This is an AI generated script to review DPDK patches against the AGENTS.md coding guidelines using AI language models.
Supported AI providers: - Anthropic Claude (default) - OpenAI ChatGPT - xAI Grok - Google Gemini The script reads a patch file and the AGENTS.md guidelines, then submits them to the selected AI provider for review. Results are organized by severity level (Error, Warning, Info) as defined in the guidelines. Features: - Provider selection via -p/--provider option - Custom model selection via -m/--model option - Verbose mode shows token usage statistics - Uses temporary files for API requests to handle large patches - Prompt caching support for Anthropic to reduce costs Usage: ./devtools/analyze-patch.py 0001-net-ixgbe-fix-something.patch ./devtools/analyze-patch.py -p xai my-patch.patch ./devtools/analyze-patch.py -l # list providers Requires the appropriate API key environment variable to be set for the chosen provider (ANTHROPIC_API_KEY, OPENAI_API_KEY, XAI_API_KEY, or GOOGLE_API_KEY). Signed-off-by: Stephen Hemminger <[email protected]> --- devtools/analyze-patch.py | 1323 +++++++++++++++++++++++++++++++++++++ 1 file changed, 1323 insertions(+) create mode 100755 devtools/analyze-patch.py diff --git a/devtools/analyze-patch.py b/devtools/analyze-patch.py new file mode 100755 index 0000000000..a2292b9516 --- /dev/null +++ b/devtools/analyze-patch.py @@ -0,0 +1,1323 @@ +#!/usr/bin/env python3 +# SPDX-License-Identifier: BSD-3-Clause +# Copyright(c) 2026 Stephen Hemminger + +""" +Analyze DPDK patches using AI providers. + +Supported providers: Anthropic Claude, OpenAI ChatGPT, xAI Grok, Google Gemini +""" + +import argparse +import json +import os +import re +import subprocess +import sys +import tempfile +from datetime import date +from email.message import EmailMessage +from pathlib import Path +from typing import Iterator +from urllib.request import Request, urlopen +from urllib.error import URLError, HTTPError + +# Output formats +OUTPUT_FORMATS = ["text", "markdown", "html", "json"] + +# Large file handling modes +LARGE_FILE_MODES = ["error", "truncate", "chunk", "commits-only", "summary"] + +# Approximate tokens per character (conservative estimate for code) +CHARS_PER_TOKEN = 3.5 + +# Default token limits by provider (leaving room for system prompt and response) +PROVIDER_INPUT_LIMITS = { + "anthropic": 180000, # 200K context, reserve for system/response + "openai": 115000, # 128K context for gpt-4o + "xai": 115000, # Assume similar to OpenAI + "google": 900000, # Gemini has 1M context +} + +# Provider configurations +PROVIDERS = { + "anthropic": { + "name": "Claude", + "endpoint": "https://api.anthropic.com/v1/messages";, + "default_model": "claude-sonnet-4-5-20250929", + "env_var": "ANTHROPIC_API_KEY", + }, + "openai": { + "name": "ChatGPT", + "endpoint": "https://api.openai.com/v1/chat/completions";, + "default_model": "gpt-4o", + "env_var": "OPENAI_API_KEY", + }, + "xai": { + "name": "Grok", + "endpoint": "https://api.x.ai/v1/chat/completions";, + "default_model": "grok-3", + "env_var": "XAI_API_KEY", + }, + "google": { + "name": "Gemini", + "endpoint": "https://generativelanguage.googleapis.com/v1beta/models";, + "default_model": "gemini-2.0-flash", + "env_var": "GOOGLE_API_KEY", + }, +} + +# Known LTS releases +LTS_RELEASES = {"23.11", "22.11", "21.11", "20.11", "19.11"} + +SYSTEM_PROMPT_BASE = """\ +You are an expert DPDK code reviewer. Analyze patches for compliance with \ +DPDK coding standards and contribution guidelines. Provide clear, actionable \ +feedback organized by severity (Error, Warning, Info) as defined in the \ +guidelines.""" + +LTS_RULES = """ +LTS (Long Term Stable) branch rules apply: +- Only bug fixes allowed, no new features +- No new APIs (experimental or stable) +- ABI must remain unchanged +- Backported fixes should reference the original commit with Fixes: tag +- Copyright years should reflect when the code was originally written +- Be conservative: reject changes that aren't clearly bug fixes""" + +FORMAT_INSTRUCTIONS = { + "text": """Provide your review in plain text format.""", + "markdown": """Provide your review in Markdown format with: +- Headers (##) for each severity level (Errors, Warnings, Info) +- Bullet points for individual issues +- Code blocks (```) for code references +- Bold (**) for emphasis on key points""", + "html": """Provide your review in HTML format with: +- <h2> tags for each severity level (Errors, Warnings, Info) +- <ul>/<li> for individual issues +- <pre><code> for code references +- <strong> for emphasis on key points +- Use appropriate semantic HTML tags +- Do NOT include <html>, <head>, or <body> tags - just the content""", + "json": """Provide your review in JSON format with this structure: +{ + "summary": "Brief one-line summary of the review", + "errors": [ + {"issue": "description", "location": "file:line", "suggestion": "fix"} + ], + "warnings": [ + {"issue": "description", "location": "file:line", "suggestion": "fix"} + ], + "info": [ + {"issue": "description", "location": "file:line", "suggestion": "fix"} + ], + "passed_checks": ["list of checks that passed"], + "overall_status": "PASS|WARN|FAIL" +} +Output ONLY valid JSON, no markdown code fences or other text.""", +} + +USER_PROMPT = """Please review the following DPDK patch file '{patch_name}' \ +against the AGENTS.md guidelines. Check for: + +1. Commit message format (subject line, body, tags) +2. License/copyright compliance +3. C coding style issues +4. API and documentation requirements +5. Any other guideline violations + +{format_instruction} + +--- PATCH CONTENT --- +""" + + +def error(msg): + """Print error message and exit.""" + print(f"Error: {msg}", file=sys.stderr) + sys.exit(1) + + +def get_git_config(key): + """Get a value from git config.""" + try: + result = subprocess.run( + ["git", "config", "--get", key], + capture_output=True, + text=True, + check=True, + ) + return result.stdout.strip() + except (subprocess.CalledProcessError, FileNotFoundError): + return None + + +def is_lts_release(release): + """Check if a release is an LTS release.""" + if not release: + return False + # Check for explicit -lts suffix or known LTS versions + if "-lts" in release.lower(): + return True + # Extract version number (e.g., "23.11" from "23.11.1") + version = release.split("-")[0] + base_version = ".".join(version.split(".")[:2]) + return base_version in LTS_RELEASES + + +def estimate_tokens(text): + """Estimate token count from text length.""" + return int(len(text) / CHARS_PER_TOKEN) + + +def split_mbox_patches(content): + """Split an mbox file into individual patches.""" + patches = [] + current_patch = [] + in_patch = False + + for line in content.split("\n"): + # Detect start of new message in mbox format + if line.startswith("From ") and ( + " Mon " in line + or " Tue " in line + or " Wed " in line + or " Thu " in line + or " Fri " in line + or " Sat " in line + or " Sun " in line + ): + if current_patch: + patches.append("\n".join(current_patch)) + current_patch = [line] + in_patch = True + elif in_patch: + current_patch.append(line) + + # Don't forget the last patch + if current_patch: + patches.append("\n".join(current_patch)) + + return patches if patches else [content] + + +def extract_commit_messages(content): + """Extract only commit messages from patch content.""" + patches = split_mbox_patches(content) + messages = [] + + for patch in patches: + lines = patch.split("\n") + msg_lines = [] + in_headers = True + in_body = False + found_subject = False + + for line in lines: + # Collect headers we care about + if in_headers: + if line.startswith("Subject:"): + msg_lines.append(line) + found_subject = True + elif line.startswith(("From:", "Date:")): + msg_lines.append(line) + elif line.startswith((" ", "\t")) and found_subject: + # Subject continuation + msg_lines.append(line) + elif line == "": + if found_subject: + in_headers = False + in_body = True + msg_lines.append("") + elif in_body: + # Stop at the diff + if line.startswith("---") and not line.startswith("----"): + break + if line.startswith("diff --git"): + break + msg_lines.append(line) + + if msg_lines: + messages.append("\n".join(msg_lines)) + + return "\n\n---\n\n".join(messages) + + +def truncate_content(content, max_tokens, provider): + """Truncate content to fit within token limit.""" + max_chars = int(max_tokens * CHARS_PER_TOKEN) + + if len(content) <= max_chars: + return content, False + + # Try to truncate at a reasonable boundary + truncated = content[:max_chars] + + # Find last complete diff hunk or patch boundary + last_diff = truncated.rfind("\ndiff --git") + last_patch = truncated.rfind("\nFrom ") + + if last_diff > max_chars * 0.5: + truncated = truncated[:last_diff] + elif last_patch > max_chars * 0.5: + truncated = truncated[:last_patch] + + truncated += "\n\n[... Content truncated due to size limits ...]