From 6e040861579661e3895a48312b299184263e20bb Mon Sep 17 00:00:00 2001 From: Justin McLellan Date: Thu, 6 Aug 2026 23:35:58 -0500 Subject: [PATCH 1/8] fix: parse the NDJSON audit stream in the browser MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The audit endpoints stream NDJSON — progress events one JSON object per line, then a final result object — but the front end called res.json() on the whole body, which threw "Unexpected non-whitespace character after JSON" as soon as it hit line 2. Branch on content type: stream and dispatch NDJSON progress events, and keep res.json() as a fallback for a buffered single-object response. This also replaces the simulated progress bar with real per-prompt progress. Also drops Vercel-specific copy, including a user-facing error that told people to check a deploy dashboard they cannot see. Co-Authored-By: Claude Opus 5 (1M context) --- index.html | 116 +++++++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 112 insertions(+), 4 deletions(-) diff --git a/index.html b/index.html index 4da65bd..0112713 100644 --- a/index.html +++ b/index.html @@ -938,7 +938,9 @@

Accessibility Audit Tool

Audit started

`; - // Simulated progress to keep the user engaged while waiting for Vercel + // Simulated progress, used only when the backend returns a + // single buffered JSON object with no progress events. An + // NDJSON stream clears this and drives the bar for real. let progressInterval = setInterval(() => { const fillEl = document.getElementById("progressFill"); if (fillEl) { @@ -961,8 +963,28 @@

Accessibility Audit Tool

throw new Error(`Server Error: ${res.status} - ${errorText}`); } - // Vercel returns the full result at once - const data = await res.json(); + // The server (entry_points/api_server.py) answers audits with + // an NDJSON stream: progress events, one JSON object per + // line, then a final {"type":"result"} object. Parsing that + // with res.json() throws "Unexpected non-whitespace character + // after JSON", so the content type decides which reader to + // use — the plain-JSON branch is a fallback for any backend + // that buffers the whole result into a single object. + const contentType = res.headers.get("content-type") || ""; + let data; + + if (contentType.includes("ndjson")) { + // Real progress events supersede the simulated bar. + clearInterval(progressInterval); + data = await readNdjsonStream(res, updateProgress); + if (!data) { + throw new Error( + "The server closed the connection before returning a result." + ); + } + } else { + data = await res.json(); + } clearInterval(progressInterval); @@ -987,7 +1009,7 @@

Accessibility Audit Tool

`; resultsSection.style.display = "block"; } finally { @@ -996,6 +1018,92 @@

Accessibility Audit Tool

} }); + // Approximate completion percentage for each named pipeline stage. + // Per-prompt and per-page events are interpolated between these. + const STAGE_PCT = { + starting: 5, + fetching: 8, + fetch_complete: 12, + crawl_complete: 15, + programmatic_complete: 18, + extraction_complete: 20, + report_generating: 92, + report_complete: 97, + }; + + /** + * Read an NDJSON response body, dispatching each {"type":"progress"} + * event to onProgress and returning the final {"type":"result"} object, + * or null if the stream ended without one. + */ + async function readNdjsonStream(res, onProgress) { + const reader = res.body.getReader(); + const decoder = new TextDecoder(); + let buffer = ""; + let result = null; + + const handleLine = (line) => { + const trimmed = line.trim(); + if (!trimmed) return; + let evt; + try { + evt = JSON.parse(trimmed); + } catch { + // A single malformed line should not abort an otherwise good run. + return; + } + if (evt.type === "result") result = evt; + else if (evt.type === "progress" && onProgress) onProgress(evt); + }; + + for (;;) { + const { done, value } = await reader.read(); + if (done) break; + buffer += decoder.decode(value, { stream: true }); + const lines = buffer.split("\n"); + buffer = lines.pop(); // last element may be a partial line + lines.forEach(handleLine); + } + handleLine(buffer); // flush whatever remained unterminated + + return result; + } + + /** Update the progress bar and status text from a server progress event. */ + function updateProgress(evt) { + const msgEl = document.getElementById("progressMessage"); + const fillEl = document.getElementById("progressFill"); + const detailEl = document.getElementById("progressDetail"); + const statusEl = document.getElementById("progressStatus"); + + if (evt.message) { + if (msgEl) msgEl.textContent = evt.message; + if (statusEl) statusEl.textContent = evt.message; + } + + let pct = null; + if (evt.stage === "llm_progress" && evt.total) { + // Prompt calls dominate the runtime, so they own the 20–90% band. + pct = 20 + Math.round((evt.completed / evt.total) * 70); + if (detailEl) { + detailEl.textContent = + `Prompt ${evt.completed} of ${evt.total}` + + (evt.prompt_name ? ` — ${evt.prompt_name}` : ""); + } + } else if (evt.stage === "auditing_page" && evt.total_pages) { + pct = Math.round((evt.page / evt.total_pages) * 90); + if (detailEl) { + detailEl.textContent = `Page ${evt.page} of ${evt.total_pages}`; + } + } else if (STAGE_PCT[evt.stage] != null) { + pct = STAGE_PCT[evt.stage]; + } + + if (pct != null && fillEl) { + fillEl.style.width = Math.min(pct, 95) + "%"; + } + } + // 868: Added 'data' parameter to access the csv_report string function attachResultListeners(container, data) { // Wire up page tree node toggles From 879f515a1cd90e08163a166f5183cb393917d810 Mon Sep 17 00:00:00 2001 From: Justin McLellan Date: Thu, 6 Aug 2026 23:36:06 -0500 Subject: [PATCH 2/8] chore: remove the Vercel deployment path Deployment moves to a Docker image on Coolify, so the serverless handler, its routing config, and the deploy workflow are no longer used. This also collapses three near-identical copies of the audit logic into one. The copies had already drifted: api/index.py called generate_report() without api_key/model, silently skipping the LLM deduplication pass that api_server.py performs, so reports served from Vercel kept duplicate findings. Removed: api/index.py serverless FastAPI handler entry_points/vercel_handler.py a third copy of the same logic vercel.json routing rewrites .github/workflows/production.yml deployed to Vercel on push to main Co-Authored-By: Claude Opus 5 (1M context) --- .github/workflows/production.yml | 36 -- api/index.py | 392 ---------------------- entry_points/vercel_handler.py | 547 ------------------------------- vercel.json | 16 - 4 files changed, 991 deletions(-) delete mode 100644 .github/workflows/production.yml delete mode 100644 api/index.py delete mode 100644 entry_points/vercel_handler.py delete mode 100644 vercel.json diff --git a/.github/workflows/production.yml b/.github/workflows/production.yml deleted file mode 100644 index 84684dd..0000000 --- a/.github/workflows/production.yml +++ /dev/null @@ -1,36 +0,0 @@ -name: Vercel Production Deployment -env: - VERCEL_ORG_ID: ${{ secrets.VERCEL_ORG_ID }} - VERCEL_PROJECT_ID: ${{ secrets.VERCEL_PROJECT_ID }} -on: - push: - branches: - - main -jobs: - Deploy-Production: - runs-on: ubuntu-latest - steps: - - name: Checkout Code - uses: actions/checkout@v4 - - - name: Install uv (Manual) - run: | - curl -LsSf https://astral.sh/uv/install.sh | sh - echo "$HOME/.local/bin" >> $GITHUB_PATH - - - name: Generate requirements.txt - run: | - # This pulls the dependencies out of pyproject.toml without needing poetry installed - grep -E '^[^#].*=' pyproject.toml | sed -E 's/ *=.*//' > requirements.txt - - - name: Install Vercel CLI - run: npm install --global vercel@latest - - - name: Pull Vercel Environment Information - run: vercel pull --yes --environment=production --token=${{ secrets.VERCEL_TOKEN }} - - - name: Build Project Artifacts - run: vercel build --prod --token=${{ secrets.VERCEL_TOKEN }} - - - name: Deploy Project Artifacts to Vercel - run: vercel deploy --prebuilt --prod --token=${{ secrets.VERCEL_TOKEN }} \ No newline at end of file diff --git a/api/index.py b/api/index.py deleted file mode 100644 index 1a51e62..0000000 --- a/api/index.py +++ /dev/null @@ -1,392 +0,0 @@ -import json -import os -import re -import shutil -import sys -import tempfile -from pathlib import Path -from fastapi import FastAPI, Request, HTTPException -from fastapi.responses import StreamingResponse -from fastapi.middleware.cors import CORSMiddleware - -# ── Project root and sys.path ───────────────────────────────────────────────── -PROJECT_ROOT = Path(__file__).resolve().parent.parent -sys.path.insert(0, str(PROJECT_ROOT)) - -# Load Environment / Imports -from entry_points.run_pipeline import run_pipeline -from entry_points.generate_report import generate_report -from vision_aid.ingestion.file_crawler import fetch_page, fetch_pages_nested -from processing_scripts.llm_client.client import is_openai_model, is_gemini_model - -_PAGE_MARKER = re.compile(r"") - -app = FastAPI() - -# Automatic CORS handling -app.add_middleware( - CORSMiddleware, - allow_origins=["*"], - allow_methods=["*"], - allow_headers=["*"], -) - -# --- REUSE YOUR EXISTING LOGIC FUNCTIONS --- -# Copy-paste split_pages, _resolve_api_key, run_audit, and _try_parse_json -# EXACTLY as they are in your current script. - -def _resolve_api_key(data: dict, model: str) -> str: - """Return the appropriate API key for *model* from the request body or env. - - OpenAI models use the ``openai_api_key`` field / ``OPENAI_API_KEY`` env. - Gemini models use the ``gemini_api_key`` field / ``GEMINI_API_KEY`` env. - Anthropic models use the ``api_key`` field / ``ANTHROPIC_API_KEY`` env. - Per-request keys take priority over environment variables. - """ - if is_openai_model(model): - return ( - data.get("openai_api_key", "").strip() - or os.getenv("OPENAI_API_KEY", "") - ) - if is_gemini_model(model): - return ( - data.get("gemini_api_key", "").strip() - or os.getenv("GEMINI_API_KEY", "") - ) - return ( - data.get("api_key", "").strip() - or os.getenv("ANTHROPIC_API_KEY", "") - ) - -def run_audit(html_content: str, api_key: str, model: str, progress_callback=None) -> dict: - """Write *html_content* to a temp file, run the pipeline, return results. - - If *api_key* is empty, the pipeline runs in dry-run mode (programmatic - checks only, no LLM calls). - """ - dry_run = not api_key - # Vercel allows writing to /tmp for ephemeral storage - tmp_dir = tempfile.mkdtemp(prefix="visionaid_audit_", dir="/tmp") - try: - html_path = Path(tmp_dir) / "input.html" - html_path.write_text(html_content, encoding="utf-8") - - - # 2. DEFINE AND CREATE THE OUTPUT DIRECTORY - output_dir = Path(tmp_dir) / "output" - output_dir.mkdir(parents=True, exist_ok=True) - - manifest = run_pipeline( - html_path=str(html_path), - output_dir=output_dir, - api_key=api_key if api_key else None, - model=model, - dry_run=dry_run, - include_summaries=False, - progress_callback=progress_callback, - ) - - # Read programmatic findings - prog_path = output_dir / "programmatic_findings.json" - programmatic_findings = ( - json.loads(prog_path.read_text(encoding="utf-8")) - if prog_path.exists() - else [] - ) - - # Read per-prompt LLM results - llm_results = {} - prompts_dir = output_dir / "prompts" - if prompts_dir.exists(): - for prompt_file in sorted(prompts_dir.glob("*.json")): - data = json.loads(prompt_file.read_text(encoding="utf-8")) - name = data.get("prompt_name", prompt_file.stem) - # ``api_result`` is only absent when the pipeline actually ran - # in dry-run mode (no key). If it's present but unsuccessful, - # a real API call was attempted and failed — that's an error, - # not a dry run, and must not be silently treated as one. - api_result = data.get("api_result") - parsed = None - if api_result is None: - status = "dry_run" - elif api_result.get("success"): - status = "success" - parsed = _try_parse_json(api_result.get("response", "")) - else: - status = "error" - usage = (api_result or {}).get("usage", {}) - llm_results[name] = { - "checklist": data.get("checklist"), - "wcag_criteria": data.get("wcag_criteria", []), - "status": status, - "error": (api_result or {}).get("error"), - "parsed": parsed, - "input_tokens": usage.get("input_tokens"), - "output_tokens": usage.get("output_tokens"), - "duration_seconds": (api_result or {}).get("duration_seconds"), - } - - # Generate CSV report (only meaningful when LLM ran) - csv_content = None - if not dry_run: - try: - if progress_callback: - progress_callback({ - "type": "progress", - "stage": "report_generating", - "message": "Generating report…", - }) - report_dir = Path(tmp_dir) / "reports" - report_path = generate_report(output_dir, report_dir) - csv_content = report_path.read_text(encoding="utf-8") - if progress_callback: - progress_callback({ - "type": "progress", - "stage": "report_complete", - "message": "Report ready", - }) - except Exception as csv_err: - print(f" Warning: CSV generation failed: {csv_err}") - - return { - "success": True, - "programmatic_findings": programmatic_findings, - "llm_results": llm_results, - "csv_report": csv_content, - "skipped_prompts": manifest.get("prompts_skipped", []), - "summary": { - "programmatic_count": manifest.get("programmatic_findings_count", 0), - "programmatic_by_checker": manifest.get( - "programmatic_findings_by_checker", {} - ), - "llm_prompts_run": len(llm_results), - "llm_prompts_skipped": len(manifest.get("prompts_skipped", [])), - "total_input_tokens": manifest.get("total_input_tokens", 0), - "total_output_tokens": manifest.get("total_output_tokens", 0), - "estimated_cost_usd": manifest.get("estimated_cost_usd"), - "model": model, - "dry_run": dry_run, - }, - } - - except Exception as exc: - return {"success": False, "error": str(exc)} - - finally: - shutil.rmtree(tmp_dir, ignore_errors=True) - - - -def _try_parse_json(text: str): - """Parse JSON from an LLM response, stripping markdown code fences.""" - m = re.search(r"```(?:json)?\s*\n?(.*?)```", text, re.DOTALL) - cleaned = m.group(1).strip() if m else text.strip() - try: - return json.loads(cleaned) - except (json.JSONDecodeError, ValueError): - return {"raw": text} - -def split_pages(html: str) -> list[tuple[str, str]]: - """Split concatenated HTML from ``fetch_pages_nested`` into per-page chunks. - - Returns a list of ``(url, html)`` tuples. If no PAGE markers are found - the entire string is returned as a single page with url ``"unknown"``. - """ - markers = list(_PAGE_MARKER.finditer(html)) - if not markers: - return [("unknown", html)] - - pages: list[tuple[str, str]] = [] - for i, m in enumerate(markers): - url = m.group(1) - start = m.end() - end = markers[i + 1].start() if i + 1 < len(markers) else len(html) - pages.append((url, html[start:end].strip())) - return pages - - - -# --- NEW FASTAPI ENDPOINTS --- - -@app.post("/api/audit") -async def audit_html(request: Request): - """ - Standard JSON response for Vercel compatibility. - Fixes the 'Unexpected character after JSON' error. - """ - try: - data = await request.json() - html_content = data.get("html_content", "").strip() - model = data.get("model", "claude-haiku-4-5-20251001") - api_key = _resolve_api_key(data, model) - - if not html_content: - return {"success": False, "error": "html_content is required"} - - # run_audit handles the pipeline and returns a dictionary. - # We no longer need the lambda progress_callback because - # standard JSON responses are not streams. - result = run_audit(html_content, api_key, model) - - # Ensure the result is marked as success/failure for the frontend - if "success" not in result: - result["success"] = True - - return result - - except Exception as e: - import traceback - return { - "success": False, - "error": f"Audit failed: {str(e)}", - "traceback": traceback.format_exc() - } - -@app.post("/api/audit/url") -async def handle_url_audit(request: Request): - try: - data = await request.json() - url = data.get("url", "").strip() - if not url.startswith('http'): url = f"https://{url}" - - # Log for debugging - print(f"Starting audit for: {url}") - - html_content = fetch_page(url) - model = data.get("model", "claude-haiku-4-5-20251001") - api_key = _resolve_api_key(data, model) - - # Pass a specific tmp directory to run_audit - result = run_audit(html_content, api_key, model) - - return result - - except Exception as e: - import traceback - # This will print the EXACT error (like "Read-only file system") to Vercel Logs - error_details = traceback.format_exc() - print(error_details) - return { - "success": False, - "error": str(e), - "traceback": error_details if not os.getenv("PROD") else None - } - -@app.post("/api/audit/url/nested") -async def handle_nested_audit(request: Request): - """ - Fetches multiple pages from a site (crawling), audits each page, - and returns a merged result. - """ - try: - data = await request.json() - url = data.get("url", "").strip() - model = data.get("model", "claude-haiku-4-5-20251001") - api_key = _resolve_api_key(data, model) - - if not url: - return {"success": False, "error": "URL is required"} - - # Ensure protocol for the crawler - if not url.startswith(("http://", "https://")): - url = f"https://{url}" - - # 1. Fetch all pages using the crawler - # This returns a large HTML string with markers and a crawl tree dict - full_html, crawl_tree = fetch_pages_nested(url) - - # 2. Split the massive HTML into individual (url, html) tuples - pages = split_pages(full_html) - - # 3. Initialize the merged response object - merged_results = { - "success": True, - "crawl_tree": crawl_tree, - "page_results": {}, - "programmatic_findings": [], - "llm_results": {}, - "pages_audited": [], - "summary": { - "programmatic_count": 0, - "llm_prompts_run": 0, - "model": model, - "pages": len(pages), - "dry_run": not api_key - } - } - - # 4. Loop through each discovered page and run the audit - for page_url, page_html in pages: - # Re-use your existing run_audit helper - res = run_audit(page_html, api_key, model) - - if not res.get("success"): - continue - - merged_results["pages_audited"].append(page_url) - - # Map results to the specific URL for the frontend tree view - merged_results["page_results"][page_url] = { - "programmatic_findings": res.get("programmatic_findings", []), - "llm_results": res.get("llm_results", {}), - "summary": res.get("summary", {}) - } - - # Flatten programmatic findings into the top-level list - for finding in res.get("programmatic_findings", []): - finding["page_url"] = page_url - merged_results["programmatic_findings"].append(finding) - - # Update global counters - merged_results["summary"]["programmatic_count"] += res["summary"].get("programmatic_count", 0) - merged_results["summary"]["llm_prompts_run"] += res["summary"].get("llm_prompts_run", 0) - - return merged_results - - except Exception as e: - import traceback - return { - "success": False, - "error": f"Nested audit failed: {str(e)}", - "traceback": traceback.format_exc() - } - -@app.post("/api/validate-key") -async def handle_validate_key(request: Request): - """ - Validates the format of the provided API key. - Replaces the old self._handle_validate_key() logic. - """ - try: - data = await request.json() - key = data.get("api_key", "").strip() - provider = data.get("provider", "anthropic") - - if not key: - return {"valid": False, "error": "No key provided"} - - # Basic format validation to prevent unnecessary API calls - if provider == "anthropic": - # Anthropic keys usually start with sk-ant- - is_valid = key.startswith("sk-ant") and len(key) > 20 - elif provider == "openai": - # OpenAI keys usually start with sk- - is_valid = key.startswith("sk-") and len(key) > 20 - elif provider == "gemini": - # Gemini key formats vary (e.g. "AIza...", "AQ...") — length is - # the only reliable signal without calling the API. - is_valid = len(key) > 20 - else: - is_valid = len(key) > 10 - - if is_valid: - return {"valid": True} - else: - return {"valid": False, "error": f"Invalid {provider} key format"} - - except Exception as e: - return {"valid": False, "error": f"Server error during validation: {str(e)}"} - -# --- STATIC FILE SERVING --- -# Vercel serves index.html and styles.css automatically if they are in the root. -# You don't need code for this anymore! \ No newline at end of file diff --git a/entry_points/vercel_handler.py b/entry_points/vercel_handler.py deleted file mode 100644 index bf1b3d6..0000000 --- a/entry_points/vercel_handler.py +++ /dev/null @@ -1,547 +0,0 @@ -#!/usr/bin/env python3 -"""Serve the team website and run the accessibility audit API locally. - -This server has two responsibilities: - 1. Serve static files (index.html, styles.css) from the project root. - 2. Handle POST /api/audit — receive raw HTML, run the pipeline, return JSON. - -Usage: - python entry_points/api_server.py - python entry_points/api_server.py --port 8080 - -Then open http://localhost:8000 in your browser. - -API keys can be supplied per-request in the POST body, or set in the .env -file / environment. Per-request keys take priority. - - Anthropic models → field ``api_key`` / env ``ANTHROPIC_API_KEY`` - OpenAI models → field ``openai_api_key`` / env ``OPENAI_API_KEY`` -""" - -import json -import os -import re -import shutil -import sys -import tempfile -from http.server import BaseHTTPRequestHandler -from pathlib import Path - -# ── Project root and sys.path ───────────────────────────────────────────────── -PROJECT_ROOT = Path(__file__).resolve().parent.parent -sys.path.insert(0, str(PROJECT_ROOT)) - -# Vercel injects environment variables from the dashboard, -# but load_dotenv is kept safe if used in a local wrapper. -try: - from dotenv import load_dotenv -except ImportError: - pass - - -# Load .env if it exists (mostly for local testing, Vercel uses dashboard envs) -if PROJECT_ROOT.joinpath(".env").exists(): - try: - load_dotenv(PROJECT_ROOT / ".env") - except NameError: - pass - -from entry_points.run_pipeline import run_pipeline # noqa: E402 -from entry_points.generate_report import generate_report # noqa: E402 -from vision_aid.ingestion.file_crawler import fetch_page, fetch_pages_nested # noqa: E402 -from processing_scripts.llm_client.client import is_openai_model, is_gemini_model # noqa: E402 - - -# ── Multi-page splitting ───────────────────────────────────────────────────── - -_PAGE_MARKER = re.compile(r"") - - -def split_pages(html: str) -> list[tuple[str, str]]: - """Split concatenated HTML from ``fetch_pages_nested`` into per-page chunks. - - Returns a list of ``(url, html)`` tuples. If no PAGE markers are found - the entire string is returned as a single page with url ``"unknown"``. - """ - markers = list(_PAGE_MARKER.finditer(html)) - if not markers: - return [("unknown", html)] - - pages: list[tuple[str, str]] = [] - for i, m in enumerate(markers): - url = m.group(1) - start = m.end() - end = markers[i + 1].start() if i + 1 < len(markers) else len(html) - pages.append((url, html[start:end].strip())) - return pages - -STATIC_DIR = PROJECT_ROOT # index.html and styles.css live at the repo root - - -# ── Key resolution ──────────────────────────────────────────────────────────── - -def _resolve_api_key(data: dict, model: str) -> str: - """Return the appropriate API key for *model* from the request body or env. - - OpenAI models use the ``openai_api_key`` field / ``OPENAI_API_KEY`` env. - Gemini models use the ``gemini_api_key`` field / ``GEMINI_API_KEY`` env. - Anthropic models use the ``api_key`` field / ``ANTHROPIC_API_KEY`` env. - Per-request keys take priority over environment variables. - """ - if is_openai_model(model): - return ( - data.get("openai_api_key", "").strip() - or os.getenv("OPENAI_API_KEY", "") - ) - if is_gemini_model(model): - return ( - data.get("gemini_api_key", "").strip() - or os.getenv("GEMINI_API_KEY", "") - ) - return ( - data.get("api_key", "").strip() - or os.getenv("ANTHROPIC_API_KEY", "") - ) - - -# ── Audit logic ─────────────────────────────────────────────────────────────── - -def run_audit(html_content: str, api_key: str, model: str, progress_callback=None) -> dict: - """Write *html_content* to a temp file, run the pipeline, return results. - - If *api_key* is empty, the pipeline runs in dry-run mode (programmatic - checks only, no LLM calls). - """ - dry_run = not api_key - # Vercel allows writing to /tmp for ephemeral storage - tmp_dir = tempfile.mkdtemp(prefix="visionaid_", dir="/tmp") - try: - html_path = Path(tmp_dir) / "input.html" - html_path.write_text(html_content, encoding="utf-8") -# tmp_dir = tempfile.mkdtemp(prefix="visionaid_audit_", dir="/tmp") - - # 2. DEFINE AND CREATE THE OUTPUT DIRECTORY - output_dir = Path(tmp_dir) / "output" - output_dir.mkdir(parents=True, exist_ok=True) - - manifest = run_pipeline( - html_path=str(html_path), - output_dir=output_dir, - api_key=api_key if api_key else None, - model=model, - dry_run=dry_run, - include_summaries=False, - progress_callback=progress_callback, - ) - - # Read programmatic findings - prog_path = output_dir / "programmatic_findings.json" - programmatic_findings = ( - json.loads(prog_path.read_text(encoding="utf-8")) - if prog_path.exists() - else [] - ) - - # Read per-prompt LLM results - llm_results = {} - prompts_dir = output_dir / "prompts" - if prompts_dir.exists(): - for prompt_file in sorted(prompts_dir.glob("*.json")): - data = json.loads(prompt_file.read_text(encoding="utf-8")) - name = data.get("prompt_name", prompt_file.stem) - # ``api_result`` is only absent when the pipeline actually ran - # in dry-run mode (no key). If it's present but unsuccessful, - # a real API call was attempted and failed — that's an error, - # not a dry run, and must not be silently treated as one. - api_result = data.get("api_result") - parsed = None - if api_result is None: - status = "dry_run" - elif api_result.get("success"): - status = "success" - parsed = _try_parse_json(api_result.get("response", "")) - else: - status = "error" - usage = (api_result or {}).get("usage", {}) - llm_results[name] = { - "checklist": data.get("checklist"), - "wcag_criteria": data.get("wcag_criteria", []), - "status": status, - "error": (api_result or {}).get("error"), - "parsed": parsed, - "input_tokens": usage.get("input_tokens"), - "output_tokens": usage.get("output_tokens"), - "duration_seconds": (api_result or {}).get("duration_seconds"), - } - - # Generate CSV report (only meaningful when LLM ran) - csv_content = None - if not dry_run: - try: - if progress_callback: - progress_callback({ - "type": "progress", - "stage": "report_generating", - "message": "Generating report…", - }) - report_dir = Path(tmp_dir) / "reports" - report_path = generate_report(output_dir, report_dir) - csv_content = report_path.read_text(encoding="utf-8") - if progress_callback: - progress_callback({ - "type": "progress", - "stage": "report_complete", - "message": "Report ready", - }) - except Exception as csv_err: - print(f" Warning: CSV generation failed: {csv_err}") - - return { - "success": True, - "programmatic_findings": programmatic_findings, - "llm_results": llm_results, - "csv_report": csv_content, - "skipped_prompts": manifest.get("prompts_skipped", []), - "summary": { - "programmatic_count": manifest.get("programmatic_findings_count", 0), - "programmatic_by_checker": manifest.get( - "programmatic_findings_by_checker", {} - ), - "llm_prompts_run": len(llm_results), - "llm_prompts_skipped": len(manifest.get("prompts_skipped", [])), - "total_input_tokens": manifest.get("total_input_tokens", 0), - "total_output_tokens": manifest.get("total_output_tokens", 0), - "estimated_cost_usd": manifest.get("estimated_cost_usd"), - "model": model, - "dry_run": dry_run, - }, - } - - except Exception as exc: - return {"success": False, "error": str(exc)} - - finally: - shutil.rmtree(tmp_dir, ignore_errors=True) - - -def _try_parse_json(text: str): - """Parse JSON from an LLM response, stripping markdown code fences.""" - m = re.search(r"```(?:json)?\s*\n?(.*?)```", text, re.DOTALL) - cleaned = m.group(1).strip() if m else text.strip() - try: - return json.loads(cleaned) - except (json.JSONDecodeError, ValueError): - return {"raw": text} - - -# ── Vercel HTTP handler ─────────────────────────────────────────────────────── - -class handler(BaseHTTPRequestHandler): - """Vercel Serverless Function entry point. Must be named 'handler'.""" - - def log_message(self, fmt, *args): # noqa: N802 - sys.stderr.write(f"[{self.address_string()}] {fmt % args}\n") - - # CORS helpers ───────────────────────────────────────────────────────────── - - def _cors_headers(self): - self.send_header("Access-Control-Allow-Origin", "*") - self.send_header("Access-Control-Allow-Methods", "GET, POST, OPTIONS") - self.send_header("Access-Control-Allow-Headers", "Content-Type") - - def do_OPTIONS(self): - self.send_response(200) - self._cors_headers() - self.end_headers() - - def do_GET(self): - path = self.path.split("?")[0] - - if path in ("/", "/index.html"): - self._serve_file(PROJECT_ROOT / "index.html", "text/html; charset=utf-8") - elif path == "/styles.css": - self._serve_file(PROJECT_ROOT / "styles.css", "text/css; charset=utf-8") - elif path == "/favicon.ico": - self._serve_file(PROJECT_ROOT / "favicon.ico", "image/x-icon") - else: - self.send_error(404, f"Path {path} not found") - - def _serve_file(self, file_path: Path, content_type: str): - if not file_path.exists(): - print(f"DEBUG: File not found at {file_path}") # Check Vercel logs for this - self.send_error(404, f"File {file_path.name} not found on server") - return - - body = file_path.read_bytes() - self.send_response(200) - self.send_header("Content-Type", content_type) - self.send_header("Content-Length", str(len(body))) - self._cors_headers() - self.end_headers() - self.wfile.write(body) - - # POST ───────────────────────────────────────────────────────────────────── - - def do_POST(self): - # Strip trailing slashes and query parameters for the match - clean_path = self.path.split('?')[0].rstrip('/') - - if clean_path == "/api/audit": - self._handle_audit() - elif clean_path == "/api/audit/url": - self._handle_url_audit(nested=False) - elif clean_path == "/api/audit/url/nested": - self._handle_url_audit(nested=True) - else: - self._send_json({"error": f"Endpoint {clean_path} Not Found"}, 404) - - def _start_ndjson_stream(self): - """Send NDJSON response headers and return a send_event callable.""" - self.send_response(200) - self.send_header("Content-Type", "application/x-ndjson; charset=utf-8") - self._cors_headers() - self.end_headers() - - def send_event(obj: dict) -> None: - line = json.dumps(obj, ensure_ascii=False) + "\n" - self.wfile.write(line.encode("utf-8")) - self.wfile.flush() - - return send_event - - def _handle_audit(self): - length = int(self.headers.get("Content-Length", 0)) - body = self.rfile.read(length) - - try: - data = json.loads(body) - except json.JSONDecodeError: - self._send_json({"success": False, "error": "Invalid JSON body"}, 400) - return - - html_content = data.get("html_content", "").strip() - if not html_content: - self._send_json( - {"success": False, "error": "html_content is required"}, 400 - ) - return - - model = data.get("model", "claude-haiku-4-5-20251001") - api_key = _resolve_api_key(data, model) - - print( - f" Audit request: {len(html_content):,} chars, " - f"model={model}, api_key={'set' if api_key else 'not set'}" - ) - - send_event = self._start_ndjson_stream() - send_event({ - "type": "progress", - "stage": "starting", - "message": "Starting audit…", - }) - result = run_audit(html_content, api_key, model, progress_callback=send_event) - result["type"] = "result" - send_event(result) - - def _handle_url_audit(self, nested: bool): - """Fetch HTML from a URL (and optionally its nested links) then audit.""" - length = int(self.headers.get("Content-Length", 0)) - body = self.rfile.read(length) - - try: - data = json.loads(body) - except json.JSONDecodeError: - self._send_json({"success": False, "error": "Invalid JSON body"}, 400) - return - - url = data.get("url", "").strip() - if not url: - self._send_json({"success": False, "error": "url is required"}, 400) - return - - model = data.get("model", "claude-haiku-4-5-20251001") - api_key = _resolve_api_key(data, model) - - print( - f" URL audit request ({'nested' if nested else 'single'}): {url}, " - f"model={model}, api_key={'set' if api_key else 'not set'}" - ) - - if not nested: - send_event = self._start_ndjson_stream() - send_event({ - "type": "progress", - "stage": "fetching", - "message": f"Fetching {url}…", - }) - try: - html_content = fetch_page(url) - except Exception as exc: - result = {"type": "result", "success": False, "error": f"Failed to fetch URL: {exc}"} - send_event(result) - return - print(f" [url_audit] Fetched {len(html_content):,} chars from {url}") - lower = html_content[:2000].lower() - if any(marker in lower for marker in ("just a moment", "cf-browser-verification", "ray id", "enable javascript and cookies")): - print(" [url_audit] WARNING: response looks like a bot-challenge page, not real content") - title_match = re.search(r"]*>(.*?)", html_content[:4000], re.IGNORECASE | re.DOTALL) - print(f" [url_audit] : {title_match.group(1).strip() if title_match else '(not found)'}") - send_event({ - "type": "progress", - "stage": "fetch_complete", - "message": "Page fetched — starting analysis…", - }) - result = run_audit(html_content, api_key, model, progress_callback=send_event) - result["type"] = "result" - send_event(result) - return - - # ── Multi-page: stream progress, run pipeline per page, merge ───── - try: - html_content, crawl_tree = fetch_pages_nested(url) - except Exception as exc: - self._send_json({"success": False, "error": f"Failed to fetch URL: {exc}"}, 502) - return - - pages = split_pages(html_content) - total_pages = len(pages) - print(f" Split into {total_pages} page(s)") - - _send_event = self._start_ndjson_stream() - - _send_event({ - "type": "progress", - "stage": "crawl_complete", - "total_pages": total_pages, - "message": f"Found {total_pages} page(s) to audit", - }) - - merged = { - "success": True, - "crawl_tree": crawl_tree, - "page_results": {}, - "programmatic_findings": [], - "llm_results": {}, - "csv_report": None, - "skipped_prompts": [], - "pages_audited": [], - "summary": { - "programmatic_count": 0, - "programmatic_by_checker": {}, - "llm_prompts_run": 0, - "llm_prompts_skipped": 0, - "total_input_tokens": 0, - "total_output_tokens": 0, - "estimated_cost_usd": None, - "model": model, - "dry_run": not api_key, - "pages": total_pages, - }, - } - - total_cost = 0.0 - csv_parts: list[str] = [] - for page_idx, (page_url, page_html) in enumerate(pages, start=1): - _send_event({ - "type": "progress", - "stage": "auditing_page", - "page": page_idx, - "total_pages": total_pages, - "page_url": page_url, - "message": f"Auditing page {page_idx}/{total_pages}: {page_url}", - }) - - print(f" Auditing: {page_url}") - page_result = run_audit(page_html, api_key, model, progress_callback=_send_event) - - if not page_result.get("success"): - print(f" FAILED: {page_result.get('error')}") - _send_event({ - "type": "progress", - "stage": "page_error", - "page": page_idx, - "page_url": page_url, - "message": f"Failed: {page_result.get('error', 'unknown')}", - }) - continue - - merged["pages_audited"].append(page_url) - - # Store per-page results for the tree view - merged["page_results"][page_url] = { - "programmatic_findings": page_result.get("programmatic_findings", []), - "llm_results": page_result.get("llm_results", {}), - "summary": page_result.get("summary", {}), - } - - page_csv = page_result.get("csv_report") - if page_csv: - if not csv_parts: - csv_parts.append(page_csv.rstrip("\n")) - else: - lines = page_csv.split("\n", 1) - if len(lines) > 1 and lines[1].strip(): - csv_parts.append(lines[1].rstrip("\n")) - - for finding in page_result.get("programmatic_findings", []): - finding["page_url"] = page_url - merged["programmatic_findings"].extend( - page_result.get("programmatic_findings", []) - ) - - for name, result_data in page_result.get("llm_results", {}).items(): - result_data["page_url"] = page_url - key = f"{name}|{page_url}" - merged["llm_results"][key] = result_data - - merged["skipped_prompts"].extend( - page_result.get("skipped_prompts", []) - ) - - page_summary = page_result.get("summary", {}) - merged["summary"]["programmatic_count"] += page_summary.get( - "programmatic_count", 0 - ) - merged["summary"]["llm_prompts_run"] += page_summary.get( - "llm_prompts_run", 0 - ) - merged["summary"]["llm_prompts_skipped"] += page_summary.get( - "llm_prompts_skipped", 0 - ) - merged["summary"]["total_input_tokens"] += page_summary.get( - "total_input_tokens", 0 - ) - merged["summary"]["total_output_tokens"] += page_summary.get( - "total_output_tokens", 0 - ) - if page_summary.get("estimated_cost_usd") is not None: - total_cost += page_summary["estimated_cost_usd"] - - _send_event({ - "type": "progress", - "stage": "page_complete", - "page": page_idx, - "total_pages": total_pages, - "page_url": page_url, - "message": f"Completed page {page_idx}/{total_pages}", - }) - - if total_cost > 0: - merged["summary"]["estimated_cost_usd"] = round(total_cost, 6) - - if csv_parts: - merged["csv_report"] = "\n".join(csv_parts) + "\n" - - # Final event: the full merged result - merged["type"] = "result" - _send_event(merged) - - def _send_json(self, obj: dict, status: int = 200): - body = json.dumps(obj, indent=2, ensure_ascii=False).encode("utf-8") - self.send_response(status) - self.send_header("Content-Type", "application/json; charset=utf-8") - self.send_header("Content-Length", str(len(body))) - self._cors_headers() - self.end_headers() - self.wfile.write(body) \ No newline at end of file diff --git a/vercel.json b/vercel.json deleted file mode 100644 index 850e39f..0000000 --- a/vercel.json +++ /dev/null @@ -1,16 +0,0 @@ -{ - "version": 2, - "rewrites": [ - { - "source": "/styles.css", - "destination": "/styles.css" - }, - { - "source": "/favicon.ico", - "destination": "/favicon.ico" - }, - { "source": "/api/validate-key", "destination": "/api/index.py" }, - { "source": "/api/(.*)", "destination": "/api/index.py" }, - { "source": "/((?!api/).*)", "destination": "/index.html" } - ] -} \ No newline at end of file From 293d851edeb05c3528e03e99ee9d4d09e744a64b Mon Sep 17 00:00:00 2001 From: Justin McLellan <jmclellan@beast.> Date: Thu, 6 Aug 2026 23:36:15 -0500 Subject: [PATCH 3/8] chore: remove superseded duplicate modules and dead deploy config None of these are reachable from any entry point, and each is a stale parallel copy of code that is still live elsewhere: vision_aid/llm_client/ last touched 2026-03-10; the live copy in processing_scripts/ gained Gemini support on 2026-07-27. prompt_loader.py and runner.py were byte-identical. vision_aid/programmatic/ a class-based rewrite of the same checks, abandoned 2026-03-07; run_pipeline.py imports processing_scripts/programmatic/. vision_aid/agentic_processing/ an empty placeholder package. render.yaml a Render config whose 'poetry install' build command never matched this project. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> --- render.yaml | 12 - vision_aid/agentic_processing/__init__.py | 0 vision_aid/llm_client/__init__.py | 0 vision_aid/llm_client/client.py | 173 --------- vision_aid/llm_client/prompt_loader.py | 72 ---- vision_aid/llm_client/runner.py | 159 --------- vision_aid/programmatic/__init__.py | 0 vision_aid/programmatic/base.py | 104 ------ vision_aid/programmatic/forms.py | 131 ------- vision_aid/programmatic/nontext.py | 117 ------- vision_aid/programmatic/semantic.py | 408 ---------------------- 11 files changed, 1176 deletions(-) delete mode 100644 render.yaml delete mode 100644 vision_aid/agentic_processing/__init__.py delete mode 100644 vision_aid/llm_client/__init__.py delete mode 100644 vision_aid/llm_client/client.py delete mode 100644 vision_aid/llm_client/prompt_loader.py delete mode 100644 vision_aid/llm_client/runner.py delete mode 100644 vision_aid/programmatic/__init__.py delete mode 100644 vision_aid/programmatic/base.py delete mode 100644 vision_aid/programmatic/forms.py delete mode 100644 vision_aid/programmatic/nontext.py delete mode 100644 vision_aid/programmatic/semantic.py diff --git a/render.yaml b/render.yaml deleted file mode 100644 index 1b5b6bc..0000000 --- a/render.yaml +++ /dev/null @@ -1,12 +0,0 @@ -services: - - type: web - name: visionaid-a11y-audit - runtime: python - buildCommand: poetry install --no-root - startCommand: python entry_points/api_server.py --host 0.0.0.0 - envVars: - - key: PORT - generateValue: false # Render injects this automatically - - key: ANTHROPIC_API_KEY - sync: false # Set this in the Render dashboard (optional — - # users can also supply their own key in the form) diff --git a/vision_aid/agentic_processing/__init__.py b/vision_aid/agentic_processing/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/vision_aid/llm_client/__init__.py b/vision_aid/llm_client/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/vision_aid/llm_client/client.py b/vision_aid/llm_client/client.py deleted file mode 100644 index 546261e..0000000 --- a/vision_aid/llm_client/client.py +++ /dev/null @@ -1,173 +0,0 @@ -""" -AuditClient — thin wrappers around the Anthropic and OpenAI APIs. - -Loads API keys from the project root .env file automatically. -""" - -import json -import os -from pathlib import Path - -import anthropic -import openai -from dotenv import load_dotenv - -# Project root is two levels up from this file (vision_aid/llm_client/) -_ENV_FILE = Path(__file__).resolve().parents[2] / ".env" -load_dotenv(_ENV_FILE) - -# OpenAI model prefixes used to detect provider from model ID -_OPENAI_PREFIXES = ("gpt-", "o1", "o3", "o4") - - -def is_openai_model(model: str) -> bool: - """Return True if *model* looks like an OpenAI model ID.""" - return model.startswith(_OPENAI_PREFIXES) - - -class AuditClient: - """ - Sends filled accessibility-audit prompts to the Claude API and returns - parsed JSON responses. - - Parameters - ---------- - model : str - Claude model ID to use (default: claude-sonnet-4-6). - temperature : float - Sampling temperature (default: 0.1 for consistent structured output). - max_tokens : int - Maximum tokens to generate per response (default: 8192). - """ - - def __init__( - self, - model: str = "claude-sonnet-4-6", - temperature: float = 0.1, - max_tokens: int = 8192, - ): - api_key = os.environ.get("ANTHROPIC_API_KEY") - if not api_key: - raise EnvironmentError( - f"ANTHROPIC_API_KEY not found. Expected in {_ENV_FILE}" - ) - self._client = anthropic.Anthropic(api_key=api_key) - self.model = model - self.temperature = temperature - self.max_tokens = max_tokens - - def call(self, prompt_text: str, payload: dict) -> tuple[dict, dict]: - """ - Fill `{payload}` in *prompt_text* with JSON-serialised *payload*, - send to the API, and return ``(parsed_response, usage)``. - - The response is expected to be a JSON object (possibly wrapped in a - markdown code fence, which is stripped automatically). - - Returns - ------- - response_json : dict - Parsed JSON from the model's reply. - usage : dict - ``{"input_tokens": int, "output_tokens": int}`` - """ - filled = prompt_text.replace("{payload}", json.dumps(payload, separators=(",", ":"))) - - message = self._client.messages.create( - model=self.model, - max_tokens=self.max_tokens, - temperature=self.temperature, - messages=[{"role": "user", "content": filled}], - ) - - usage = { - "input_tokens": message.usage.input_tokens, - "output_tokens": message.usage.output_tokens, - } - - raw = message.content[0].text.strip() - - # Strip markdown code fences if present - if raw.startswith("```"): - raw = raw.split("\n", 1)[1] - raw = raw.rsplit("```", 1)[0].strip() - - return json.loads(raw), usage - - -class OpenAIAuditClient: - """ - Sends filled accessibility-audit prompts to the OpenAI API and returns - parsed JSON responses. Same interface as :class:`AuditClient`. - - Parameters - ---------- - model : str - OpenAI model ID to use (default: gpt-4o). - temperature : float - Sampling temperature (default: 0.1 for consistent structured output). - max_tokens : int - Maximum tokens to generate per response (default: 8192). - """ - - def __init__( - self, - model: str = "gpt-4o", - temperature: float = 0.1, - max_tokens: int = 8192, - ): - api_key = os.environ.get("OPENAI_API_KEY") - if not api_key: - raise EnvironmentError( - f"OPENAI_API_KEY not found. Expected in {_ENV_FILE}" - ) - self._client = openai.OpenAI(api_key=api_key) - self.model = model - self.temperature = temperature - self.max_tokens = max_tokens - - def call(self, prompt_text: str, payload: dict) -> tuple[dict, dict]: - """ - Fill `{payload}` in *prompt_text* with JSON-serialised *payload*, - send to the API, and return ``(parsed_response, usage)``. - - Returns - ------- - response_json : dict - Parsed JSON from the model's reply. - usage : dict - ``{"input_tokens": int, "output_tokens": int}`` - """ - filled = prompt_text.replace("{payload}", json.dumps(payload, separators=(",", ":"))) - - response = self._client.chat.completions.create( - model=self.model, - max_tokens=self.max_tokens, - temperature=self.temperature, - messages=[{"role": "user", "content": filled}], - ) - - usage = { - "input_tokens": response.usage.prompt_tokens, - "output_tokens": response.usage.completion_tokens, - } - - raw = response.choices[0].message.content.strip() - - # Strip markdown code fences if present - if raw.startswith("```"): - raw = raw.split("\n", 1)[1] - raw = raw.rsplit("```", 1)[0].strip() - - return json.loads(raw), usage - - -def create_audit_client( - model: str = "claude-sonnet-4-6", - temperature: float = 0.1, - max_tokens: int = 8192, -) -> AuditClient | OpenAIAuditClient: - """Factory that returns the right client class based on the model ID.""" - if is_openai_model(model): - return OpenAIAuditClient(model=model, temperature=temperature, max_tokens=max_tokens) - return AuditClient(model=model, temperature=temperature, max_tokens=max_tokens) diff --git a/vision_aid/llm_client/prompt_loader.py b/vision_aid/llm_client/prompt_loader.py deleted file mode 100644 index 60d33d6..0000000 --- a/vision_aid/llm_client/prompt_loader.py +++ /dev/null @@ -1,72 +0,0 @@ -""" -Parses the numbered prompt sections from the LLM prompt-library text files. - -File format (see processing_scripts/llm/*.txt): - --------------------------------- - N) PROMPT TITLE - --------------------------------- - <prompt body> - Data: {payload} - - --------------------------------- - N+1) NEXT PROMPT TITLE - ... -""" - -import re -from pathlib import Path - - -_HEADER_RE = re.compile(r"^\s{2,}(\d+)\)\s+.+", re.MULTILINE) -_DIVIDER_RE = re.compile(r"^\s*-{5,}\s*$", re.MULTILINE) - - -def load_prompts(filepath: str | Path) -> dict[int, str]: - """ - Parse *filepath* and return ``{prompt_number: prompt_text}`` for every - numbered section found. Divider lines (``---...``) are stripped. - - The returned text for each prompt still contains the ``{payload}`` - placeholder so the caller can fill it later. - """ - text = Path(filepath).read_text(encoding="utf-8") - - # Find all header positions and their prompt numbers - headers = list(_HEADER_RE.finditer(text)) - if not headers: - return {} - - prompts: dict[int, str] = {} - - for i, header in enumerate(headers): - num = int(header.group(1)) - start = header.end() # character just after the header line - end = headers[i + 1].start() if i + 1 < len(headers) else len(text) - - body = text[start:end] - - # Remove divider lines - body = _DIVIDER_RE.sub("", body) - - prompts[num] = body.strip() - - return prompts - - -def load_all_prompts(prompts_dir: str | Path) -> dict[str, dict[int, str]]: - """ - Load all ``*.txt`` prompt files in *prompts_dir*. - - Returns ``{stem: {prompt_number: prompt_text}}``, e.g.:: - - { - "semantic_checklist_01": {1: "...", 2: "...", ...}, - "forms_checklist_02": {1: "...", ...}, - "nontext_checklist_03": {1: "...", ...}, - } - """ - prompts_dir = Path(prompts_dir) - result: dict[str, dict[int, str]] = {} - for txt_file in sorted(prompts_dir.glob("*.txt")): - result[txt_file.stem] = load_prompts(txt_file) - return result diff --git a/vision_aid/llm_client/runner.py b/vision_aid/llm_client/runner.py deleted file mode 100644 index 97bbee8..0000000 --- a/vision_aid/llm_client/runner.py +++ /dev/null @@ -1,159 +0,0 @@ -""" -High-level runner that executes one or all checklist prompt sets against -pre-built JSON payloads, collects responses, and aggregates token usage. -""" - -from __future__ import annotations - -from typing import Any - -from .client import AuditClient - - -def run_checklist( - client: AuditClient, - prompts: dict[int, str], - slices: dict[str, Any | None], - *, - verbose: bool = True, -) -> dict[str, Any]: - """ - Run every prompt in *prompts* against the matching payload slice in *slices*. - - Parameters - ---------- - client : AuditClient - Configured API client. - prompts : dict[int, str] - ``{prompt_number: prompt_text}`` from ``load_prompts()``. - slices : dict[str, payload | None] - Mapping of label → payload dict (or ``None`` to skip). - Labels are used as keys in the returned results dict. - verbose : bool - Print progress to stdout while running. - - Returns - ------- - dict with keys: - - ``"results"`` : ``{label: response_json}`` - - ``"skipped"`` : list of skipped labels - - ``"usage"`` : ``{"input_tokens": int, "output_tokens": int}`` - - ``"errors"`` : ``{label: error_message}`` - """ - results: dict[str, Any] = {} - skipped: list[str] = [] - errors: dict[str, str] = {} - total_input = 0 - total_output = 0 - - # Map labels → prompt numbers by position (label order == prompt order) - labels = list(slices.keys()) - - for idx, label in enumerate(labels): - prompt_num = idx + 1 - payload = slices[label] - - if payload is None: - if verbose: - print(f" [{prompt_num}] {label} — SKIPPED (filtered by Pass 1)") - skipped.append(label) - continue - - # Skip if the payload is empty after filtering - if _is_empty_payload(payload): - if verbose: - print(f" [{prompt_num}] {label} — SKIPPED (empty payload after filtering)") - skipped.append(label) - continue - - prompt_text = prompts.get(prompt_num) - if prompt_text is None: - if verbose: - print(f" [{prompt_num}] {label} — SKIPPED (no prompt text found)") - skipped.append(label) - continue - - if verbose: - print(f" [{prompt_num}] {label} ...", end=" ", flush=True) - - try: - response, usage = client.call(prompt_text, payload) - results[label] = response - total_input += usage["input_tokens"] - total_output += usage["output_tokens"] - if verbose: - print(f"✓ ({usage['input_tokens']}in / {usage['output_tokens']}out tokens)") - except Exception as exc: - errors[label] = str(exc) - if verbose: - print(f"✗ ERROR: {exc}") - - return { - "results": results, - "skipped": skipped, - "usage": {"input_tokens": total_input, "output_tokens": total_output}, - "errors": errors, - } - - -def run_all( - client: AuditClient, - all_prompts: dict[str, dict[int, str]], - all_slices: dict[str, dict[str, Any | None]], - *, - verbose: bool = True, -) -> dict[str, Any]: - """ - Run all checklists in *all_slices* and return a consolidated report dict. - - Parameters - ---------- - client : AuditClient - all_prompts : dict[str, dict[int, str]] - ``{checklist_stem: {prompt_num: prompt_text}}`` from ``load_all_prompts()``. - all_slices : dict[str, dict[str, payload|None]] - ``{checklist_stem: {label: payload|None}}``. - verbose : bool - - Returns - ------- - dict with keys: - - ``"checklists"`` : ``{stem: checklist_result}`` - - ``"total_usage"`` : ``{"input_tokens": int, "output_tokens": int}`` - """ - checklists: dict[str, Any] = {} - grand_input = 0 - grand_output = 0 - - for stem, slices in all_slices.items(): - prompts = all_prompts.get(stem, {}) - if verbose: - print(f"\n--- {stem} ---") - - result = run_checklist(client, prompts, slices, verbose=verbose) - checklists[stem] = result - grand_input += result["usage"]["input_tokens"] - grand_output += result["usage"]["output_tokens"] - - return { - "checklists": checklists, - "total_usage": {"input_tokens": grand_input, "output_tokens": grand_output}, - } - - -# --------------------------------------------------------------------------- -# Helpers -# --------------------------------------------------------------------------- - -def _is_empty_payload(payload: Any) -> bool: - """Return True if every list-valued entry in the payload is empty.""" - if not isinstance(payload, dict): - return False - for v in payload.values(): - if isinstance(v, list) and v: - return False - if isinstance(v, dict) and v: - return False - if isinstance(v, str) and v.strip(): - return False - return True diff --git a/vision_aid/programmatic/__init__.py b/vision_aid/programmatic/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/vision_aid/programmatic/base.py b/vision_aid/programmatic/base.py deleted file mode 100644 index 02935e1..0000000 --- a/vision_aid/programmatic/base.py +++ /dev/null @@ -1,104 +0,0 @@ -from abc import abstractmethod, ABC -from bs4 import BeautifulSoup -import sys - -class AuditBase(ABC): - - def __init__( - self, - file_path:str - ): - self.file_path = file_path - self.soup = self.get_soup() - self.results = [] - - @staticmethod - def css_path(el): - """ - Generate a CSS-like DOM path for an element. - """ - path = [] - while el and el.name: - sibling_index = 1 - sibling = el - while sibling.previous_sibling: - sibling = sibling.previous_sibling - if getattr(sibling, "name", None) == el.name: - sibling_index += 1 - - if sibling_index > 1: - path.append(f"{el.name}:nth-of-type({sibling_index})") - else: - path.append(el.name) - - el = el.parent - - return " > ".join(reversed(path)) - - @staticmethod - def element_location(element): - """ - Build structured location metadata for an element. - """ - if element is None: - return None - - attrs = dict(element.attrs) - - return { - "tag": element.name, - "id": attrs.get("id"), - "class": attrs.get("class"), - "css_path": AuditBase.css_path(element), - "attributes": attrs, - "text_preview": element.get_text(strip=True)[:80] - } - - @staticmethod - def issue(rule_id, rule_name, element, description): - """ - Create a standardized issue object. - """ - return { - "rule_id": rule_id, - "rule_name": rule_name, - "location": AuditBase.element_location(element), - "description": description - } - - @staticmethod - def parse_results(results): - if not results: - print("No issues found.") - sys.exit(0) - - for r in results: - print(f"[{r['rule_id']}] {r['rule_name']}") - - location = r.get("location") - - if location: - if location.get("css_path"): - print(f" Location: {location['css_path']}") - if location.get("id"): - print(f" ID: {location['id']}") - if location.get("attributes"): - print(f" Attributes: {location['attributes']}") - if location.get("text_preview"): - print(f" Text Preview: \"{location['text_preview']}\"") - - print(f" Description: {r['description']}") - print() - - def get_soup(self): - with open(self.file_path, "r", encoding="utf-8") as f: - soup = BeautifulSoup(f.read(), "lxml") - return soup - - @abstractmethod - def run_audit(self): - """ - Abstract method for defining programmatic - audits for each of the element types. - """ - pass \ No newline at end of file diff --git a/vision_aid/programmatic/forms.py b/vision_aid/programmatic/forms.py deleted file mode 100644 index b792ad4..0000000 --- a/vision_aid/programmatic/forms.py +++ /dev/null @@ -1,131 +0,0 @@ -from base import AuditBase -import sys -import os - -class FormAudit(AuditBase): - def __init__(self, file_path): - super().__init__(file_path) - self.form_controls = self.get_controls() - - def get_controls(self): - form_controls = [] - - for control in self.soup.find_all(["input", "select", "textarea"]): - - # Skip non-interactive input types - if control.name == "input": - input_type = (control.get("type") or "text").lower() - - if input_type in [ - "hidden", - "submit", - "reset", - "button", - "image" - ]: - continue - - form_controls.append(control) - - return form_controls - - def set_legend(self): - for fieldset in self.soup.find_all("fieldset"): - - legend = fieldset.find("legend") - - # FORM_GROUP_001 — Fieldset missing legend - if not legend: - self.results.append(FormAudit.issue( - "FORM_GROUP_001", - "Fieldset missing legend", - fieldset, - "Fieldset does not contain a legend element." - )) - - def set_required_fields(self): - for control in self.form_controls: - - # Already programmatically required - if "required" in control.attrs: - continue - - control_id = control.get("id") - - # Heuristic: label contains * - if control_id: - label = self.soup.find("label", attrs={"for": control_id}) - if label and "*" in label.get_text(): - self.results.append(FormAudit.issue( - "FORM_REQUIRED_001", - "Required field not programmatically designated", - control, - "Field appears visually required but lacks 'required' attribute." - )) - - def set_aria(self): - for control in self.form_controls: - - describedby = control.get("aria-describedby") - if describedby: - ids = describedby.split() - for ref_id in ids: - if not self.soup.find(id=ref_id): - self.results.append(FormAudit.issue( - "FORM_INSTR_001", - "aria-describedby reference not found", - control, - f"aria-describedby references missing ID '{ref_id}'." - )) - - def set_message_assc(self): - for control in self.form_controls: - - if control.get("aria-invalid") == "true": - describedby = control.get("aria-describedby") - - if not describedby: - self.results.append(FormAudit.issue( - "FORM_ERROR_001", - "Error message not programmatically associated", - control, - "Invalid form control lacks aria-describedby linking to error message." - )) - - def set_custom_interactive(self): - for el in self.soup.find_all(True): - - if el.get("onclick") and el.name not in ["button", "a", "input"]: - if not el.get("role"): - self.results.append(FormAudit.issue( - "FORM_CUSTOM_001", - "Custom interactive element missing role", - el, - "Element has click handler but no semantic role." - )) - - def run_audit(self): - self.set_legend() - self.set_required_fields() - self.set_aria() - self.set_message_assc() - self.set_custom_interactive() - return self.results - -if __name__=='__main__': - if len(sys.argv) != 2: - print("Usage: python audit_forms.py <file.html>") - sys.exit(1) - - file_path = sys.argv[1] - - if not os.path.exists(file_path): - print(f"Error: File '{file_path}' not found.") - sys.exit(1) - - form_audit = FormAudit(file_path) - results = form_audit.run_audit() - - print("\n=== FORM ACCESSIBILITY AUDIT RESULTS ===\n") - - form_audit.parse_results(results) \ No newline at end of file diff --git a/vision_aid/programmatic/nontext.py b/vision_aid/programmatic/nontext.py deleted file mode 100644 index 97fd5c3..0000000 --- a/vision_aid/programmatic/nontext.py +++ /dev/null @@ -1,117 +0,0 @@ -from base import AuditBase -import sys -import os - -class NontextAudit(AuditBase): - def __init__(self, file_path): - super().__init__(file_path) - - def set_img_alt_txt(self): - # Images that convey content MUST have programmatically-discernible alternative text. - for img in self.soup.find_all("img"): - - # NON_TEXT_001 — Missing alt attribute - if img.get("alt") is None: - self.results.append(NontextAudit.issue( - "NON_TEXT_001", - "Image missing alt attribute", - img, - "<img> element does not contain an alt attribute." - )) - - # All actionable images MUST have alternative text. - for a in self.soup.find_all("a"): - img = a.find("img") - if img: - alt = img.get("alt") - if alt is None or alt.strip() == "": - self.results.append(NontextAudit.issue( - "NON_TEXT_002", - "Actionable image missing alt text", - img, - "Image inside a link must have non-empty alt text." - )) - - # Form inputs with type="image" MUST have alternative text. - for inp in self.soup.find_all("input", attrs={"type": "image"}): - alt = inp.get("alt") - if alt is None or alt.strip() == "": - self.results.append(NontextAudit.issue( - "NON_TEXT_003", - "Image input missing alt text", - inp, - "Form input type='image' must have non-empty alt text." - )) - - def set_img_maps(self): - # The alternative text for the <area> element MUST be available. - for area in self.soup.find_all("area"): - alt = area.get("alt") - if alt is None or alt.strip() == "": - self.results.append(NontextAudit.issue( - "NON_TEXT_004", - "Image map area missing alt text", - area, - "<area> element must have non-empty alt text." - )) - - def set_svg(self): - # SVG SHOULD NOT be embedded via <object> or <iframe>. - for obj in self.soup.find_all(["object", "iframe"]): - src = obj.get("data") or obj.get("src") - if src and src.lower().endswith(".svg"): - self.results.append(NontextAudit.issue( - "NON_TEXT_005", - "SVG embedded via object or iframe", - obj, - "SVG should not be embedded using <object> or <iframe>." - )) - - def set_canvas(self): - # All <canvas> elements MUST have a text alternative. - for canvas in self.soup.find_all("canvas"): - if not canvas.get_text(strip=True): - self.results.append(NontextAudit.issue( - "NON_TEXT_006", - "Canvas missing fallback text", - canvas, - "<canvas> element must contain fallback text content." - )) - - def set_plug_ins(self): - # All <object> elements MUST have alternative text. - for obj in self.soup.find_all("object"): - if not obj.get_text(strip=True): - self.results.append(NontextAudit.issue( - "NON_TEXT_007", - "Object missing alternative text", - obj, - "<object> element must contain alternative text content." - )) - - def run_audit(self): - self.set_img_alt_txt() - self.set_img_maps() - self.set_svg() - self.set_canvas() - self.set_plug_ins() - return self.results - -if __name__ == "__main__": - - if len(sys.argv) != 2: - print("Usage: python audit_nontext.py <file.html>") - sys.exit(1) - - file_path = sys.argv[1] - - if not os.path.exists(file_path): - print(f"Error: File '{file_path}' not found.") - sys.exit(1) - - nontext_audit = NontextAudit(file_path) - results = nontext_audit.run_audit() - - print("\n=== NON-TEXT ACCESSIBILITY AUDIT RESULTS ===\n") - - nontext_audit.parse_results(results) \ No newline at end of file diff --git a/vision_aid/programmatic/semantic.py b/vision_aid/programmatic/semantic.py deleted file mode 100644 index 9793eba..0000000 --- a/vision_aid/programmatic/semantic.py +++ /dev/null @@ -1,408 +0,0 @@ -from base import AuditBase -import sys -import os -import re - -class SemanticAudit(AuditBase): - def __init__(self, file_path): - super().__init__(file_path) - self.LANGUAGE_TAG_REGEX = re.compile(r"^[a-zA-Z]{2,3}(-[a-zA-Z0-9]{2,8})*$") - - def set_titles(self): - titles = self.soup.find_all("title") - - # PAGE_TITLE_001 — Missing <title> - if len(titles) == 0: - head = self.soup.find("head") - self.results.append(SemanticAudit.issue( - "PAGE_TITLE_001", - "Missing <title>", - head, - "The page does not contain a <title> element." - )) - - # PAGE_TITLE_002 — Multiple <title> - if len(titles) > 1: - for t in titles: - self.results.append(SemanticAudit.issue( - "PAGE_TITLE_002", - "Multiple <title> elements", - t, - "More than one <title> element found." - )) - - # PAGE_TITLE_003 — Empty <title> - if titles and not titles[0].get_text(strip=True): - self.results.append(SemanticAudit.issue( - "PAGE_TITLE_003", - "Empty <title>", - titles[0], - "<title> element exists but contains no text." - )) - - def set_lang(self): - html = self.soup.find("html") - if html: - lang = html.get("lang") - - if not lang: - self.results.append(SemanticAudit.issue( - "LANG_001", - "Missing primary language", - html, - "<html> element missing lang attribute." - )) - - # LANG_002 — Invalid primary language code - elif not self.LANGUAGE_TAG_REGEX.match(lang): - self.results.append(SemanticAudit.issue( - "LANG_002", - "Invalid primary language code", - html, - f"Invalid language code '{lang}' on <html>." - )) - - # LANG_003 — Invalid inline language code - for el in self.soup.find_all(attrs={"lang": True}): - lang_val = el.get("lang") - if not self.LANGUAGE_TAG_REGEX.match(lang_val): - self.results.append(SemanticAudit.issue( - "LANG_003", - "Invalid inline language code", - el, - f"Invalid lang attribute '{lang_val}'." - )) - - def set_landmark(self): - # HTML5 landmark elements mapped to ARIA landmark roles - landmark_map = { - "header": "banner", - "nav": "navigation", - "main": "main", - "footer": "contentinfo", - "aside": "complementary" - } - - aria_landmark_roles = { - "banner", - "navigation", - "main", - "contentinfo", - "complementary", - "search", - "form", - "region" - } - - landmarks = [] - - # Collect semantic landmark elements - for tag, role in landmark_map.items(): - for el in self.soup.find_all(tag): - landmarks.append((el, role)) - - # Collect ARIA landmark roles - for el in self.soup.find_all(attrs={"role": True}): - role = el.get("role") - if role in aria_landmark_roles: - landmarks.append((el, role)) - - role_map = {} - - for el, role in landmarks: - role_map.setdefault(role, []).append(el) - - # LAND_001 — No main landmark - if "main" not in role_map: - body = self.soup.find("body") - self.results.append(SemanticAudit.issue( - "LAND_001", - "Missing main landmark", - body, - "Page does not contain a <main> landmark." - )) - - # LAND_002 — Multiple main landmarks - if len(role_map.get("main", [])) > 1: - for el in role_map["main"]: - self.results.append(SemanticAudit.issue( - "LAND_002", - "Multiple main landmarks", - el, - "More than one 'main' landmark found." - )) - - # LAND_003 — Multiple banner landmarks - if len(role_map.get("banner", [])) > 1: - for el in role_map["banner"]: - self.results.append(SemanticAudit.issue( - "LAND_003", - "Multiple banner landmarks", - el, - "More than one 'banner' landmark found." - )) - - # LAND_004 — Multiple contentinfo landmarks - if len(role_map.get("contentinfo", [])) > 1: - for el in role_map["contentinfo"]: - self.results.append(SemanticAudit.issue( - "LAND_004", - "Multiple contentinfo landmarks", - el, - "More than one 'contentinfo' landmark found." - )) - - # LAND_005 — Multiple same-type landmarks without labels - for role, elements in role_map.items(): - if len(elements) > 1: - for el in elements: - if not el.get("aria-label") and not el.get("aria-labelledby"): - self.results.append(SemanticAudit.issue( - "LAND_005", - f"Multiple '{role}' landmarks without accessible labels", - el, - f"Multiple '{role}' landmarks should have distinguishing aria-label or aria-labelledby attributes." - )) - - # LAND_006 — Content outside landmark regions - landmark_elements = [el for el, _ in landmarks] - body = self.soup.find("body") - - if body: - for child in body.find_all(recursive=False): - if child not in landmark_elements and child.name not in ["script", "style"]: - if child.get_text(strip=True): - self.results.append(SemanticAudit.issue( - "LAND_006", - "Content outside landmark regions", - child, - "Content found directly under <body> that is not contained within a landmark region." - )) - break - - def set_headings(self): - headings = self.soup.find_all(re.compile("^h[1-6]$")) - previous_level = 0 - - # HEAD_001 — Skipped heading levels - for h in headings: - level = int(h.name[1]) - if previous_level and level > previous_level + 1: - self.results.append(SemanticAudit.issue( - "HEAD_001", - "Skipped heading level", - h, - "Heading level skipped (e.g., h2 to h4)." - )) - previous_level = level - - h1_elements = [h for h in headings if h.name == "h1"] - - # HEAD_003 — Missing <h1> - if len(h1_elements) == 0: - body = self.soup.find("body") - self.results.append(SemanticAudit.issue( - "HEAD_003", - "Missing <h1> element", - body, - "The page does not contain an <h1> element." - )) - - # HEAD_002 — Multiple <h1> - if len(h1_elements) > 1: - for h in h1_elements: - self.results.append(SemanticAudit.issue( - "HEAD_002", - "Multiple <h1> elements", - h, - "More than one <h1> found." - )) - - # HEAD_004 — Empty heading - for h in headings: - if not h.get_text(strip=True): - self.results.append(SemanticAudit.issue( - "HEAD_004", - "Empty heading", - h, - "Heading element contains no text." - )) - - def set_links(self): - for a in self.soup.find_all("a"): - - # LINK_001 — Missing accessible name - if not a.get_text(strip=True) and not a.get("aria-label"): - self.results.append(SemanticAudit.issue( - "LINK_001", - "Link without accessible name", - a, - "Link has no text or aria-label." - )) - - # LINK_002 — Anchor without href - if not a.get("href"): - self.results.append(SemanticAudit.issue( - "LINK_002", - "Anchor without href", - a, - "Anchor element does not contain an href attribute." - )) - - def set_skip_links(self): - skip_links = [] - - # Identify potential skip links (anchor with internal target and "skip" text) - for a in self.soup.find_all("a"): - href = a.get("href") - text = a.get_text(strip=True).lower() - - if href and href.startswith("#") and "skip" in text: - skip_links.append(a) - - # NAV_001 — Skip link not present - if not skip_links: - body = self.soup.find("body") - self.results.append(SemanticAudit.issue( - "NAV_001", - "Skip link not present", - body, - "Page does not contain a skip navigation link." - )) - else: - # Validate each skip link - for skip in skip_links: - target_id = skip.get("href")[1:] - target_element = self.soup.find(id=target_id) - - # NAV_002 — Skip link target missing - if not target_element: - self.results.append(SemanticAudit.issue( - "NAV_002", - "Skip link target does not exist", - skip, - f"Skip link points to '#{target_id}' but no element with that ID exists." - )) - - # NAV_003 — Skip link is not first focusable element - focusable_elements = [] - - for el in self.soup.find_all(True): - if el.name in ["a", "button", "input", "select", "textarea"]: - if el.name != "a" or el.get("href"): - focusable_elements.append(el) - elif el.get("tabindex") and el.get("tabindex").isdigit(): - if int(el.get("tabindex")) >= 0: - focusable_elements.append(el) - - if focusable_elements: - first_focusable = focusable_elements[0] - if first_focusable not in skip_links: - self.results.append(SemanticAudit.issue( - "NAV_003", - "Skip link is not first focusable element", - first_focusable, - "The first focusable element on the page is not a skip navigation link." - )) - - def set_tab_index(self): - # FOCUS_001 — Positive tabindex used - for el in self.soup.find_all(attrs={"tabindex": True}): - val = el.get("tabindex") - if val.isdigit() and int(val) > 0: - self.results.append(SemanticAudit.issue( - "FOCUS_001", - "Positive tabindex used", - el, - "tabindex greater than 0 should not be used." - )) - - def set_tables(self): - for table in self.soup.find_all("table"): - - # TABLE_001 — Missing caption - if not table.find("caption"): - self.results.append(SemanticAudit.issue( - "TABLE_001", - "Missing table caption", - table, - "Data table does not contain a <caption>." - )) - - # TABLE_002 — Missing headers - if not table.find("th"): - self.results.append(SemanticAudit.issue( - "TABLE_002", - "Missing table headers", - table, - "Table does not contain <th> elements." - )) - - def set_iframes(self): - for iframe in self.soup.find_all("iframe"): - - # IFRAME_001 — Missing title - title = iframe.get("title") - if not title: - self.results.append(SemanticAudit.issue( - "IFRAME_001", - "Missing iframe title", - iframe, - "Iframe does not have a title attribute." - )) - - # IFRAME_002 — Empty title - elif not title.strip(): - self.results.append(SemanticAudit.issue( - "IFRAME_002", - "Empty iframe title", - iframe, - "Iframe title attribute is empty." - )) - - def set_duplicate_ids(self): - ids = {} - for el in self.soup.find_all(attrs={"id": True}): - id_val = el.get("id") - if id_val in ids: - self.results.append(SemanticAudit.issue( - "PARSE_001", - "Duplicate ID", - el, - f"Duplicate id '{id_val}' found." - )) - else: - ids[id_val] = el - - def run_audit(self): - self.set_titles() - self.set_lang() - self.set_landmark() - self.set_headings() - self.set_links() - self.set_skip_links() - self.set_tab_index() - self.set_tables() - self.set_iframes() - self.set_duplicate_ids() - return self.results - -if __name__=='__main__': - if len(sys.argv) != 2: - print("Usage: python audit.py <file.html>") - sys.exit(1) - - file_path = sys.argv[1] - - if not os.path.exists(file_path): - print(f"Error: File '{file_path}' not found.") - sys.exit(1) - - semantic_audit = SemanticAudit(file_path=file_path) - results = semantic_audit.run_audit() - - print("\n=== SEMANTIC ACCESSIBILITY AUDIT RESULTS ===\n") - - semantic_audit.parse_results(results) - - sys.exit(2) \ No newline at end of file From 1ad10888e9518d9237028afae388b445de9e16fd Mon Sep 17 00:00:00 2001 From: Justin McLellan <jmclellan@beast.> Date: Thu, 6 Aug 2026 23:36:25 -0500 Subject: [PATCH 4/8] build: standardize on uv with a committed lockfile MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The project carried the same seven dependencies in two hand-maintained lists (pyproject.toml and requirements.txt) with no lock file, so nothing was pinned: every teammate and every Docker build resolved independently. pyproject.toml is now the only hand-edited list, uv.lock pins all 36 packages including transitives, and requirements.txt becomes a generated export kept for graders and Colab — its header carries the regeneration command, and CI fails if it drifts. .python-version pins 3.12 to match the container. uv also manages the interpreter, which avoids the 'python -m venv' ensurepip failure on Debian/Ubuntu systems without python3-venv. Also drops fastapi, uvicorn and python-multipart: they existed only for the removed serverless handler, and api_server.py uses http.server. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> --- .python-version | 1 + pyproject.toml | 3 - requirements.txt | 117 +++++- uv.lock | 981 +++++++++++++++++++++++++++++++++++++++++++++++ 4 files changed, 1089 insertions(+), 13 deletions(-) create mode 100644 .python-version create mode 100644 uv.lock diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/pyproject.toml b/pyproject.toml index e1b88b9..29ab6af 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -16,9 +16,6 @@ dependencies = [ "google-genai>=1.0.0", "python-dotenv~=1.2.1", "requests>=2.32.2", - "fastapi>=0.110.0", - "uvicorn>=0.27.0", - "python-multipart>=0.0.9", ] [tool.setuptools] diff --git a/requirements.txt b/requirements.txt index 9c45b95..1a5da01 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,10 +1,107 @@ -anthropic~=0.84.0 -beautifulsoup4>=4.9.2 -lxml>=4.9.0 -openai>=1.0.0 -google-genai>=1.0.0 -python-dotenv~=1.2.1 -requests>=2.32.2 -fastapi>=0.110.0 -uvicorn>=0.27.0 -python-multipart>=0.0.9 +# This file was autogenerated by uv via the following command: +# uv export --format requirements.txt --no-dev --no-emit-project --no-hashes -o requirements.txt +annotated-types==0.8.0 + # via pydantic +anthropic==0.84.0 + # via visionaid +anyio==4.14.2 + # via + # anthropic + # google-genai + # httpx + # openai +beautifulsoup4==4.15.0 + # via visionaid +certifi==2026.7.22 + # via + # httpcore + # httpx + # requests +cffi==2.1.1 ; platform_python_implementation != 'PyPy' + # via cryptography +charset-normalizer==3.4.9 + # via requests +colorama==0.4.6 ; sys_platform == 'win32' + # via tqdm +cryptography==50.0.0 + # via google-auth +distro==1.9.0 + # via + # anthropic + # google-genai + # openai +docstring-parser==0.18.0 + # via anthropic +google-auth==2.56.3 + # via google-genai +google-genai==2.17.0 + # via visionaid +h11==0.16.0 + # via httpcore +httpcore==1.0.9 + 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2a727c5f940751917d7dcdc93bffeee038ad67c0 Mon Sep 17 00:00:00 2001 From: Justin McLellan <jmclellan@beast.> Date: Thu, 6 Aug 2026 23:36:33 -0500 Subject: [PATCH 5/8] build: containerize for Coolify deployment MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Multi-stage build: uv sync --frozen into a builder, then the venv copied into a clean runtime with no uv or build tooling. --frozen fails the build if uv.lock and pyproject.toml disagree. Ordering matters here: creating the user before the venv and copying with --chown avoids a chown -R over /app/.venv, which duplicates the whole virtualenv into a second layer and doubles the image. docker-compose.yml is for local runs; Coolify deploys the published image directly, so its read_only/tmpfs hardening does not apply in production. It deliberately passes no provider API keys — users supply their own in the web form, and an interpolated ${ANTHROPIC_API_KEY:-} would silently inject a developer's local .env key into the container and bill it for every anonymous audit. DEPLOY.md covers the proxy settings that matter: response buffering breaks the progress stream, and short read timeouts cut off long audits. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> --- .dockerignore | 38 ++++++++++++++++ DEPLOY.md | 108 +++++++++++++++++++++++++++++++++++++++++++++ Dockerfile | 67 ++++++++++++++++++++++++++++ docker-compose.yml | 56 +++++++++++++++++++++++ 4 files changed, 269 insertions(+) create mode 100644 .dockerignore create mode 100644 DEPLOY.md create mode 100644 Dockerfile create mode 100644 docker-compose.yml diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000..14ddc3f --- /dev/null +++ b/.dockerignore @@ -0,0 +1,38 @@ +# Secrets — never copy into an image layer. Keys are supplied at runtime via +# Coolify's environment variables, or per-request from the web form. +.env +.env.* + +# Local virtualenvs and Python build noise. Patterns are matched from the +# build-context root, so nested matches need an explicit **/ prefix. +venv/ +.venv/ +**/__pycache__/ +**/*.py[cod] +**/*.egg-info/ +build/ +dist/ + +# Version control and editor/tooling state +.git/ +.gitignore +.github/ +.claude/ +.idea/ +.vscode/ + +# Runtime output — regenerated per audit, never part of the image +output/ +reports/ +test_results/ + +# Sample inputs and reference material. Only needed for the CLI pipeline +# (entry_points/run_pipeline.py), not for serving the app. Drop these lines +# if you want to run the CLI inside the container. +test_files/ +semantic_checklist/ +docs/ +*.ipynb + +# Deployment docs — not needed inside the image +DEPLOY.md diff --git a/DEPLOY.md b/DEPLOY.md new file mode 100644 index 0000000..ee300fb --- /dev/null +++ b/DEPLOY.md @@ -0,0 +1,108 @@ +# Deploying to Coolify + +The app is a single long-running container serving both the website +(`index.html`, `styles.css`) and the audit API from +`entry_points/api_server.py`. + +## Quick start + +```bash +docker compose up --build # http://localhost:8000 +HOST_PORT=8789 docker compose up --build # if 8000 is already in use +``` + +In Coolify: create a **Docker Compose** resource pointed at this repo, set the +environment variables below, attach a domain, and deploy. + +## Environment variables + +| Variable | Required | Notes | +|---|---|---| +| `HOST` | No | Set to `0.0.0.0` by the image; do not override | +| `PORT` | No | Defaults to 8000; Coolify may inject its own | +| `HOST_PORT` | No | Local-only: host port for `docker compose up` (default 8000) | + +**No provider API keys are configured, deliberately.** Each user pastes their +own key into the web form, so the deployment never bills a shared account. +Per-request keys take priority over the environment +(`api_server.py:_resolve_api_key`). + +Consequence worth knowing: **a request with no resolvable key silently runs a +dry run** — programmatic checks only, no LLM findings, no CSV report, and a +`200 OK` either way. The only signal is `summary.dry_run` in the response. A +user who forgets to paste a key gets a partial-looking audit rather than an +error. + +### The `.env` interpolation trap + +Do **not** add lines like this back into `docker-compose.yml`: + +```yaml +environment: + ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY:-} # DON'T +``` + +Compose automatically loads `./.env` from the project directory to resolve +`${...}`. On any developer machine with a local `.env`, that line silently +injects their personal key into the container, and every anonymous audit bills +it. This was verified the hard way: with that line present, a container built +from an image containing no `.env`, started from a shell exporting no key, +still made live API calls. + +`.dockerignore` keeps `.env` out of the *image*; interpolation reads it from +the *host* at run time. Different mechanism — `.dockerignore` cannot stop it. +Coolify deployments are not affected (`.env` is gitignored, so it never reaches +the clone), but local `docker compose up` is. + +## Proxy configuration — read this one + +`POST /api/audit`, `/api/audit/url`, and `/api/audit/url/nested` return an +**NDJSON stream** that stays open for the whole audit, emitting progress events +as it goes. Two default proxy behaviours will break this: + +1. **Response buffering.** A proxy that buffers will hold every progress event + until the audit finishes, so the browser shows a frozen progress bar and then + all results at once. Disable buffering for `/api/`. +2. **Read timeouts.** A single-page audit runs 17+ sequential LLM calls and + commonly takes 1–3 minutes; a nested crawl audits every discovered page and + can run far longer. Anything under ~10 minutes risks cutting audits off + mid-run. Traefik's default is generous, but Coolify installs vary — verify. + +In Coolify, set these as Traefik labels on the service, or raise the equivalent +values in the proxy settings: + +```yaml +labels: + - traefik.http.routers.audit.middlewares=audit-buffering@docker + - traefik.http.middlewares.audit-buffering.buffering.maxResponseBodyBytes=0 + - traefik.http.services.audit.loadbalancer.responseForwarding.flushInterval=100ms +``` + +`flushInterval` is the important one — it forces Traefik to flush each chunk +through rather than accumulating it. + +If you front this with nginx instead: + +```nginx +location /api/ { + proxy_buffering off; + proxy_read_timeout 600s; +} +``` + +## Sizing + +Audits are I/O-bound on the LLM API, not CPU-bound. 512 MB RAM and 0.5 vCPU is +enough for light use. The server is a stdlib `ThreadingHTTPServer`, so each +concurrent audit holds a thread and its own temp directory — fine for a handful +of simultaneous users, not for public high traffic. The `tmpfs` mount is capped +at 512 MB; a large nested crawl of very large pages could approach that, so +raise it if you see failures writing temp files. + +## Serving + +`entry_points/api_server.py` is the single server: it serves `index.html` and +`styles.css` at `/`, and handles the audit endpoints under `/api/`. There is +deliberately no second, serverless copy of the audit logic — the project +previously carried two, and they drifted until one silently skipped the LLM +deduplication pass. Keep the logic in one place. diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000..555501e --- /dev/null +++ b/Dockerfile @@ -0,0 +1,67 @@ +# syntax=docker/dockerfile:1 + +# Serves the team website and the accessibility audit API +# (entry_points/api_server.py). Built for a long-running container, which is +# what makes the NDJSON progress stream viable — unlike a serverless function, +# there is no execution-time cap to work around. + +# ── Build stage: resolve and install into /app/.venv ────────────────────────── +FROM python:3.12-slim AS builder + +# uv installs from uv.lock, so the image gets exactly the versions committed to +# the repo. Pinned deliberately rather than tracking latest mid-semester. +COPY --from=ghcr.io/astral-sh/uv:0.11.21 /uv /bin/uv + +ENV UV_COMPILE_BYTECODE=1 \ + UV_LINK_MODE=copy \ + UV_PYTHON=python3.12 \ + UV_PYTHON_DOWNLOADS=never \ + UV_NO_CACHE=1 + +WORKDIR /app + +# Dependencies first, without the project itself, so editing source does not +# invalidate this layer. --frozen fails the build if uv.lock is out of date +# with pyproject.toml, which keeps the two from silently diverging. +COPY pyproject.toml uv.lock ./ +RUN uv sync --frozen --no-install-project --no-dev + +# Application code. See .dockerignore — .env and venv/ are deliberately +# excluded so no API key is ever baked into an image layer. +COPY . . +RUN uv sync --frozen --no-dev + +# ── Runtime stage: no uv, no build tooling ─────────────────────────────────── +FROM python:3.12-slim + +ENV PYTHONUNBUFFERED=1 \ + PYTHONDONTWRITEBYTECODE=1 + +# Single chowned COPY: the virtualenv lands in exactly one layer. Copying it +# after creating it, rather than chown -R'ing it in place, keeps the image from +# carrying two copies. The path must match the builder's so the venv's +# absolute shebangs stay valid. +RUN useradd --create-home --uid 10001 appuser +WORKDIR /app +COPY --from=builder --chown=appuser:appuser /app /app + +# Put the synced virtualenv first on PATH so `python` is the project's. +ENV PATH="/app/.venv/bin:$PATH" + +# api_server.py reads both of these from the environment (see its main()). +# Coolify injects its own PORT; HOST must be 0.0.0.0 to accept traffic from +# outside the container. +ENV HOST=0.0.0.0 \ + PORT=8000 + +EXPOSE 8000 + +# Run unprivileged. /tmp must stay writable: every audit runs inside a +# tempfile.mkdtemp() directory that is removed when the request completes. +USER appuser + +# GET / serves index.html; urlopen raises on any non-2xx, failing the check. +HEALTHCHECK --interval=30s --timeout=5s --start-period=10s --retries=3 \ + CMD ["python", "-c", "import os,urllib.request; urllib.request.urlopen('http://127.0.0.1:' + os.environ.get('PORT','8000') + '/', timeout=4)"] + +CMD ["python", "entry_points/api_server.py"] diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000..2e35e9a --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,56 @@ +# Deployment for Coolify (and plain `docker compose up` locally). +# +# Coolify supplies the domain, TLS and reverse proxy itself. No API keys are +# configured here or in Coolify: users supply their own in the web form. +# See DEPLOY.md for the proxy timeout/buffering settings this app needs. + +services: + audit: + build: + context: . + dockerfile: Dockerfile + image: visionaid-a11y-audit:latest + restart: unless-stopped + + environment: + HOST: 0.0.0.0 + PORT: 8000 + + # No provider API keys are passed in, by design: every user supplies their + # own key in the web form, so the deployment never bills a shared account. + # + # Do NOT "helpfully" add lines like `ANTHROPIC_API_KEY: ${ANTHROPIC_API_KEY:-}`. + # Compose auto-loads ./.env for ${...} interpolation, so on any developer + # machine that has a local .env, that line silently injects their personal + # key into the container and every anonymous audit bills it. .dockerignore + # keeps .env out of the *image*, but interpolation reads it from the *host* + # at run time — a different mechanism that .dockerignore cannot stop. + # + # If a server-side fallback key is ever genuinely wanted, set it in + # Coolify's Environment Variables UI rather than reintroducing that line. + + # Coolify normally routes to the container through its own proxy and you + # can drop this mapping. Keep it for local `docker compose up`; set + # HOST_PORT to avoid clashing with a dev server already on 8000. + ports: + - "${HOST_PORT:-8000}:8000" + + healthcheck: + test: + - CMD + - python + - -c + - import os,urllib.request; urllib.request.urlopen('http://127.0.0.1:' + os.environ.get('PORT','8000') + '/', timeout=4) + interval: 30s + timeout: 5s + start_period: 10s + retries: 3 + + # Audits write only to per-request tempfile.mkdtemp() directories, so the + # root filesystem can stay read-only; /tmp below is the one writable mount. + read_only: true + tmpfs: + - /tmp:size=512m + + security_opt: + - no-new-privileges:true From 35a187468abf1a36e08428db354db0860c886ed5 Mon Sep 17 00:00:00 2001 From: Justin McLellan <jmclellan@beast.> Date: Thu, 6 Aug 2026 23:36:41 -0500 Subject: [PATCH 6/8] ci: add PR checks and publish-on-main workflows MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ci.yml runs on pull requests to main and needs no API key — every check is free. It verifies uv.lock matches pyproject.toml, requirements.txt matches the lock, entry points import, a full pipeline dry run produces prompts and findings while consuming zero tokens, index.html's inline JavaScript parses, and the image builds, becomes healthy, serves the site and returns a valid NDJSON audit. publish.yml runs on push to main: builds the image, pushes it to ghcr.io/c4g/va-dat, smoke tests the published image, then triggers the Coolify deploy. The smoke test exists because CI only runs on pull requests, so the merge commit itself is otherwise never exercised before it deploys; it also asserts the image carries no credentials. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> --- .github/workflows/ci.yml | 206 ++++++++++++++++++++++++++++++++++ .github/workflows/publish.yml | 123 ++++++++++++++++++++ .gitignore | 3 + 3 files changed, 332 insertions(+) create mode 100644 .github/workflows/ci.yml create mode 100644 .github/workflows/publish.yml diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..774f495 --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,206 @@ +name: CI + +on: + pull_request: + branches: [main] + +# A new push to the same PR cancels the previous run. +concurrency: + group: ci-${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + +permissions: + contents: read + +jobs: + checks: + name: Dependencies, imports, pipeline + runs-on: ubuntu-latest + timeout-minutes: 10 + steps: + - uses: actions/checkout@v7 + + - name: Install uv + uses: astral-sh/setup-uv@v9.0.0 + with: + version: "0.11.21" + enable-cache: true + + # Fails if pyproject.toml and uv.lock disagree — i.e. someone changed a + # dependency without re-running `uv lock`. + - name: uv.lock is up to date + run: uv lock --check + + - name: Install locked dependencies + run: uv sync --frozen + + # requirements.txt is a generated export, not a hand-maintained list. + # Regenerate it and fail if the committed copy differs. + - name: requirements.txt matches uv.lock + run: | + uv export --format requirements.txt --no-dev --no-emit-project \ + --no-hashes -o requirements.txt + if ! git diff --exit-code --stat -- requirements.txt; then + echo "::error::requirements.txt is out of date. Regenerate it with the command in its header and commit the result." + exit 1 + fi + + - name: Entry points import + run: | + uv run python -c " + import entry_points.api_server, entry_points.run_pipeline, entry_points.generate_report + from vision_aid.ingestion.file_crawler import fetch_page, fetch_pages_nested + print('all entry points import cleanly') + " + + # Exercises extractors, slicers, prompt templates and the programmatic + # checkers end to end. --dry-run makes no API calls, so this needs no key + # and costs nothing. + - name: Pipeline dry run + run: | + uv run python entry_points/run_pipeline.py \ + --html test_files/dat_visionaid_home.html \ + --dry-run --output-dir ./ci-output + + - name: Pipeline produced expected output + run: | + uv run python - <<'PY' + import json, pathlib, sys + + manifest = json.loads(pathlib.Path("ci-output/manifest.json").read_text()) + prompts = list(pathlib.Path("ci-output/prompts").glob("*.json")) + findings = json.loads( + pathlib.Path("ci-output/programmatic_findings.json").read_text() + ) + + problems = [] + if not manifest["dry_run"]: + problems.append("manifest says this was not a dry run") + if manifest["total_input_tokens"] or manifest["total_output_tokens"]: + problems.append("a dry run consumed tokens — an API call escaped") + if not manifest["prompts_dry_run"]: + problems.append("no prompts were generated") + if not findings: + problems.append("programmatic checkers found nothing") + if len(prompts) != len(manifest["prompts_dry_run"]): + problems.append( + f"{len(prompts)} prompt files vs " + f"{len(manifest['prompts_dry_run'])} in manifest" + ) + + if problems: + for p in problems: + print(f"::error::{p}") + sys.exit(1) + + print( + f"OK — {len(manifest['prompts_dry_run'])} prompts generated, " + f"{len(manifest['prompts_skipped'])} skipped, " + f"{len(findings)} programmatic findings" + ) + PY + + # index.html carries all of the front-end logic inline, so a syntax error + # there ships a broken page with nothing else to catch it. + - name: index.html JavaScript parses + run: | + python3 - <<'PY' + import pathlib, re + html = pathlib.Path("index.html").read_text(encoding="utf-8", errors="replace") + blocks = re.findall(r"<script[^>]*>(.