From 8550d0731bb35f53efe69501e01fbed89f0b8118 Mon Sep 17 00:00:00 2001 From: Ananya Bhat Date: Fri, 20 Jun 2025 20:18:27 +0530 Subject: [PATCH 1/8] Final --- .../.gitignore | 78 + .../CMakeLists.txt | 71 + .../README.md | 246 + .../docs/IMPLEMENTATION_GUIDE.md | 306 + .../include/BertTokenizer.h | 31 + .../include/GitHubFetcher.h | 41 + .../include/PRData.h | 30 + .../include/PRParser.h | 36 + .../include/ReviewerSuggester.h | 32 + .../models/vocab.txt | 30522 ++++++++++++++++ .../scripts/example_usage.sh | 66 + .../scripts/setup_macos.sh | 117 + .../src/BertTokenizer.cpp | 147 + .../src/GitHubFetcher.cpp | 360 + .../src/PRParser.cpp | 296 + .../src/ReviewerSuggester.cpp | 160 + .../src/main.cpp | 151 + 17 files changed, 32690 insertions(+) create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/.gitignore create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/CMakeLists.txt create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/README.md create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/docs/IMPLEMENTATION_GUIDE.md create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/include/BertTokenizer.h create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/include/GitHubFetcher.h create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/include/PRData.h create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/include/PRParser.h create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/include/ReviewerSuggester.h create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/models/vocab.txt create mode 100755 clang/tools/ai-powered-reviewer-suggestion-tool/scripts/example_usage.sh create mode 100755 clang/tools/ai-powered-reviewer-suggestion-tool/scripts/setup_macos.sh create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/src/BertTokenizer.cpp create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/src/GitHubFetcher.cpp create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/src/PRParser.cpp create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/src/ReviewerSuggester.cpp create mode 100644 clang/tools/ai-powered-reviewer-suggestion-tool/src/main.cpp diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/.gitignore b/clang/tools/ai-powered-reviewer-suggestion-tool/.gitignore new file mode 100644 index 0000000000000..6b43d3cafec18 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/.gitignore @@ -0,0 +1,78 @@ +# Build directories +build/ +bin/ +lib/ +cmake-build-*/ + +# Model files (too large for git) +models/*.onnx +models/*.bin +models/*.safetensors + +# Keep vocab.txt as it's small +!models/vocab.txt + +# IDE files +.vscode/ +.idea/ +*.swp +*.swo +*~ + +# macOS specific +.DS_Store +.AppleDouble +.LSOverride + +# Thumbnails +._* + +# Files that might appear in the root of a volume +.DocumentRevisions-V100 +.fseventsd +.Spotlight-V100 +.TemporaryItems +.Trashes +.VolumeIcon.icns +.com.apple.timemachine.donotpresent + +# Directories potentially created on remote AFP share +.AppleDB +.AppleDesktop +Network Trash Folder +Temporary Items +.apdisk + +# CMake +CMakeCache.txt +CMakeFiles/ +cmake_install.cmake +Makefile + +# Compiled Object files +*.o +*.obj + +# Executables +*.exe +*.out +*.app +reviewer-suggester + +# Debug files +*.dSYM/ +*.su +*.idb +*.pdb + +# Logs +*.log + +# Temporary files +*.tmp +*.temp + +# API tokens and secrets +.env +*.token +secrets.txt diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/CMakeLists.txt b/clang/tools/ai-powered-reviewer-suggestion-tool/CMakeLists.txt new file mode 100644 index 0000000000000..b0e1ea089e10c --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/CMakeLists.txt @@ -0,0 +1,71 @@ +cmake_minimum_required(VERSION 3.15) +project(reviewer-suggester C CXX) + +set(CMAKE_CXX_STANDARD 17) +set(CMAKE_CXX_STANDARD_REQUIRED ON) + +# Find required packages +find_package(LLVM REQUIRED CONFIG) +find_package(CURL REQUIRED) +find_package(nlohmann_json REQUIRED) + +# Find ONNX Runtime +find_path(ONNXRUNTIME_INCLUDE_DIR onnxruntime_cxx_api.h PATHS /opt/homebrew/include/onnxruntime /usr/local/include/onnxruntime) +find_library(ONNXRUNTIME_LIB onnxruntime PATHS /opt/homebrew/lib /usr/local/lib) + +if(NOT ONNXRUNTIME_INCLUDE_DIR OR NOT ONNXRUNTIME_LIB) + message(FATAL_ERROR "ONNX Runtime not found. Please install it via 'brew install onnxruntime'") +endif() + +message(STATUS "ONNX Runtime include: ${ONNXRUNTIME_INCLUDE_DIR}") +message(STATUS "ONNX Runtime library: ${ONNXRUNTIME_LIB}") + +# Include directories - THIS IS THE KEY FIX +include_directories(${LLVM_INCLUDE_DIRS}) +include_directories(${ONNXRUNTIME_INCLUDE_DIR}) +include_directories(${CMAKE_SOURCE_DIR}/include) # Add this line for your headers + +# Add definitions +add_definitions(${LLVM_DEFINITIONS}) + +# Source files +set(SOURCES + src/main.cpp + src/GitHubFetcher.cpp + src/PRParser.cpp + src/ReviewerSuggester.cpp + src/BertTokenizer.cpp +) + +# Header files (optional, for IDE support) +set(HEADERS + include/GitHubFetcher.h + include/PRParser.h + include/ReviewerSuggester.h + include/BertTokenizer.h + include/PRData.h # Add this line +) + +# Create executable +add_executable(reviewer-suggester ${SOURCES} ${HEADERS}) + +# Link libraries +target_link_libraries(reviewer-suggester + ${LLVM_LIBRARIES} + ${CURL_LIBRARIES} + nlohmann_json::nlohmann_json + ${ONNXRUNTIME_LIB} +) + +# Set output directory +set_target_properties(reviewer-suggester PROPERTIES + RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin +) + +# macOS specific settings +if(APPLE) + set_target_properties(reviewer-suggester PROPERTIES + MACOSX_RPATH TRUE + BUILD_RPATH "${ONNXRUNTIME_LIB}/.." + ) +endif() diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/README.md b/clang/tools/ai-powered-reviewer-suggestion-tool/README.md new file mode 100644 index 0000000000000..3d0896c1a0cd2 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/README.md @@ -0,0 +1,246 @@ +# AI-Powered Reviewer Suggestion Tool for OpenMP PRs + +A Clang-based CLI tool that automatically suggests the most relevant OpenMP reviewers for a given Pull Request using semantic analysis and machine learning. + +## Features + +- **Semantic Analysis**: Uses all-MiniLM-L6-v2 transformer model for deep understanding of PR content +- **File Similarity**: Analyzes changed files to find reviewers with relevant expertise +- **Historical Learning**: Learns from past PR review patterns in the LLVM OpenMP project +- **Fast Inference**: ONNX Runtime integration for efficient model execution +- **Clang Integration**: Built with LLVM/Clang infrastructure for robust C++ processing + + +## Requirements + +### System Requirements + +- Ubuntu 20.04 or later (or any modern Linux distribution) +- CMake 3.20+ +- C++17 compatible compiler (e.g., g++ 9+ or clang 10+) +- Python 3.7+ (for model/vocab download) + + +### Dependencies + +- LLVM/Clang development libraries +- ONNX Runtime +- libcurl for GitHub API requests +- nlohmann/json for JSON processing + +--- + +## Installation + +### 1. Install Dependencies + +```bash +# Update package lists +sudo apt update + +# Install build essentials and required packages +sudo apt install -y build-essential cmake curl wget git + +# Install LLVM and Clang (choose your preferred version, e.g., 18) +sudo apt install -y llvm-18 llvm-18-dev clang-18 libclang-18-dev + +# Install ONNX Runtime (CPU version) +sudo apt install -y libonnxruntime-dev + +# Install nlohmann-json +sudo apt install -y nlohmann-json-dev + +# Install