Created using Colab

Author: OneFineStarstuff

agi_pipeline.ipynb

@@ -5,7 +5,7 @@
     "colab": {
       "private_outputs": true,
       "provenance": [],
-      "authorship_tag": "ABX9TyPoHH519BuqGSnR/HON75UP",
+      "authorship_tag": "ABX9TyNk2WJFhV2VGr1cGsUqJ/ai",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -30,42 +30,38 @@
     {
       "cell_type": "code",
       "source": [
-        "# === Imports ===\n",
         "import os\n",
         "import asyncio\n",
-        "import time\n",
-        "from typing import List\n",
         "import torch\n",
-        "from transformers import T5Tokenizer, T5ForConditionalGeneration\n",
+        "from typing import List\n",
         "from PIL import Image\n",
-        "from fastapi import FastAPI, UploadFile, Depends, HTTPException, Request\n",
+        "from fastapi import FastAPI, UploadFile, Depends, HTTPException\n",
         "from fastapi.security import OAuth2PasswordBearer\n",
         "from pydantic import BaseModel, SecretStr\n",
-        "import whisper\n",
-        "from ultralytics import YOLO\n",
         "import pyttsx3\n",
         "from loguru import logger\n",
         "import io\n",
-        "import nest_asyncio\n",
         "import uvicorn\n",
+        "import nest_asyncio\n",
+        "from transformers import T5Tokenizer, T5ForConditionalGeneration\n",
+        "from ultralytics import YOLO\n",
+        "import whisper\n",
         "\n",
-        "# === Logging Setup ===\n",
+        "# === Configuration and Logging Setup ===\n",
+        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
         "logger.add(\"pipeline_{time}.log\", rotation=\"1 MB\", level=\"DEBUG\", enqueue=True, backtrace=True, diagnose=True)\n",
         "logger.info(\"Application startup\")\n",
         "\n",
-        "# === Security Enhancement: Environment Variable for Secure Token ===\n",
+        "# === Security Setup ===\n",
         "SECURE_TOKEN = SecretStr(os.getenv(\"SECURE_TOKEN\", \"YvZz9Hni0hWJPh_UWW4dQYf9rhIe9nNYcC5ZQTTZz0Q\"))\n",
-        "\n",
-        "# === OAuth2PasswordBearer for Authentication ===\n",
         "oauth2_scheme = OAuth2PasswordBearer(tokenUrl=\"token\")\n",
         "\n",
-        "# === Authentication Function ===\n",
         "def authenticate_user(token: str = Depends(oauth2_scheme)):\n",
         "    if token != SECURE_TOKEN.get_secret_value():\n",
         "        logger.warning(\"Authentication failed.\")\n",
         "        raise HTTPException(status_code=401, detail=\"Invalid token\")\n",
         "\n",
-        "# === Request and Response Models (Pydantic) ===\n",
+        "# === Pydantic Models ===\n",
         "class TextRequest(BaseModel):\n",
         "    text: str\n",
         "\n",
@@ -84,17 +80,17 @@
         "        if not prompt.strip():\n",
         "            raise ValueError(\"Prompt cannot be empty.\")\n",
         "        logger.debug(f\"Generating text for prompt: {prompt}\")\n",
-        "        inputs = self.tokenizer(prompt, return_tensors=\"pt\")\n",
-        "        outputs = self.model.generate(inputs[\"input_ids\"], max_length=100)\n",
+        "        inputs = self.tokenizer(prompt, return_tensors=\"pt\").to(device)\n",
+        "        with torch.no_grad():\n",
+        "            outputs = self.model.generate(inputs[\"input_ids\"], max_length=100)\n",
         "        response = self.tokenizer.decode(outputs[0], skip_special_tokens=True)\n",
         "        logger.info(f\"Generated response: {response}\")\n",
         "        return response\n",
         "\n",
         "# === CV Module (YOLOv8 for Object Detection) ===\n",
         "class CVModule:\n",
         "    def __init__(self):\n",
-        "        self.device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
-        "        self.model = YOLO('yolov8n.pt').to(self.device)\n",
+        "        self.model = YOLO('yolov8n.pt').to(device)\n",
         "        logger.info(\"CV model loaded successfully.\")\n",
         "\n",
         "    def detect_objects(self, image: Image.Image) -> str:\n",
@@ -181,9 +177,7 @@
         "# === Run the Application with HTTPS (uvicorn) ===\n",
         "if __name__ == \"__main__\":\n",
         "    nest_asyncio.apply()\n",
-        "    config = uvicorn.Config(app, host=\"0.0.0.0\", port=8000)\n",
-        "    server = uvicorn.Server(config)\n",
-        "    asyncio.run(server.serve())"
+        "    uvicorn.run(app, host=\"0.0.0.0\", port=8000)"
       ],
       "metadata": {
         "id": "UgUAMujBWqGS"