Update app.py

app.py

@@ -0,0 +1,97 @@
+import os
+import whisper
+import requests
+from flask import Flask, request, jsonify, render_template
+from dotenv import load_dotenv
+from deepgram import DeepgramClient, PrerecordedOptions
+import tempfile
+import json
+import subprocess
+from youtube_transcript_api import YouTubeTranscriptApi
+
+
+import warnings
+warnings.filterwarnings("ignore", message="FP16 is not supported on CPU; using FP32 instead")
+
+app = Flask(__name__)
+print("APP IS RUNNING, ANIKET")
+
+# Load the .env file
+load_dotenv()
+
+print("ENV LOADED, ANIKET")
+
+# Fetch the API key from the .env file
+API_KEY = os.getenv("FIRST_API_KEY")
+DEEPGRAM_API_KEY = os.getenv("SECOND_API_KEY")
+
+# Ensure the API key is loaded correctly
+if not API_KEY:
+    raise ValueError("API Key not found. Make sure it is set in the .env file.")
+
+if not DEEPGRAM_API_KEY:
+    raise ValueError("DEEPGRAM_API_KEY not found. Make sure it is set in the .env file.")
+
+GEMINI_API_ENDPOINT = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent"
+GEMINI_API_KEY = API_KEY
+
+@app.route("/", methods=["GET"])
+def health_check():
+    return jsonify({"status": "success", "message": "API is running successfully!"}), 200
+
+
+
+def query_gemini_api(transcription):
+    """
+    Send transcription text to Gemini API and fetch structured recipe information synchronously.
+    """
+    try:
+        # Define the structured prompt
+        prompt = (
+            "Analyze the provided cooking video transcription and extract the following structured information:\n"
+            "1. Recipe Name: Identify the name of the dish being prepared.\n"
+            "2. Ingredients List: Extract a detailed list of ingredients with their respective quantities (if mentioned).\n"
+            "3. Steps for Preparation: Provide a step-by-step breakdown of the recipe's preparation process, organized and numbered sequentially.\n"
+            "4. Cooking Techniques Used: Highlight the cooking techniques demonstrated in the video, such as searing, blitzing, wrapping, etc.\n"
+            "5. Equipment Needed: List all tools, appliances, or utensils mentioned, e.g., blender, hot pan, cling film, etc.\n"
+            "6. Nutritional Information (if inferred): Provide an approximate calorie count or nutritional breakdown based on the ingredients used.\n"
+            "7. Serving size: In count of people or portion size.\n"
+            "8. Special Notes or Variations: Include any specific tips, variations, or alternatives mentioned.\n"
+            "9. Festive or Thematic Relevance: Note if the recipe has any special relevance to holidays, events, or seasons.\n"
+            f"Text: {transcription}\n"
+        )
+
+        # Prepare the payload and headers
+        payload = {
+            "contents": [
+                {
+                    "parts": [
+                        {"text": prompt}
+                    ]
+                }
+            ]
+        }
+        headers = {"Content-Type": "application/json"}
+
+        # Send request to Gemini API synchronously
+        response = requests.post(
+            f"{GEMINI_API_ENDPOINT}?key={GEMINI_API_KEY}",
+            json=payload,
+            headers=headers,
+        )
+
+        # Raise error if response code is not 200
+        response.raise_for_status()
+
+        data = response.json()
+
+        return data.get("candidates", [{}])[0].get("content", {}).get("parts", [{}])[0].get("text", "No result found")
+
+    except requests.exceptions.RequestException as e:
+        print(f"Error querying Gemini API: {e}")
+        return {"error": str(e)}
+
+
+if __name__ == '__main__':
+    app.run(debug=True)
+