libcurl +sudo apt install -y libcurl4-openssl-dev +``` +--- + +### 2. Download Model Files + +```bash +# Create models directory +mkdir -p models + +# Download the ONNX model (from HuggingFace) +wget -O models/all-MiniLM-L6-v2.onnx https://huggingface.co/onnx-models/all-MiniLM-L6-v2-onnx/resolve/main/model.onnx + +# Download vocabulary file +wget -O models/vocab.txt https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/resolve/main/vocab.txt +``` + + +--- + +### 3. Build the Project + +```bash +# Create build directory +mkdir build && cd build + +# Configure with CMake +cmake .. -DCMAKE_BUILD_TYPE=Release + +# Build the project +make -j$(nproc) +``` + +--- + +## Usage + +### Basic Usage + +```bash +# Get reviewer suggestions for PR #12345 +./bin/reviewer-suggester --pr 12345 --token YOUR_GITHUB_TOKEN + +# Specify custom model paths +./bin/reviewer-suggester \ + --pr 12345 \ + --token YOUR_GITHUB_TOKEN \ + --model-path ../models/all-MiniLM-L6-v2.onnx \ + --vocab-path ../models/vocab.txt +``` + +![Demo SS]("/ai-powered-reviewer-suggestion-tool/media/demo_ss.png") + +![Demo GIF]("/ai-powered-reviewer-suggestion-tool/media/demo.gif") + + +### Advanced Options + +```bash +# Customize the analysis +./bin/reviewer-suggester \ + --pr 12345 \ + --token YOUR_GITHUB_TOKEN \ + --max-pages 10 \ + --top-reviewers 10 +``` + + +### Command Line Options + +- `--pr `: Pull Request number to analyze (required) +- `--token `: GitHub API token (required) +- `--model-path `: Path to ONNX model file (default: models/all-MiniLM-L6-v2.onnx) +- `--vocab-path `: Path to vocabulary file (default: models/vocab.txt) +- `--max-pages `: Maximum pages of historical PRs to fetch (default: 5) +- `--top-reviewers `: Number of top reviewers to suggest (default: 5) + +--- + +## Getting a GitHub Token + +1. Go to GitHub Settings → Developer settings → Personal access tokens +2. Generate a new token with `repo` permissions +3. Copy the token and use it with the `--token` parameter + +--- + +## Example Output + +``` +=== Reviewer Suggestions for PR #12345 === +Title: Add support for OpenMP 5.1 task reductions +Files changed: 8 + +Top 5 Suggested Reviewers: +--------------------------------------- +1. jdenny-ornl (Similarity Score: 0.847) +2. AlexeySachkov (Similarity Score: 0.823) +3. jplehr (Similarity Score: 0.791) +4. tianshilei1992 (Similarity Score: 0.756) +5. dreachem (Similarity Score: 0.734) +``` + + +--- + +## Architecture + +### Components + +1. **GitHubFetcher**: Handles GitHub API communication +2. **BertTokenizer**: Custom C++ tokenizer for BERT-compatible text processing +3. **PRParser**: Processes PR data and generates embeddings using ONNX Runtime +4. **ReviewerSuggester**: Calculates similarity and ranks potential reviewers + +### Machine Learning Pipeline + +1. **Text Preprocessing**: Clean and tokenize PR titles and descriptions +2. **Embedding Generation**: Use all-MiniLM-L6-v2 to create 384-dimensional embeddings +3. **Similarity Calculation**: Combine semantic (cosine) and structural (Jaccard) similarity +4. **Ranking**: Score and rank reviewers based on historical review patterns + +--- + +## Model Details + +- **Model**: all-MiniLM-L6-v2 (ONNX format) +- **Embedding Dimension**: 384 +- **Max Sequence Length**: 256 tokens +- **Model Size**: ~80MB +- **Inference Speed**: ~10ms per PR on modern hardware + +--- + +## Troubleshooting + +### Common Issues + +1. **ONNX Runtime not found**: + +```bash +sudo apt install libonnxruntime-dev +export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH +``` + +2. **LLVM libraries not found**: + +```bash +sudo apt install llvm-18 llvm-18-dev clang-18 libclang-18-dev +export LLVM_DIR=/usr/lib/llvm-18 +``` + +3. **Model files missing**: + - Ensure model files are downloaded to the `models/` directory + - Check file permissions and paths + +### Debug Build + +For debugging issues: + +```bash +cmake .. -DCMAKE_BUILD_TYPE=Debug +make -j$(nproc) +``` + + +--- + +## Contributing + +1. Fork the repository +2. Create a feature branch +3. Make your changes +4. Add tests for new functionality +5. Submit a pull request + +--- + +## License + +This project is licensed under the Apache License 2.0 - see the LICENSE file for details. + +--- + +## Acknowledgments + +- LLVM OpenMP community for providing the dataset +- HuggingFace for the pre-trained all-MiniLM-L6-v2 model +- Microsoft for ONNX Runtime +- The sentence-transformers project for model architecture insights + +--- + diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/docs/IMPLEMENTATION_GUIDE.md b/clang/tools/ai-powered-reviewer-suggestion-tool/docs/IMPLEMENTATION_GUIDE.md new file mode 100644 index 0000000000000..37d548337c8ba --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/docs/IMPLEMENTATION_GUIDE.md @@ -0,0 +1,306 @@ +# Step-by-Step Implementation Guide + +## AI-Powered Reviewer Suggestion Tool for OpenMP PRs + +This guide walks you through setting up and running the AI-powered reviewer suggestion tool on macOS. + +### Prerequisites + +Before starting, ensure you have: +- macOS 10.15+ (Catalina or later) +- Admin access to install software +- Stable internet connection for downloading dependencies +- A GitHub account with access to LLVM repository + +### Step 1: System Preparation + +#### 1.1 Install Xcode Command Line Tools +```bash +xcode-select --install +``` +- This installs essential development tools including the C++ compiler +- Follow the on-screen prompts to complete installation +- Verify installation: `gcc --version` + +#### 1.2 Install Homebrew Package Manager +```bash +/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" +``` +- Follow the installation prompts +- For Apple Silicon Macs, add Homebrew to your PATH: +```bash +echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> ~/.zprofile +eval "$(/opt/homebrew/bin/brew shellenv)" +``` + +### Step 2: Install Dependencies + +#### 2.1 Install Core Dependencies +```bash +brew update +brew install cmake llvm curl nlohmann-json onnxruntime +``` + +**What each dependency does:** +- `cmake`: Build system generator +- `llvm`: LLVM/Clang development libraries for CLI integration +- `curl`: HTTP client for GitHub API requests +- `nlohmann-json`: JSON parsing library +- `onnxruntime`: Machine learning inference runtime + +#### 2.2 Verify Installations +```bash +cmake --version # Should show 3.20+ +llvm-config --version # Should show LLVM version +curl --version # Should show curl version +pkg-config --exists onnxruntime && echo "ONNX Runtime found" +``` + +### Step 3: Obtain GitHub API Token + +#### 3.1 Create Personal Access Token +1. Go to https://github.com/settings/tokens +2. Click "Generate new token (classic)" +3. Give it a descriptive name: "OpenMP Reviewer Tool" +4. Select scopes: `repo` (Full control of private repositories) +5. Click "Generate token" +6. **Important**: Copy the token immediately (you won't see it again) + +#### 3.2 Store Token Securely +```bash +# Option 1: Environment variable (recommended) +echo 'export GITHUB_TOKEN="your_token_here"' >> ~/.zprofile +source ~/.zprofile + +# Option 2: Use it directly in commands (less secure) +# We'll show this in the usage examples +``` + +### Step 4: Download and Prepare Model Files + +#### 4.1 Create Models Directory +```bash +mkdir -p models +cd models +``` + +#### 4.2 Download Model Files + +**Method 1: Using wget** +```bash +# Download ONNX model (~80MB) +wget -O all-MiniLM-L6-v2.onnx