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Add Python SDK public API and examples (#14446)
## 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>
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Shaqayeq
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GitHub
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@@ -0,0 +1,125 @@
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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 assistant_text_from_turn, ensure_local_sdk_src, find_turn_by_id, runtime_config
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ensure_local_sdk_src()
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import asyncio
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from codex_app_server import (
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AskForApproval,
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AsyncCodex,
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Personality,
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ReasoningEffort,
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ReasoningSummary,
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SandboxPolicy,
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TextInput,
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)
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REASONING_RANK = {
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"none": 0,
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"minimal": 1,
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"low": 2,
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"medium": 3,
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"high": 4,
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"xhigh": 5,
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}
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PREFERRED_MODEL = "gpt-5.4"
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def _pick_highest_model(models):
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visible = [m for m in models if not m.hidden] or models
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preferred = next((m for m in visible if m.model == PREFERRED_MODEL or m.id == PREFERRED_MODEL), None)
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if preferred is not None:
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return preferred
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known_names = {m.id for m in visible} | {m.model for m in visible}
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top_candidates = [m for m in visible if not (m.upgrade and m.upgrade in known_names)]
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pool = top_candidates or visible
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return max(pool, key=lambda m: (m.model, m.id))
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def _pick_highest_turn_effort(model) -> ReasoningEffort:
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if not model.supported_reasoning_efforts:
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return ReasoningEffort.medium
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best = max(
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model.supported_reasoning_efforts,
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key=lambda option: REASONING_RANK.get(option.reasoning_effort.value, -1),
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)
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return ReasoningEffort(best.reasoning_effort.value)
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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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SANDBOX_POLICY = SandboxPolicy.model_validate(
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{
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"type": "readOnly",
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"access": {"type": "fullAccess"},
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}
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)
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APPROVAL_POLICY = AskForApproval.model_validate("never")
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async def main() -> None:
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async with AsyncCodex(config=runtime_config()) as codex:
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models = await codex.models(include_hidden=True)
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selected_model = _pick_highest_model(models.data)
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selected_effort = _pick_highest_turn_effort(selected_model)
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print("selected.model:", selected_model.model)
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print("selected.effort:", selected_effort.value)
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thread = await codex.thread_start(
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model=selected_model.model,
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config={"model_reasoning_effort": selected_effort.value},
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)
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first_turn = await thread.turn(
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TextInput("Give one short sentence about reliable production releases."),
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model=selected_model.model,
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effort=selected_effort,
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)
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first = await first_turn.run()
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persisted = await thread.read(include_turns=True)
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first_persisted_turn = find_turn_by_id(persisted.thread.turns, first.id)
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print("agent.message:", assistant_text_from_turn(first_persisted_turn))
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print("items:", 0 if first_persisted_turn is None else len(first_persisted_turn.items or []))
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second_turn = await thread.turn(
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TextInput("Return JSON for a safe feature-flag rollout plan."),
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approval_policy=APPROVAL_POLICY,
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cwd=str(Path.cwd()),
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effort=selected_effort,
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model=selected_model.model,
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output_schema=OUTPUT_SCHEMA,
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personality=Personality.pragmatic,
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sandbox_policy=SANDBOX_POLICY,
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summary=ReasoningSummary.model_validate("concise"),
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)
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second = await second_turn.run()
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persisted = await thread.read(include_turns=True)
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second_persisted_turn = find_turn_by_id(persisted.thread.turns, second.id)
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print("agent.message.params:", assistant_text_from_turn(second_persisted_turn))
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print("items.params:", 0 if second_persisted_turn is None else len(second_persisted_turn.items or []))
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -0,0 +1,116 @@
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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 assistant_text_from_turn, ensure_local_sdk_src, find_turn_by_id, runtime_config
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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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ReasoningEffort,
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ReasoningSummary,
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SandboxPolicy,
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TextInput,
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)
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REASONING_RANK = {
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"none": 0,
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"minimal": 1,
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"low": 2,
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"medium": 3,
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"high": 4,
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"xhigh": 5,
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}
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PREFERRED_MODEL = "gpt-5.4"
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def _pick_highest_model(models):
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visible = [m for m in models if not m.hidden] or models
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preferred = next((m for m in visible if m.model == PREFERRED_MODEL or m.id == PREFERRED_MODEL), None)
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if preferred is not None:
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return preferred
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known_names = {m.id for m in visible} | {m.model for m in visible}
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top_candidates = [m for m in visible if not (m.upgrade and m.upgrade in known_names)]
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pool = top_candidates or visible
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return max(pool, key=lambda m: (m.model, m.id))
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def _pick_highest_turn_effort(model) -> ReasoningEffort:
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if not model.supported_reasoning_efforts:
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return ReasoningEffort.medium
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best = max(
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model.supported_reasoning_efforts,
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key=lambda option: REASONING_RANK.get(option.reasoning_effort.value, -1),
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)
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return ReasoningEffort(best.reasoning_effort.value)
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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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SANDBOX_POLICY = SandboxPolicy.model_validate(
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{
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"type": "readOnly",
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"access": {"type": "fullAccess"},
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}
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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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models = codex.models(include_hidden=True)
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selected_model = _pick_highest_model(models.data)
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selected_effort = _pick_highest_turn_effort(selected_model)
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print("selected.model:", selected_model.model)
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print("selected.effort:", selected_effort.value)
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thread = codex.thread_start(
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model=selected_model.model,
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config={"model_reasoning_effort": selected_effort.value},
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)
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first = thread.turn(
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TextInput("Give one short sentence about reliable production releases."),
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model=selected_model.model,
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effort=selected_effort,
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).run()
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persisted = thread.read(include_turns=True)
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first_turn = find_turn_by_id(persisted.thread.turns, first.id)
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print("agent.message:", assistant_text_from_turn(first_turn))
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print("items:", 0 if first_turn is None else len(first_turn.items or []))
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second = thread.turn(
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TextInput("Return JSON for a safe feature-flag rollout plan."),
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approval_policy=APPROVAL_POLICY,
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cwd=str(Path.cwd()),
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effort=selected_effort,
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model=selected_model.model,
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output_schema=OUTPUT_SCHEMA,
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personality=Personality.pragmatic,
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sandbox_policy=SANDBOX_POLICY,
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summary=ReasoningSummary.model_validate("concise"),
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).run()
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persisted = thread.read(include_turns=True)
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second_turn = find_turn_by_id(persisted.thread.turns, second.id)
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print("agent.message.params:", assistant_text_from_turn(second_turn))
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print("items.params:", 0 if second_turn is None else len(second_turn.items or []))
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