prepairing for production

app.py

@@ -8,6 +8,7 @@ import google_auth_oauthlib.flow
 from starlette.middleware.sessions import SessionMiddleware
 import gradio as gr
 from gpt_summary import Ui
+from utils import credentials_to_dict
 
 # Create an instance of the FastAPI app
 app = FastAPI()
@@ -23,42 +24,32 @@ app.mount("/assets", StaticFiles(directory="assets"), name="assets")
 async def home(request: Request):
     # Load the html content of the auth page
     html_content = load_page("./pages/auth_page.html")
-    # print("request session")
-    # print(request.session)
-    # creds = request.session.get("credentials", None)
-    creds = request.session.get("credentials", {})
 
-    if creds:
-        try:
-            creds = Credentials.from_authorized_user_info(info=creds)
-
-        except Exception as e:
-            raise Exception(
-                f"Invalid credentials in session with the following error{e}"
-            )
-
-    if not creds or not creds.valid:
+    if "credentials" not in request.session:
         return HTMLResponse(content=html_content, status_code=200)
+
     else:
         return RedirectResponse("/gradio/?__theme=dark")
 
 
 # Define the endpoint for Google authentication
 @app.get("/auth")
-async def integrate_google(request: Request):
-    # print(SCOPES)
+async def authorize(request: Request):
     flow = google_auth_oauthlib.flow.Flow.from_client_secrets_file(
         "credentials.json", scopes=SCOPES
     )
-    # flow.redirect_uri = "https://gpt-summary-u8pr.onrender.com/auth_callback"
-    # flow.redirect_uri = "http://127.0.0.1:8000/auth_callback"
-    flow.redirect_uri = (
-        request.url.scheme
-        + "://"
-        + request.url.hostname
-        + (":" + str(request.url.port) if request.url.port else "")
-        + app.url_path_for("auth_callback")
-    )
+
+    # for dev
+    flow.redirect_uri = "http://127.0.0.1:8000/auth_callback"
+    # for production
+    # flow.redirect_uri = (
+    #     request.url.scheme
+    #     + "://"
+    #     + request.url.hostname
+    #     + (":" + str(request.url.port) if request.url.port else "")
+    #     + app.url_path_for("auth_callback")
+    # )
+
     authorization_url, state = flow.authorization_url(
         access_type="offline",
         include_granted_scopes="true",
@@ -74,26 +65,16 @@ async def auth_callback(request: Request):
     flow = google_auth_oauthlib.flow.Flow.from_client_secrets_file(
         "credentials.json", scopes=SCOPES, state=state
     )
-    print(request.url.hostname)
-    # if request.url.hostname == "0.0.0.0":
-    #     flow.redirect_uri = "https://gpt-summary-u8pr.onrender.com/auth_callback"
-    # else:
-    #     flow.redirect_uri = (
-    #         request.url.scheme
-    #         + "://"
-    #         + request.url.hostname
-    #         + (":" + str(request.url.port) if request.url.port else "")
-    #         + app.url_path_for("auth_callback")
-    #     )
-    # flow.redirect_uri = "https://gpt-summary-u8pr.onrender.com/auth_callback"
-    # flow.redirect_uri = "http://127.0.0.1:8000/auth_callback"
-    flow.redirect_uri = (
-        request.url.scheme
-        + "://"
-        + request.url.hostname
-        + (":" + str(request.url.port) if request.url.port else "")
-        + app.url_path_for("auth_callback")
-    )
+    # for dev
+    flow.redirect_uri = "http://127.0.0.1:8000/auth_callback"
+    # for production
+    # flow.redirect_uri = (
+    #     request.url.scheme
+    #     + "://"
+    #     + request.url.hostname
+    #     + (":" + str(request.url.port) if request.url.port else "")
+    #     + app.url_path_for("auth_callback")
+    # )
 
     # Use the authorization server's response to fetch the OAuth 2.0 tokens.
     authorization_response = str(request.url)
@@ -105,14 +86,3 @@ async def auth_callback(request: Request):
 
 # Mount the Gradio UI
 app = gr.mount_gradio_app(app, Ui, path="/gradio")
-
-# Define a helper function to convert credentials to dictionary
-def credentials_to_dict(credentials):
-    return {
-        "token": credentials.token,
-        "refresh_token": credentials.refresh_token,
-        "token_uri": credentials.token_uri,
-        "client_id": credentials.client_id,
-        "client_secret": credentials.client_secret,
-        "scopes": credentials.scopes,
-    }

google_manager/fassade.py

@@ -8,8 +8,6 @@ class Fassade:
         self.creds = None
 
     def upload_to_drive(creds, content, FOLDER_NAME=FOLDER_NAME):
-        FOLDER_NAME = "GptSummary"
-
         files = search_folder(creds, FOLDER_NAME)
 
         if not files:
@@ -22,3 +20,5 @@ class Fassade:
         doc_response = save_doc(creds, doc_name, content)
 
         move_doc(creds, doc_response["documentId"], folder_id)
+
+        return {"status": "200"}

gpt_summary.py

@@ -7,6 +7,8 @@ from google_manager.fassade import Fassade
 from google.oauth2.credentials import Credentials
 from description import DESCRIPTION
 import gradio as gr
+from utils import credentials_to_dict
+import asyncio
 
 
 load_dotenv()
@@ -46,31 +48,54 @@ def transcribe(audio_file):
     return transcription
 