https://huggingface.co/onnx-models/all-MiniLM-L6-v2-onnx/resolve/main/model.onnx + +# Download vocabulary file (~230KB) +wget -O vocab.txt https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/resolve/main/vocab.txt +``` + +**Method 2: Using curl** +```bash +# Download ONNX model +curl -L -o all-MiniLM-L6-v2.onnx https://huggingface.co/onnx-models/all-MiniLM-L6-v2-onnx/resolve/main/model.onnx + +# Download vocabulary file +curl -L -o vocab.txt https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/resolve/main/vocab.txt +``` + +**Method 3: Manual Download** +1. Visit: https://huggingface.co/onnx-models/all-MiniLM-L6-v2-onnx +2. Download `model.onnx` and save as `all-MiniLM-L6-v2.onnx` +3. Visit: https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 +4. Download `vocab.txt` + +#### 4.3 Verify Model Files +```bash +ls -la models/ +# Should show: +# all-MiniLM-L6-v2.onnx (~80MB) +# vocab.txt (~230KB) +``` + +### Step 5: Build the Project + +#### 5.1 Create Build Directory +```bash +mkdir build +cd build +``` + +#### 5.2 Configure with CMake +```bash +cmake .. -DCMAKE_BUILD_TYPE=Release +``` + +**Troubleshooting CMake Issues:** +- If LLVM not found: `export LLVM_DIR=/opt/homebrew/opt/llvm` +- If ONNX Runtime not found: `export ONNXRUNTIME_ROOT=/opt/homebrew` + +#### 5.3 Compile the Project +```bash +make -j$(sysctl -n hw.ncpu) +``` +- This uses all available CPU cores for faster compilation +- Compilation should take 2-5 minutes depending on your system + +#### 5.4 Verify Build +```bash +ls -la bin/ +# Should show: reviewer-suggester (executable) + +# Test the executable +./bin/reviewer-suggester --help +``` + +### Step 6: Test the Tool + +#### 6.1 Quick Test Run +```bash +# Test with a known OpenMP PR (replace with actual token) +./bin/reviewer-suggester --pr 12345 --token "your_github_token_here" +``` + +#### 6.2 Understanding the Output +The tool will: +1. Fetch historical OpenMP PRs (may take 2-3 minutes) +2. Process PR content and generate embeddings +3. Calculate similarity scores +4. Output ranked reviewer suggestions + +**Example Output:** +``` +=== Reviewer Suggestions for PR #12345 === +Title: Add support for OpenMP 5.1 task reductions +Files changed: 8 + +Top 5 Suggested Reviewers: +--------------------------------------- +1. jdenny-ornl (Similarity Score: 0.847) +2. AlexeySachkov (Similarity Score: 0.823) +3. jplehr (Similarity Score: 0.791) +4. tianshilei1992 (Similarity Score: 0.756) +5. dreachem (Similarity Score: 0.734) +``` + +### Step 7: Advanced Usage + +#### 7.1 Customize Analysis Parameters +```bash +# Analyze more historical data +./bin/reviewer-suggester --pr 12345 --token "$GITHUB_TOKEN" --max-pages 10 + +# Get more reviewer suggestions +./bin/reviewer-suggester --pr 12345 --token "$GITHUB_TOKEN" --top-reviewers 10 + +# Use custom model paths +./bin/reviewer-suggester \ + --pr 12345 \ + --token "$GITHUB_TOKEN" \ + --model-path ../models/all-MiniLM-L6-v2.onnx \ + --vocab-path ../models/vocab.txt +``` + +#### 7.2 Performance Optimization +For faster repeated runs: +- The tool fetches historical data each time (for accuracy) +- Consider caching if running frequently on the same dataset +- Use `--max-pages 3` for faster testing with less historical data + +### Step 8: Troubleshooting Common Issues + +#### 8.1 Build Issues + +**Error: "LLVM not found"** +```bash +export LLVM_DIR=/opt/homebrew/opt/llvm +cmake .. -DCMAKE_BUILD_TYPE=Release +``` + +**Error: "ONNX Runtime not found"** +```bash +brew reinstall onnxruntime +export DYLD_LIBRARY_PATH=/opt/homebrew/lib:$DYLD_LIBRARY_PATH +``` + +**Error: "nlohmann/json not found"** +```bash +brew reinstall nlohmann-json +``` + +#### 8.2 Runtime Issues + +**Error: "curl_easy_perform() failed"** +- Check internet connection +- Verify GitHub token is valid +- Check if GitHub API rate limit is reached + +**Error: "Failed to load ONNX model"** +- Verify model file exists and is not corrupted +- Re-download the model file +- Check file permissions + +**Error: "Could not open vocabulary file"** +- Verify vocab.txt exists in models/ directory +- Check file permissions +- Re-download if necessary + +#### 8.3 GitHub API Issues + +**Rate Limiting:** +- GitHub API has rate limits (5000 requests/hour for authenticated users) +- Use `--max-pages` to reduce API calls during testing +- Wait if you hit the rate limit + +**Authentication Issues:** +- Ensure token has `repo` scope +- Token should start with `ghp_` (classic tokens) +- Check token hasn't expired + +### Step 9: Understanding the Algorithm + +#### 9.1 How It Works +1. **Data Collection**: Fetches historical OpenMP PRs from LLVM repository +2. **Text Processing**: Tokenizes PR titles and descriptions using BERT tokenizer +3. **Embedding Generation**: Creates 384-dimensional vectors using all-MiniLM-L6-v2 +4. **Similarity Calculation**: + - Semantic similarity (cosine similarity on embeddings): 70% weight + - File similarity (Jaccard similarity on changed files): 30% weight +5. **Reviewer Ranking**: Aggregates similarity scores for each potential reviewer + +#### 9.2 Model Details +- **Model**: all-MiniLM-L6-v2 (sentence transformer) +- **Input**: Text up to 256 tokens +- **Output**: 384-dimensional normalized embeddings +- **Inference Time**: ~10ms per PR on modern hardware +- **Memory Usage**: ~200MB for model + embeddings + +#### 9.3 Customization Opportunities +- Adjust similarity weights in `ReviewerSuggester::calculateSimilarity()` +- Modify tokenization in `BertTokenizer` class +- Add recency weighting based on PR creation dates +- Include additional features (PR size, commit patterns, etc.) + +### Step 10: Production Usage Tips + +#### 10.1 Best Practices +- Use environment variables for GitHub tokens +- Run with `--max-pages 5-10` for good balance of accuracy and speed +- Monitor GitHub API rate limits +- Keep model files updated + +#### 10.2 Integration Ideas +- Integrate with GitHub webhooks for automatic suggestions +- Add to CI/CD pipeline for PR analysis +- Create web interface for easier access +- Export suggestions to JSON for further processing + +#### 10.3 Maintenance +- Update ONNX Runtime periodically: `brew upgrade onnxruntime` +- Update LLVM: `brew upgrade llvm` +- Monitor HuggingFace for model updates +- Regularly test with new OpenMP PRs + +### Conclusion + +You now have a fully functional AI-powered reviewer suggestion tool! The system uses state-of-the-art NLP techniques to analyze PR content and suggest the most relevant reviewers based on historical patterns in the LLVM OpenMP project. + +For questions or issues, refer to the README.md or create an issue in the project repository. diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/include/BertTokenizer.h b/clang/tools/ai-powered-reviewer-suggestion-tool/include/BertTokenizer.h new file mode 100644 index 0000000000000..3e329cc540e39 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/include/BertTokenizer.h @@ -0,0 +1,31 @@ +#ifndef BERT_TOKENIZER_H +#define BERT_TOKENIZER_H + +#include +#include +#include + +class BertTokenizer { +public: + explicit BertTokenizer(const std::string& vocabPath); + + std::vector tokenize(const std::string& text); + +private: + std::unordered_map vocab; + std::vector id_to_token; + + // Special tokens + int64_t cls_token_id = 101; + int64_t sep_token_id = 102; + int64_t pad_token_id = 0; + int64_t unk_token_id = 100; + + void loadVocabulary(const std::string& vocabPath); + std::vector