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

tests/agent/test_deepseek_anthropic_thinking.py

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+"""Regression guard: preserve thinking blocks on DeepSeek's /anthropic endpoint.
+
+DeepSeek's ``api.deepseek.com/anthropic`` route speaks the Anthropic Messages
+protocol but, when thinking mode is enabled, requires ``thinking`` blocks from
+prior assistant turns to round-trip on subsequent requests.  The generic
+third-party path strips them (signatures are Anthropic-proprietary and other
+proxies cannot validate them), so without a DeepSeek-specific carve-out the
+next tool-call turn fails with HTTP 400::
+
+    The content[].thinking in the thinking mode must be passed back to the
+    API.
+
+DeepSeek's compatibility matrix lists ``thinking`` as supported but
+``redacted_thinking`` and ``cache_control`` on thinking blocks as not
+supported.  Handling is the same as Kimi's ``/coding`` endpoint: strip
+Anthropic-signed blocks (DeepSeek can't validate them) but preserve unsigned
+blocks that Hermes synthesises from ``reasoning_content``.
+
+See hermes-agent#16748.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+
+class TestDeepSeekAnthropicPreservesThinking:
+    """convert_messages_to_anthropic must replay DeepSeek thinking blocks."""
+
+
+
+    def test_signed_anthropic_thinking_block_is_stripped(self) -> None:
+        """Anthropic-signed blocks (that leaked through) must still be stripped.
+
+        DeepSeek issues its own signatures and cannot validate Anthropic's —
+        the strip-signed / keep-unsigned split matches the Kimi policy.
+        """
+        from agent.anthropic_adapter import convert_messages_to_anthropic
+
+        messages = [
+            {"role": "user", "content": "hi"},
+            {
+                "role": "assistant",
+                "content": [
+                    {
+                        "type": "thinking",
+                        "thinking": "anthropic-signed payload",
+                        "signature": "anthropic-sig-xyz",
+                    },
+                    {"type": "text", "text": "hello"},
+                ],
+            },
+            {"role": "user", "content": "again"},
+        ]
+        _system, converted = convert_messages_to_anthropic(
+            messages, base_url="https://api.deepseek.com/anthropic"
+        )
+
+        assistant_msg = next(m for m in converted if m["role"] == "assistant")
+        thinking_blocks = [
+            b for b in assistant_msg["content"]
+            if isinstance(b, dict) and b.get("type") == "thinking"
+        ]
+        assert thinking_blocks == [], (
+            "Signed Anthropic thinking blocks must be stripped on DeepSeek — "
+            "DeepSeek cannot validate Anthropic-proprietary signatures."
+        )
+
+    def test_cache_control_stripped_from_thinking_block(self) -> None:
+        """cache_control must still be stripped even when the block is preserved.
+
+        DeepSeek's compatibility matrix lists cache_control on thinking blocks
+        as ignored — cache markers interfere with signature validation on
+        upstreams that do check them, so Hermes strips them everywhere.
+        """
+        from agent.anthropic_adapter import convert_messages_to_anthropic
+
+        messages = [
+            {"role": "user", "content": "hi"},
+            {
+                "role": "assistant",
+                "reasoning_content": "r1",
+                "tool_calls": [
+                    {
+                        "id": "call_1",
+                        "type": "function",
+                        "function": {"name": "f", "arguments": "{}"},
+                    }
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "ok"},
+        ]
+        # Inject cache_control on the synthesised thinking block after-the-fact
+        # by running conversion once, mutating, then re-running would be
+        # indirect.  Instead check the simpler invariant: no thinking block in
+        # the converted output carries cache_control.
+        _system, converted = convert_messages_to_anthropic(
+            messages, base_url="https://api.deepseek.com/anthropic"
+        )
+        for m in converted:
+            if not isinstance(m.get("content"), list):
+                continue
+            for b in m["content"]:
+                if isinstance(b, dict) and b.get("type") in {"thinking", "redacted_thinking"}:
+                    assert "cache_control" not in b
+
+