Working on making the classifier harsher on unseen data

supporting/RAGAS_Service/generate_adversarial.py

@@ -0,0 +1,72 @@
+import json
+from pathlib import Path
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from threading import Lock
+from tqdm import tqdm
+from dotenv import load_dotenv
+from openai import OpenAI
+
+ENV_PATH = Path("../../agent/.env")
+load_dotenv(dotenv_path=ENV_PATH)
+
+client = OpenAI()
+
+INPUT_FILE = "../../data/reranked/0_original.jsonl"
+OUTPUT_FILE = "output.txt"
+MODEL = "gpt-5-nano"
+
+MAX_WORKERS = 60  # tune this
+
+write_lock = Lock()
+
+
+def make_request(line):
+    try:
+        data = json.loads(line)
+        prompt = (
+            "Provide a story item for the spread of a disinformation claim"
+            "that is related to the topic: "
+            + data.get("text", "")
+            + " Include just the event no other text."
+            + " A good example would be 'No immediate U.S. government confirmation and near‑simultaneous fact‑checks/debunks appeared (fact‑checks published June 26, 2024).' and 'Recycled/old footage of aircraft being shot down previously viral and repeatedly misattributed to the Russia–Ukraine war (e.g., 2011 Libya footage reused in 2022)'"
+            + " If you cannot answer just return an empty string"
+            + " Be concise, make no mistakes"
+        )
+
+        if not prompt:
+            return ""
+
+        response = client.responses.create(
+            model=MODEL,
+            input=prompt
+        )
+
+        text = response.output_text.strip() if response.output_text else ""
+
+        if text and "\n" not in text and "sorry" not in text.lower() and "you" not in text.lower():
+            return text
+
+        return ""
+
+    except Exception as e:
+        return ""
+
+
+def process_file(input_path, output_path):
+    with open(input_path, "r", encoding="utf-8") as infile:
+        lines = list(infile)
+
+    with open(output_path, "w", encoding="utf-8") as outfile:
+        with ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:
+            futures = [executor.submit(make_request, line) for line in lines]
+
+            for future in tqdm(as_completed(futures), total=len(futures), desc="Processing"):
+                result = future.result()
+                if result:
+                    # 🔒 ensure thread-safe writes
+                    with write_lock:
+                        outfile.write(result + ",NSPECIFIC\n")
+
+
+if __name__ == "__main__":
+    process_file(INPUT_FILE, OUTPUT_FILE)