multi agent

app.py

@@ -153,8 +153,8 @@ With the right competitive research, you don’t just react to the market—you
     btn_recommend.click(fn=bestPractice, inputs=in_verbatim, outputs=out_product)
 
     gr.Markdown("""
-    Example Output
-    =============
+Example Output
+=============
 Based on the provided information from both researchers and security experts, we now have a comprehensive guide on understanding and effectively using Dock
 er containers in modern software development. Here's a summary:
 
@@ -204,31 +204,31 @@ ts.
 If there are any specific aspects or components you'd like further details on, feel free to ask!
 
     
-    The faster we build, the higher the risk of introducing vulnerabilities—especially in applications tied to personal banking workflows, where financial fraud can directly impact customer trust.
-    =====================
-    Yet most security tools today are reactive, slow, and generic—they don't reflect specific infrastructure, threat profile, or code patterns.
+The faster we build, the higher the risk of introducing vulnerabilities—especially in applications tied to personal banking workflows, where financial fraud can directly impact customer trust.
+=====================
+Yet most security tools today are reactive, slow, and generic—they don't reflect specific infrastructure, threat profile, or code patterns.
 
-    So here’s the core question we should be asking:
+So here’s the core question we should be asking:
 
-    How can we turn application security from a bottleneck into a competitive advantage—one that provides developers with fast, context-aware, and proactive feedback tailored to unique environment?
+How can we turn application security from a bottleneck into a competitive advantage—one that provides developers with fast, context-aware, and proactive feedback tailored to unique environment?
 
-    ### ✅ Reframed Customer Need
-    - Developers want actionable feedback during the build process—not after deployment.
+### ✅ Reframed Customer Need
+- Developers want actionable feedback during the build process—not after deployment.
 
-    - Security teams need to detect and explain vulnerabilities in specific patterns—across containers, APIs, and legacy integrations.
+- Security teams need to detect and explain vulnerabilities in specific patterns—across containers, APIs, and legacy integrations.
 
-    Product & revenue teams need confidence that customer-facing banking apps will not just ship fast—but also protect users and unlock new monetization opportunities.
+Product & revenue teams need confidence that customer-facing banking apps will not just ship fast—but also protect users and unlock new monetization opportunities.
 
-    ### 💡 Proposed Solution
-    A multi-agent GenAI system trained on RBC’s codebase, policy docs, and threat data—
-    that provides real-time, localized security feedback, explains why something’s a risk, and suggests secure-by-default alternatives.
+### 💡 Proposed Solution
+A multi-agent GenAI system trained on RBC’s codebase, policy docs, and threat data—
+that provides real-time, localized security feedback, explains why something’s a risk, and suggests secure-by-default alternatives.
 
-    Agents include:
-    - Code risk explainer agent: Detects common security flaws (e.g., insecure API calls) and provides context-specific impact analysis.
+Agents include:
+- Code risk explainer agent: Detects common security flaws (e.g., insecure API calls) and provides context-specific impact analysis.
 
-    - Infrastructure policy checker agent: Validates use of containers and deployment patterns against RBC’s internal compliance standards.
+- Infrastructure policy checker agent: Validates use of containers and deployment patterns against RBC’s internal compliance standards.
 
-    - Refactor assistant agent: Suggests how to fix the issue, with references to existing secure modules.
+- Refactor assistant agent: Suggests how to fix the issue, with references to existing secure modules.
     """)
 
   with gr.Tab("Graphrag Marketing"):