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Update app.py
Browse files
app.py
CHANGED
@@ -1,16 +1,14 @@
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import os
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import whisper
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import requests
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import
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import aiohttp # For making async HTTP requests
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from quart import Quart, request, jsonify, render_template
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from dotenv import load_dotenv
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from deepgram import DeepgramClient, PrerecordedOptions
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import warnings
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warnings.filterwarnings("ignore", message="FP16 is not supported on CPU; using FP32 instead")
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app =
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print("APP IS RUNNING, ANIKET")
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# Load the .env file
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@@ -26,11 +24,9 @@ DEEPGRAM_API_KEY = os.getenv("SECOND_API_KEY")
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if not API_KEY:
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raise ValueError("API Key not found. Make sure it is set in the .env file.")
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# Ensure the API key is loaded correctly
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if not DEEPGRAM_API_KEY:
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raise ValueError("DEEPGRAM_API_KEY not found. Make sure it is set in the .env file.")
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GEMINI_API_ENDPOINT = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent"
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GEMINI_API_KEY = API_KEY
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@@ -41,17 +37,17 @@ GEMINI_API_KEY = API_KEY
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@app.route("/", methods=["GET"])
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return jsonify({"status": "success", "message": "API is running successfully!"}), 200
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@app.route("/mbsa")
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return
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@app.route('/process-audio', methods=['POST'])
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print("GOT THE PROCESS AUDIO REQUEST, ANIKET")
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if 'audio' not in request.files:
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@@ -63,8 +59,14 @@ async def process_audio():
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try:
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print("STARTING TRANSCRIPTION, ANIKET")
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# Step 1:
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print("BEFORE THE transcription FAILED ERROR, CHECKING IF I GOT THE TRANSCRIPTION", transcription)
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@@ -73,21 +75,21 @@ async def process_audio():
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print("GOT THE transcription")
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print("Starting the GEMINI REQUEST TO STRUCTURE IT")
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structured_data = await query_gemini_api(transcription)
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print("GOT THE STRUCTURED DATA", structured_data)
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# Step
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return jsonify(structured_data)
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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"""
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Transcribe audio from a video file using
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Args:
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wav_file_path (str): Path to save the converted WAV file.
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@@ -100,14 +102,6 @@ async def transcribe_audio(wav_file_path):
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# Initialize Deepgram client
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deepgram = DeepgramClient(DEEPGRAM_API_KEY)
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# # Convert video to audio in WAV format using FFmpeg
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# print("Converting video to audio (WAV format)...")
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# ffmpeg_command = [
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# "ffmpeg", "-i", video_file_path, "-q:a", "0", "-map", "a", wav_file_path
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# ]
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# subprocess.run(ffmpeg_command, check=True)
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# print(f"Conversion successful! WAV file saved at: {wav_file_path}")
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# Open the converted WAV file
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with open(wav_file_path, 'rb') as buffer_data:
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payload = {'buffer': buffer_data}
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@@ -142,22 +136,13 @@ async def transcribe_audio(wav_file_path):
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except KeyError as e:
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return {"status": "error", "message": f"Error extracting transcript: {e}"}
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# output_text_file = "deepGramNovaTranscript.txt"
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# Write the transcript to the text file
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# with open(output_text_file, "w", encoding="utf-8") as file:
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# file.write(transcript)
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print(f"Transcript saved to: {output_text_file}")
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return transcript
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else:
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return {"status": "error", "message": "Invalid response from Deepgram."}
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except FileNotFoundError:
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return {"status": "error", "message": f"Video file not found: {
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except subprocess.CalledProcessError as e:
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return {"status": "error", "message": f"Error during audio conversion: {e}"}
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except Exception as e:
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return {"status": "error", "message": f"Unexpected error: {e}"}
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finally:
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@@ -167,9 +152,9 @@ async def transcribe_audio(wav_file_path):
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print(f"Temporary WAV file deleted: {wav_file_path}")
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"""
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Send transcription text to Gemini API and fetch structured recipe information
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"""
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try:
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# Define the structured prompt
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@@ -199,20 +184,22 @@ async def query_gemini_api(transcription):
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}
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headers = {"Content-Type": "application/json"}
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# Send request to Gemini API
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return data.get("candidates", [{}])[0].get("content", {}).get("parts", [{}])[0].get("text", "No result found")
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except
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print(f"Error querying Gemini API: {e}")
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return {"error": str(e)}
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import os
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import whisper
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import requests
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from flask import Flask, request, jsonify, render_template
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from dotenv import load_dotenv
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from deepgram import DeepgramClient, PrerecordedOptions
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import warnings
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warnings.filterwarnings("ignore", message="FP16 is not supported on CPU; using FP32 instead")
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app = Flask(__name__)
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print("APP IS RUNNING, ANIKET")
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# Load the .env file
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if not API_KEY:
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raise ValueError("API Key not found. Make sure it is set in the .env file.")
