remove unused legacy endpoint

Author: Yukigeshiki

README.md

@@ -1,8 +1,8 @@
-# Agent Query Engine
+# Document Query Engine
 
-[![API Tests](https://github.com/Yukigeshiki/agent-query-engine-python/actions/workflows/api-tests.yml/badge.svg)](https://github.com/Yukigeshiki/agent-query-engine-python/actions/workflows/api-tests.yml)
-[![API Build](https://github.com/Yukigeshiki/agent-query-engine-python/actions/workflows/api-build.yml/badge.svg)](https://github.com/Yukigeshiki/agent-query-engine-python/actions/workflows/api-build.yml)
-[![UI Build](https://github.com/Yukigeshiki/agent-query-engine-python/actions/workflows/ui-build.yml/badge.svg)](https://github.com/Yukigeshiki/agent-query-engine-python/actions/workflows/ui-build.yml)
+[![API Tests](https://github.com/Yukigeshiki/document-query-engine-python/actions/workflows/api-tests.yml/badge.svg)](https://github.com/Yukigeshiki/document-query-engine-python/actions/workflows/api-tests.yml)
+[![API Build](https://github.com/Yukigeshiki/document-query-engine-python/actions/workflows/api-build.yml/badge.svg)](https://github.com/Yukigeshiki/document-query-engine-python/actions/workflows/api-build.yml)
+[![UI Build](https://github.com/Yukigeshiki/document-query-engine-python/actions/workflows/ui-build.yml/badge.svg)](https://github.com/Yukigeshiki/document-query-engine-python/actions/workflows/ui-build.yml)
 
 A document ingestion and query engine built with Python/FastAPI, LlamaIndex, Neo4j, and pgvector. Upload documents (PDF, DOCX, TXT — max 5MB), extract knowledge graph triplets and vector embeddings, then query across both using natural language. LlamaIndex orchestrates the full pipeline — chunking documents, extracting entity-relationship triplets via OpenAI into Neo4j, embedding chunks into pgvector, and synthesizing answers from dual retrieval (graph traversal + vector similarity). Documents are stored in GCS and processed asynchronously via Celery. The UI provides testing for document upload with interactive graph visualization, a query interface with retrieval mode selection, and document deletion.
 
@@ -18,7 +18,7 @@ A document ingestion and query engine built with Python/FastAPI, LlamaIndex, Neo
 
 ## Prerequisites
 
-- Python 3.13+ and [Poetry](https://python-poetry.org/)
+- Python 3.12+ and [Poetry](https://python-poetry.org/)
 - Docker
 - Node.js + pnpm
 - `OPENAI_API_KEY` environment variable
@@ -124,12 +124,14 @@ curl -X POST http://localhost:8000/api/v1/kg/ingest/upload \
 |--------|------|-------------|
 | POST | `/kg/query` | Query documents with natural language |
 | POST | `/kg/ingest/upload` | Upload a file for async ingestion (max 5MB) |
+| POST | `/kg/ingest/source` | Ingest from a source connector (async) |
 | GET | `/kg/documents` | List ingested documents (paginated, newest first) |
 | DELETE | `/kg/documents/{docId}` | Delete a document from all storage layers |
 | GET | `/kg/documents/graph` | Get knowledge graph for a document |
 | GET | `/kg/subgraph` | Get subgraph around an entity |
 | GET | `/tasks/{taskId}` | Poll background task status |
-| GET | `/api/v1/health` | Health check |
+| DELETE | `/tasks/{taskId}` | Cancel a background task |
+| GET | `/health` | Health check |
 | GET | `/metrics` | Prometheus metrics |
 
 ## Build Commands

services/query-engine/app/api/v1/knowledge_graph.py

@@ -10,8 +10,6 @@
 from app.models.knowledge_graph import (
     DocumentInfo,
     DocumentListResponse,
-    IngestRequest,
-    IngestResponse,
     QueryRequest,
     QueryResponse,
     SourceIngestRequest,
@@ -70,21 +68,6 @@ async def delete_document(
     return TaskAcceptedResponse(task_id=result.id)
 