basicTokenize(const std::string& text); + std::vector wordpieceTokenize(const std::string& token); + std::string toLowerCase(const std::string& text); + std::string cleanText(const std::string& text); +}; + +#endif // BERT_TOKENIZER_H diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/include/GitHubFetcher.h b/clang/tools/ai-powered-reviewer-suggestion-tool/include/GitHubFetcher.h new file mode 100644 index 0000000000000..4fb012eb34ff6 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/include/GitHubFetcher.h @@ -0,0 +1,41 @@ +#ifndef GITHUB_FETCHER_H +#define GITHUB_FETCHER_H + +#include +#include +#include +#include "PRData.h" + +using json = nlohmann::json; + +class GitHubFetcher { +public: + GitHubFetcher(const std::string& owner, const std::string& repo, const std::string& token); + ~GitHubFetcher(); + + // New interface methods to match main.cpp usage + PRRepresentation getPR(const std::string& prNumber); + std::vector searchPRs(const std::string& query, int maxPages = 5); + + // Original methods + json getOpenMPPRs(int page = 1); + json getPRDetails(int pr_number); + json getPRReviews(int pr_number); + json getPRFiles(int pr_number); + +private: + std::string owner; + std::string repo; + std::string api_token; + const std::string base_url = "https://api.github.com/repos/"; + // Add this helper function + std::string getStringValue(const json& obj, const std::string& key, const std::string& defaultValue = ""); + + // Helper functions + json makeRequest(const std::string& endpoint); + json searchRequest(const std::string& query, int page); + std::string urlEncode(const std::string& value); // Add this line + static size_t WriteCallback(void* contents, size_t size, size_t nmemb, void* userp); +}; + +#endif // GITHUB_FETCHER_H diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/include/PRData.h b/clang/tools/ai-powered-reviewer-suggestion-tool/include/PRData.h new file mode 100644 index 0000000000000..20dadc98799cf --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/include/PRData.h @@ -0,0 +1,30 @@ +#ifndef PRDATA_H +#define PRDATA_H + +#include +#include + +struct PRRepresentation { + std::string title; + std::string body; + std::string author; + std::string created_at; + int number; + std::vector changed_files; + std::vector reviewers; + std::vector text_embedding; + + PRRepresentation() : number(0) {} +}; + +struct ReviewerSuggestion { + std::string reviewer; + double score; + + // Add default constructor + ReviewerSuggestion() : reviewer(""), score(0.0) {} + + ReviewerSuggestion(const std::string& r, double s) : reviewer(r), score(s) {} +}; + +#endif // PRDATA_H diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/include/PRParser.h b/clang/tools/ai-powered-reviewer-suggestion-tool/include/PRParser.h new file mode 100644 index 0000000000000..19e07807d516e --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/include/PRParser.h @@ -0,0 +1,36 @@ +#ifndef PRPARSER_H +#define PRPARSER_H + +#include +#include +#include +#include +#include "BertTokenizer.h" + +class PRParser { +public: + PRParser(const std::string& modelPath, const std::string& vocabPath); + ~PRParser(); + + std::vector generateEmbedding(const std::string& text); + std::vector extractFiles(const std::string& prContent); + +private: + std::unique_ptr env; + std::unique_ptr session; + std::unique_ptr tokenizer; + Ort::MemoryInfo memory_info; + Ort::AllocatorWithDefaultOptions allocator; + + std::vector input_names; + std::vector output_names; + std::vector> input_shapes; + std::vector> output_shapes; + + std::vector processOutput(Ort::Value& output_tensor); + std::string cleanText(const std::string& text); + void initializeModelInfo(); + std::vector padSequence(const std::vector& sequence, size_t max_length); +}; + +#endif // PRPARSER_H diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/include/ReviewerSuggester.h b/clang/tools/ai-powered-reviewer-suggestion-tool/include/ReviewerSuggester.h new file mode 100644 index 0000000000000..e7634ae30ab6f --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/include/ReviewerSuggester.h @@ -0,0 +1,32 @@ +#ifndef REVIEWER_SUGGESTER_H +#define REVIEWER_SUGGESTER_H + +#include "PRData.h" +#include "PRParser.h" +#include +#include +#include + +using json = nlohmann::json; + +class ReviewerSuggester { +public: + ReviewerSuggester(); + + std::vector suggestReviewers( + const PRRepresentation& currentPR, + const std::vector& historicalPRs, + PRParser& parser, + int topCount = 5 + ); + +private: + double calculateSimilarity(const PRRepresentation& pr1, const PRRepresentation& pr2); + double cosineSimilarity(const std::vector& v1, const std::vector& v2); + double jaccardSimilarity(const std::vector& s1, const std::vector& s2); + + PRRepresentation createPRRepresentation(const json& prData, PRParser& parser); + std::vector extractReviewers(const json& prData); +}; + +#endif // REVIEWER_SUGGESTER_H diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/models/vocab.txt b/clang/tools/ai-powered-reviewer-suggestion-tool/models/vocab.txt new file mode 100644 index 0000000000000..fb140275c155a --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/models/vocab.txt @@ -0,0 +1,30522 @@ +[PAD] +[unused0] +[unused1] +[unused2] +[unused3] +[unused4] +[unused5] +[unused6] +[unused7] +[unused8] +[unused9] +[unused10] +[unused11] +[unused12] +[unused13] +[unused14] +[unused15] +[unused16] +[unused17] +[unused18] +[unused19] +[unused20] +[unused21] +[unused22] +[unused23] +[unused24] +[unused25] +[unused26] +[unused27] +[unused28] +[unused29] +[unused30] +[unused31] +[unused32] +[unused33] +[unused34] +[unused35] +[unused36] +[unused37] +[unused38] +[unused39] +[unused40] +[unused41] +[unused42] +[unused43] +[unused44] 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a/clang/tools/ai-powered-reviewer-suggestion-tool/scripts/example_usage.sh b/clang/tools/ai-powered-reviewer-suggestion-tool/scripts/example_usage.sh new file mode 100755 index 0000000000000..3feb31de74792 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/scripts/example_usage.sh @@ -0,0 +1,66 @@ +#!/bin/bash + +# Example Usage Script for AI-Powered Reviewer Suggestion Tool +# This script demonstrates various ways to use the tool + +echo "🔍 AI-Powered Reviewer Suggestion Tool - Example Usage" +echo "=====================================================" + +# Check if the tool is built +if [ ! -f "./bin/reviewer-suggester" ]; then + echo "❌ Tool not found. Please build the project first:" + echo " mkdir build && cd build" + echo " cmake .. && make" + exit 1 +fi + +# Check if token is provided +if [ -z "$GITHUB_TOKEN" ]; then + echo "❌ GitHub token not found. Please set GITHUB_TOKEN environment variable:" + echo " export GITHUB_TOKEN='your_token_here'" + exit 1 +fi + +echo "✅ Tool found and token configured" +echo "" + +# Example 1: Basic usage +echo "📝 Example 1: Basic usage with a recent OpenMP PR" +echo "./bin/reviewer-suggester --pr 12345 --token \$GITHUB_TOKEN" +echo "" + +# Example 2: Custom parameters +echo "📝 Example 2: Custom parameters for thorough analysis" +echo "./bin/reviewer-suggester \" +echo " --pr 12345 \" +echo " --token \$GITHUB_TOKEN \" +echo " --max-pages 10 \" +echo " --top-reviewers 10" +echo "" + +# Example 3: Quick analysis +echo "📝 Example 3: Quick analysis for testing" +echo "./bin/reviewer-suggester \" +echo " --pr 12345 \" +echo " --token \$GITHUB_TOKEN \" +echo " --max-pages 2 \" +echo " --top-reviewers 3" +echo "" + +# Example 4: Custom model paths +echo "📝 Example 4: Using custom model paths" +echo "./bin/reviewer-suggester \" +echo " --pr 12345 \" +echo " --token \$GITHUB_TOKEN \" +echo " --model-path ./models/all-MiniLM-L6-v2.onnx \" +echo " --vocab-path ./models/vocab.txt" +echo "" + +echo "💡 Tips:" +echo " - Start with --max-pages 2 for quick testing" +echo " - Use --max-pages 5-10 for production usage" +echo " - Higher --max-pages values give more accurate results but take longer" +echo " - The tool analyzes historical OpenMP PRs to make suggestions" +echo "" + +echo "🚀 Run any of the examples above to get reviewer suggestions!" diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/scripts/setup_macos.sh b/clang/tools/ai-powered-reviewer-suggestion-tool/scripts/setup_macos.sh new file mode 100755 index 0000000000000..a1b6a1ec6d349 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/scripts/setup_macos.sh @@ -0,0 +1,117 @@ +#!