Q&A and migration cases are added for principle explanation, and source verification and case operation verification are recorded separately.
After reading, you can explain the principles, boundaries, and trade-offs against these standards. It is up to you to evaluate your mastery; if further verification is needed, complete the small tasks below.
Without calling the real model, use paper or local tables to interpret five teaching tracks: A. response.completed after text increment, including normal text; B. response.completed after complete function_call, the client tool has not yet been executed; C. response.completed, the message content is refusal; D. response.incomplete and the reason is max_output_tokens; E. tool response.function_call_arguments.done, response.output_item.done Then the connection was disconnected and the entire response was not terminated. For each entry, fill in the transmission evidence, whether the final state of the model is known, the content type, the allowed next step, and the status description for the user. Then change E to "The read-only tool has been started after the complete item" and re-judge the two statuses.