 
-@router.post("/ingest", response_model=IngestResponse)
-@limiter.limit(settings.rate_limit_ingest)
-async def ingest_document(
-    request: Request,
-    body: IngestRequest,
-    service: KnowledgeGraphService = Depends(get_kg_service),
-) -> IngestResponse:
-    """Ingest a text document into the knowledge graph."""
-    doc_id, triplet_count = await service.ingest(
-        text=body.text,
-        metadata=body.metadata,
-    )
-    return IngestResponse(document_id=doc_id, triplet_count=triplet_count)
-
-
 @router.post(
     "/ingest/source",
     response_model=TaskAcceptedResponse,

services/query-engine/app/models/knowledge_graph.py

@@ -42,22 +42,6 @@ class QueryRequest(CamelModel):
     retrieval_mode: RetrievalMode = Field(default=RetrievalMode.DUAL)
 
 
-class IngestRequest(CamelModel):
-    """Request body for document ingestion."""
-
-    text: str = Field(..., min_length=1, description="Document text to ingest")
-    metadata: dict[str, Any] | None = Field(
-        default=None, description="Optional metadata key-value pairs"
-    )
-
-
-class IngestResponse(CamelModel):
-    """Response after successful document ingestion."""
-
-    document_id: str
-    triplet_count: int
-
-
 class SourceIngestRequest(CamelModel):
     """Request body for bulk document ingestion from a source."""
 

services/query-engine/tests/test_knowledge_graph.py

@@ -23,7 +23,6 @@
 def mock_kg_service() -> AsyncMock:
     """Create a mock KnowledgeGraphService."""
     service = AsyncMock()
-    service.ingest.return_value = ("test-doc-id", 5)
     service.query.return_value = (
         "Test response about the topic.",
         [SourceNodeInfo(source_type=SourceRetrievalType.VECTOR, score=0.9, metadata=SourceNodeMetadata(file_name="test.txt"))],
@@ -71,34 +70,6 @@ async def kg_client(mock_kg_service: AsyncMock) -> AsyncIterator[AsyncClient]:
         yield ac
 
 
-@pytest.mark.asyncio
-async def test_ingest_document(kg_client: AsyncClient, mock_kg_service: AsyncMock) -> None:
-    """Verify ingest endpoint returns document ID and triplet count."""
-    response = await kg_client.post(
-        "/api/v1/kg/ingest",
-        json={"text": "Alice works at Acme Corp in New York."},
-    )
-    assert response.status_code == 200
-    data = response.json()
-    assert data["documentId"] == "test-doc-id"
-    assert data["tripletCount"] == 5
-    mock_kg_service.ingest.assert_called_once()
-
-
-@pytest.mark.asyncio
-async def test_ingest_with_metadata(kg_client: AsyncClient, mock_kg_service: AsyncMock) -> None:
-    """Verify ingest accepts optional metadata."""
-    response = await kg_client.post(
-        "/api/v1/kg/ingest",
-        json={"text": "Some document.", "metadata": {"source": "test"}},
-    )
-    assert response.status_code == 200
-    mock_kg_service.ingest.assert_called_once_with(
-        text="Some document.",
-        metadata={"source": "test"},
-    )
-
-
 @pytest.mark.asyncio
 async def test_query_knowledge_graph(
     kg_client: AsyncClient, mock_kg_service: AsyncMock
@@ -198,16 +169,6 @@ async def test_document_graph_missing_doc_ids(kg_client: AsyncClient) -> None:
     assert response.status_code == 422
 
 
-@pytest.mark.asyncio
-async def test_ingest_empty_text(kg_client: AsyncClient) -> None:
-    """Verify validation rejects empty text."""
-    response = await kg_client.post(
-        "/api/v1/kg/ingest",
-        json={"text": ""},
-    )
-    assert response.status_code == 422
-
-
 @pytest.mark.asyncio
 async def test_query_empty_query(kg_client: AsyncClient) -> None:
     """Verify validation rejects empty query."""