Reading the response — content blocks, stop_reason, usage (step 9/9) · llm apis

Checkpoint

One last thing before we move on. Same surface as a write step — but the lesson doesn't complete until this passes.

Final drill. Build a session-level aggregator across multiple responses. Write summarize_session(responses) that:

For each response in the list, calls parse_response(r) (provided).
Aggregates across all responses:
- total_text: all text fields joined with " | " (skip empty texts).
- tool_call_count: total number of tool_use blocks across all responses.
- total_tokens: sum of tokens across all responses.
- final_stop: the stop_reason of the LAST response.
Returns the aggregate dict.

Two sessions run. Expected output:

agent session: text='Searching... | Found Tokyo ramen guide.' tools=1 tokens=180 final=end_turn
truncated session: text='Starting...' tools=0 tokens=1024 final=max_tokens

Checkpoint

One last thing before we move on. Same surface as a write step — but the lesson doesn't complete until this passes.

Final drill. Build a session-level aggregator across multiple responses. Write summarize_session(responses) that:

For each response in the list, calls parse_response(r) (provided).
Aggregates across all responses:
- total_text: all text fields joined with " | " (skip empty texts).
- tool_call_count: total number of tool_use blocks across all responses.
- total_tokens: sum of tokens across all responses.
- final_stop: the stop_reason of the LAST response.
Returns the aggregate dict.

Two sessions run. Expected output:

agent session: text='Searching... | Found Tokyo ramen guide.' tools=1 tokens=180 final=end_turn
truncated session: text='Starting...' tools=0 tokens=1024 final=max_tokens

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Reading the response — content blocks, stop_reason, usage — step 9 of 9