\n" + return truncated, True + + +def chunk_content(content, max_tokens, provider) -> Iterator[tuple[str, int, int]]: + """Split content into chunks that fit within token limit. + + Yields tuples of (chunk_content, chunk_number, total_chunks). + """ + patches = split_mbox_patches(content) + + if len(patches) == 1: + # Single large patch - split by diff sections + yield from chunk_single_patch(content, max_tokens) + return + + # Multiple patches - group them to fit within limits + chunks = [] + current_chunk = [] + current_size = 0 + max_chars = int(max_tokens * CHARS_PER_TOKEN * 0.9) # 90% to leave margin + + for patch in patches: + patch_size = len(patch) + if current_size + patch_size > max_chars and current_chunk: + chunks.append("\n".join(current_chunk)) + current_chunk = [] + current_size = 0 + + if patch_size > max_chars: + # Single patch too large, truncate it + if current_chunk: + chunks.append("\n".join(current_chunk)) + current_chunk = [] + current_size = 0 + truncated, _ = truncate_content(patch, max_tokens * 0.9, provider) + chunks.append(truncated) + else: + current_chunk.append(patch) + current_size += patch_size + + if current_chunk: + chunks.append("\n".join(current_chunk)) + + total = len(chunks) + for i, chunk in enumerate(chunks, 1): + yield chunk, i, total + + +def chunk_single_patch(content, max_tokens) -> Iterator[tuple[str, int, int]]: + """Split a single large patch by diff sections.""" + max_chars = int(max_tokens * CHARS_PER_TOKEN * 0.9) + + # Extract header (everything before first diff) + first_diff = content.find("\ndiff --git") + if first_diff == -1: + # No diff sections, just truncate + truncated, _ = truncate_content(content, max_tokens * 0.9, "anthropic") + yield truncated, 1, 1 + return + + header = content[: first_diff + 1] + diff_content = content[first_diff + 1 :] + + # Split by diff sections + diffs = [] + current_diff = [] + for line in diff_content.split("\n"): + if line.startswith("diff --git") and current_diff: + diffs.append("\n".join(current_diff)) + current_diff = [] + current_diff.append(line) + if current_diff: + diffs.append("\n".join(current_diff)) + + # Group diffs into chunks + chunks = [] + current_chunk_diffs = [] + current_size = len(header) + + for diff in diffs: + diff_size = len(diff) + if current_size + diff_size > max_chars and current_chunk_diffs: + chunks.append(header + "\n".join(current_chunk_diffs)) + current_chunk_diffs = [] + current_size = len(header) + + if diff_size + len(header) > max_chars: + # Single diff too large + if current_chunk_diffs: + chunks.append(header + "\n".join(current_chunk_diffs)) + current_chunk_diffs = [] + truncated_diff = diff[: max_chars - len(header) - 100] + truncated_diff += "\n[... diff truncated ...]\n" + chunks.append(header + truncated_diff) + current_size = len(header) + else: + current_chunk_diffs.append(diff) + current_size += diff_size + + if current_chunk_diffs: + chunks.append(header + "\n".join(current_chunk_diffs)) + + total = len(chunks) + for i, chunk in enumerate(chunks, 1): + yield chunk, i, total + + +def get_summary_prompt(): + """Get prompt modifications for summary mode.""" + return """ +NOTE: This is a LARGE patch series. Provide a HIGH-LEVEL summary review only: +- Focus on overall architecture and design concerns +- Check commit message formatting across the series +- Identify any obvious policy violations +- Do NOT attempt detailed line-by-line code review +- Summarize the scope and purpose of the changes +""" + + +def format_combined_reviews(reviews, output_format, patch_name): + """Combine multiple chunk/patch reviews into a single output.""" + if output_format == "json": + combined = { + "patch_file": patch_name, + "sections": [ + {"label": label, "review": review} for label, review in reviews + ], + } + return json.dumps(combined, indent=2) + elif output_format == "html": + sections = [] + for label, review in reviews: + sections.append(f"<h2>{label}</h2>\n{review}") + return "\n<hr>\n".join(sections) + elif output_format == "markdown": + sections = [] + for label, review in reviews: + sections.append(f"## {label}\n\n{review}") + return "\n\n---\n\n".join(sections) + else: # text + sections = [] + for label, review in reviews: + sections.append(f"=== {label} ===\n\n{review}") + return "\n\n" + "=" * 60 + "\n\n".join(sections) + + +def build_system_prompt(review_date, release): + """Build system prompt with date and release context.""" + prompt = SYSTEM_PROMPT_BASE + prompt += f"\n\nCurrent date: {review_date}." + + if release: + prompt += f"\nTarget DPDK release: {release}." + if is_lts_release(release): + prompt += LTS_RULES + else: + prompt += "\nThis is a main branch or standard release." + prompt += "\nNew features and experimental APIs are allowed." + + return prompt + + +def build_anthropic_request( + model, + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format="text", +): + """Build request payload for Anthropic API.""" + format_instruction = FORMAT_INSTRUCTIONS.get(output_format, "") + user_prompt = USER_PROMPT.format( + patch_name=patch_name, format_instruction=format_instruction + ) + return { + "model": model, + "max_tokens": max_tokens, + "system": [ + {"type": "text", "text": system_prompt}, + { + "type": "text", + "text": agents_content, + "cache_control": {"type": "ephemeral"}, + }, + ], + "messages": [ + { + "role": "user", + "content": user_prompt + patch_content, + } + ], + } + + +def