server: clamp max_tokens to the server cap instead of rejecting it (fixes #260)

opencode / the ai-sdk OpenAI-compatible client sends a large default max_tokens
(> the server's --max-tokens cap, 1024 by default), and generation_options
returned 400 "must be an integer between 1 and 1024" — even for a trivial
"hello". OpenAI-compatible servers clamp to their own ceiling rather than
reject. Now max_tokens > limit is clamped to limit; only non-int / non-positive
values are a hard error. Test updated to assert the clamp + keep the <1 reject.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

c/openai_server.py

@@ -410,8 +410,11 @@ def generation_options(body, limit):
     top_p = body.get("top_p")
     temperature = 0.7 if temperature is None else temperature
     top_p = 0.9 if top_p is None else top_p
-    if isinstance(maximum, bool) or not isinstance(maximum, int) or not 1 <= maximum <= limit:
-        raise APIError(400, f"`{maximum_param}` must be an integer between 1 and {limit}.", maximum_param)
+    if isinstance(maximum, bool) or not isinstance(maximum, int) or maximum < 1:
+        raise APIError(400, f"`{maximum_param}` must be a positive integer.", maximum_param)
+    if maximum > limit:
+        maximum = limit   # clamp to the server's --max-tokens cap instead of 400 (#260): OpenAI
+                          # clients (opencode/ai-sdk) default to large max_tokens; rejecting breaks them.
     if (isinstance(temperature, bool) or not isinstance(temperature, (int, float)) or
             not math.isfinite(temperature) or not 0 <= temperature <= 2):
         raise APIError(400, "`temperature` must be between 0 and 2.", "temperature")

c/tests/test_openai_server.py

@@ -72,8 +72,13 @@ class TemplateTest(unittest.TestCase):
     def test_validates_generation_limits(self):
         self.assertEqual(generation_options({"max_tokens": 4, "temperature": 0, "top_p": 1}, 8),
                          (4, 0.0, 1.0))
+        # max_tokens above the server cap is clamped, not rejected (#260): OpenAI
+        # clients default to large values; erroring breaks them.
+        self.assertEqual(generation_options({"max_tokens": 9, "temperature": 0, "top_p": 1}, 8),
+                         (8, 0.0, 1.0))
+        # non-positive / non-int max_tokens is still a hard error
         with self.assertRaises(APIError):
-            generation_options({"max_tokens": 9}, 8)
+            generation_options({"max_tokens": 0}, 8)
         with self.assertRaises(APIError):
             generation_options({"temperature": math.nan}, 8)
         with self.assertRaises(APIError):