Fast Api JSONResponst change

app.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-from fastapi import FastAPI
+from fastapi import FastAPI, responses, status
 import controller
 from data import data_type
 from typing import List, Dict, Tuple
@@ -25,7 +25,7 @@
 @app.get("/classification/recommend/{data_type}")
 def recommendations(
     data_type: str,
-) -> Tuple[List[Dict[str, str]], int]:
+) -> responses.JSONResponse:
     recommends = [
         ### English ###
         {
@@ -92,39 +92,44 @@ def recommendations(
         },
     ]
 
-    return recommends, 200
+    return responses.JSONResponse(status_code=status.HTTP_200_OK, content=recommends)
 
 
 @app.post("/classification/encode")
-def encode_classification(request: data_type.Request) -> Tuple[int, str]:
+def encode_classification(request: data_type.Request) -> responses.PlainTextResponse:
     # session logic for threads in side
-    return controller.start_encoding_thread(request, "classification"), ""
+    status_code = controller.start_encoding_thread(request, "classification")
+
+    return responses.PlainTextResponse(status_code=status_code)
 
 
 @app.post("/extraction/encode")
-def encode_extraction(request: data_type.Request) -> Tuple[int, str]:
+def encode_extraction(request: data_type.Request) -> responses.PlainTextResponse:
     # session logic for threads in side
-    return controller.start_encoding_thread(request, "extraction"), ""
+    status_code = controller.start_encoding_thread(request, "extraction")
+    return responses.PlainTextResponse(status_code=status_code)
 
 
 @app.delete("/delete/{project_id}/{embedding_id}")
-def delete_embedding(project_id: str, embedding_id: str) -> Tuple[int, str]:
+def delete_embedding(project_id: str, embedding_id: str) -> responses.PlainTextResponse:
     session_token = general.get_ctx_token()
-    return_value = controller.delete_embedding(project_id, embedding_id)
+    status_code = controller.delete_embedding(project_id, embedding_id)
     general.remove_and_refresh_session(session_token)
-    return return_value, ""
+    return responses.PlainTextResponse(status_code=status_code)
 
 
 @app.post("/upload_tensor_data/{project_id}/{embedding_id}")
-def upload_tensor_data(project_id: str, embedding_id: str) -> Tuple[int, str]:
+def upload_tensor_data(
+    project_id: str, embedding_id: str
+) -> responses.PlainTextResponse:
     session_token = general.get_ctx_token()
     controller.upload_embedding_as_file(project_id, embedding_id)
     request_util.post_embedding_to_neural_search(project_id, embedding_id)
     general.remove_and_refresh_session(session_token)
-    return 200, ""
+    return responses.PlainTextResponse(status_code=status.HTTP_200_OK)
 
 
 @app.put("/config_changed")
-def config_changed() -> int:
+def config_changed() -> responses.PlainTextResponse:
     config_handler.refresh_config()
-    return 200
+    return responses.PlainTextResponse(status_code=status.HTTP_200_OK)

controller.py

@@ -10,6 +10,7 @@
     notification,
     organization,
 )
+from fastapi import status
 import pickle
 import torch
 import traceback
@@ -85,7 +86,7 @@ def get_docbins(
 def start_encoding_thread(request: data_type.Request, embedding_type: str) -> int:
     doc_ock.post_embedding_creation(request.user_id, request.config_string)
     daemon.run(prepare_run_encoding, request, embedding_type)
-    return 200
+    return status.HTTP_200_OK
 
 
 def prepare_run_encoding(request: data_type.Request, embedding_type: str) -> int:
@@ -215,7 +216,7 @@ def run_encoding(
             send_project_update(
                 request.project_id, f"notification_created:{request.user_id}", True
             )
-            return 422
+            return status.HTTP_422_UNPROCESSABLE_ENTITY
         except ValueError:
             embedding.update_embedding_state_failed(
                 request.project_id,
@@ -239,7 +240,7 @@ def run_encoding(
             send_project_update(
                 request.project_id, f"notification_created:{request.user_id}", True
             )
-            return 422
+            return status.HTTP_422_UNPROCESSABLE_ENTITY
 
