Create app.py

app.py

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+import gradio as gr
+    import nltk
+    from nltk.sentiment.vader import SentimentIntensityAnalyzer
+    import re
+
+    # Download required NLTK resources
+    nltk.download('vader_lexicon')
+    nltk.download('punkt')
+
+    def calculate_scores(work_completion, delay_reports, incident_logs):
+        """
+        Calculates vendor performance scores based on log entries.
+        This is a simplified, rule-based demo version.
+        """
+
+        quality_score = 100  # Start with a base score
+        timeliness_score = 100
+        safety_score = 100
+        communication_score = 100
+
+        # --- Quality Score ---
+        quality_keywords_positive = ["good", "excellent", "high quality", "efficient", "precise"]
+        quality_keywords_negative = ["poor", "bad", "low quality", "defect", "error"]
+        for keyword in quality_keywords_positive:
+            quality_score += work_completion.lower().count(keyword) * 5
+        for keyword in quality_keywords_negative:
+            quality_score -= work_completion.lower().count(keyword) * 10
+    
+        # --- Timeliness Score ---
+        timeliness_keywords_positive = ["on time", "punctual", "early", "ahead of schedule"]
+        timeliness_keywords_negative = ["late", "delayed", "behind schedule"]
+        for keyword in timeliness_keywords_positive:
+            timeliness_score += work_completion.lower().count(keyword) * 5 + delay_reports.lower().count(keyword) * 5
+        for keyword in timeliness_keywords_negative:
+            timeliness_score -= delay_reports.lower().count(keyword) * 10
+    
+        # --- Safety Score ---
+        safety_keywords_positive = ["safe", "safety protocol", "no accidents", "precaution"]
+        safety_keywords_negative = ["unsafe", "accident", "injury", "hazard"]
+        for keyword in safety_keywords_positive:
+            safety_score += work_completion.lower().count(keyword) * 5 + incident_logs.lower().count(keyword) * 5
+        for keyword in safety_keywords_negative:
+            safety_score -= incident_logs.lower().count(keyword) * 15
+    
+        # --- Communication Score ---
+        communication_keywords_positive = ["clear communication", "responsive", "proactive", "helpful"]
+        communication_keywords_negative = ["unresponsive", "late reply", "miscommunication", "unclear"]
+        for keyword in communication_keywords_positive:
+            communication_score += work_completion.lower().count(keyword) * 5 + delay_reports.lower().count(keyword) * 5 + incident_logs.lower().count(keyword) * 5
+        for keyword in communication_keywords_negative:
+            communication_score -= delay_reports.lower().count(keyword) * 10
+
+        # Basic Sentiment Analysis (Optional - Requires NLTK Download)
+        # analyzer = SentimentIntensityAnalyzer()
+        # vs = analyzer.polarity_scores(work_completion + " " + delay_reports + " " + incident_logs)
+        # sentiment_score = vs['compound']
+        # communication_score += sentiment_score * 10  # Adjust weight as needed
+
+        # Ensure scores are within 0-100 range
+        quality_score = max(0, min(quality_score, 100))
+        timeliness_score = max(0, min(timeliness_score, 100))
+        safety_score = max(0, min(safety_score, 100))
+        communication_score = max(0, min(communication_score, 100))
+
+        # Calculate Final Score (as per Salesforce formula)
+        final_score = (0.4 * quality_score + 0.3 * timeliness_score + 0.15 * safety_score + 0.15 * communication_score)
+
+        return {
+            "Quality Score": round(quality_score, 2),
+            "Timeliness Score": round(timeliness_score, 2),
+            "Safety Score": round(safety_score, 2),
+            "Communication Score": round(communication_score, 2),
+            "Final Score": round(final_score, 2)
+        }
+
+    if __name__ == "__main__":
+        iface = gr.Interface(
+            fn=calculate_scores,
+            inputs=[
+                gr.inputs.Textbox(lines=5, label="Work Completion Details"),
+                gr.inputs.Textbox(lines=5, label="Delay Reports"),
+                gr.inputs.Textbox(lines=5, label="Incident Logs")
+            ],
+            outputs=gr.outputs.Label(label="Performance Scores"),
+            title="Vendor Performance Scoring",
+            description="Enter vendor logs to calculate performance scores."
+        )
+        iface.launch()