Create dispute_module.py

dispute_module.py

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+# Disclaimer + Right to Reply / Dispute module
+# Mục đích: đảm bảo tính công bằng và minh bạch của hệ thống
+
+DISCLAIMER = """
+---
+> ⚠️ **Disclaimer:** Results are generated by AI based on publicly available data
+> (visitor reviews, inspection reports, site metadata). EcoVerify AI does not
+> guarantee the absolute accuracy of third-party source data. Risk scores are
+> indicative only and should be used alongside official inspection processes.
+> This tool supports — but does not replace — formal certification audits.
+---
+"""
+
+def get_disclaimer() -> str:
+    return DISCLAIMER
+
+
+def process_dispute(
+    site_name: str,
+    dispute_reason: str,
+    evidence_text: str,
+    evidence_image,
+    current_nlp_risk: float,
+    current_img_risk: float,
+) -> tuple[str, float, float]:
+    """
+    Xử lý dispute từ operator.
+    - Phân tích evidence_text bằng NLP
+    - Phân tích evidence_image nếu có
+    - Điều chỉnh risk score nếu evidence hợp lệ
+    """
+
+    if not dispute_reason.strip() and not evidence_text.strip():
+        return "⚠️ Please provide a reason and/or evidence to submit a dispute.", current_nlp_risk, current_img_risk
+
+    adjustments = []
+    new_nlp_risk = current_nlp_risk
+    new_img_risk = current_img_risk
+
+    # ── Phân tích evidence text ───────────────────────────────────────
+    if evidence_text.strip():
+        from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
+        analyzer = SentimentIntensityAnalyzer()
+
+        POSITIVE_EVIDENCE = [
+            "installed", "improved", "upgraded", "certified", "trained",
+            "composting", "recycling", "reduced", "clean", "sorted",
+            "hired", "contracted", "fixed", "resolved", "invested",
+            "new bins", "waste system", "collection", "audit", "inspection passed"
+        ]
+
+        evidence_lower = evidence_text.lower()
+        sentiment      = analyzer.polarity_scores(evidence_text)['compound']
+        hits           = [w for w in POSITIVE_EVIDENCE if w in evidence_lower]
+
+        # Tính mức điều chỉnh
+        text_adjustment = 0.0
+        if sentiment > 0.3:
+            text_adjustment += 0.08
+        if len(hits) >= 3:
+            text_adjustment += 0.10
+        elif len(hits) >= 1:
+            text_adjustment += 0.05
+
+        if text_adjustment > 0:
+            new_nlp_risk = round(max(0.0, current_nlp_risk - text_adjustment), 3)
+            adjustments.append(
+                f"✅ Evidence text accepted — NLP risk reduced by {text_adjustment:.2f} "
+                f"(keywords found: {', '.join(hits[:5])})"
+            )
+        else:
+            adjustments.append("⚠️ Evidence text did not contain sufficient positive indicators.")
+
+    # ── Phân tích evidence image ──────────────────────────────────────
+    if evidence_image is not None:
+        try:
+            from image_module import analyze_image
+            from PIL import Image
+            import numpy as np
+
+            img_output, new_evidence_risk = analyze_image(evidence_image)
+
+            if new_evidence_risk < current_img_risk:
+                reduction = round(current_img_risk - new_evidence_risk, 3)
+                new_img_risk = new_evidence_risk
+                adjustments.append(
+                    f"✅ Evidence image accepted — Image risk reduced by {reduction:.3f} "
+                    f"(new image risk: {new_evidence_risk:.3f})"
+                )
+            else:
+                adjustments.append(
+                    f"⚠️ Evidence image did not show improvement over original "
+                    f"(image risk: {new_evidence_risk:.3f} vs original: {current_img_risk:.3f})"
+                )
+        except Exception as e:
+            adjustments.append(f"⚠️ Could not analyze evidence image: {e}")
+
+    # ── Tính combined risk mới ────────────────────────────────────────
+    new_combined = round((new_nlp_risk + new_img_risk) / 2, 3)
+    old_combined = round((current_nlp_risk + current_img_risk) / 2, 3)
+    delta        = round(old_combined - new_combined, 3)
+
+    if delta > 0:
+        verdict = f"✅ Dispute accepted — risk score updated"
+        color   = "improved"
+    else:
+        verdict = "ℹ️ Dispute noted — insufficient evidence to update score"
+        color   = "unchanged"
+
+    adj_str = "\n".join(adjustments)
+
+    output = f"""## 🏳️ Dispute / Right to Reply — {site_name}
+
+### {verdict}
+
+---
+
+### 📋 Dispute Summary
+| Field | Value |
+|-------|-------|
+| Reason submitted | {dispute_reason[:100] if dispute_reason else "Not provided"} |
+| Evidence text | {"Provided ✅" if evidence_text.strip() else "Not provided"} |
+| Evidence image | {"Provided ✅" if evidence_image is not None else "Not provided"} |
+
+---
+
+### 🔍 AI Review of Evidence
+{adj_str}
+
+---
+
+### 📊 Score Update
+| Metric | Before | After | Change |
+|--------|--------|-------|--------|
+| NLP Risk | {current_nlp_risk:.3f} | {new_nlp_risk:.3f} | {"↓ " + str(round((current_nlp_risk - new_nlp_risk)*100)) + "%" if new_nlp_risk < current_nlp_risk else "—"} |
+| Image Risk | {current_img_risk:.3f} | {new_img_risk:.3f} | {"↓ " + str(round((current_img_risk - new_img_risk)*100)) + "%" if new_img_risk < current_img_risk else "—"} |
+| **Combined Risk** | **{old_combined:.3f}** | **{new_combined:.3f}** | **{"↓ " + str(delta) if delta > 0 else "No change"}** |
+
+---
+
+{DISCLAIMER}
+
+> 💡 **Note:** All disputes are logged for transparency. Updated scores reflect
+> newly submitted evidence and do not erase original analysis. Both original
+> and updated scores are retained in the final report.
+"""
+    return output, new_nlp_risk, new_img_risk