         if not embedder:
             embedding.update_embedding_state_failed(
@@ -288,7 +289,7 @@ def run_encoding(
             f"embedding:{embedding_id}:state:{enums.EmbeddingState.FAILED.value}",
         )
         doc_ock.post_embedding_failed(request.user_id, request.config_string)
-        return 422
+        return status.HTTP_422_UNPROCESSABLE_ENTITY
 
     try:
         record_ids, attribute_values_raw = record.get_attribute_data(
@@ -410,7 +411,7 @@ def run_encoding(
         )
         print(traceback.format_exc(), flush=True)
         doc_ock.post_embedding_failed(request.user_id, request.config_string)
-        return 500
+        return status.HTTP_500_INTERNAL_SERVER_ERROR
 
     if embedding.get(request.project_id, embedding_id):
         for warning_type, idx_list in embedder.get_warnings().items():
@@ -484,7 +485,7 @@ def run_encoding(
         doc_ock.post_embedding_finished(request.user_id, request.config_string)
     general.commit()
     general.remove_and_refresh_session(session_token)
-    return 200
+    return status.HTTP_200_OK
 
 
 def delete_embedding(project_id: str, embedding_id: str) -> int:
@@ -494,12 +495,12 @@ def delete_embedding(project_id: str, embedding_id: str) -> int:
     object_name = f"embedding_tensors_{embedding_id}.csv.bz2"
 
     org_id = organization.get_id_by_project_id(project_id)
-    s3.delete_object(org_id, project_id + "/" + object_name)
+    s3.delete_object(org_id, f"{project_id}/{object_name}")
     request_util.delete_embedding_from_neural_search(embedding_id)
     pickle_path = os.path.join("/inference", project_id, f"embedder-{embedding_id}.pkl")
     if os.path.exists(pickle_path):
         os.remove(pickle_path)
-    return 200
+    return status.HTTP_200_OK
 
 
 @param_throttle(seconds=5)

data/doc_ock.py

@@ -49,9 +49,13 @@ def _post_event(user_id: str, config_string: str, state: str) -> Any:
         "State": state,
         "Host": os.getenv("S3_ENDPOINT"),
     }
+
     response = requests.post(url, json=data)
-    if response.status_code == 200:
-        result, _ = response.json()
-        return result
-    else:
+
+    if response.status_code != 200:
         raise Exception("Could not send data to Doc Ock")
+
+    if response.headers.get("content-type") == "application/json":
+        return response.json()
+    else:
+        return response.text

util/config_handler.py

@@ -20,22 +20,21 @@ def __get_config() -> Dict[str, Any]:
 
 def refresh_config():
     response = requests.get(REQUEST_URL)
-    if response.status_code == 200:
-        global __config
-        __config = json.loads(json.loads(response.text))
-        daemon.run(invalidate_after, 3600)  # one hour
-    else:
-        raise Exception(
+    if response.status_code != 200:
+        raise ValueError(
             f"Config service cant be reached -- response.code{response.status_code}"
         )
+    global __config
+    __config = response.json()
+    daemon.run(invalidate_after, 3600)  # one hour
 
 
 def get_config_value(
     key: str, subkey: Optional[str] = None
 ) -> Union[str, Dict[str, str]]:
     config = __get_config()
     if key not in config:
-        raise Exception(f"Key {key} coudn't be found in config")
+        raise ValueError(f"Key {key} coudn't be found in config")
     value = config[key]
 
     if not subkey:
@@ -44,7 +43,7 @@ def get_config_value(
     if isinstance(value, dict) and subkey in value:
         return value[subkey]
     else:
-        raise Exception(f"Subkey {subkey} coudn't be found in config[{key}]")
+        raise ValueError(f"Subkey {subkey} coudn't be found in config[{key}]")
 
 
 def invalidate_after(sec: int) -> None: