import json
import os

# Load extracted findings
with open("extracted_findings.json", "r", encoding="utf-8") as f:
    findings = json.load(f)

# Let's read all lane markdown files to aggregate the inventory
lanes_dir = "/home/donghyeon/Documents/LLM Wiki/docs/superpowers/specs/2026-05-27-branch-notes-audit/lanes"
lane_files = sorted(os.listdir(lanes_dir))

all_inventory = []
for lf in lane_files:
    if not lf.endswith(".md"):
        continue
    path = os.path.join(lanes_dir, lf)
    with open(path, "r", encoding="utf-8") as f:
        content = f.read()
    
    # Simple regex to extract rows from the inventory table
    import re
    rows = re.findall(r"\|\s*(raw/branch-notes/[a-zA-Z0-9\-\._]+)\s*\|\s*([A-Z_]+)\s*\|\s*([^|]+)\s*\|\s*([^|\n]+)\s*\|", content)
    for r in rows:
        p, s, e, f_text = r
        all_inventory.append({
            "path": p.strip(),
            "status": s.strip(),
            "evidence": e.strip(),
            "facts": f_text.strip(),
            "lane_file": lf
        })

print(f"Loaded {len(all_inventory)} inventory files.")

# Write consolidated evidence matrix markdown
print("\n=== EVIDENCE MATRIX TABLE ===")
matrix_lines = [
    "| Path | Status | Evidence | Extracted facts |",
    "| --- | --- | --- | --- |"
]
for item in all_inventory:
    matrix_lines.append(f"| {item['path']} | {item['status']} | {item['evidence']} | {item['facts']} |")

evidence_matrix_md = "\n".join(matrix_lines)
with open("evidence_matrix.md", "w", encoding="utf-8") as out_m:
    out_m.write(evidence_matrix_md)
print("Saved evidence_matrix.md")


# Map findings to each file in the inventory
file_findings_map = {}
for item in all_inventory:
    file_findings_map[item['path']] = []

for f in findings:
    sp = f['source_file'].replace("`", "").strip()
    # Normalize path if needed
    if not sp.startswith("raw/"):
        sp = "raw/branch-notes/" + sp
    if sp in file_findings_map:
        file_findings_map[sp].append(f)
    else:
        # Try fuzzy match
        matched = False
        for k in file_findings_map.keys():
            if os.path.basename(k) in sp or sp in k:
                file_findings_map[k].append(f)
                matched = True
                break
        if not matched:
            print(f"Warning: Finding source file '{f['source_file']}' not in inventory!")

# Create Per-File Findings Summary Table
print("\n=== PER-FILE FINDINGS SUMMARY TABLE ===")
summary_lines = [
    "| # | File | Findings | Critical | High | Medium | Low | 통과 |",
    "| --- | --- | --- | --- | --- | --- | --- | --- |"
]

idx = 1
for path, fs in sorted(file_findings_map.items()):
    crit = sum(1 for f in fs if f['severity'] == 'Critical')
    high = sum(1 for f in fs if f['severity'] == 'High')
    med = sum(1 for f in fs if f['severity'] == 'Medium')
    low = sum(1 for f in fs if f['severity'] == 'Low')
    tot = len(fs)
    
    pass_status = "N/A"
    if tot == 0:
        pass_status = "PASS"
        
    base = os.path.basename(path)
    summary_lines.append(f"| 4.{idx} | [{base}](file:///home/donghyeon/Documents/LLM%20Wiki/{path}) | {tot} | {crit} | {high} | {med} | {low} | {pass_status} |")
    idx += 1

per_file_summary_md = "\n".join(summary_lines)
with open("per_file_summary.md", "w", encoding="utf-8") as out_s:
    out_s.write(per_file_summary_md)
print("Saved per_file_summary.md")


# Generate Priority Recommendations (Critical & High)
print("\n=== PRIORITY RECOMMENDATIONS ===")
priority_lines = [
    "| 우선순위 | 권고 액션 | 근거 파일:라인 | 원래 목표 | 현재 간극 | 조치 후 효과 |",
    "| --- | --- | --- | --- | --- | --- |"
]

p_idx = 1
# Order: Critical first, then High
sorted_priority_findings = []
for path, fs in sorted(file_findings_map.items()):
    for f in fs:
        if f['severity'] in ['Critical', 'High']:
            sorted_priority_findings.append((path, f))

# Sort by severity (Critical first)
sorted_priority_findings.sort(key=lambda x: x[1]['severity'] == 'Critical', reverse=True)

for path, f in sorted_priority_findings[:20]: # Show top 20 or all
    base = os.path.basename(path)
    # We will put placeholders or short descriptions.
    # In the actual report, we will fill this in based on the findings.
    priority_lines.append(f"| {p_idx} ({f['severity']}) | {f['title']} | [{base}](file:///home/donghyeon/Documents/LLM%20Wiki/{path}) | 명세 정의 의도 | 명세 구현 간극 및 설계 결함 | 스켈레톤의 실무 적합성 극대화 및 보안 강화 |")
    p_idx += 1

priority_md = "\n".join(priority_lines)
with open("priority_recommendations.md", "w", encoding="utf-8") as out_p:
    out_p.write(priority_md)
print("Saved priority_recommendations.md")