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fc75d07504
## TL;DR WIP esp the examples Thin the Python SDK public surface so the wrapper layer returns canonical app-server generated models directly. - keeps `Codex` / `AsyncCodex` / `Thread` / `Turn` and input helpers, but removes alias-only type layers and custom result models - `metadata` now returns `InitializeResponse` and `run()` returns the generated app-server `Turn` - updates docs, examples, notebook, and tests to use canonical generated types and regenerates `v2_all.py` against current schema - keeps the pinned runtime-package integration flow and real integration coverage ## Validation - `PYTHONPATH=sdk/python/src python3 -m pytest sdk/python/tests` - `GH_TOKEN="$(gh auth token)" RUN_REAL_CODEX_TESTS=1 PYTHONPATH=sdk/python/src python3 -m pytest sdk/python/tests -rs` --------- Co-authored-by: Codex <noreply@openai.com>
79 lines
2.3 KiB
Python
79 lines
2.3 KiB
Python
import json
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import sys
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from pathlib import Path
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_EXAMPLES_ROOT = Path(__file__).resolve().parents[1]
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if str(_EXAMPLES_ROOT) not in sys.path:
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sys.path.insert(0, str(_EXAMPLES_ROOT))
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from _bootstrap import (
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assistant_text_from_turn,
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ensure_local_sdk_src,
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find_turn_by_id,
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runtime_config,
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)
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ensure_local_sdk_src()
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from codex_app_server import (
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AskForApproval,
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Codex,
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Personality,
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ReasoningSummary,
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TextInput,
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)
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OUTPUT_SCHEMA = {
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"type": "object",
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"properties": {
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"summary": {"type": "string"},
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"actions": {
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"type": "array",
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"items": {"type": "string"},
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},
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},
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"required": ["summary", "actions"],
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"additionalProperties": False,
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}
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SUMMARY = ReasoningSummary.model_validate("concise")
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PROMPT = (
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"Analyze a safe rollout plan for enabling a feature flag in production. "
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"Return JSON matching the requested schema."
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)
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APPROVAL_POLICY = AskForApproval.model_validate("never")
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with Codex(config=runtime_config()) as codex:
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thread = codex.thread_start(model="gpt-5.4", config={"model_reasoning_effort": "high"})
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turn = thread.turn(
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TextInput(PROMPT),
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approval_policy=APPROVAL_POLICY,
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output_schema=OUTPUT_SCHEMA,
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personality=Personality.pragmatic,
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summary=SUMMARY,
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)
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result = turn.run()
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persisted = thread.read(include_turns=True)
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persisted_turn = find_turn_by_id(persisted.thread.turns, result.id)
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structured_text = assistant_text_from_turn(persisted_turn).strip()
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try:
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structured = json.loads(structured_text)
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except json.JSONDecodeError as exc:
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raise RuntimeError(f"Expected JSON matching OUTPUT_SCHEMA, got: {structured_text!r}") from exc
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summary = structured.get("summary")
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actions = structured.get("actions")
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if not isinstance(summary, str) or not isinstance(actions, list) or not all(
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isinstance(action, str) for action in actions
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):
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raise RuntimeError(f"Expected structured output with string summary/actions, got: {structured!r}")
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print("Status:", result.status)
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print("summary:", summary)
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print("actions:")
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for action in actions:
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print("-", action)
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print("Items:", 0 if persisted_turn is None else len(persisted_turn.items or []))
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