build_openai_request( + model, + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format="text", +): + """Build request payload for OpenAI-compatible APIs.""" + format_instruction = FORMAT_INSTRUCTIONS.get(output_format, "") + user_prompt = USER_PROMPT.format( + patch_name=patch_name, format_instruction=format_instruction + ) + return { + "model": model, + "max_tokens": max_tokens, + "messages": [ + {"role": "system", "content": system_prompt}, + {"role": "system", "content": agents_content}, + { + "role": "user", + "content": user_prompt + patch_content, + }, + ], + } + + +def build_google_request( + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format="text", +): + """Build request payload for Google Gemini API.""" + format_instruction = FORMAT_INSTRUCTIONS.get(output_format, "") + user_prompt = USER_PROMPT.format( + patch_name=patch_name, format_instruction=format_instruction + ) + return { + "contents": [ + {"role": "user", "parts": [{"text": system_prompt}]}, + {"role": "user", "parts": [{"text": agents_content}]}, + { + "role": "user", + "parts": [{"text": user_prompt + patch_content}], + }, + ], + "generationConfig": {"maxOutputTokens": max_tokens}, + } + + +def call_api( + provider, + api_key, + model, + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format="text", + verbose=False, +): + """Make API request to the specified provider.""" + config = PROVIDERS[provider] + + # Build request based on provider + if provider == "anthropic": + request_data = build_anthropic_request( + model, + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format, + ) + headers = { + "Content-Type": "application/json", + "x-api-key": api_key, + "anthropic-version": "2023-06-01", + } + url = config["endpoint"] + elif provider == "google": + request_data = build_google_request( + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format, + ) + headers = {"Content-Type": "application/json"} + url = f"{config['endpoint']}/{model}:generateContent?key={api_key}" + else: # openai, xai + request_data = build_openai_request( + model, + max_tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + output_format, + ) + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {api_key}", + } + url = config["endpoint"] + + # Make request + request_body = json.dumps(request_data).encode("utf-8") + req = Request(url, data=request_body, headers=headers, method="POST") + + try: + with urlopen(req) as response: + result = json.loads(response.read().decode("utf-8")) + except HTTPError as e: + error_body = e.read().decode("utf-8") + try: + error_data = json.loads(error_body) + error(f"API error: {error_data.get('error', error_body)}") + except json.JSONDecodeError: + error(f"API error ({e.code}): {error_body}") + except URLError as e: + error(f"Connection error: {e.reason}") + + # Show verbose info + if verbose: + print("=== Token Usage ===", file=sys.stderr) + if provider == "anthropic": + usage = result.get("usage", {}) + print(f"Input tokens: {usage.get('input_tokens', 'N/A')}", file=sys.stderr) + print( + f"Cache creation: {usage.get('cache_creation_input_tokens', 0)}", + file=sys.stderr, + ) + print( + f"Cache read: {usage.get('cache_read_input_tokens', 0)}", + file=sys.stderr, + ) + print( + f"Output tokens: {usage.get('output_tokens', 'N/A')}", file=sys.stderr + ) + elif provider == "google": + usage = result.get("usageMetadata", {}) + print( + f"Prompt tokens: {usage.get('promptTokenCount', 'N/A')}", + file=sys.stderr, + ) + print( + f"Output tokens: {usage.get('candidatesTokenCount', 'N/A')}", + file=sys.stderr, + ) + else: # openai, xai + usage = result.get("usage", {}) + print( + f"Prompt tokens: {usage.get('prompt_tokens', 'N/A')}", file=sys.stderr + ) + print( + f"Completion tokens: {usage.get('completion_tokens', 'N/A')}", + file=sys.stderr, + ) + print("===================", file=sys.stderr) + + # Extract response text + if provider == "anthropic": + if "error" in result: + error(f"API error: {result['error'].get('message', result)}") + content = result.get("content", []) + return "".join( + block.get("text", "") for block in content if block.get("type") == "text" + ) + elif provider == "google": + if "error" in result: + error(f"API error: {result['error'].get('message', result)}") + candidates = result.get("candidates", []) + if not candidates: + error("No response from Gemini") + parts = candidates[0].get("content", {}).get("parts", []) + return "".join(part.get("text", "") for part in parts) + else: # openai, xai + if "error" in result: + error(f"API error: {result['error'].get('message', result)}") + choices = result.get("choices", []) + if not choices: + error("No response from API") + return choices[0].get("message", {}).get("content", "") + + +def get_last_message_id(patch_content): + """Extract Message-ID from the last patch in an mbox.""" + msg_ids = re.findall( + r"^Message-I[Dd]:\s*(.