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A web interface for evaluating agentic AI projects against the
AISA (Agentic AI Systems Architecture) reference architecture.
"""
import gradio as gr
import tempfile
import zipfile
import shutil
from pathlib import Path
from datetime import datetime
from aisa.scanner.detector import detect_frameworks
from aisa.scanner.analyzer import scan_project
from aisa.ai_checker.agent import ai_check_project, AICheckConfig
from aisa.ai_checker.combined import combine_results
from aisa.report.generator import generate_markdown_report
from aisa.report.recommendations import get_recommendation, get_priority
from aisa.layers import ALL_LAYERS, ALL_CONTRACTS
# ---------------------------------------------------------------------------
# Core Analysis Functions
# ---------------------------------------------------------------------------
def run_analysis(
zip_file,
analysis_mode: str,
provider: str,
api_key: str,
model_name: str,
progress=gr.Progress(),
):
"""Run AISA compliance analysis on an uploaded project."""
if zip_file is None:
raise gr.Error("Please upload a ZIP file of your project.")
# Step 1: Extract ZIP
progress(0.05, desc="Extracting project files...")
temp_dir = tempfile.mkdtemp(prefix="aisa_")
project_path = Path(temp_dir) / "project"
project_path.mkdir()
try:
with zipfile.ZipFile(zip_file.name, "r") as zf:
zf.extractall(project_path)
except (zipfile.BadZipFile, Exception) as e:
shutil.rmtree(temp_dir, ignore_errors=True)
raise gr.Error(f"Invalid ZIP file: {e}")
# Check if ZIP has a single root folder
items = list(project_path.iterdir())
if len(items) == 1 and items[0].is_dir():
project_path = items[0]
try:
# Step 2: Detect frameworks
progress(0.15, desc="Detecting frameworks...")
frameworks = detect_frameworks(project_path)
# Step 3: Pattern scan
progress(0.25, desc="Running pattern-based scan...")
pattern_result = scan_project(project_path, frameworks)
ai_result = None
# Step 4: AI analysis (if requested)
if analysis_mode in ("AI Analysis", "Full Analysis (Pattern + AI)"):
if not api_key.strip():
if analysis_mode == "Full Analysis (Pattern + AI)":
progress(0.60, desc="No API key provided, using pattern results only...")
else:
shutil.rmtree(temp_dir, ignore_errors=True)
raise gr.Error("API key is required for AI Analysis. Please enter your API key.")
else:
progress(0.40, desc=f"Running AI analysis with {provider}...")
config = AICheckConfig(
provider=provider.lower(),
model=model_name.strip() or "",
api_key=api_key.strip(),
)
config = config.resolve()
try:
ai_result = ai_check_project(project_path, config)
except Exception as e:
if analysis_mode == "AI Analysis":
shutil.rmtree(temp_dir, ignore_errors=True)
raise gr.Error(f"AI analysis failed: {e}")
# For full-check, fall back to pattern only
# Step 5: Combine results
progress(0.70, desc="Generating report...")
if analysis_mode == "AI Analysis" and ai_result:
result = ai_result
elif analysis_mode == "Full Analysis (Pattern + AI)" and ai_result:
result = combine_results(pattern_result, ai_result)
else:
result = pattern_result
# Step 6: Generate outputs
progress(0.85, desc="Formatting results...")
# Summary card
summary = _build_summary(result, analysis_mode)
# Layer details
layer_details = _build_layer_details(result)
# Full markdown report
full_report = generate_markdown_report(result)
# Save report to file for download
report_path = Path(temp_dir) / "aisa_report.md"
report_path.write_text(full_report)
progress(1.0, desc="Done!")
return summary, layer_details, full_report, str(report_path)
finally:
# Clean up extracted files but keep report
pass
# ---------------------------------------------------------------------------
# Output Builders
# ---------------------------------------------------------------------------
def _build_summary(result, mode: str) -> str:
"""Build the summary overview card."""
score = result.overall_score
grade = _get_grade(score)
layer_score = result.layer_score
contract_score = result.contract_score
# Framework detection
fw_text = ""
if result.frameworks_detected:
fw_list = sorted(result.frameworks_detected.items(), key=lambda x: -x[1])
fw_text = " | ".join(f"**{name}** ({conf:.0%})" for name, conf in fw_list[:5])
else:
fw_text = "No known frameworks detected"
# Stats
files_text = ""
if result.files_scanned > 0:
files_text = f"**Files Scanned:** {result.files_scanned} Python files ({result.total_lines:,} lines)"
# Score bar
filled = int(score / 100 * 30)
bar = "β" * filled + "β" * (30 - filled)
# Count gaps
total_criteria = sum(lr.total_count for lr in result.layer_results + result.contract_results)
total_covered = sum(lr.covered_count for lr in result.layer_results + result.contract_results)
gaps = total_criteria - total_covered
return f"""## AISA Compliance Score
# {score:.0f}/100 β {grade}
`{bar}`
| Metric | Value |
|--------|-------|
| **Analysis Mode** | {mode} |
| **Layer Score** | {layer_score:.0f}% |
| **Contract Score** | {contract_score:.0f}% |
| **Criteria Covered** | {total_covered}/{total_criteria} |
| **Gaps Found** | {gaps} |
| {files_text} | |
### Detected Frameworks
{fw_text}
"""
def _build_layer_details(result) -> str:
"""Build detailed layer-by-layer breakdown."""
lines = ["## Layer-by-Layer Breakdown\n"]
# Layer table
lines.append("### Architectural Layers\n")
lines.append("| Layer | Coverage | Status | Covered | Gaps |")
lines.append("|-------|:--------:|:------:|:-------:|:----:|")
for lr in result.layer_results:
score = lr.coverage_score
status = _score_label(score)
bar = _mini_bar(score)
lines.append(f"| {lr.id}: {lr.name} | {bar} {score:.0f}% | {status} | {lr.covered_count}/{lr.total_count} | {lr.total_count - lr.covered_count} |")
lines.append("")
# Contract table
lines.append("### Cross-Layer Contracts\n")
lines.append("| Contract | Coverage | Status | Covered | Gaps |")
lines.append("|----------|:--------:|:------:|:-------:|:----:|")
for cr in result.contract_results:
score = cr.coverage_score
status = _score_label(score)
bar = _mini_bar(score)
lines.append(f"| {cr.id}: {cr.name} | {bar} {score:.0f}% | {status} | {cr.covered_count}/{cr.total_count} | {cr.total_count - cr.covered_count} |")
lines.append("")
# Top gaps with recommendations
gaps = []
for lr in result.layer_results + result.contract_results:
priority = get_priority(lr.id)
for cr in lr.criteria_results:
if not cr.covered:
rec = get_recommendation(cr.criterion_id) or ""
gaps.append((priority, cr.criterion_id, cr.criterion_name, rec))
priority_order = {"Critical": 0, "High": 1, "Medium": 2}
gaps.sort(key=lambda g: (priority_order.get(g[0], 3), g[1]))
if gaps:
lines.append("### Top Gaps & Recommendations\n")
lines.append("| Priority | Criterion | Gap | Recommendation |")
lines.append("|:--------:|-----------|-----|----------------|")
for priority, cid, name, rec in gaps[:15]:
lines.append(f"| **{priority}** | {cid} | {name} | {rec} |")
if len(gaps) > 15:
lines.append(f"\n*...and {len(gaps) - 15} more gaps. Download the full report for details.*")
return "\n".join(lines)
def _get_grade(score: float) -> str:
if score >= 80:
return "Grade A β Production Ready"
elif score >= 60:
return "Grade B β Maturing"
elif score >= 40:
return "Grade C β Developing"
elif score >= 20:
return "Grade D β Early Stage"
else:
return "Grade F β Significant Gaps"
def _score_label(score: float) -> str:
if score >= 80:
return "β
Strong"
elif score >= 50:
return "π‘ Partial"
elif score >= 20:
return "π Minimal"
else:
return "π΄ Absent"
def _mini_bar(score: float) -> str:
filled = int(score / 100 * 10)
return "β" * filled + "β" * (10 - filled)
# ---------------------------------------------------------------------------
# Gradio UI
# ---------------------------------------------------------------------------
HEADER_MD = """
# π AISA Compliance Checker
**Evaluate your agentic AI project against the AISA reference architecture.**
Upload your project as a **ZIP file** and get an instant compliance report across
**7 architectural layers** and **4 cross-layer contracts**.
| Layer | What's Checked |
|-------|---------------|
| L1: LLM Foundation | Model adapters, prompts, context management, safety |
| L2: Tool & Environment | Tool schemas, sandboxing, permissions, MCP |
| L3: Cognitive Agent | Planning, memory, goals, reflection |
| L4: Infrastructure | Orchestration, state, multi-agent, tracing |
| L5: Evaluation | Tests, monitoring, regression, human eval |
| L6: Dev & Deployment | Versioning, CI/CD, A/B testing, rollout |
| L7: Governance | Policy-as-code, privacy, fairness, oversight |
**CLI version:** `pip install aisa-checker`
---
"""
FOOTER_MD = """
---
**AISA** (Agentic AI Systems Architecture) β A unified layered reference architecture
for designing, deploying, evaluating, and governing agentic AI systems.
*Nacar, O., Alquffari, D., & Alkhalifa, M. (2026). Tuwaiq Academy β TRDC.*
[Paper & Resources](https://huggingface.co/AISA-Framework) |
[PyPI Package](https://pypi.org/project/aisa-checker/) |
[Mapping Study](https://huggingface.co/AISA-Framework)
"""
def create_app():
"""Build the Gradio application."""
with gr.Blocks(
title="AISA Compliance Checker",
theme=gr.themes.Soft(primary_hue="blue", secondary_hue="purple"),
) as app:
gr.Markdown(HEADER_MD)
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### Upload & Configure")
zip_input = gr.File(
label="Upload Project (ZIP)",
file_types=[".zip"],
type="filepath",
)
analysis_mode = gr.Radio(
choices=[
"Pattern Scan (Fast)",
"AI Analysis",
"Full Analysis (Pattern + AI)",
],
value="Pattern Scan (Fast)",
label="Analysis Mode",
info="Pattern scan is free. AI modes require an API key.",
)
with gr.Accordion("AI Settings (optional)", open=False):
provider = gr.Dropdown(
choices=["openai", "anthropic", "google"],
value="openai",
label="LLM Provider",
)
api_key = gr.Textbox(
label="API Key",
placeholder="sk-... or sk-ant-... or AIza...",
type="password",
)
model_name = gr.Textbox(
label="Model (optional, uses default if empty)",
placeholder="e.g., gpt-4o, claude-sonnet-4-20250514, gemini-2.0-flash",
)
run_btn = gr.Button(
"Run AISA Check",
variant="primary",
size="lg",
)
gr.Markdown("""
**How to prepare your ZIP:**
1. ZIP your project's root directory
2. Include all Python files, configs, CI/CD files
3. Exclude `node_modules`, `.venv`, `.git` (they're auto-skipped)
""")
with gr.Column(scale=2):
gr.Markdown("### Results")
with gr.Tabs():
with gr.Tab("Summary"):
summary_output = gr.Markdown(
value="*Upload a project and click 'Run AISA Check' to see results.*"
)
with gr.Tab("Layer Details"):
details_output = gr.Markdown(
value="*Results will appear here after analysis.*"
)
with gr.Tab("Full Report"):
report_output = gr.Markdown(
value="*Full markdown report will appear here.*"
)
with gr.Tab("Download"):
download_output = gr.File(
label="Download Full Report (Markdown)",
)
# Wire up the button
run_btn.click(
fn=run_analysis,
inputs=[zip_input, analysis_mode, provider, api_key, model_name],
outputs=[summary_output, details_output, report_output, download_output],
show_progress="full",
)
gr.Markdown(FOOTER_MD)
return app
# ---------------------------------------------------------------------------
# Launch
# ---------------------------------------------------------------------------
if __name__ == "__main__":
app = create_app()
app.launch()
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