*?)</script>", html, re.DOTALL) + assert blocks, "no <script> blocks found in index.html" + pathlib.Path("/tmp/inline.js").write_text("\n".join(blocks), encoding="utf-8") + print(f"extracted {len(blocks)} script block(s)") + PY + node --check /tmp/inline.js + + docker: + name: Image builds and serves + runs-on: ubuntu-latest + timeout-minutes: 15 + steps: + - uses: actions/checkout@v7 + + - name: Build image + run: docker build -t va-dat:ci . + + # No API key is provided, so the audit runs in dry-run mode: programmatic + # checks only, no LLM calls, nothing billable. + - name: Start container + run: | + docker run -d --name va-dat-ci -p 8000:8000 \ + --tmpfs /tmp:size=512m --read-only va-dat:ci + + - name: Wait for healthcheck + run: | + for i in $(seq 1 30); do + status=$(docker inspect -f '{{.State.Health.Status}}' va-dat-ci) + echo "attempt $i: $status" + [ "$status" = "healthy" ] && exit 0 + [ "$status" = "unhealthy" ] && break + sleep 2 + done + echo "::error::container never became healthy" + docker logs va-dat-ci + exit 1 + + - name: Serves the site + run: | + code=$(curl -s -o /dev/null -w '%{http_code}' http://localhost:8000/) + [ "$code" = "200" ] || { echo "::error::GET / returned $code"; exit 1; } + code=$(curl -s -o /dev/null -w '%{http_code}' http://localhost:8000/styles.css) + [ "$code" = "200" ] || { echo "::error::GET /styles.css returned $code"; exit 1; } + + - name: Audit endpoint returns a usable NDJSON stream + run: | + curl -s -D headers.txt -X POST http://localhost:8000/api/audit \ + -H 'Content-Type: application/json' \ + -d '{"html_content":"<html><head><title>CIclick here"}' \ + -o body.ndjson + + grep -qi 'application/x-ndjson' headers.txt || { + echo "::error::expected an NDJSON content type"; cat headers.txt; exit 1; } + + python3 - <<'PY' + import json, pathlib, sys + + lines = [ + json.loads(l) + for l in pathlib.Path("body.ndjson").read_text().splitlines() + if l.strip() + ] + results = [l for l in lines if l.get("type") == "result"] + progress = [l for l in lines if l.get("type") == "progress"] + + problems = [] + if len(results) != 1: + problems.append(f"expected exactly 1 result event, got {len(results)}") + if not progress: + problems.append("no progress events — the stream is not streaming") + if results: + r = results[0] + if not r.get("success"): + problems.append(f"audit failed: {r.get('error')}") + if not r["summary"]["dry_run"]: + problems.append("ran with an API key — CI must never bill an account") + if not r.get("programmatic_findings"): + problems.append("no programmatic findings returned") + + if problems: + for p in problems: + print(f"::error::{p}") + sys.exit(1) + + print( + f"OK — {len(progress)} progress events, " + f"{len(results[0]['programmatic_findings'])} findings" + ) + PY + + - name: Container logs + if: always() + run: docker logs va-dat-ci || true + + - name: Stop container + if: always() + run: docker rm -f va-dat-ci || true diff --git a/.github/workflows/publish.yml b/.github/workflows/publish.yml new file mode 100644 index 0000000..5e1f52f --- /dev/null +++ b/.github/workflows/publish.yml @@ -0,0 +1,123 @@ +name: Publish Image + +# Builds the application image and pushes it to GHCR so Coolify pulls a +# finished image instead of building on the deployment host, then triggers the +# deployment once the push has completed. + +on: + push: + branches: [main] + workflow_dispatch: + +concurrency: + group: publish-${{ github.ref }} + cancel-in-progress: true + +env: + # Must be lowercase — GHCR rejects mixed-case image names, and the org is "C4G". + IMAGE_BASE: ghcr.io/c4g/va-dat + +jobs: + publish: + runs-on: ubuntu-latest + permissions: + contents: read + packages: write + + steps: + - uses: actions/checkout@v7 + + - uses: docker/setup-buildx-action@v4 + + - uses: docker/login-action@v4 + with: + registry: ghcr.io + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Build and push + uses: docker/build-push-action@v7 + with: + context: . + push: true + tags: | + ${{ env.IMAGE_BASE }}:latest + ${{ env.IMAGE_BASE }}:${{ github.sha }} + cache-from: type=gha + cache-to: type=gha,mode=max + + # Deploy only what has been shown to start and serve. CI runs on pull + # requests, so a merge commit itself is never exercised before this point. + # No API key is supplied, so the audit runs in dry-run mode and bills + # nothing. + - name: Smoke test the published image + run: | + docker run -d --name va-dat-smoke -p 8000:8000 \ + --tmpfs /tmp:size=512m --read-only "${IMAGE_BASE}:${GITHUB_SHA}" + + healthy= + for i in $(seq 1 30); do + status=$(docker inspect -f '{{.State.Health.Status}}' va-dat-smoke) + echo "attempt $i: $status" + if [ "$status" = "healthy" ]; then healthy=1; break; fi + if [ "$status" = "unhealthy" ]; then break; fi + sleep 2 + done + + if [ "$healthy" != "1" ]; then + echo "::error::published image never became healthy" + docker logs va-dat-smoke + exit 1 + fi + + code=$(curl -s -o /dev/null -w '%{http_code}' http://localhost:8000/) + [ "$code" = "200" ] || { echo "::error::GET / returned $code"; exit 1; } + + curl -s -X POST http://localhost:8000/api/audit \ + -H 'Content-Type: application/json' \ + -d '{"html_content":"smoke"}' \ + -o body.ndjson + + python3 - <<'PY' + import json, pathlib, sys + lines = [json.loads(l) for l in + pathlib.Path("body.ndjson").read_text().splitlines() if l.strip()] + results = [l for l in lines if l.get("type") == "result"] + if len(results) != 1 or not results[0].get("success"): + print("::error::published image did not return a successful audit") + sys.exit(1) + if not results[0]["summary"]["dry_run"]: + print("::error::image ran with an API key — it must not carry credentials") + sys.exit(1) + print(f"OK — {len(results[0]['programmatic_findings'])} findings") + PY + + - name: Stop smoke test container + if: always() + run: docker rm -f va-dat-smoke || true + + - name: Summary + run: | + { + echo "### Image published" + echo '' + echo '```' + echo "${IMAGE_BASE}:latest" + echo "${IMAGE_BASE}:${GITHUB_SHA}" + echo '```' + } >> "$GITHUB_STEP_SUMMARY" + + # Deploying from here (rather than letting Coolify redeploy on git push) + # avoids a race where Coolify pulls `:latest` before this workflow has + # finished pushing it. Skipped automatically until the secret exists. + # The secret is surfaced through `env` because the `secrets` context is + # not available in a step-level `if:`. + - name: Trigger Coolify deployment + env: + COOLIFY_TOKEN: ${{ secrets.COOLIFY_TOKEN }} + COOLIFY_APP_UUID: ${{ vars.COOLIFY_APP_UUID }} + if: ${{ env.COOLIFY_TOKEN != '' && env.COOLIFY_APP_UUID != '' }} + run: | + curl -fsS -X GET \ + "https://coolify.c4g.dev/api/v1/deploy?uuid=${COOLIFY_APP_UUID}" \ + -H "Authorization: Bearer ${COOLIFY_TOKEN}" diff --git a/.gitignore b/.gitignore index da2969c..51e9796 100644 --- a/.gitignore +++ b/.gitignore @@ -208,3 +208,6 @@ __marimo__/ # Pipeline output output/ + +# CI smoke-test output +ci-output/ From b3a142cfd0c1255c05e3477884d6b788c8212e90 Mon Sep 17 00:00:00 2001 From: Justin McLellan Date: Thu, 6 Aug 2026 23:36:55 -0500 Subject: [PATCH 7/8] docs: update README and CLAUDE.md for the current architecture MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Both had drifted far enough to mislead. CLAUDE.md described a venv/pip setup, told contributors not to add JavaScript to a site that is now ~700 lines of inline JS, and made no mention of api_server.py, Docker, Coolify or uv. Documents what exists now: the uv workflow, the web app and its NDJSON contract, the deployment path, and CI. Records two failure modes that cost real money during this work — a 'dry run' still spends if a key resolves from .env (sending api_key: "" does not force one), and compose interpolation of ${ANTHROPIC_API_KEY:-} reads the host's .env. README gains Running the Web App, Deployment and CI sections, and its structure tree now matches the repository. Co-Authored-By: Claude Opus 5 (1M context) --- CLAUDE.md | 117 ++++++++++++++---------- README.md | 135 +++++++++++++++++++++++----- docs/modular-prompts-plan.md | 4 +- processing_scripts/docs/pipeline.md | 2 +- 4 files changed, 188 insertions(+), 70 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index ecf9ef7..4301431 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -13,83 +13,106 @@ The system has three planned stages: ``` project-root/ -├── index.html # Team/project website (served via GitHub Pages) -├── styles.css # Website styles +├── index.html # Web UI + team site (served by api_server.py) +├── styles.css +├── entry_points/ +│ ├── api_server.py # HTTP server: static site + /api/* audit endpoints +│ ├── run_pipeline.py # CLI pipeline orchestrator +│ └── generate_report.py # Pipeline output → unified CSV ├── processing_scripts/ │ ├── llm/ # Modular prompt system -│ │ ├── registry.py # PromptSpec dataclass + PROMPT_REGISTRY (21 specs) -│ │ ├── slicers.py # Payload slicer functions (one per prompt) -│ │ ├── templates.py # Prompt .txt parser + {payload} filler -│ │ ├── semantic_checklist_01.txt # 7 prompts for semantic structure (CL01) -│ │ ├── forms_checklist_02.txt # 6 prompts for forms (CL02) -│ │ └── nontext_checklist_03.txt # 8 prompts for non-text content (CL03) +│ │ ├── registry.py # PromptSpec dataclass + PROMPT_REGISTRY +│ │ ├── slicers.py # Payload slicer functions (one per prompt) +│ │ ├── filters.py # Pass-1 payload filters +│ │ ├── templates.py # Prompt .txt parser + {payload} filler +│ │ └── *_checklist_0*.txt # Prompt templates (CL01/CL02/CL03) │ ├── llm_preprocessing/ # HTML → structured JSON extractors -│ │ ├── semantic_checklist_01.py # CL01 extractor -│ │ ├── forms_checklist_02.py # CL02 extractor -│ │ └── nontext_checklist_03.py # CL03 extractor -│ └── programmatic/ # Rule-based checks (no API needed) -│ └── semantic_checklist_01.py # Missing alt, duplicate IDs, etc. -├── entry_points/ -│ ├── run_pipeline.py # Full pipeline orchestrator -│ ├── generate_report.py # JSON → CSV report generator -│ └── get_visionaid_home.py # HTML downloader -├── test_files/ # HTML files to analyze (may be very large, 500K+ tokens) -└── docs/ - └── modular-prompts-plan.md # Architecture plan +│ ├── programmatic/ # Rule-based checks (no API needed) +│ └── llm_client/ # Provider client (Anthropic/OpenAI/Gemini) +├── vision_aid/ingestion/ +│ ├── file_crawler.py # fetch_page / fetch_pages_nested (used by the server) +│ └── pull_html.py # Standalone HTML download helper +├── Dockerfile # Multi-stage uv build → runtime image +├── docker-compose.yml # Local run; Coolify deploys the image directly +├── DEPLOY.md # Coolify deployment notes (proxy settings matter) +├── .github/workflows/ +│ ├── ci.yml # On PR to main: deps, imports, pipeline, image smoke +│ └── publish.yml # On push to main: build → GHCR → trigger Coolify +├── test_files/ # HTML inputs (may be very large, 500K+ tokens) +└── docs/modular-prompts-plan.md ``` -## Website (GitHub Pages) +## Environment & Dependencies -The team project website lives at the repo root (`index.html` + `styles.css`). It is a pure HTML5/CSS3 static site with no build tools or JavaScript frameworks — served directly via GitHub Pages from the main branch root. +This project uses **uv**. There is no `pip install` step and no hand-managed `venv`. -- Design: DM Serif Display + DM Sans, teal/amber palette, fully responsive -- Accessibility: skip link, semantic HTML, ARIA landmarks, WCAG AA contrast -- Lighthouse scores (last measured): Performance 92 · Accessibility 96 · Best Practices 100 · SEO 100 -- Do not add JavaScript or external CSS frameworks to the website +```bash +uv sync # create .venv and install from uv.lock +uv run python