/bin/bash + +# AI-Powered Reviewer Suggestion Tool Setup Script for macOS +# This script automates the installation and setup process + +set -e # Exit on any error + +echo "🚀 Setting up AI-Powered Reviewer Suggestion Tool for OpenMP PRs" +echo "================================================================" + +# Color codes for output +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +NC='\033[0m' # No Color + +# Function to print colored output +print_status() { + echo -e "${GREEN}[INFO]${NC} $1" +} + +print_warning() { + echo -e "${YELLOW}[WARNING]${NC} $1" +} + +print_error() { + echo -e "${RED}[ERROR]${NC} $1" +} + +# Check if running on macOS +if [[ "$OSTYPE" != "darwin"* ]]; then + print_error "This script is designed for macOS only" + exit 1 +fi + +# Check if Xcode Command Line Tools are installed +if ! command -v gcc &> /dev/null; then + print_warning "Xcode Command Line Tools not found. Installing..." + xcode-select --install + print_status "Please complete the Xcode Command Line Tools installation and run this script again" + exit 1 +fi + +# Check if Homebrew is installed +if ! command -v brew &> /dev/null; then + print_warning "Homebrew not found. Installing..." + /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" + + # Add Homebrew to PATH for M1 Macs + if [[ $(uname -m) == "arm64" ]]; then + echo 'eval "$(/opt/homebrew/bin/brew shellenv)"' >> ~/.zprofile + eval "$(/opt/homebrew/bin/brew shellenv)" + fi +fi + +print_status "Installing dependencies via Homebrew..." + +# Install required packages +brew update +brew install cmake llvm curl nlohmann-json onnxruntime + +print_status "Creating project directories..." +mkdir -p models +mkdir -p build + +print_status "Downloading model files..." + +# Download ONNX model +if [ ! -f "models/all-MiniLM-L6-v2.onnx" ]; then + print_status "Downloading all-MiniLM-L6-v2 ONNX model..." + if command -v wget &> /dev/null; then + wget -O models/all-MiniLM-L6-v2.onnx https://huggingface.co/onnx-models/all-MiniLM-L6-v2-onnx/resolve/main/model.onnx + elif command -v curl &> /dev/null; then + curl -L -o models/all-MiniLM-L6-v2.onnx https://huggingface.co/onnx-models/all-MiniLM-L6-v2-onnx/resolve/main/model.onnx + else + print_error "Neither wget nor curl found. Please download the model manually." + exit 1 + fi +else + print_status "ONNX model already exists" +fi + +# Download vocabulary file +if [ ! -f "models/vocab.txt" ]; then + print_status "Downloading vocabulary file..." + if command -v wget &> /dev/null; then + wget -O models/vocab.txt https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/resolve/main/vocab.txt + elif command -v curl &> /dev/null; then + curl -L -o models/vocab.txt https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2/resolve/main/vocab.txt + else + print_error "Neither wget nor curl found. Please download the vocabulary manually." + exit 1 + fi +else + print_status "Vocabulary file already exists" +fi + +print_status "Building the project..." + +cd build + +# Configure with CMake +cmake .. -DCMAKE_BUILD_TYPE=Release + +# Build +make -j$(sysctl -n hw.ncpu) + +print_status "✅ Setup completed successfully!" +echo "" +echo "📋 Next steps:" +echo "1. Get a GitHub API token from: https://github.com/settings/tokens" +echo "2. Run the tool with: ./build/bin/reviewer-suggester --pr --token " +echo "" +echo "📚 Example usage:" +echo " ./build/bin/reviewer-suggester --pr 12345 --token ghp_xxxxxxxxxxxx" +echo "" +print_warning "Make sure to keep your GitHub token secure and never commit it to version control!" diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/src/BertTokenizer.cpp b/clang/tools/ai-powered-reviewer-suggestion-tool/src/BertTokenizer.cpp new file mode 100644 index 0000000000000..a851c24c18899 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/src/BertTokenizer.cpp @@ -0,0 +1,147 @@ +#include "BertTokenizer.h" +#include +#include +#include +#include +#include + +BertTokenizer::BertTokenizer(const std::string& vocabPath) { + loadVocabulary(vocabPath); +} + +void BertTokenizer::loadVocabulary(const std::string& vocabPath) { + std::ifstream file(vocabPath); + if (!file.is_open()) { + throw std::runtime_error("Could not open vocabulary file: " + vocabPath); + } + + std::string token; + int64_t id = 0; + + while (std::getline(file, token)) { + vocab[token] = id; + id_to_token.push_back(token); + id++; + } + + std::cout << "Loaded vocabulary with " << vocab.size() << " tokens" << std::endl; + file.close(); +} + +std::string BertTokenizer::toLowerCase(const std::string& text) { + std::string result = text; + std::transform(result.begin(), result.end(), result.begin(), ::tolower); + return result; +} + +std::string BertTokenizer::cleanText(const std::string& text) { + // Remove control characters and normalize whitespace + std::string cleaned = std::regex_replace(text, std::regex("[\\x00-\\x1F\\x7F-\\x9F]"), " "); + cleaned = std::regex_replace(cleaned, std::regex("\\s+"), " "); + + // Trim + cleaned = std::regex_replace(cleaned, std::regex("^\\s+|\\s+$"), ""); + + return cleaned; +} + +std::vector BertTokenizer::basicTokenize(const std::string& text) { + std::vector tokens; + std::string cleaned = cleanText(toLowerCase(text)); + + // Split on whitespace and punctuation + std::regex token_regex(R"(\w+|[^\w\s])"); + std::sregex_iterator iter(cleaned.begin(), cleaned.end(), token_regex); + std::sregex_iterator end; + + for (; iter != end; ++iter) { + std::string token = iter->str(); + if (!token.empty()) { + tokens.push_back(token); + } + } + + return tokens; +} + +std::vector BertTokenizer::wordpieceTokenize(const std::string& token) { + std::vector output_tokens; + + if (token.length() > 200) { + output_tokens.push_back("[UNK]"); + return output_tokens; + } + + bool is_bad = false; + int start = 0; + std::vector sub_tokens; + + while (start < static_cast(token.length())) { + int end = token.length(); + std::string cur_substr; + bool found = false; + + while (start < end) { + std::string substr = token.substr(start, end - start); + if (start > 0) { + substr = "##" + substr; + } + + if (vocab.find(substr) != vocab.end()) { + cur_substr = substr; + found = true; + break; + } + end--; + } + + if (!found) { + is_bad = true; + break; + } + + sub_tokens.push_back(cur_substr); + start = end; + } + + if (is_bad) { + output_tokens.push_back("[UNK]"); + } else { + output_tokens = sub_tokens; + } + + return output_tokens; +} + +std::vector BertTokenizer::tokenize(const std::string& text) { + std::vector token_ids; + + if (text.empty()) { + return token_ids; + } + + // Add [CLS] token + token_ids.push_back(cls_token_id); + + // Basic tokenization + auto basic_tokens = basicTokenize(text); + + // WordPiece tokenization + for (const auto& token : basic_tokens) { + auto wordpiece_tokens = wordpieceTokenize(token); + + for (const auto& wp_token : wordpiece_tokens) { + auto it = vocab.find(wp_token); + if (it != vocab.end()) { + token_ids.push_back(it->second); + } else { + token_ids.push_back(unk_token_id); + } + } + } + + // Add [SEP] token + token_ids.push_back(sep_token_id); + + return token_ids; +} diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/src/GitHubFetcher.cpp b/clang/tools/ai-powered-reviewer-suggestion-tool/src/GitHubFetcher.cpp new file mode 100644 index 0000000000000..ad538da424675 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/src/GitHubFetcher.cpp @@ -0,0 +1,360 @@ +#include "GitHubFetcher.h" +#include +#include +#include +#include +#include +#include + +// Add this helper function after the includes +std::string GitHubFetcher::getStringValue(const json& obj, const std::string& key, const std::string& defaultValue) { + if (!obj.contains(key)) { + return defaultValue; + } + + const auto& value = obj[key]; + if (value.is_null()) { + return defaultValue; + } + + if (value.is_string()) { + return value.get(); + } + + return defaultValue; +} + + +GitHubFetcher::GitHubFetcher(const std::string& owner, const std::string& repo, const std::string& token) + : owner(owner), repo(repo), api_token(token) { + curl_global_init(CURL_GLOBAL_DEFAULT); +} + +GitHubFetcher::~GitHubFetcher() { + curl_global_cleanup(); +} + +size_t GitHubFetcher::WriteCallback(void* contents, size_t size, size_t nmemb, void* userp) { + ((std::string*)userp)->append((char*)contents, size * nmemb); + return size * nmemb; +} + +// Add this new function for URL encoding +std::string GitHubFetcher::urlEncode(const std::string& value) { + CURL* curl = curl_easy_init(); + if (!curl) { + return value; + } + + char* encoded = curl_easy_escape(curl, value.c_str(), static_cast(value.length())); + if (!encoded) { + curl_easy_cleanup(curl); + return value; + } + + std::string result(encoded); + curl_free(encoded); + curl_easy_cleanup(curl); + + return result; +} + +json GitHubFetcher::makeRequest(const std::string& endpoint) { + CURL* curl; + CURLcode res; + std::string readBuffer; + + curl = curl_easy_init(); + if (!curl) { + throw std::runtime_error("Failed to initialize curl"); + } + + std::string url = base_url + owner + "/" + repo + "/" + endpoint; + struct curl_slist* headers = NULL; + headers = curl_slist_append(headers, ("Authorization: token " + api_token).c_str()); + headers = curl_slist_append(headers, "User-Agent: Reviewer-Suggester"); + headers = curl_slist_append(headers, "Accept: application/vnd.github.v3+json"); + + curl_easy_setopt(curl, CURLOPT_URL, url.c_str()); + curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers); + curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, WriteCallback); + curl_easy_setopt(curl, CURLOPT_WRITEDATA, &readBuffer); + curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L); + curl_easy_setopt(curl, CURLOPT_TIMEOUT, 30L); + + res = curl_easy_perform(curl); + + if (res != CURLE_OK) { + curl_easy_cleanup(curl); + curl_slist_free_all(headers); + throw std::runtime_error("curl_easy_perform() failed: " + std::string(curl_easy_strerror(res))); + } + + // Check HTTP response code + long http_code = 0; + curl_easy_getinfo(curl, CURLINFO_RESPONSE_CODE, &http_code); + curl_easy_cleanup(curl); + curl_slist_free_all(headers); + + if (http_code != 200) { + std::cerr << "HTTP request failed with code " << http_code << std::endl; + std::cerr << "Response: " << readBuffer << std::endl; + throw std::runtime_error("HTTP request failed with code " + std::to_string(http_code)); + } + + // Parse JSON response + try { + return json::parse(readBuffer); + } catch (const json::parse_error& e) { + std::cerr << "Failed to parse JSON response: " << e.what() << std::endl; + std::cerr << "Response: " << readBuffer << std::endl; + throw std::runtime_error("Failed to parse JSON response: " + std::string(e.what())); + } +} + +json GitHubFetcher::searchRequest(const std::string& query, int page) { + CURL* curl; + CURLcode res; + std::string readBuffer; + + curl = curl_easy_init(); + if (!curl) { + throw std::runtime_error("Failed to initialize curl"); + } + + // Use maximum per_page (100) to reduce API calls + std::string encoded_query = urlEncode(query); + std::string url = "https://api.github.com/search/issues?q=" + encoded_query + + "&per_page=100&sort=created&order=desc&page=" + std::to_string(page); + + std::cout << "Search URL: " << url << std::endl; + + struct curl_slist* headers = NULL; + headers = curl_slist_append(headers, ("Authorization: token " + api_token).c_str()); + headers = curl_slist_append(headers, "User-Agent: Reviewer-Suggester"); + headers = curl_slist_append(headers, "Accept: application/vnd.github.v3+json"); + + curl_easy_setopt(curl, CURLOPT_URL, url.c_str()); + curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers); + curl_easy_setopt(curl, CURLOPT_WRITEFUNCTION, WriteCallback); + curl_easy_setopt(curl, CURLOPT_WRITEDATA, &readBuffer); + curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L); + curl_easy_setopt(curl, CURLOPT_TIMEOUT, 60L); // Increase timeout + + res = curl_easy_perform(curl); + + long http_code = 0; + curl_easy_getinfo(curl, CURLINFO_RESPONSE_CODE, &http_code); + + curl_easy_cleanup(curl); + curl_slist_free_all(headers); + + if (res != CURLE_OK) { + throw std::runtime_error("curl_easy_perform() failed: " + std::string(curl_easy_strerror(res))); + } + + // Handle rate limiting + if (http_code == 403) { + std::cerr << "Rate limit hit. Response: " << readBuffer << std::endl; + throw std::runtime_error("GitHub API rate limit exceeded"); + } + + if (http_code != 200) { + std::cerr << "Search API returned HTTP " << http_code << std::endl; + std::cerr << "Response: " << readBuffer << std::endl; + throw std::runtime_error("GitHub Search API returned HTTP " + std::to_string(http_code)); + } + + try { + return json::parse(readBuffer); + } catch (const json::parse_error& e) { + std::cerr << "Failed to parse search response: " << e.what() << std::endl; + std::cerr << "Response: " << readBuffer << std::endl; + throw std::runtime_error("Failed to parse search response"); + } +} + +// Rest of the methods remain the same... +PRRepresentation GitHubFetcher::getPR(const std::string& prNumber) { + std::string endpoint = "pulls/" + prNumber; + json prData = makeRequest(endpoint); + + PRRepresentation pr; + pr.number = std::stoi(prNumber); + pr.title = getStringValue(prData, "title", "No title"); + pr.body = getStringValue(prData, "body", "No description"); + + // Handle nested user object safely + if (prData.contains("user") && !prData["user"].is_null()) { + pr.author = getStringValue(prData["user"], "login", "unknown"); + } else { + pr.author = "unknown"; + } + + pr.created_at = getStringValue(prData, "created_at", ""); + + // Get files + try { + json filesData = makeRequest("pulls/" + prNumber + "/files"); + for (const auto& file : filesData) { + std::string filename = getStringValue(file, "filename", ""); + if (!filename.empty()) { + pr.changed_files.push_back(filename); + } + } + } catch (const std::exception& e) { + std::cerr << "Error fetching PR files: " << e.what() << std::endl; + } + + // Get reviewers + try { + json reviewsData = makeRequest("pulls/" + prNumber + "/reviews"); + std::set unique_reviewers; + for (const auto& review : reviewsData) { + if (review.contains("user") && !review["user"].is_null()) { + std::string reviewer = getStringValue(review["user"], "login", ""); + if (!reviewer.empty()) { + unique_reviewers.insert(reviewer); + } + } + } + pr.reviewers.assign(unique_reviewers.begin(), unique_reviewers.end()); + } catch (const std::exception& e) { + std::cerr << "Error fetching PR reviews: " << e.what() << std::endl; + } + + return pr; +} + + +std::vector GitHubFetcher::searchPRs(const std::string& query, int maxPages) { + std::vector prs; + int totalApiCalls = 0; + + for (int page = 1; page <= maxPages; page++) { + std::cout << "Fetching page " << page << " (up to 100 PRs per page)..." << std::endl; + + try { + json searchResults = searchRequest(query, page); + totalApiCalls++; + + if (!searchResults.contains("items")) { + std::cout << "No 'items' field in search results" << std::endl; + break; + } + + auto items = searchResults["items"]; + std::cout << "Found " << items.size() << " items on page " << page << std::endl; + + // Check if we've hit GitHub's search limit + if (searchResults.contains("total_count")) { + int totalCount = searchResults["total_count"]; + std::cout << "Total available results: " << totalCount << " (GitHub limit: 1000)" << std::endl; + } + + for (const auto& item : items) { + if (item.contains("pull_request")) { + PRRepresentation pr; + pr.number = item.value("number", 0); + pr.title = getStringValue(item, "title", "No title"); + pr.body = getStringValue(item, "body", "No description"); + + if (item.contains("user") && !item["user"].is_null()) { + pr.author = getStringValue(item["user"], "login", "unknown"); + } else { + pr.author = "unknown"; + } + + pr.created_at = getStringValue(item, "created_at", ""); + + std::cout << "Processing PR #" << pr.number << ": " << pr.title.substr(0, 50) << "..." << std::endl; + + // Get additional details (this will make more API calls) + try { + std::string prNumberStr = std::to_string(pr.number); + json filesData = makeRequest("pulls/" + prNumberStr + "/files"); + totalApiCalls++; + + for (const auto& file : filesData) { + std::string filename = getStringValue(file, "filename", ""); + if (!filename.empty()) { + pr.changed_files.push_back(filename); + } + } + + json reviewsData = makeRequest("pulls/" + prNumberStr + "/reviews"); + totalApiCalls++; + + std::set unique_reviewers; + for (const auto& review : reviewsData) { + if (review.contains("user") && !review["user"].is_null()) { + std::string reviewer = getStringValue(review["user"], "login", ""); + if (!reviewer.empty()) { + unique_reviewers.insert(reviewer); + } + } + } + pr.reviewers.assign(unique_reviewers.begin(), unique_reviewers.end()); + + // Add rate limiting protection + if (totalApiCalls % 100 == 0) { + std::cout << "Made " << totalApiCalls << " API calls. Pausing 1 second to avoid rate limiting..." << std::endl; + std::this_thread::sleep_for(std::chrono::seconds(1)); + } + + } catch (const std::exception& e) { + std::cerr << "Error fetching details for PR #" << pr.number << ": " << e.what() << std::endl; + continue; + } + + prs.push_back(pr); + } + } + + // Check if we've reached the end (less than 100 items means last page) + if (items.size() < 100) { + std::cout << "Reached end of results at page " << page << std::endl; + break; + } + + // Check if we're approaching GitHub's 1000 result limit + if (prs.size() >= 900) { + std::cout << "Approaching GitHub's 1000 result limit. Stopping at " << prs.size() << " PRs." << std::endl; + break; + } + + } catch (const std::exception& e) { + std::cerr << "Error fetching page " << page << ": " << e.what() << std::endl; + if (e.what() == std::string("GitHub API rate limit exceeded")) { + std::cout << "Rate limit hit. Stopping at " << prs.size() << " PRs." << std::endl; + break; + } + continue; + } + } + + std::cout << "Total API calls made: " << totalApiCalls << std::endl; + return prs; +} + + +// Keep the original methods for backward compatibility +json GitHubFetcher::getOpenMPPRs(int page) { + std::string endpoint = "pulls?state=all&labels=openmp&per_page=100&page=" + std::to_string(page); + return makeRequest(endpoint); +} + +json GitHubFetcher::getPRDetails(int pr_number) { + std::string endpoint = "pulls/" + std::to_string(pr_number); + return makeRequest(endpoint); +} + +json GitHubFetcher::getPRReviews(int pr_number) { + std::string endpoint = "pulls/" + std::to_string(pr_number) + "/reviews"; + return makeRequest(endpoint); +} + +json GitHubFetcher::getPRFiles(int pr_number) { + std::string endpoint = "pulls/" + std::to_string(pr_number) + "/files"; + return makeRequest(endpoint); +} diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/src/PRParser.cpp b/clang/tools/ai-powered-reviewer-suggestion-tool/src/PRParser.cpp new file mode 100644 index 0000000000000..559e4e892ae55 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/src/PRParser.cpp @@ -0,0 +1,296 @@ +#include "PRParser.h" +#include +#include +#include +#include + +PRParser::PRParser(const std::string& modelPath, const std::string& vocabPath) + : memory_info(Ort::MemoryInfo::CreateCpu(OrtArenaAllocator, OrtMemTypeDefault)) { + + try { + // Initialize ONNX Runtime environment with logging disabled + env = std::make_unique(ORT_LOGGING_LEVEL_ERROR, "PRParser"); + + // Create session options + Ort::SessionOptions session_options; + session_options.SetIntraOpNumThreads(1); + session_options.SetGraphOptimizationLevel(GraphOptimizationLevel::ORT_ENABLE_BASIC); + + // Load the model + session = std::make_unique(*env, modelPath.c_str(), session_options); + + // Initialize tokenizer + tokenizer = std::make_unique(vocabPath); + + // Get model input/output information + initializeModelInfo(); + + std::cout << "PRParser initialized with model: " << modelPath << std::endl; + std::cout << "Model loaded successfully with " << input_names.size() + << " inputs and " << output_names.size() << " outputs" << std::endl; + + // Print input details for debugging + for (size_t i = 0; i < input_names.size(); i++) { + std::cout << "Input " << i << ": " << input_names[i] << " Shape: ["; + for (size_t j = 0; j < input_shapes[i].size(); j++) { + std::cout << input_shapes[i][j]; + if (j < input_shapes[i].size() - 1) std::cout << ", "; + } + std::cout << "]" << std::endl; + } + + } catch (const std::exception& e) { + std::cerr << "Error initializing PRParser: " << e.what() << std::endl; + throw; + } +} + +PRParser::~PRParser() = default; + +void PRParser::initializeModelInfo() { + // Get input information + size_t num_inputs = session->GetInputCount(); + input_names.clear(); + input_shapes.clear(); + + for (size_t i = 0; i < num_inputs; i++) { + // Get input name + auto input_name_ptr = session->GetInputNameAllocated(i, allocator); + input_names.push_back(std::string(input_name_ptr.get())); + + // Get input shape + auto input_type_info = session->GetInputTypeInfo(i); + auto input_tensor_info = input_type_info.GetTensorTypeAndShapeInfo(); + auto input_shape = input_tensor_info.GetShape(); + input_shapes.push_back(input_shape); + } + + // Get output information + size_t num_outputs = session->GetOutputCount(); + output_names.clear(); + output_shapes.clear(); + + for (size_t i = 0; i < num_outputs; i++) { + // Get output name + auto