fix: restore LEANN HTTP server OpenAPI and search body parsing

packages/leann-core/src/leann/server.py

@@ -25,7 +25,7 @@
 def _ensure_fastapi():
     """Lazy import FastAPI and Pydantic, with a clear error if missing."""
     try:
-        from fastapi import FastAPI, HTTPException  # type: ignore
+        from fastapi import Body, FastAPI, HTTPException  # type: ignore
         from pydantic import BaseModel  # type: ignore
     except ImportError as e:  # pragma: no cover - dependency error path
         raise RuntimeError(
@@ -34,7 +34,7 @@ def _ensure_fastapi():
             "  uv pip install 'fastapi>=0.115' 'pydantic>=2' 'uvicorn[standard]'\n"
         ) from e
 
-    return FastAPI, HTTPException, BaseModel
+    return FastAPI, HTTPException, BaseModel, Body
 
 
 def _resolve_index_path(index_name: str) -> str:
@@ -92,7 +92,7 @@ def create_app():
     - POST /indexes/{name}/search      -> semantic search
     """
 
-    FastAPI, HTTPException, BaseModel = _ensure_fastapi()
+    FastAPI, HTTPException, BaseModel, Body = _ensure_fastapi()
 
     class SearchRequest(BaseModel):
         query: str
@@ -132,25 +132,26 @@ async def list_indexes() -> list[dict[str, Any]]:
         return _list_current_project_indexes()
 
     @app.post("/indexes/{index_name}/search", response_model=list[SearchResultModel])
-    async def search_index(index_name: str, body: SearchRequest):
+    async def search_index(index_name: str, body: dict[str, Any] = Body(...)):
         """
         Run semantic search against an existing LEANN index.
         """
+        parsed = SearchRequest(**body)
         try:
             index_path = _resolve_index_path(index_name)
         except FileNotFoundError as e:
             raise HTTPException(status_code=404, detail=str(e))  # type: ignore[misc]
 
         searcher = LeannSearcher(index_path=index_path)
         results = searcher.search(
-            query=body.query,
-            top_k=body.top_k,
-            complexity=body.complexity,
-            beam_width=body.beam_width,
-            prune_ratio=body.prune_ratio,
-            recompute_embeddings=body.recompute_embeddings,
-            pruning_strategy=body.pruning_strategy,  # type: ignore[arg-type]
-            use_grep=body.use_grep,
+            query=parsed.query,
+            top_k=parsed.top_k,
+            complexity=parsed.complexity,
+            beam_width=parsed.beam_width,
+            prune_ratio=parsed.prune_ratio,
+            recompute_embeddings=parsed.recompute_embeddings,
+            pruning_strategy=parsed.pruning_strategy,  # type: ignore[arg-type]
+            use_grep=parsed.use_grep,
         )
 
         # Normalize into JSON-serializable structures

tests/test_http_server_api.py

@@ -0,0 +1,61 @@
+import pytest
+
+pytest.importorskip("fastapi")
+
+from fastapi.testclient import TestClient
+
+from leann import server as leann_server
+
+
+class _DummySearchResult:
+    def __init__(self):
+        self.id = "doc-1"
+        self.score = 0.99
+        self.text = "dummy result"
+        self.metadata = {"source": "test"}
+
+
+class _DummySearcher:
+    def __init__(self, index_path: str):
+        self.index_path = index_path
+
+    def search(self, **kwargs):
+        return [_DummySearchResult()]
+
+
+def test_openapi_schema_loads():
+    app = leann_server.create_app()
+    client = TestClient(app)
+
+    response = client.get("/openapi.json")
+
+    assert response.status_code == 200
+    schema = response.json()
+    assert "/indexes/{index_name}/search" in schema["paths"]
+
+
+def test_search_endpoint_accepts_json_body(monkeypatch):
+    monkeypatch.setattr(leann_server, "_resolve_index_path", lambda _: "/tmp/fake.leann")
+    monkeypatch.setattr(leann_server, "LeannSearcher", _DummySearcher)
+
+    app = leann_server.create_app()
+    client = TestClient(app)
+
+    response = client.post(
+        "/indexes/demo/search",
+        json={
+            "query": "travel insurance",
+            "top_k": 2,
+            "complexity": 32,
+            "beam_width": 1,
+            "prune_ratio": 0.0,
+            "recompute_embeddings": True,
+            "pruning_strategy": "global",
+            "use_grep": False,
+        },
+    )
+
+    assert response.status_code == 200
+    data = response.json()
+    assert len(data) == 1
+    assert data[0]["id"] == "doc-1"