Preserve thinking block signatures for multi-turn conversations

The Anthropic API returns a signature field in thinking blocks that
must be replayed in subsequent turns. Store full thinking blocks
(including signatures) instead of just the text content.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

nanobot/providers/anthropic_oauth.py

@@ -90,12 +90,12 @@ class AnthropicOAuthProvider(LLMProvider):
             if role == "assistant" and msg.get("tool_calls"):
                 # Convert OpenAI tool_calls to Anthropic content blocks
                 content_blocks: list[dict[str, Any]] = []
-                # Preserve thinking block if present
-                if msg.get("reasoning_content"):
-                    content_blocks.append({
-                        "type": "thinking",
-                        "thinking": msg["reasoning_content"],
-                    })
+                # Preserve thinking blocks (list=raw API blocks with signatures, str=legacy)
+                rc = msg.get("reasoning_content")
+                if isinstance(rc, list):
+                    content_blocks.extend(rc)
+                elif isinstance(rc, str) and rc:
+                    content_blocks.append({"type": "thinking", "thinking": rc})
                 text = msg.get("content")
                 if text:
                     content_blocks.append({"type": "text", "text": text})
@@ -118,9 +118,11 @@ class AnthropicOAuthProvider(LLMProvider):
 
             if role == "assistant" and msg.get("reasoning_content"):
                 # Plain assistant message with thinking (no tool calls)
-                content_blocks = [
-                    {"type": "thinking", "thinking": msg["reasoning_content"]},
-                ]
+                rc = msg["reasoning_content"]
+                if isinstance(rc, list):
+                    content_blocks = list(rc)
+                else:
+                    content_blocks = [{"type": "thinking", "thinking": rc}]
                 text = msg.get("content")
                 if text:
                     content_blocks.append({"type": "text", "text": text})
@@ -275,12 +277,13 @@ class AnthropicOAuthProvider(LLMProvider):
         content_blocks = response.get("content", [])
 
         text_content = ""
-        thinking_content = ""
+        thinking_blocks: list[dict[str, Any]] = []
         tool_calls = []
 
         for block in content_blocks:
             if block.get("type") == "thinking":
-                thinking_content += block.get("thinking", "")
+                # Preserve full block including signature for multi-turn replay
+                thinking_blocks.append(block)
             elif block.get("type") == "text":
                 text_content += block.get("text", "")
             elif block.get("type") == "tool_use":
@@ -306,7 +309,7 @@ class AnthropicOAuthProvider(LLMProvider):
             tool_calls=tool_calls,
             finish_reason=response.get("stop_reason", "end_turn"),
             usage=usage,
-            reasoning_content=thinking_content or None,
+            reasoning_content=thinking_blocks or None,
         )
 
     def get_default_model(self) -> str:

nanobot/providers/base.py

@@ -20,7 +20,7 @@ class LLMResponse:
     tool_calls: list[ToolCallRequest] = field(default_factory=list)
     finish_reason: str = "stop"
     usage: dict[str, int] = field(default_factory=dict)
-    reasoning_content: str | None = None  # Kimi, DeepSeek-R1 etc.
+    reasoning_content: Any = None  # str for Kimi/DeepSeek-R1; list[dict] for Anthropic thinking blocks
     
     @property
     def has_tool_calls(self) -> bool: