Update app.py

app.py

@@ -1,101 +1,132 @@
-import io
-import tempfile
 import gradio as gr
-from transformers import pipeline
-from fpdf import FPDF
-import matplotlib.pyplot as plt
 
-# ---- 1. Model (text2text because FLAN-T5 is encoder-decoder) ----
-generator = pipeline("text2text-generation", model="google/flan-t5-small", device=-1)
-
-# ---- 2. Survey-driven report builder ----
-def generate_detailed_report(company_name, answers):
-    # convert answers dict into prompt text
-    survey_text = "\n".join([f"{k}: {v}" for k, v in answers.items()])
-    prompt = f"Generate a compliance assessment for {company_name} based on:\n{survey_text}. Mention their responses and the general findings."
-
-    # call model
-    result = generator(prompt, max_new_tokens=300)
-    report = result[0]["generated_text"]
-
-    # ---- 3. Simple chart (scores just for demo) ----
-    # map answers to numeric scores (Yes=1, No=0, Partially=0.5)
-    label_map = {"Yes": 1, "No": 0, "Partially": 0.5}
-    labels, values = [], []
-    for k, v in answers.items():
-        labels.append(k)
-        values.append(label_map.get(v, 0.5))
-
-    plt.figure(figsize=(6, 3))
-    plt.barh(labels, values, color="skyblue")
-    plt.xlim(0, 1)
-    plt.tight_layout()
-
-    # Save chart as temporary file
-    tmp_chart_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
-    plt.savefig(tmp_chart_file.name)
-    plt.close()
-
-    # ---- 4. Build PDF ----
-    pdf = FPDF()
-    pdf.add_page()
-    pdf.set_font("Arial", "B", 16)
-    pdf.cell(0, 10, f"{company_name} Compliance Report", ln=True, align="C")
-    pdf.ln(10)
-    pdf.set_font("Arial", "", 12)
-    pdf.multi_cell(0, 8, report)
-    pdf.image(tmp_chart_file.name, x=10, y=None, w=180)
-
-    # Save PDF as temporary file for Gradio
-    tmp_pdf_file = tempfile.NamedTemporaryFile(suffix=".pdf", delete=False)
-    pdf.output(tmp_pdf_file.name)
-
-    return report, tmp_chart_file.name, tmp_pdf_file.name
-
-# ---- 5. Gradio UI ----
-with gr.Blocks() as demo:
-    gr.Markdown("## 📝 Compliance Survey + Report Generator")
-
-    company_name = gr.Textbox(label="Company / Project Name", placeholder="Acme Corp")
-
-    # survey with a few quick yes/no/partial questions, now with labels
-    survey = {
-        "Data Encryption Implemented": gr.Radio(
-            ["Yes", "No", "Partially"], 
-            label="Data Encryption Implemented", 
-            value="Yes"
-        ),
-        "Regular Security Audits": gr.Radio(
-            ["Yes", "No", "Partially"], 
-            label="Regular Security Audits", 
-            value="No"
-        ),
-        "Privacy Policy Updated": gr.Radio(
-            ["Yes", "No", "Partially"], 
-            label="Privacy Policy Updated", 
-            value="Partially"
-        ),
-        "Employee Training Conducted": gr.Radio(
-            ["Yes", "No", "Partially"], 
-            label="Employee Training Conducted", 
-            value="Yes"
-        ),
+# -------------------------
+# Questions Configuration
+# -------------------------
+survey_questions = [
+    {
+        "label": "Company/Project Name",
+        "type": "text",
+        "key": "company"
+    },
+    {
+        "label": "1. Is data encryption implemented?",
+        "type": "radio",
+        "choices": ["Yes", "No", "Partially"],
+        "key": "encryption"
+    },
+    {
+        "label": "2. Are regular security audits performed?",
+        "type": "radio",
+        "choices": ["Yes", "No", "Partially"],
+        "key": "audits"
+    },
+    {
+        "label": "3. Is your privacy policy up to date and accessible to users?",
+        "type": "radio",
+        "choices": ["Yes", "No", "Partially"],
+        "key": "privacy"
+    },
+    {
+        "label": "4. Have employees received data governance training?",
+        "type": "checkbox",
+        "choices": ["Technical Staff", "HR & Admin", "All Employees", "Not Conducted"],
+        "key": "training"
+    },
+    {
+        "label": "5. Rate your organization’s data access control maturity:",
+        "type": "slider",
+        "key": "access_control",
+        "min": 1,
+        "max": 5
+    },
+    {
+        "label": "6. Are third-party vendors assessed for data compliance?",
+        "type": "radio",
+        "choices": ["Yes", "No", "Sometimes"],
+        "key": "third_party"
+    },
+    {
+        "label": "7. Additional notes or context (optional):",
+        "type": "text_area",
+        "key": "comments"
     }
-
-    submit = gr.Button("Generate Compliance Report")
-
-    report_out = gr.Textbox(label="Generated Report", lines=8)
-    chart_out = gr.Image(label="Compliance Chart")
-    pdf_out = gr.File(label="Download PDF")
-
-    def collect_and_generate(cname, *vals):
-        answers = {k: v for k, v in zip(survey.keys(), vals)}
-        return generate_detailed_report(cname, answers)
-
-    submit.click(
-        collect_and_generate,
-        inputs=[company_name] + list(survey.values()),
-        outputs=[report_out, chart_out, pdf_out],
+]
+
+# -------------------------
+# Report Generator
+# -------------------------
+def generate_compliance_report(**responses):
+    company = responses.get("company", "[Unknown Company]")
+    report = f"# Compliance Report for {company}\n\n"
+
+    # Score calculation (simplified logic)
+    score_map = {"Yes": 1, "Partially": 0.5, "No": 0, "Sometimes": 0.5}
+    score = 0
+    score += score_map.get(responses.get("encryption"), 0.5)
+    score += score_map.get(responses.get("audits"), 0.5)
+    score += score_map.get(responses.get("privacy"), 0.5)
+    score += score_map.get(responses.get("third_party"), 0.5)
+    score += (int(responses.get("access_control", 3)) / 5)
+    
+    training = responses.get("training", [])
+    if isinstance(training, list):
+        score += 1 if "All Employees" in training else 0.5 if training else 0
+
+    avg_score = score / 6  # weighted average
+    
+    if avg_score >= 0.8:
+        rating = "Excellent"
+    elif avg_score >= 0.5:
+        rating = "Moderate"
+    else:
+        rating = "Critical Risk"
+
+    report += f"**Overall Compliance Rating:** {rating}\n\n"
+    report += "## Survey Summary\n"
+    for q in survey_questions:
+        key = q["key"]
+        label = q["label"]
+        answer = responses.get(key, "[No Response]")
+        if isinstance(answer, list):
+            answer = ", ".join(answer) if answer else "None"
+        report += f"- **{label}**: {answer}\n"
+
+    notes = responses.get("comments", "No additional comments.")
+    report += f"\n**Additional Notes:**\n{notes}\n\n"
+    report += "\n_This report was generated using AI-assisted compliance heuristics._"
+    return report
+
+# -------------------------
+# Gradio UI
+# -------------------------
+with gr.Blocks(title="AI Compliance Survey") as demo:
+    gr.Markdown("""
+    # 🛡️ AI-Driven Compliance & Governance Survey
+    Answer the following questions to receive an AI-generated personalized compliance assessment report.
+    """)
+
+    inputs = {}
+    for q in survey_questions:
+        if q["type"] == "text":
+            inputs[q["key"]] = gr.Textbox(label=q["label"])
+        elif q["type"] == "radio":
+            inputs[q["key"]] = gr.Radio(q["choices"], label=q["label"])
+        elif q["type"] == "checkbox":
+            inputs[q["key"]] = gr.CheckboxGroup(q["choices"], label=q["label"])
+        elif q["type"] == "slider":
+            inputs[q["key"]] = gr.Slider(minimum=q["min"], maximum=q["max"], step=1, label=q["label"])
+        elif q["type"] == "text_area":
+            inputs[q["key"]] = gr.Textbox(label=q["label"], lines=4)
+
+    submit_btn = gr.Button("Generate Report")
+    report_output = gr.Textbox(label="Compliance Report", lines=20, interactive=False)
+
+    submit_btn.click(
+        fn=lambda **kwargs: generate_compliance_report(**kwargs),
+        inputs=[el for el in inputs.values()],
+        outputs=report_output
     )
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()