Import AITURK IDE 1.0.0-beta.1 from Hermes 63279301; preserve MIT license

tests/agent/transports/test_meta_codex_cache.py

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+"""Tests for Meta api.meta.ai prompt_cache_retention and transport plumbing."""
+
+import json
+from types import SimpleNamespace
+
+import pytest
+
+from agent.transports import get_transport
+from agent.transports.codex import _default_prompt_cache_retention_for_request
+
+
+@pytest.fixture
+def transport():
+    import agent.transports.codex  # noqa: F401
+    return get_transport("codex_responses")
+
+
+class TestMetaRetention:
+    def test_meta_retention_24h(self, transport):
+        kw = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=[],
+            base_url="https://api.meta.ai/v1",
+            session_id="test-session",
+        )
+        assert kw.get("prompt_cache_retention") == "24h"
+
+    def test_meta_retention_also_for_generic_model_name(self, transport):
+        for model in ["muse-spark", "meta/muse-spark-1.2-2026-04-01", "gpt-5.4", ""]:
+            kw = transport.build_kwargs(
+                model=model,
+                messages=[{"role": "user", "content": "Hi"}],
+                tools=[],
+                base_url="https://api.meta.ai/v1",
+                session_id="sid",
+            )
+            assert kw.get("prompt_cache_retention") == "24h", f"model={model!r}"
+
+    def test_meta_retention_helper_direct(self):
+        assert _default_prompt_cache_retention_for_request("muse-spark-1.2", "https://api.meta.ai/v1") == "24h"
+        assert _default_prompt_cache_retention_for_request("muse-spark-1.2", "https://API.META.AI/v1") == "24h"
+        assert _default_prompt_cache_retention_for_request("muse-spark-1.2", "https://api.meta.ai:443/v1") == "24h"
+
+    def test_meta_retention_override_wins(self, transport):
+        kw = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=[],
+            base_url="https://api.meta.ai/v1",
+            session_id="sid",
+            request_overrides={"prompt_cache_retention": "in_memory"},
+        )
+        assert kw.get("prompt_cache_retention") == "in_memory"
+
+    def test_non_meta_no_retention(self, transport):
+        kw = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=[],
+            base_url="https://generic.example.com/v1",
+            session_id="sid",
+        )
+        assert "prompt_cache_retention" not in kw
+
+    def test_non_meta_no_retention_helper(self):
+        assert _default_prompt_cache_retention_for_request("muse-spark-1.2", "https://generic.example.com/v1") is None
+
+    def test_meta_prompt_cache_key_is_content_addressed(self, transport):
+        messages = [{"role": "user", "content": "Hi"}]
+        kw = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=messages,
+            tools=[],
+            base_url="https://api.meta.ai/v1",
+            session_id="cron_job_xxx_20260624_143000",
+        )
+        pck = kw.get("prompt_cache_key", "")
+        assert pck.startswith("pck_")
+        # stable across different cron fire timestamps (same scope)
+        kw2 = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=messages,
+            tools=[],
+            base_url="https://api.meta.ai/v1",
+            session_id="cron_job_xxx_20260624_143500",
+        )
+        assert kw["prompt_cache_key"] == kw2["prompt_cache_key"]
+
+    def test_meta_reasoning_effort_passthrough(self, transport):
+        kw = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=[],
+            base_url="https://api.meta.ai/v1",
+            session_id="sid",
+            reasoning_config={"effort": "high", "enabled": True},
+        )
+        assert kw.get("reasoning") == {"effort": "high", "summary": "auto"}
+
+    def test_meta_request_hits_responses_plan(self, transport):
+        # Transport api_mode must be codex_responses so conversation_loop hits /v1/responses
+        assert transport.api_mode == "codex_responses"
+        kw = transport.build_kwargs(
+            model="muse-spark-1.2",
+            messages=[{"role": "user", "content": "Hi"}],
+            tools=[{"type": "function", "function": {"name": "terminal", "description": "x", "parameters": {"type": "object", "properties": {"command": {"type": "string"}}}}}],
+            base_url="https://api.meta.ai/v1",
+            session_id="sid",
+        )
+        # Ensure instructions/input/tools and retention present - i.e., responses shape
+        assert "instructions" in kw or "input" in kw
+        assert kw.get("prompt_cache_retention") == "24h"
+        assert "prompt_cache_key" in kw