refactor: migrate AI tree generator to provider abstraction

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/tests/test_ai_endpoints.py

@@ -1,6 +1,6 @@
 """Integration tests for AI Flow Builder endpoints.
 
-All Anthropic API calls are mocked — zero real API spend.
+All AI provider calls are mocked — zero real API spend.
 """
 import json
 from unittest.mock import AsyncMock, patch, MagicMock
@@ -64,12 +64,11 @@ BRANCH_DETAIL_JSON = json.dumps({
 })
 
 
-def _mock_anthropic_response(text: str, input_tokens: int = 100, output_tokens: int = 200):
-    """Create a mock Anthropic API response."""
-    response = MagicMock()
-    response.content = [MagicMock(text=text)]
-    response.usage = MagicMock(input_tokens=input_tokens, output_tokens=output_tokens)
-    return response
+def _mock_ai_provider(text: str, input_tokens: int = 100, output_tokens: int = 200):
+    """Create a mock AI provider whose generate_json returns the given text and token counts."""
+    provider = MagicMock()
+    provider.generate_json = AsyncMock(return_value=(text, input_tokens, output_tokens))
+    return provider
 
 
 @pytest.fixture
@@ -194,11 +193,9 @@ async def test_scaffold_success(client, auth_headers, enable_ai):
     )
     conversation_id = start_resp.json()["conversation_id"]
 
-    # Mock Anthropic
-    mock_response = _mock_anthropic_response(SCAFFOLD_RESPONSE_JSON)
-    with patch("app.core.ai_tree_generator_service._get_client") as mock_client:
-        mock_client.return_value.messages.create = AsyncMock(return_value=mock_response)
-
+    # Mock AI provider
+    mock_provider = _mock_ai_provider(SCAFFOLD_RESPONSE_JSON)
+    with patch("app.core.ai_tree_generator_service.get_ai_provider", return_value=mock_provider):
         response = await client.post(
             "/api/v1/ai/scaffold",
             json={"conversation_id": conversation_id},
@@ -241,9 +238,8 @@ async def test_branch_detail_success(client, auth_headers, enable_ai):
     )
     conversation_id = start_resp.json()["conversation_id"]
 
-    scaffold_mock = _mock_anthropic_response(SCAFFOLD_RESPONSE_JSON)
-    with patch("app.core.ai_tree_generator_service._get_client") as mock_client:
-        mock_client.return_value.messages.create = AsyncMock(return_value=scaffold_mock)
+    scaffold_provider = _mock_ai_provider(SCAFFOLD_RESPONSE_JSON)
+    with patch("app.core.ai_tree_generator_service.get_ai_provider", return_value=scaffold_provider):
         await client.post(
             "/api/v1/ai/scaffold",
             json={"conversation_id": conversation_id},
@@ -251,10 +247,8 @@ async def test_branch_detail_success(client, auth_headers, enable_ai):
         )
 
     # Now generate branch detail
-    detail_mock = _mock_anthropic_response(BRANCH_DETAIL_JSON)
-    with patch("app.core.ai_tree_generator_service._get_client") as mock_client:
-        mock_client.return_value.messages.create = AsyncMock(return_value=detail_mock)
-
+    detail_provider = _mock_ai_provider(BRANCH_DETAIL_JSON)
+    with patch("app.core.ai_tree_generator_service.get_ai_provider", return_value=detail_provider):
         response = await client.post(
             "/api/v1/ai/branch-detail",
             json={
@@ -290,9 +284,8 @@ async def test_assemble_success(client, auth_headers, enable_ai):
     conversation_id = start_resp.json()["conversation_id"]
 
     # Scaffold
-    scaffold_mock = _mock_anthropic_response(SCAFFOLD_RESPONSE_JSON)
-    with patch("app.core.ai_tree_generator_service._get_client") as mock_client:
-        mock_client.return_value.messages.create = AsyncMock(return_value=scaffold_mock)
+    scaffold_provider = _mock_ai_provider(SCAFFOLD_RESPONSE_JSON)
+    with patch("app.core.ai_tree_generator_service.get_ai_provider", return_value=scaffold_provider):
         await client.post(
             "/api/v1/ai/scaffold",
             json={"conversation_id": conversation_id},