initial upload

data/human_writing_profile_info.txt

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+Generated with https://github.com/sam-paech/slop-forensics
+
+Using (human written) outputs sourced from: Nitral-AI/Reddit-SFW-Writing_Prompts_ShareGPT
+
+
+
+#!/usr/bin/env python3
+"""
+Convert the Nitral-AI ShareGPT dataset into a JSONL file that the
+slop-forensics analysis pipeline can read directly.
+"""
+
+import os, json, logging
+from tqdm import tqdm
+from datasets import load_dataset, disable_caching
+
+# ---------- config ----------
+OUTPUT_PATH = "results/datasets/generated_Nitral-AI__human.jsonl"
+SOURCE_NAME  = "Nitral-AI"         # kept for consistency with other scripts
+MODEL_FIELD  = "human-authored"    # any string is fine – it’s just a label
+# -----------------------------
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s — %(levelname)s — %(message)s")
+disable_caching()
+
+def main():
+    os.makedirs(os.path.dirname(OUTPUT_PATH), exist_ok=True)
+    ds = load_dataset("Nitral-AI/Reddit-SFW-Writing_Prompts_ShareGPT", split="train")
+
+    with open(OUTPUT_PATH, "w", encoding="utf-8") as f_out:
+        kept = 0
+        for idx, row in enumerate(tqdm(ds, desc="Extracting GPT turns")):
+            # locate first GPT message in the ShareGPT conversation
+            gpt_msg = None
+            for msg in row.get("conversations", []):
+                if isinstance(msg, dict) and msg.get("from") == "gpt":
+                    gpt_msg = msg.get("value", "").strip()
+                    break
+            if not gpt_msg:
+                continue  # skip rows without a GPT response
+
+            record = {
+                "source": SOURCE_NAME,
+                "id": idx,
+                "prompt": row.get("title", ""),   # not used by analysis but nice to keep
+                "model": MODEL_FIELD,
+                "output": gpt_msg
+            }
+            f_out.write(json.dumps(record, ensure_ascii=False) + "\n")
+            kept += 1
+
+    logging.info(f"Finished. Wrote {kept} records to {OUTPUT_PATH}")
+
+if __name__ == "__main__":
+    main()
+
+
+# Then:
+python3 scripts/slop_profile.py   --input-dir results/datasets   --analysis-output-dir results/analysis_human   --combined-output-file results/human_slop_profile.json   --top-n 1000000 --max-items 9999999