🐛(backend) fix sanitize problem IA

Albert send us back a malformed IA json, the
sanitize function was not able to handle it correctly.
We add a try catch on it, to not use the sanitizer if
the json.loads fails.

CHANGELOG.md

@@ -18,11 +18,15 @@ and this project adheres to
 
 - 🔒️(collaboration) increase collaboration access security #472
 - 🔨(frontend) encapsulated title to its own component #474
-- 🐛(frontend) Fix hidden menu on Firefox #468
 - ⚡️(backend) optimize number of queries on document list view #411
 - ♻️(frontend) stop to use provider with version #480
 - 🚚(collaboration) change the websocket key name #480
 
+## Fixed
+
+- 🐛(frontend) Fix hidden menu on Firefox #468
+- 🐛(backend) fix sanitize problem IA #490
+
 
 ## [1.8.2] - 2024-11-28
 

src/backend/core/services/ai_services.py

@@ -67,10 +67,14 @@ class AIService:
         )
 
         content = response.choices[0].message.content
-        sanitized_content = re.sub(r"(?<!\\)\n", "\\\\n", content)
-        sanitized_content = re.sub(r"(?<!\\)\t", "\\\\t", sanitized_content)
 
-        json_response = json.loads(sanitized_content)
+        try:
+            sanitized_content = re.sub(r"(?<!\\)\n", "\\\\n", content)
+            sanitized_content = re.sub(r"(?<!\\)\t", "\\\\t", sanitized_content)
+
+            json_response = json.loads(sanitized_content)
+        except (json.JSONDecodeError, IndexError):
+            json_response = json.loads(content)
 
         if "answer" not in json_response:
             raise RuntimeError("AI response does not contain an answer")

src/backend/core/tests/test_services_ai_services.py

@@ -102,3 +102,24 @@ def test_api_ai__success_sanitize(mock_create):
     response = AIService().transform("hello", "prompt")
 
     assert response == {"answer": "Salut\n \tle \nmonde"}
+
+
+@override_settings(
+    AI_BASE_URL="http://example.com", AI_API_KEY="test-key", AI_MODEL="test-model"
+)
+@patch("openai.resources.chat.completions.Completions.create")
+def test_api_ai__success_when_sanitize_fails(mock_create):
+    """The AI request should work as expected even with badly formatted response."""
+
+    # pylint: disable=C0303
+    answer = """{ 
+        "answer"        :       
+        "Salut le monde"
+    }"""
+    mock_create.return_value = MagicMock(
+        choices=[MagicMock(message=MagicMock(content=answer))]
+    )
+
+    response = AIService().transform("hello", "prompt")
+
+    assert response == {"answer": "Salut le monde"}