Add analysis feature

backend/tests/test_conversation_history.py

@@ -9,6 +9,45 @@ from services.conversation_history import ConversationRecorder
 
 
 class ConversationRecorderTest(unittest.IsolatedAsyncioTestCase):
+    async def test_completed_conversation_queues_enabled_analysis(self):
+        conversation = SimpleNamespace(
+            status="active",
+            ended_at=None,
+            message_count=0,
+            analysis_status="none",
+            analysis_data={},
+            analysis_error="",
+        )
+
+        class FakeSession:
+            async def __aenter__(self):
+                return self
+
+            async def __aexit__(self, *_args):
+                return None
+
+            async def get(self, _model, _session_id):
+                return conversation
+
+            async def commit(self):
+                return None
+
+        plan = {
+            "enabled": True,
+            "model_resource_id": "model_001",
+            "fields": [{"name": "customer_name", "type": "string"}],
+        }
+        recorder = ConversationRecorder("conv_test", plan)
+        recorder._sequence = 1
+        with patch(
+            "services.conversation_history.SessionLocal",
+            return_value=FakeSession(),
+        ):
+            await recorder._finish(status="completed")
+
+        self.assertEqual(conversation.analysis_status, "pending")
+        self.assertEqual(conversation.analysis_data, {"plan": plan})
+
     async def test_finish_waits_for_database_cleanup_when_cancelled(self):
         recorder = ConversationRecorder("conv_test")
         started = asyncio.Event()

backend/tests/test_post_call_analysis.py

@@ -0,0 +1,81 @@
+from __future__ import annotations
+
+import unittest
+
+from pydantic import ValidationError
+from schemas import AnalysisConfig
+from services.post_call.analyzer import (
+    _json_schema,
+    _parse_json_content,
+    _validated_result,
+)
+
+
+FIELDS = [
+    {
+        "id": "intent",
+        "name": "customer_intent",
+        "type": "enum",
+        "description": "客户意向",
+        "enum_values": ["high", "low"],
+    },
+    {
+        "id": "follow_up",
+        "name": "need_follow_up",
+        "type": "boolean",
+        "description": "是否需要跟进",
+        "enum_values": [],
+    },
+]
+
+
+class AnalysisConfigTest(unittest.TestCase):
+    def test_enabled_analysis_requires_model_and_fields(self):
+        with self.assertRaises(ValidationError):
+            AnalysisConfig(enabled=True)
+
+    def test_field_names_must_be_unique(self):
+        field = {
+            "id": "one",
+            "name": "customer_name",
+            "type": "string",
+            "description": "客户姓名",
+        }
+        with self.assertRaises(ValidationError):
+            AnalysisConfig(
+                enabled=True,
+                model_resource_id="model_001",
+                fields=[field, {**field, "id": "two"}],
+            )
+
+
+class StructuredExtractionTest(unittest.TestCase):
+    def test_schema_marks_every_field_nullable_and_required(self):
+        schema = _json_schema(FIELDS)
+        self.assertEqual(
+            schema["required"], ["customer_intent", "need_follow_up"]
+        )
+        self.assertEqual(
+            schema["properties"]["customer_intent"]["enum"],
+            ["high", "low", None],
+        )
+
+    def test_invalid_values_are_normalized_to_null(self):
+        result = _validated_result(
+            {"customer_intent": "medium", "need_follow_up": "yes"},
+            FIELDS,
+        )
+        self.assertEqual(
+            result,
+            {"customer_intent": None, "need_follow_up": None},
+        )
+
+    def test_json_parser_accepts_fenced_model_output(self):
+        self.assertEqual(
+            _parse_json_content('```json\n{"need_follow_up": true}\n```'),
+            {"need_follow_up": True},
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()