 
-def predict(input, request: gr.Request, history=[]):
+# def predict(input, request: gr.Request, history=[]):
+#     compress(input)
+#     print("whisper starts")
+#     transcription = transcribe(input)
+#     print("whisper ends")
+#     print("gpt starts")
+#     answer = chat(transcription)
+#     print("gpt ends")
+
+#     # upload the input/answer to google drive
+#     session_dict = vars(request.session)
+#     if "credentials" in session_dict:
+#         creds = Credentials(**vars(session_dict["credentials"]))
+
+#         doc_content = "user:\n" f"{transcription}\n" "\n" "summary:\n" f"{answer}\n"
+#         Fassade.upload_to_drive(creds, doc_content)
+#         # request.session["credentials"] = credentials_to_dict(creds)
+#         setattr(request.session, "credentials", credentials_to_dict(creds))
+
+
+async def predict(input, request: gr.Request, history=[]):
     compress(input)
     print("whisper starts")
-    transcription = transcribe(input)
+    transcription = await asyncio.to_thread(transcribe, input)
     print("whisper ends")
     print("gpt starts")
-    answer = chat(transcription)
+    answer = await asyncio.to_thread(chat, transcription)
     print("gpt ends")
 
+    loop = asyncio.get_event_loop()
     # upload the input/answer to google drive
-
-    doc_content = "user:\n" f"{transcription}\n" "\n" "summary:\n" f"{answer}\n"
-
-    creds_dict = vars(request.session).get("credentials", {})
-    if not creds_dict:
-        raise Exception("Credentials not found in session")
-
-    # Create credentials object from dictionary
-    try:
-        creds = Credentials.from_authorized_user_info(info=vars(creds_dict))
-
-    except Exception as e:
-        raise Exception(f"Invalid credentials in session with the following error{e}")
-
-    Fassade.upload_to_drive(creds, doc_content)
+    session_dict = vars(request.session)
+    if "credentials" in session_dict:
+        creds = Credentials(**vars(session_dict["credentials"]))
+
+        doc_content = "user:\n" f"{transcription}\n" "\n" "summary:\n" f"{answer}\n"
+        # await asyncio.to_thread(Fassade.upload_to_drive, creds, doc_content)
+        loop.run_in_executor(None, Fassade.upload_to_drive, creds, doc_content)
+        setattr(request.session, "credentials", credentials_to_dict(creds))
+
+    # session_data = request.session.get("credentials", None)
+    # if session_data:
+    #     creds = Credentials(**vars(session_data["credentials"]))
+
+    #     doc_content = "user:\n" f"{transcription}\n" "\n" "summary:\n" f"{answer}\n"
+    #     Fassade.upload_to_drive(creds, doc_content)
+    #     session_data.update(credentials_to_dict(creds))
+    #     request.session["credentials"] = session_data
 
     history.append((transcription, answer))
     response = history

main.py

@@ -2,15 +2,16 @@ import uvicorn
 import os
 from app import app
 
-os.environ["OAUTHLIB_INSECURE_TRANSPORT"] = "1"
 os.environ["OAUTHLIB_RELAX_TOKEN_SCOPE"] = "1"
 
 app = app
 
 # use this for local development
-# if __name__ == "__main__":
-#     uvicorn.run(
-#         f"app:app",
-#         port=8000,
-#         reload=True,
-#     )
+if __name__ == "__main__":
+    os.environ["OAUTHLIB_INSECURE_TRANSPORT"] = "1"
+
+    uvicorn.run(
+        f"app:app",
+        port=8000,
+        reload=True,
+    )

utils.py

@@ -6,3 +6,15 @@ def compress(audio_file):
     y, s = librosa.load(audio_file, sr=8000)  # Downsample 44.1kHz to 8kHz
     sf.write(audio_file, y, s, "PCM_24")
     return audio_file
+
+
+# Define a helper function to convert credentials to dictionary
+def credentials_to_dict(credentials):
+    return {
+        "token": credentials.token,
+        "refresh_token": credentials.refresh_token,
+        "token_uri": credentials.token_uri,
+        "client_id": credentials.client_id,
+        "client_secret": credentials.client_secret,
+        "scopes": credentials.scopes,
+    }