feat(api): enhance max_tokens field with robust null handling

- Update LLMModelConfigUpdate schema to accept Union[int, str] for max_tokens
- Add field validator to gracefully handle various null representations:
  - Convert string "null" to null
  - Convert empty strings to null
  - Convert numeric strings to integers
  - Accept proper JSON null values
- Update documentation to reflect new behavior and explain robust null handling
- Prevents validation errors from incorrect null serialization by clients

docs/gns3-copilot/implemented/llm-model-configs.md

@@ -148,7 +148,7 @@ The `model_type` field accepts the following values:
 | `model` | string (optional) | Model name |
 | `temperature` | float (optional) | Temperature |
 | `api_key` | string (optional) | API key |
-| `max_tokens` | integer (optional) | Max tokens |
+| `max_tokens` | integer or string (optional) | Max tokens for generation. Accepts integers, null, or the string "null" (which will be converted to null) |
 | `context_limit` | integer (optional) | Model context window limit in K tokens |
 | `context_strategy` | string (optional) | Context trimming strategy |
 | `is_default` | boolean (optional) | Default flag |
@@ -156,6 +156,14 @@ The `model_type` field accepts the following values:
 
 **Note:** When using `expected_version`, the API will verify the version hasn't changed since you read the data. If it has, you'll receive a 409 Conflict error.
 
+**Robust Null Handling:** The `max_tokens` field includes a validator that gracefully handles various null representations:
+- Accepts proper JSON `null` values
+- Accepts the string `"null"` (common serialization issue) and converts it to `null`
+- Accepts empty strings `""` and converts them to `null`
+- Accepts numeric strings (e.g., `"4096"`) and converts them to integers
+
+This prevents validation errors when clients incorrectly serialize `null` as the string `"null"`.
+
 ### LLMModelConfigResponse
 
 | Field | Type | Description |

gns3server/schemas/controller/llm_model_configs.py

@@ -14,8 +14,8 @@
 # You should have received a copy of the GNU General Public License
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
-from typing import Optional, Literal
-from pydantic import BaseModel, Field, ConfigDict
+from typing import Optional, Literal, Union
+from pydantic import BaseModel, Field, ConfigDict, field_validator
 from uuid import UUID
 
 from .base import DateTimeModelMixin
@@ -100,7 +100,7 @@ class LLMModelConfigUpdate(BaseModel):
     model: Optional[str] = None
     temperature: Optional[float] = Field(None, ge=0.0, le=2.0)
     api_key: Optional[str] = None
-    max_tokens: Optional[int] = Field(None, gt=0)
+    max_tokens: Optional[Union[int, str]] = Field(None, description="Max tokens for generation (can be null)")
     context_limit: Optional[int] = Field(None, gt=0, description="Model context window limit in K tokens (e.g., 128 = 128K tokens)")
     context_strategy: Optional[Literal["conservative", "balanced", "aggressive"]] = Field(
         None, description="Context trimming strategy"
@@ -113,6 +113,19 @@ class LLMModelConfigUpdate(BaseModel):
     # Allow extra config fields
     model_config = ConfigDict(extra="allow")
 
+    @field_validator('max_tokens', mode='before')
+    @classmethod
+    def validate_max_tokens(cls, v):
+        """Handle string 'null' values for max_tokens."""
+        if v == "null" or v == "":
+            return None
+        if v is None:
+            return None
+        # Convert to int if it's a valid integer string
+        if isinstance(v, str) and v.isdigit():
+            return int(v)
+        return v
+
 
 # Response schemas
 class LLMModelConfigResponse(DateTimeModelMixin):