diff --git a/evalharness/model/adapter.py b/evalharness/model/adapter.py
index 44cbc75..a4153a4 100644
--- a/evalharness/model/adapter.py
+++ b/evalharness/model/adapter.py
@@ -164,8 +164,12 @@ def _parse_text_tool_calls(text: str) -> list:
                         args[kw_.arg] = _ast.unparse(kw_.value)
             except SyntaxError:
                 return None
+        # literal_eval happily returns Ellipsis (code like `f(key=...)`) and
+        # other non-JSON constants; default=str keeps the serializer alive
+        # instead of killing the whole benchmark at parse time
         return {'id': '', 'type': 'function',
-                'function': {'name': name, 'arguments': json.dumps(args)}}
+                'function': {'name': name,
+                             'arguments': json.dumps(args, default=str)}}
 
     for m_ in _re.finditer(r'([A-Za-z_][A-Za-z0-9_]*)\((.*?)\)', text):
         c = _py_call(m_)
@@ -222,10 +226,10 @@ class OpenAICompatible(ModelAdapter):
                                 break
                     data = await self._post_stream_aggregate(
                         f'{self.api_base}/chat/completions', payload, headers)
-                    out = self._parse(data)
+                    out = self._parse(data, allow_text_calls=bool(tools))
                 else:
                     data = await self._post(f'{self.api_base}/chat/completions', payload, headers)
-                    out = self._parse(data)
+                    out = self._parse(data, allow_text_calls=bool(tools))
                 out.usage.latency_s = round(_time.time() - t0, 3)
                 out.usage.retries = attempt
                 return out
@@ -333,7 +337,7 @@ class OpenAICompatible(ModelAdapter):
             'usage': (usage_ev or {}).get('usage') or {},
             'model': self.model,
         }
-        out = self._parse(data)
+        out = self._parse(data, allow_text_calls=True)
         out.usage.ttft_s = round(ttft, 3) if ttft is not None else None
         out.usage.itl_mean_s = round(sum(itl_vals) / len(itl_vals), 4) if itl_vals else None
         out.usage.http_status = status
@@ -379,12 +383,17 @@ class OpenAICompatible(ModelAdapter):
                 payload['chat_template_kwargs'] = {'enable_thinking': False}
         return payload
 
-    def _parse(self, data: Dict[str, Any]) -> ModelOutput:
+    def _parse(self, data: Dict[str, Any],
+               allow_text_calls: bool = True) -> ModelOutput:
         choice = (data.get('choices') or [{}])[0]
         msg = choice.get('message') or {}
         calls = []
         raw_calls = list(msg.get('tool_calls') or [])
-        if not raw_calls:
+        if not raw_calls and allow_text_calls:
+            # text-protocol fallback ONLY for requests that carried tools:
+            # running it on plain prose/code (humaneval!) regex-matched
+            # `f(key=...)` style code as "calls", literal_eval'd the `...`
+            # into an Ellipsis and crashed json.dumps mid-generation
             raw_calls = _parse_text_tool_calls(msg.get('content') or '')
         for c in raw_calls:
             fn = c.get('function') or {}