Merge origin/main into fix/retry-after-robust

Made-with: Cursor

nanobot/providers/base.py

@@ -52,7 +52,7 @@ class LLMResponse:
     finish_reason: str = "stop"
     usage: dict[str, int] = field(default_factory=dict)
     retry_after: float | None = None  # Provider supplied retry wait in seconds.
-    reasoning_content: str | None = None  # Kimi, DeepSeek-R1 etc.
+    reasoning_content: str | None = None  # Kimi, DeepSeek-R1, MiMo etc.
     thinking_blocks: list[dict] | None = None  # Anthropic extended thinking
     
     @property

nanobot/providers/openai_compat_provider.py

@@ -385,9 +385,13 @@ class OpenAICompatProvider(LLMProvider):
                 content = self._extract_text_content(
                     response_map.get("content") or response_map.get("output_text")
                 )
+                reasoning_content = self._extract_text_content(
+                    response_map.get("reasoning_content")
+                )
                 if content is not None:
                     return LLMResponse(
                         content=content,
+                        reasoning_content=reasoning_content,
                         finish_reason=str(response_map.get("finish_reason") or "stop"),
                         usage=self._extract_usage(response_map),
                     )
@@ -482,6 +486,7 @@ class OpenAICompatProvider(LLMProvider):
     @classmethod
     def _parse_chunks(cls, chunks: list[Any]) -> LLMResponse:
         content_parts: list[str] = []
+        reasoning_parts: list[str] = []
         tc_bufs: dict[int, dict[str, Any]] = {}
         finish_reason = "stop"
         usage: dict[str, int] = {}
@@ -535,6 +540,9 @@ class OpenAICompatProvider(LLMProvider):
                 text = cls._extract_text_content(delta.get("content"))
                 if text:
                     content_parts.append(text)
+                text = cls._extract_text_content(delta.get("reasoning_content"))
+                if text:
+                    reasoning_parts.append(text)
                 for idx, tc in enumerate(delta.get("tool_calls") or []):
                     _accum_tc(tc, idx)
                 usage = cls._extract_usage(chunk_map) or usage
@@ -549,6 +557,10 @@ class OpenAICompatProvider(LLMProvider):
             delta = choice.delta
             if delta and delta.content:
                 content_parts.append(delta.content)
+            if delta:
+                reasoning = getattr(delta, "reasoning_content", None)
+                if reasoning:
+                    reasoning_parts.append(reasoning)
             for tc in (delta.tool_calls or []) if delta else []:
                 _accum_tc(tc, getattr(tc, "index", 0))
 
@@ -567,6 +579,7 @@ class OpenAICompatProvider(LLMProvider):
             ],
             finish_reason=finish_reason,
             usage=usage,
+            reasoning_content="".join(reasoning_parts) or None,
         )
 
     @staticmethod
@@ -635,6 +648,9 @@ class OpenAICompatProvider(LLMProvider):
                     break
                 chunks.append(chunk)
                 if on_content_delta and chunk.choices:
+                    text = getattr(chunk.choices[0].delta, "reasoning_content", None)
+                    if text:
+                        await on_content_delta(text)
                     text = getattr(chunk.choices[0].delta, "content", None)
                     if text:
                         await on_content_delta(text)

nanobot/providers/registry.py

@@ -297,6 +297,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         backend="openai_compat",
         default_api_base="https://api.stepfun.com/v1",
     ),
+    # Xiaomi MIMO (小米): OpenAI-compatible API
+    ProviderSpec(
+        name="xiaomi_mimo",
+        keywords=("xiaomi_mimo", "mimo"),
+        env_key="XIAOMIMIMO_API_KEY",
+        display_name="Xiaomi MIMO",
+        backend="openai_compat",
+        default_api_base="https://api.xiaomimimo.com/v1",
+    ),
     # === Local deployment (matched by config key, NOT by api_base) =========
     # vLLM / any OpenAI-compatible local server
     ProviderSpec(