feat(providers): add extra_body config for OpenAI-compatible endpoints

Add an `extra_body` field to `ProviderConfig` that merges arbitrary
key-value pairs into every OpenAI-compatible request body. This is the
escape hatch for provider-specific features that nanobot does not have
first-class fields for.

Real-world use cases this unblocks via config alone (no code changes):
- vLLM/TGI `chat_template_kwargs` (e.g. `enable_thinking: false`)
- vLLM guided decoding (`guided_json`, `guided_regex`)
- Local model sampling params (`repetition_penalty`, `top_k`, `min_p`)
- Any future provider-specific param without a new PR each time

The config extra_body is applied last via recursive deep-merge, so it
can extend or override provider-specific defaults (e.g. thinking
params) without clobbering sibling keys set by internal logic.

Changes:
- Add `extra_body: dict[str, Any] | None` to `ProviderConfig`
- Pass it through `factory.py` to `OpenAICompatProvider.__init__`
- Deep-merge into `_build_kwargs` after all internal extra_body entries
- Add `_deep_merge` helper (recursive dict merge, does not mutate inputs)
- 21 tests: deep-merge semantics, provider init, _build_kwargs
  integration, thinking coexistence, real-world patterns (guided_json,
  repetition_penalty), and schema validation

nanobot/providers/openai_compat_provider.py

@@ -232,6 +232,25 @@ def _responses_circuit_key(
     return f"{model_name}:{effort}"
 
 
+def _deep_merge(base: dict[str, Any], override: dict[str, Any]) -> dict[str, Any]:
+    """Recursively merge *override* into *base*, returning a new dict.
+
+    Nested dicts are merged key-by-key; all other types in *override*
+    replace the corresponding key in *base*.
+    """
+    merged = dict(base)
+    for key, value in override.items():
+        if (
+            key in merged
+            and isinstance(merged[key], dict)
+            and isinstance(value, dict)
+        ):
+            merged[key] = _deep_merge(merged[key], value)
+        else:
+            merged[key] = value
+    return merged
+
+
 class OpenAICompatProvider(LLMProvider):
     """Unified provider for all OpenAI-compatible APIs.
 
@@ -246,11 +265,13 @@ class OpenAICompatProvider(LLMProvider):
         default_model: str = "gpt-4o",
         extra_headers: dict[str, str] | None = None,
         spec: ProviderSpec | None = None,
+        extra_body: dict[str, Any] | None = None,
     ):
         super().__init__(api_key, api_base)
         self.default_model = default_model
         self.extra_headers = extra_headers or {}
         self._spec = spec
+        self._extra_body = extra_body or {}
 
         if api_key and spec and spec.env_key:
             self._setup_env(api_key, api_base)
@@ -597,6 +618,15 @@ class OpenAICompatProvider(LLMProvider):
                 if msg.get("role") == "assistant" and "reasoning_content" not in msg:
                     msg["reasoning_content"] = ""
 
+        # Merge user-configured extra_body last so it can override or
+        # extend provider-specific defaults (e.g. chat_template_kwargs,
+        # guided_json, repetition_penalty).  Uses recursive merge so
+        # nested dicts like {"chat_template_kwargs": {"enable_thinking": false}}
+        # do not clobber sibling keys already set by thinking-style logic.
+        if self._extra_body:
+            existing = kwargs.get("extra_body", {})
+            kwargs["extra_body"] = _deep_merge(existing, self._extra_body)
+
         return kwargs
 
     def _should_use_responses_api(