ArtVision / demo_script.py
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import csv
import os
import sys
import base64
import requests
import logging
from pathlib import Path
# ==================== CONFIGURAZIONE ====================
API_KEY = "ChiaveAPI"
MODEL_NAME = "gpt-4o"
IMAGE_DIR = Path("images")
CSV_PATH = Path("Dataset_Art-0725.csv")
OUTPUT_CSV = Path("risposte_output.csv")
CATEGORIE = {
"AR": "art_recognition",
"CR": "chronological_reasoning",
"CS": "contextual_summary",
"VR": "vision_reading",
"VB": "vision_basic",
"VL": "vision_logic",
"VRS": "vision_reasoning",
"IG" : "img_gen"
}
# ==================== LOGGING ====================
logging.basicConfig(
filename='task_log.txt',
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s'
)
# ==================== FUNZIONI ====================
def encode_image(image_path: Path) -> str:
with open(image_path, "rb") as img:
return base64.b64encode(img.read()).decode("utf-8")
def validate_image_paths(row):
missing = []
for col in ['immagine_1_path', 'immagine_2_path']:
if row[col].strip():
path = IMAGE_DIR / row[col].strip()
if not path.exists():
missing.append(path)
return missing
def invia_task(prompt, image_paths):
content = [{"type": "text", "text": prompt}]
for img_path in image_paths:
if img_path.exists():
b64 = encode_image(img_path)
content.append({
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{b64}"
}
})
payload = {
"model": MODEL_NAME,
"messages": [
{
"role": "system",
"content": (
"Sei uno storico dell’arte specializzato in analisi iconografiche e storico-stilistiche. "
"Rispondi sempre in italiano, in stile accademico, formale e neutrale. "
"Analizza secondo i criteri storico-artistici e rispondi in modo rigoroso e preciso."
)
},
{"role": "user", "content": content}
],
"max_tokens": 1000
}
response = requests.post(
"https://api.openai.com/v1/chat/completions",
headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
json=payload
)
if response.status_code == 200:
return response.json()["choices"][0]["message"]["content"]
else:
raise Exception(f"Errore API: {response.status_code} - {response.text}")
# ==================== MAIN ====================
def main():
if len(sys.argv) < 2:
print("Uso: python test_01.py AR CR ...")
sys.exit(1)
categorie_input = sys.argv[1:]
categorie_mapped = {CATEGORIE[c] for c in categorie_input if c in CATEGORIE}
if not categorie_mapped:
print("Nessuna categoria valida fornita.")
sys.exit(1)
results = []
with open(CSV_PATH, encoding='utf-8') as f:
reader = csv.DictReader(f)
for idx, row in enumerate(reader, 1):
if row["categoria"] not in categorie_mapped:
continue
image_paths = [IMAGE_DIR / row["immagine_1_path"].strip()]
if row["immagine_2_path"].strip():
image_paths.append(IMAGE_DIR / row["immagine_2_path"].strip())
missing = validate_image_paths(row)
if missing:
msg = f"[TASK {idx}] Immagini mancanti: {[str(m) for m in missing]}"
logging.warning(msg)
print(msg)
continue
# Costruzione del prompt
base_prompt = row["prompt"].strip() + " " + row["instructions"].strip()
opzioni = [row.get("opzione_1", ""), row.get("opzione_2", ""), row.get("opzione_3", "")]
opzioni = [opt.strip() for opt in opzioni if opt.strip()]
if opzioni:
base_prompt += "\n\nOpzioni disponibili:\n" + "\n".join(f"- {opt}" for opt in opzioni)
try:
result = invia_task(base_prompt, image_paths)
logging.info(f"[TASK {idx}] Completato con successo.")
results.append({
"task_id": idx,
"risposta": result,
"prompt_inviato": base_prompt
})
except Exception as e:
logging.error(f"[TASK {idx}] Errore durante l'invio: {e}")
print(f"[TASK {idx}] Errore - vedi log")
# Scrittura risultati su CSV
if results:
with open(OUTPUT_CSV, mode='w', encoding='utf-8', newline='') as out_csv:
writer = csv.DictWriter(out_csv, fieldnames=["task_id", "risposta", "prompt_inviato"])
writer.writeheader()
for r in results:
writer.writerow(r)
print(f"Esecuzione completata. Risposte salvate in {OUTPUT_CSV}.")
if __name__ == "__main__":
main()