+)$", patch_content, re.MULTILINE | re.IGNORECASE + ) + if msg_ids: + msg_id = msg_ids[-1].strip() + # Normalize: remove < > and add them back + msg_id = msg_id.strip("<>") + return f"<{msg_id}>" + return None + + +def get_last_subject(patch_content): + """Extract subject from the last patch in an mbox.""" + # Find all Subject lines with potential continuations + subjects = [] + lines = patch_content.split("\n") + i = 0 + while i < len(lines): + if lines[i].lower().startswith("subject:"): + subject = lines[i][8:].strip() + i += 1 + # Handle continuation lines + while i < len(lines) and lines[i].startswith((" ", "\t")): + subject += lines[i].strip() + i += 1 + subjects.append(subject) + else: + i += 1 + return subjects[-1] if subjects else None + + +def send_email( + to_addrs, cc_addrs, from_addr, subject, in_reply_to, body, dry_run=False +): + """Send review email using git send-email, sendmail, or msmtp.""" + msg = EmailMessage() + msg["From"] = from_addr + msg["To"] = ", ".join(to_addrs) + if cc_addrs: + msg["Cc"] = ", ".join(cc_addrs) + msg["Subject"] = subject + if in_reply_to: + msg["In-Reply-To"] = in_reply_to + msg["References"] = in_reply_to + msg.set_content(body) + + email_text = msg.as_string() + + if dry_run: + print("=== Email Preview (dry-run) ===", file=sys.stderr) + print(email_text, file=sys.stderr) + print("=== End Preview ===", file=sys.stderr) + return True + + # Write to temp file for git send-email + with tempfile.NamedTemporaryFile(mode="w", suffix=".eml", delete=False) as f: + f.write(email_text) + temp_file = f.name + + try: + # Try git send-email first + if get_git_config("sendemail.smtpserver"): + # Build command with all arguments + flat_cmd = ["git", "send-email", "--confirm=never", "--quiet"] + for addr in to_addrs: + flat_cmd.extend(["--to", addr]) + for addr in cc_addrs: + flat_cmd.extend(["--cc", addr]) + if from_addr: + flat_cmd.extend(["--from", from_addr]) + if in_reply_to: + flat_cmd.extend(["--in-reply-to", in_reply_to]) + flat_cmd.append(temp_file) + + try: + subprocess.run(flat_cmd, check=True, capture_output=True) + print("Email sent via git send-email", file=sys.stderr) + return True + except (subprocess.CalledProcessError, FileNotFoundError): + pass + + # Try sendmail + try: + subprocess.run( + ["sendmail", "-t"], + input=email_text, + text=True, + capture_output=True, + check=True, + ) + print("Email sent via sendmail", file=sys.stderr) + return True + except (subprocess.CalledProcessError, FileNotFoundError): + pass + + # Try msmtp + try: + subprocess.run( + ["msmtp", "-t"], + input=email_text, + text=True, + capture_output=True, + check=True, + ) + print("Email sent via msmtp", file=sys.stderr) + return True + except (subprocess.CalledProcessError, FileNotFoundError): + pass + + error("Could not send email. Configure git send-email, sendmail, or msmtp.") + + finally: + os.unlink(temp_file) + + +def list_providers(): + """Print available providers and exit.""" + print("Available AI Providers:\n") + print(f"{'Provider':<12} {'Default Model':<30} {'API Key Variable'}") + print(f"{'--------':<12} {'-------------':<30} {'----------------'}") + for name, config in PROVIDERS.items(): + print(f"{name:<12} {config['default_model']:<30} {config['env_var']}") + sys.exit(0) + + +def main(): + parser = argparse.ArgumentParser( + description="Analyze DPDK patches using AI providers", + formatter_class=argparse.RawDescriptionHelpFormatter, + epilog=""" +Examples: + %(prog)s patch.patch # Review with default settings + %(prog)s -p openai my-patch.patch # Use OpenAI ChatGPT + %(prog)s -f markdown patch.patch # Output as Markdown + %(prog)s -f json -o review.json patch.patch # Save JSON to file + %(prog)s -f html -o review.html patch.patch # Save HTML to file + %(prog)s -r 24.11 patch.patch # Review for specific release + %(prog)s -r 23.11-lts patch.patch # Review for LTS branch + %(prog)s --send-email --to [email protected] series.mbox + %(prog)s --send-email --to [email protected] --dry-run series.mbox + +Large File Handling: + %(prog)s --split-patches series.mbox # Review each patch separately + %(prog)s --split-patches --patch-range 1-5 series.mbox # Review patches 1-5 + %(prog)s --large-file=truncate patch.mbox # Truncate to fit limit + %(prog)s --large-file=commits-only series.mbox # Review commit messages only + %(prog)s --large-file=summary series.mbox # High-level summary only + %(prog)s --large-file=chunk series.mbox # Split and review in chunks + +Large File Modes: + error - Fail with error (default) + truncate - Truncate content to fit token limit + chunk - Split into chunks and review each + commits-only - Extract and review only commit messages + summary - Request high-level summary review + +LTS Releases: + Use -r/--release with LTS version (e.g., 23.11-lts, 22.11) to enable + stricter review rules: bug fixes only, no new features or APIs. + """, + ) + + parser.add_argument("patch_file", nargs="?", help="Patch file to analyze") + parser.add_argument( + "-p", + "--provider", + choices=PROVIDERS.keys(), + default="anthropic", + help="AI provider (default: anthropic)", + ) + parser.add_argument( + "-a", + "--agents", + default="AGENTS.md", + help="Path to AGENTS.md file (default: AGENTS.md)", + ) + parser.add_argument( + "-m", + "--model", + help="Model to use (default: provider-specific)", + ) + parser.add_argument( + "-t", + "--tokens", + type=int, + default=4096, + help="Max tokens for response (default: 4096)", + ) + parser.add_argument( + "-v", + "--verbose", + action="store_true", + help="Show API request details", + ) + parser.add_argument( + "-f", + "--format", + choices=OUTPUT_FORMATS, + default="text", + dest="output_format", + help="Output format: text, markdown, html, json (default: text)", + ) + parser.add_argument( + "-o", + "--output", + metavar="FILE", + help="Write output to file instead of stdout", + ) + parser.add_argument( + "-l", + "--list-providers", + action="store_true", + help="List available providers and exit", + ) + + # Date and release options + parser.add_argument( + "-D", + "--date", + metavar="YYYY-MM-DD", + help="Review date context (default: today)", + ) + parser.add_argument( + "-r", + "--release", + metavar="VERSION", + help="Target DPDK release (e.g., 24.11, 23.11-lts)", + ) + + # Large file handling options + large_group = parser.add_argument_group("Large File Handling") + large_group.add_argument( + "--large-file", + choices=LARGE_FILE_MODES, + default="error", + metavar="MODE", + help="How to handle large files: error (default), truncate, " + "chunk, commits-only, summary", + ) + large_group.add_argument( + "--max-tokens", + type=int, + metavar="N", + help="Max input tokens (default: provider-specific)", + ) + large_group.add_argument( + "--split-patches", + action="store_true", + help="Split mbox into individual patches and review each separately", + ) + large_group.add_argument( + "--patch-range", + metavar="N-M", + help="Review only patches N through M (1-indexed, use with --split-patches)", + ) + + # Email options + email_group = parser.add_argument_group("Email Options") + email_group.add_argument( + "--send-email", + action="store_true", + help="Send review via email", + ) + email_group.add_argument( + "--to", + action="append", + dest="to_addrs", + default=[], + metavar="ADDRESS", + help="Email recipient (can be specified multiple times)", + ) + email_group.add_argument( + "--cc", + action="append", + dest="cc_addrs", + default=[], + metavar="ADDRESS", + help="CC recipient (can be specified multiple times)", + ) + email_group.add_argument( + "--from", + dest="from_addr", + metavar="ADDRESS", + help="From address (default: from git config)", + ) + email_group.add_argument( + "--dry-run", + action="store_true", + help="Show email without sending", + ) + + args = parser.parse_args() + + if args.list_providers: + list_providers() + + # Check patch file is provided + if not args.patch_file: + parser.error("patch_file is required") + + # Get provider config + config = PROVIDERS[args.provider] + model = args.model or config["default_model"] + + # Get API key + api_key = os.environ.get(config["env_var"]) + if not api_key: + error(f"{config['env_var']} environment variable not set") + + # Validate files + agents_path = Path(args.agents) + if not agents_path.exists(): + error(f"AGENTS.md not found: {args.agents}") + + patch_path = Path(args.patch_file) + if not patch_path.exists(): + error(f"Patch file not found: {args.patch_file}") + + # Validate email options + if args.send_email and not args.to_addrs: + error("--send-email requires at least one --to address") + + # Get from address for email + from_addr = args.from_addr + if args.send_email and not from_addr: + git_name = get_git_config("user.name") + git_email = get_git_config("user.email") + if git_email: + from_addr = f"{git_name} <{git_email}>" if git_name else git_email + else: + error("No --from specified and git user.email not configured") + + # Determine review date + review_date = args.date or date.today().isoformat() + + # Build system prompt with date and release context + system_prompt = build_system_prompt(review_date, args.release) + + # Read files + agents_content = agents_path.read_text() + patch_content = patch_path.read_text() + patch_name = patch_path.name + + # Determine max tokens for this provider + max_input_tokens = args.max_tokens or PROVIDER_INPUT_LIMITS.get( + args.provider, 100000 + ) + + # Estimate