fix: large system message in XpertAssistant

learning_assistant/api.py

@@ -133,7 +133,34 @@ def render_prompt_template(request, user_id, course_run_id, unit_usage_key, cour
     # buffer. This limit also prevents an error from occurring wherein unusually long prompt templates cause an
     # error due to using too many tokens.
     UNIT_CONTENT_MAX_CHAR_LENGTH = getattr(settings, 'CHAT_COMPLETION_UNIT_CONTENT_MAX_CHAR_LENGTH', 11750)
-    unit_content = unit_content[0:UNIT_CONTENT_MAX_CHAR_LENGTH]
+
+    # --- Proportional trimming logic ---
+    if isinstance(unit_content, list):
+        # Create a new list of dictionaries to hold trimmed content
+        trimmed_unit_content = []
+
+        total_chars = sum(len(str(item.get("content_text", "")).strip()) for item in unit_content) or 1
+        current_length = 0
+
+        for item in unit_content:
+            ctype = item.get("content_type", "")
+            text = str(item.get("content_text", "")).strip()
+
+            if not text:
+                trimmed_unit_content.append({"content_type": ctype, "content_text": ""})
+                continue
+
+            allowed_chars = max(1, int((len(text) / total_chars) * UNIT_CONTENT_MAX_CHAR_LENGTH))
+            trimmed_text = text[:allowed_chars]
+            trimmed_unit_content.append({"content_type": ctype, "content_text": trimmed_text})
+            current_length += len(trimmed_text)
+
+        # Keep the trimmed content as a list of dictionaries
+        unit_content = trimmed_unit_content
+
+    else:
+        # For non-list content, keep as string trimmed
+        unit_content = unit_content[0:UNIT_CONTENT_MAX_CHAR_LENGTH]
 
     course_data = get_cache_course_data(course_id, ['skill_names', 'title'])
     skill_names = course_data['skill_names']

tests/test_api.py

@@ -197,13 +197,26 @@ def test_get_block_content(self, mock_get_children_contents, mock_get_single_blo
         self.assertEqual(items, content_items)
 
     @ddt.data(
-        'This is content.',
-        ''
+        'This is content.',  # Short string case
+        '',                  # Empty string case
+        'A' * 20000,         # Long string case to test trimming
+        [  # VIDEO content case
+            {'content_type': 'VIDEO', 'content_text': f"Video transcript {i} " + ("A" * 2000)} for i in range(10)
+        ],
+        [  # TEXT content case
+            {'content_type': 'TEXT', 'content_text': f"Paragraph {i} " + ("B" * 1000)} for i in range(20)
+        ],
+        [  # Mixed VIDEO + TEXT case
+            {'content_type': 'VIDEO', 'content_text': "Video intro " + ("C" * 1000)},
+            {'content_type': 'TEXT', 'content_text': "Some explanation " + ("D" * 1000)},
+        ],
+        [  # Explicitly test empty content in a list
+            {'content_type': 'TEXT', 'content_text': ''},
+        ],
     )
     @patch('learning_assistant.api.get_cache_course_data')
     @patch('learning_assistant.api.get_block_content')
     def test_render_prompt_template(self, unit_content, mock_get_content, mock_cache):
-        mock_get_content.return_value = (len(unit_content), unit_content)
         skills_content = ['skills']
         title = 'title'
         mock_cache.return_value = {'skill_names': skills_content, 'title': title}
@@ -216,17 +229,45 @@ def test_render_prompt_template(self, unit_content, mock_get_content, mock_cache
         unit_usage_key = 'block-v1:edX+A+B+type@vertical+block@verticalD'
         course_id = 'edx+test'
         template_string = getattr(settings, 'LEARNING_ASSISTANT_PROMPT_TEMPLATE', '')
+        unit_content_max_length = settings.CHAT_COMPLETION_UNIT_CONTENT_MAX_CHAR_LENGTH
+
+        # Determine total content length for mock
+        if isinstance(unit_content, list):
+            total_length = sum(len(c['content_text']) for c in unit_content)
+        else:
+            total_length = len(unit_content)
+
+        mock_get_content.return_value = (total_length, unit_content)
 
         prompt_text = render_prompt_template(
             request, user_id, course_run_id, unit_usage_key, course_id, template_string
         )
 
-        if unit_content:
-            self.assertIn(unit_content, prompt_text)
-        else:
-            self.assertNotIn('The following text is useful.', prompt_text)
-        self.assertIn(str(skills_content), prompt_text)
         self.assertIn(title, prompt_text)
+        self.assertIn(str(skills_content), prompt_text)
+
+        if isinstance(unit_content, list):
+            with patch('learning_assistant.api.Environment') as mock_env_cls:
+                mock_template = mock_env_cls.return_value.from_string.return_value
+                mock_template.render.return_value = "rendered prompt"
+
+                prompt_text = render_prompt_template(
+                    request, user_id, course_run_id, unit_usage_key, course_id, template_string
+                )
+
+                args, kwargs = mock_template.render.call_args
+                trimmed_unit_content = kwargs['unit_content']
+                total_trimmed_chars = sum(len(item['content_text']) for item in trimmed_unit_content)
+                self.assertLessEqual(total_trimmed_chars, unit_content_max_length)
+                self.assertEqual(prompt_text, "rendered prompt")
+        elif isinstance(unit_content, str):
+            if unit_content:
+                trimmed = unit_content[0:unit_content_max_length]
+                self.assertIn(trimmed, prompt_text)
+                if len(unit_content) > unit_content_max_length:
+                    self.assertNotIn(unit_content, prompt_text)
+            else:
+                self.assertNotIn('The following text is useful.', prompt_text)
 
     @patch('learning_assistant.api.get_cache_course_data', MagicMock())
     @patch('learning_assistant.api.get_block_content')