Update app.py

app.py

@@ -6,49 +6,49 @@ from transformers import RobertaForSequenceClassification, RobertaTokenizer
 
 Load custom fine-tuned sentiment model
 
-sentiment_model = AutoModelForSequenceClassification.from_pretrained("SamanthaStorm/tether-sentiment”)
-sentiment_tokenizer = AutoTokenizer.from_pretrained(“SamanthaStorm/tether-sentiment”)
+sentiment_model = AutoModelForSequenceClassification.from_pretrained("SamanthaStorm/tether-sentiment")
+sentiment_tokenizer = AutoTokenizer.from_pretrained("SamanthaStorm/tether-sentiment")
 
 Load abuse pattern model
 
-model_name = “SamanthaStorm/abuse-pattern-detector-v2”
+model_name = "SamanthaStorm/abuse-pattern-detector-v2"
 model = RobertaForSequenceClassification.from_pretrained(model_name, trust_remote_code=True)
 tokenizer = RobertaTokenizer.from_pretrained(model_name, trust_remote_code=True)
 
 LABELS = [
-"gaslighting”, “mockery”, “dismissiveness”, “control”, “guilt_tripping”, “apology_baiting”, “blame_shifting”, “projection”,
-"contradictory_statements”, “manipulation”, “deflection”, “insults”, “obscure_formal”, “recovery_phase”, “non_abusive”,
-"suicidal_threat”, “physical_threat”, “extreme_control”
+"gaslighting", "mockery", "dismissiveness", "control", "guilt_tripping", "apology_baiting", "blame_shifting", "projection",
+"contradictory_statements", "manipulation", "deflection", "insults", "obscure_formal", "recovery_phase", "non_abusive",
+"suicidal_threat", "physical_threat", "extreme_control"
 ]
 
 THRESHOLDS = {
-"gaslighting”: 0.25, “mockery”: 0.15, “dismissiveness”: 0.30, “control”: 0.43, “guilt_tripping”: 0.19,
-"apology_baiting”: 0.45, “blame_shifting”: 0.23, “projection”: 0.50, “contradictory_statements”: 0.25,
-"manipulation”: 0.25, “deflection”: 0.30, “insults”: 0.34, “obscure_formal”: 0.25, “recovery_phase”: 0.25,
-"non_abusive”: 2.0, “suicidal_threat”: 0.45, “physical_threat”: 0.02, “extreme_control”: 0.36
+"gaslighting": 0.25, "mockery": 0.15, "dismissiveness": 0.30, "control": 0.43, "guilt_tripping": 0.19,
+"apology_baiting": 0.45, "blame_shifting": 0.23, "projection": 0.50, "contradictory_statements": 0.25,
+"manipulation": 0.25, "deflection": 0.30, "insults": 0.34, "obscure_formal": 0.25, "recovery_phase": 0.25,
+"non_abusive": 2.0, "suicidal_threat": 0.45, "physical_threat": 0.02, "extreme_control": 0.36
 }
 
 PATTERN_LABELS = LABELS[:15]
 DANGER_LABELS = LABELS[15:18]
 
 EXPLANATIONS = {
-"gaslighting”: “Gaslighting involves making someone question their own reality or perceptions…”,
-"blame_shifting”: “Blame-shifting is when one person redirects the responsibility…”,
-"projection”: “Projection involves accusing the victim of behaviors the abuser exhibits.”,
-"dismissiveness”: “Dismissiveness is belittling or disregarding another person’s feelings.”,
-"mockery”: “Mockery ridicules someone in a hurtful, humiliating way.”,
-"recovery_phase”: “Recovery phase dismisses someone’s emotional healing process.”,
-"insults”: “Insults are derogatory remarks aimed at degrading someone.”,
-"apology_baiting”: “Apology-baiting manipulates victims into apologizing for abuser’s behavior.”,
-"deflection”: “Deflection avoids accountability by redirecting blame.”,
-"control”: “Control restricts autonomy through manipulation or coercion.”,
-"extreme_control”: “Extreme control dominates decisions and behaviors entirely.”,
-"physical_threat”: “Physical threats signal risk of bodily harm.”,
-"suicidal_threat”: “Suicidal threats manipulate others using self-harm threats.”,
-"guilt_tripping”: “Guilt-tripping uses guilt to manipulate someone’s actions.”,
-"manipulation”: “Manipulation deceives to influence or control outcomes.”,
-"non_abusive”: “Non-abusive language is respectful and free of coercion.”,
-"obscure_formal”: “Obscure/formal language manipulates through confusion or superiority.”
+"gaslighting": "Gaslighting involves making someone question their own reality or perceptions...",
+"blame_shifting": "Blame-shifting is when one person redirects the responsibility...",
+"projection": "Projection involves accusing the victim of behaviors the abuser exhibits.",
+"dismissiveness": "Dismissiveness is belittling or disregarding another person’s feelings.",
+"mockery": "Mockery ridicules someone in a hurtful, humiliating way.",
+"recovery_phase": "Recovery phase dismisses someone's emotional healing process.",
+"insults": "Insults are derogatory remarks aimed at degrading someone.",
+"apology_baiting": "Apology-baiting manipulates victims into apologizing for abuser's behavior.",
+"deflection": "Deflection avoids accountability by redirecting blame.",
+"control": "Control restricts autonomy through manipulation or coercion.",
+"extreme_control": "Extreme control dominates decisions and behaviors entirely.",
+"physical_threat": "Physical threats signal risk of bodily harm.",
+"suicidal_threat": "Suicidal threats manipulate others using self-harm threats.",
+"guilt_tripping": "Guilt-tripping uses guilt to manipulate someone’s actions.",
+"manipulation": "Manipulation deceives to influence or control outcomes.",
+"non_abusive": "Non-abusive language is respectful and free of coercion.",
+"obscure_formal": "Obscure/formal language manipulates through confusion or superiority."
 }
 
 def custom_sentiment(text):
@@ -60,7 +60,6 @@ label_idx = torch.argmax(probs).item()
 
 label_map = {0: "supportive", 1: "undermining"}
 label = label_map[label_idx]
-
 score = probs[0][label_idx].item()
 return {"label": label, "score": score}
 
@@ -114,8 +113,7 @@ else:
     resources = "For more information on abuse patterns, consider reaching out to support groups or professional counselors."
 
 scored_patterns = [
-    (label, score) for label, score in zip(LABELS, scores)
-    if label != "non_abusive" and score > adjusted_thresholds[label]
+    (label, score) for label, score in zip(PATTERN_LABELS, scores[:15]) if label != "non_abusive"
 ]
 top_patterns = sorted(scored_patterns, key=lambda x: x[1], reverse=True)[:2]
 
@@ -142,15 +140,15 @@ return result
 iface = gr.Interface(
 fn=analyze_messages,
 inputs=[
-gr.Textbox(lines=10, placeholder=“Enter message here…”),
+gr.Textbox(lines=10, placeholder="Enter message here…"),
 gr.CheckboxGroup(label=“Do any of these apply to your situation?”, choices=[
-“They’ve threatened harm”, “They isolate me”, “I’ve changed my behavior out of fear”,
-“They monitor/follow me”, “I feel unsafe when alone with them”
+"They’ve threatened harm", "They isolate me", "I’ve changed my behavior out of fear",
+"They monitor/follow me", "I feel unsafe when alone with them"
 ])
 ],
 outputs=[gr.Textbox(label=“Analysis Result”)],
 title=“Abuse Pattern Detector”
 )
 
-if name == “main”:
+if name == "main":
 iface.launch()