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if not DEEPGRAM_API_KEY:
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raise ValueError("DEEPGRAM_API_KEY not found. Make sure it is set in the .env file.")
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GEMINI_API_ENDPOINT = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent"
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GEMINI_API_KEY = API_KEY
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@app.route("/", methods=["GET"])
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def health_check():
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return jsonify({"status": "success", "message": "API is running successfully!"}), 200
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@app.route("/mbsa")
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def mbsa():
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return render_template("mbsa.html")
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@app.route('/process-audio', methods=['POST'])
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def process_audio():
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print("GOT THE PROCESS AUDIO REQUEST, ANIKET")
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if 'audio' not in request.files:
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try:
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print("STARTING TRANSCRIPTION, ANIKET")
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# Step 1: Save the audio file temporarily
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# Save the audio file to a temporary location for processing
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temp_audio_path = "/path/to/save/audio.wav" # Adjust this as needed
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with open(temp_audio_path, 'wb') as f:
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f.write(audio_file.read())
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# Step 2: Transcribe the uploaded audio file synchronously
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transcription = transcribe_audio(temp_audio_path)
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print("BEFORE THE transcription FAILED ERROR, CHECKING IF I GOT THE TRANSCRIPTION", transcription)
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print("GOT THE transcription")
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# Step 3: Generate structured recipe information using Gemini API synchronously
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print("Starting the GEMINI REQUEST TO STRUCTURE IT")
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structured_data = query_gemini_api(transcription)
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print("GOT THE STRUCTURED DATA", structured_data)
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# Step 4: Return the structured data
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return jsonify(structured_data)
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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def transcribe_audio(wav_file_path):
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"""
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Transcribe audio from a video file using Deepgram API synchronously.
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Args:
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wav_file_path (str): Path to save the converted WAV file.
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# Initialize Deepgram client
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deepgram = DeepgramClient(DEEPGRAM_API_KEY)
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# Open the converted WAV file
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with open(wav_file_path, 'rb') as buffer_data:
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payload = {'buffer': buffer_data}
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except KeyError as e:
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return {"status": "error", "message": f"Error extracting transcript: {e}"}
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print(f"Transcript obtained: {transcript}")
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return transcript
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else:
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return {"status": "error", "message": "Invalid response from Deepgram."}
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except FileNotFoundError:
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return {"status": "error", "message": f"Video file not found: {wav_file_path}"}
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except Exception as e:
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return {"status": "error", "message": f"Unexpected error: {e}"}
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finally:
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print(f"Temporary WAV file deleted: {wav_file_path}")
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def query_gemini_api(transcription):
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"""
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Send transcription text to Gemini API and fetch structured recipe information synchronously.
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"""
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try:
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# Define the structured prompt
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}
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headers = {"Content-Type": "application/json"}
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# Send request to Gemini API synchronously
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response = requests.post(
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f"{GEMINI_API_ENDPOINT}?key={GEMINI_API_KEY}",
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json=payload,
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headers=headers,
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timeout=60 # 60 seconds timeout for the request
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)
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# Raise error if response code is not 200
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response.raise_for_status()
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data = response.json()
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return data.get("candidates", [{}])[0].get("content", {}).get("parts", [{}])[0].get("text", "No result found")
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except requests.exceptions.RequestException as e:
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print(f"Error querying Gemini API: {e}")
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return {"error": str(e)}
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