token count + estimated_tokens = estimate_tokens(patch_content + agents_content) + + # Parse patch range if specified + patch_start, patch_end = None, None + if args.patch_range: + try: + if "-" in args.patch_range: + start, end = args.patch_range.split("-", 1) + patch_start = int(start) + patch_end = int(end) + else: + patch_start = patch_end = int(args.patch_range) + except ValueError: + error(f"Invalid --patch-range format: {args.patch_range}") + + # Handle --split-patches mode + if args.split_patches: + patches = split_mbox_patches(patch_content) + total_patches = len(patches) + + if total_patches == 1: + print( + f"Note: Only 1 patch found in mbox, --split-patches has no effect", + file=sys.stderr, + ) + else: + print( + f"Found {total_patches} patches in mbox", + file=sys.stderr, + ) + + # Apply patch range filter + if patch_start is not None: + if patch_start < 1 or patch_start > total_patches: + error( + f"Patch range start {patch_start} out of range (1-{total_patches})" + ) + if patch_end < patch_start or patch_end > total_patches: + error( + f"Patch range end {patch_end} out of range ({patch_start}-{total_patches})" + ) + patches = patches[patch_start - 1 : patch_end] + print( + f"Reviewing patches {patch_start}-{patch_end} ({len(patches)} patches)", + file=sys.stderr, + ) + + # Review each patch separately + all_reviews = [] + for i, patch in enumerate(patches, patch_start or 1): + patch_label = f"Patch {i}/{total_patches}" + print(f"\nReviewing {patch_label}...", file=sys.stderr) + + review_text = call_api( + args.provider, + api_key, + model, + args.tokens, + system_prompt, + agents_content, + patch, + f"{patch_name} ({patch_label})", + args.output_format, + args.verbose, + ) + all_reviews.append((patch_label, review_text)) + + # Combine reviews + review_text = format_combined_reviews( + all_reviews, args.output_format, patch_name + ) + + # Skip the normal API call + estimated_tokens = 0 # Bypass size check since we've already processed + + # Check if content is too large + is_large = estimated_tokens > max_input_tokens + + if is_large: + print( + f"Warning: Estimated {estimated_tokens:,} tokens exceeds limit of " + f"{max_input_tokens:,}", + file=sys.stderr, + ) + + if args.large_file == "error": + error( + f"Patch file too large ({estimated_tokens:,} tokens). " + f"Use --large-file=truncate|chunk|commits-only|summary to handle, " + f"or --split-patches to review patches individually." + ) + elif args.large_file == "truncate": + print("Truncating content to fit token limit...", file=sys.stderr) + patch_content, was_truncated = truncate_content( + patch_content, max_input_tokens, args.provider + ) + if was_truncated: + print("Content was truncated.", file=sys.stderr) + elif args.large_file == "commits-only": + print("Extracting commit messages only...", file=sys.stderr) + patch_content = extract_commit_messages(patch_content) + new_estimate = estimate_tokens(patch_content + agents_content) + print( + f"Reduced to ~{new_estimate:,} tokens (commit messages only)", + file=sys.stderr, + ) + if new_estimate > max_input_tokens: + patch_content, _ = truncate_content( + patch_content, max_input_tokens, args.provider + ) + elif args.large_file == "summary": + print("Using summary mode for large patch...", file=sys.stderr) + system_prompt += get_summary_prompt() + patch_content, _ = truncate_content( + patch_content, max_input_tokens, args.provider + ) + elif args.large_file == "chunk": + print("Processing in chunks...", file=sys.stderr) + all_reviews = [] + for chunk, chunk_num, total_chunks in chunk_content( + patch_content, max_input_tokens, args.provider + ): + chunk_label = f"Chunk {chunk_num}/{total_chunks}" + print(f"Reviewing {chunk_label}...", file=sys.stderr) + + review_text = call_api( + args.provider, + api_key, + model, + args.tokens, + system_prompt, + agents_content, + chunk, + f"{patch_name} ({chunk_label})", + args.output_format, + args.verbose, + ) + all_reviews.append((chunk_label, review_text)) + + # Combine chunk reviews + review_text = format_combined_reviews( + all_reviews, args.output_format, patch_name + ) + + # Skip the normal single API call below + estimated_tokens = 0 + + if args.verbose: + print("=== Request ===", file=sys.stderr) + print(f"Provider: {args.provider}", file=sys.stderr) + print(f"Model: {model}", file=sys.stderr) + print(f"Review date: {review_date}", file=sys.stderr) + if args.release: + lts_status = " (LTS)" if is_lts_release(args.release) else "" + print(f"Target release: {args.release}{lts_status}", file=sys.stderr) + print(f"Output format: {args.output_format}", file=sys.stderr) + print(f"AGENTS file: {args.agents}", file=sys.stderr) + print(f"Patch file: {args.patch_file}", file=sys.stderr) + print(f"Estimated tokens: {estimated_tokens:,}", file=sys.stderr) + print(f"Max input tokens: {max_input_tokens:,}", file=sys.stderr) + if args.large_file != "error": + print(f"Large file mode: {args.large_file}", file=sys.stderr) + if args.split_patches: + print("Split patches: yes", file=sys.stderr) + if args.output: + print(f"Output file: {args.output}", file=sys.stderr) + if args.send_email: + print("Send email: yes", file=sys.stderr) + print(f"To: {', '.join(args.to_addrs)}", file=sys.stderr) + if args.cc_addrs: + print(f"Cc: {', '.join(args.cc_addrs)}", file=sys.stderr) + print(f"From: {from_addr}", file=sys.stderr) + print("===============", file=sys.stderr) + + # Call API (unless already processed via chunks/split) + if estimated_tokens > 0: # Not already processed + review_text = call_api( + args.provider, + api_key, + model, + args.tokens, + system_prompt, + agents_content, + patch_content, + patch_name, + args.output_format, + args.verbose, + ) + + if not review_text: + error(f"No response received from {args.provider}") + + # Format output based on requested format + provider_name = config["name"] + + if args.output_format == "json": + # For JSON, try to parse and add metadata + try: + review_data = json.loads(review_text) + except json.JSONDecodeError: + # If AI didn't return valid JSON, wrap the text + review_data = {"raw_review": review_text} + + output_data = { + "metadata": { + "patch_file": patch_name, + "provider": args.provider, + "provider_name": provider_name, + "model": model, + "review_date": review_date, + "target_release": args.release, + "is_lts": is_lts_release(args.release) if args.release else False, + }, + "review": review_data, + } + output_text = json.dumps(output_data, indent=2) + elif args.output_format == "html": + # Wrap HTML content with header + release_info = "" + if args.release: + lts_badge = " (LTS)" if is_lts_release(args.release) else "" + release_info = f"<br>Target release: {args.release}{lts_badge}" + output_text = f"""<!-- AI-generated review of {patch_name} --> +<!-- Reviewed using {provider_name} ({model}) on {review_date} --> +<div class="patch-review"> +<h1>Patch Review: {patch_name}</h1> +<p class="review-meta">Reviewed by {provider_name} ({model}) on {review_date}{release_info}</p> +{review_text} +</div> +""" + elif args.output_format == "markdown": + release_info = "" + if args.release: + lts_badge = " (LTS)" if is_lts_release(args.release) else "" + release_info = f"\n*Target release: {args.release}{lts_badge}*\n" + output_text = f"""# Patch Review: {patch_name} + +*Reviewed by {provider_name} ({model}) on {review_date}* +{release_info} +{review_text} +""" + else: # text + release_info = "" + if args.release: + lts_badge = " (LTS)" if is_lts_release(args.release) else "" + release_info = f"Target release: {args.release}{lts_badge}\n" + output_text = f"=== Patch Review: {patch_name} (via {provider_name}) ===\n" + output_text += f"Review date: {review_date}\n" + output_text += release_info + output_text += "\n" + review_text + + # Write output + if args.output: + Path(args.output).write_text(output_text) + print(f"Review written to: {args.output}", file=sys.stderr) + else: + print(output_text) + + # Send email if requested + if args.send_email: + # Email always uses plain text - warn if different format requested + if args.output_format != "text": + print( + f"Note: Email will be sent as plain text regardless of " + f"--format={args.output_format}", + file=sys.stderr, + ) + + in_reply_to = get_last_message_id(patch_content) + orig_subject = get_last_subject(patch_content) + + if orig_subject: + # Remove [PATCH n/m] prefix + review_subject = re.sub(r"^\[PATCH[^\]]*\]\s*", "", orig_subject) + review_subject = f"[REVIEW] {review_subject}" + else: + review_subject = f"[REVIEW] {patch_name}" + + # Build email body - always use plain text version + release_info = "" + if args.release: + lts_badge = " (LTS)" if is_lts_release(args.release) else "" + release_info = f"Target release: {args.release}{lts_badge}\n" + + email_body = f"""AI-generated review of {patch_name} +Reviewed using {provider_name} ({model}) on {review_date} +{release_info} +This is an automated review. Please verify all suggestions. + +--- + +{review_text} +""" + + if args.verbose: + print("", file=sys.stderr) + print("=== Email Details ===", file=sys.stderr) + print(f"Subject: {review_subject}", file=sys.stderr) + print(f"In-Reply-To: {in_reply_to}", file=sys.stderr) + print("=====================", file=sys.stderr) + + send_email( + args.to_addrs, + args.cc_addrs, + from_addr, + review_subject, + in_reply_to, + email_body, + args.dry_run, + ) + + if not args.dry_run: + print("", file=sys.stderr) + print(f"Review sent to: {', '.join(args.to_addrs)}", file=sys.stderr) + + +if __name__ == "__main__": + main() -- 2.51.0