output_name_ptr = session->GetOutputNameAllocated(i, allocator); + output_names.push_back(std::string(output_name_ptr.get())); + + // Get output shape + auto output_type_info = session->GetOutputTypeInfo(i); + auto output_tensor_info = output_type_info.GetTensorTypeAndShapeInfo(); + auto output_shape = output_tensor_info.GetShape(); + output_shapes.push_back(output_shape); + } +} + +std::string PRParser::cleanText(const std::string& text) { + if (text.empty()) return ""; + + // Remove excessive whitespace and newlines + std::string cleaned = std::regex_replace(text, std::regex("\\s+"), " "); + + // Trim leading and trailing whitespace + cleaned = std::regex_replace(cleaned, std::regex("^\\s+|\\s+$"), ""); + + // Limit length to prevent memory issues + if (cleaned.length() > 2048) { + cleaned = cleaned.substr(0, 2048); + } + + return cleaned; +} + +std::vector PRParser::padSequence(const std::vector& sequence, size_t max_length) { + std::vector padded(max_length, 0); // PAD token ID is typically 0 + + size_t copy_length = std::min(sequence.size(), max_length); + std::copy(sequence.begin(), sequence.begin() + copy_length, padded.begin()); + + return padded; +} + +std::vector PRParser::generateEmbedding(const std::string& text) { + try { + // Validate input + if (text.empty()) { + std::cerr << "Warning: Empty text provided for embedding" << std::endl; + return std::vector(384, 0.0f); + } + + // Clean the text + std::string cleaned_text = cleanText(text); + if (cleaned_text.empty()) { + std::cerr << "Warning: Text becomes empty after cleaning" << std::endl; + return std::vector(384, 0.0f); + } + + // Tokenize the text + auto tokens = tokenizer->tokenize(cleaned_text); + if (tokens.empty()) { + std::cerr << "Warning: No tokens generated for text: " << cleaned_text.substr(0, 50) << "..." << std::endl; + return std::vector(384, 0.0f); + } + + // Prepare sequences with proper length (max 512 for BERT models) + const size_t max_length = 512; + std::vector input_ids = padSequence(tokens, max_length); + + // Create attention mask (1 for real tokens, 0 for padding) + std::vector attention_mask(max_length, 0); + for (size_t i = 0; i < std::min(tokens.size(), max_length); i++) { + attention_mask[i] = 1; + } + + // Create token type ids (all 0s for single sentence) + std::vector token_type_ids(max_length, 0); + + // Create input tensors + std::vector input_shape = {1, static_cast(max_length)}; + + auto input_ids_tensor = Ort::Value::CreateTensor( + memory_info, input_ids.data(), input_ids.size(), + input_shape.data(), input_shape.size()); + + auto attention_mask_tensor = Ort::Value::CreateTensor( + memory_info, attention_mask.data(), attention_mask.size(), + input_shape.data(), input_shape.size()); + + // Prepare inputs based on model requirements + std::vector input_tensors; + std::vector input_names_cstr; + + // Most sentence transformers need input_ids and attention_mask + if (input_names.size() >= 2) { + input_names_cstr.push_back(input_names[0].c_str()); // input_ids + input_names_cstr.push_back(input_names[1].c_str()); // attention_mask + input_tensors.push_back(std::move(input_ids_tensor)); + input_tensors.push_back(std::move(attention_mask_tensor)); + + // Add token_type_ids if model expects it + if (input_names.size() >= 3) { + auto token_type_ids_tensor = Ort::Value::CreateTensor( + memory_info, token_type_ids.data(), token_type_ids.size(), + input_shape.data(), input_shape.size()); + input_names_cstr.push_back(input_names[2].c_str()); + input_tensors.push_back(std::move(token_type_ids_tensor)); + } + } else { + std::cerr << "Error: Model has insufficient inputs (" << input_names.size() << ")" << std::endl; + return std::vector(384, 0.0f); + } + + // Convert output names to const char* + std::vector output_names_cstr; + for (const auto& name : output_names) { + output_names_cstr.push_back(name.c_str()); + } + + // Validate input names are not empty + for (const auto& name : input_names_cstr) { + if (!name || strlen(name) == 0) { + std::cerr << "Error: Empty input name detected" << std::endl; + return std::vector(384, 0.0f); + } + } + + // Run inference + auto output_tensors = session->Run(Ort::RunOptions{nullptr}, + input_names_cstr.data(), + input_tensors.data(), + input_names_cstr.size(), + output_names_cstr.data(), + output_names_cstr.size()); + + if (output_tensors.empty()) { + std::cerr << "Error: No output tensors returned" << std::endl; + return std::vector(384, 0.0f); + } + + // Process output (usually the last hidden state) + return processOutput(output_tensors[0]); + + } catch (const Ort::Exception& e) { + std::cerr << "ONNX Runtime error: " << e.what() << std::endl; + return std::vector(384, 0.0f); + } catch (const std::exception& e) { + std::cerr << "Error generating embedding: " << e.what() << std::endl; + return std::vector(384, 0.0f); + } +} + +std::vector PRParser::processOutput(Ort::Value& output_tensor) { + try { + // Get tensor info + auto tensor_info = output_tensor.GetTensorTypeAndShapeInfo(); + auto shape = tensor_info.GetShape(); + + if (shape.size() < 3) { + std::cerr << "Error: Unexpected output tensor shape" << std::endl; + return std::vector(384, 0.0f); + } + + // Get tensor data + float* tensor_data = output_tensor.GetTensorMutableData(); + size_t batch_size = shape[0]; + size_t seq_length = shape[1]; + size_t hidden_size = shape[2]; + + // Perform mean pooling over sequence length + std::vector result(hidden_size, 0.0f); + + for (size_t i = 0; i < seq_length; i++) { + for (size_t j = 0; j < hidden_size; j++) { + result[j] += tensor_data[i * hidden_size + j]; + } + } + + // Average the pooled values + for (size_t j = 0; j < hidden_size; j++) { + result[j] /= static_cast(seq_length); + } + + // L2 normalize the embedding + float norm = 0.0f; + for (float val : result) { + norm += val * val; + } + norm = std::sqrt(norm); + + if (norm > 0.0f) { + for (float& val : result) { + val /= norm; + } + } + + return result; + + } catch (const std::exception& e) { + std::cerr << "Error processing output: " << e.what() << std::endl; + return std::vector(384, 0.0f); + } +} + +std::vector PRParser::extractFiles(const std::string& prContent) { + std::vector files; + std::istringstream stream(prContent); + std::string line; + + // Look for file patterns in PR content + std::regex file_pattern(R"(\+\+\+ b/(.+))"); + std::regex diff_pattern(R"(diff --git a/.+ b/(.+))"); + + while (std::getline(stream, line)) { + std::smatch match; + if (std::regex_search(line, match, file_pattern) && match.size() > 1) { + files.push_back(match[1].str()); + } else if (std::regex_search(line, match, diff_pattern) && match.size() > 1) { + files.push_back(match[1].str()); + } + } + + // Remove duplicates + std::sort(files.begin(), files.end()); + files.erase(std::unique(files.begin(), files.end()), files.end()); + + return files; +} diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/src/ReviewerSuggester.cpp b/clang/tools/ai-powered-reviewer-suggestion-tool/src/ReviewerSuggester.cpp new file mode 100644 index 0000000000000..0f0946e51e922 --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/src/ReviewerSuggester.cpp @@ -0,0 +1,160 @@ +#include "ReviewerSuggester.h" +#include +#include // Add this line +#include +#include +#include + +ReviewerSuggester::ReviewerSuggester() { + // Default constructor +} + +double ReviewerSuggester::cosineSimilarity(const std::vector& v1, const std::vector& v2) { + if (v1.size() != v2.size() || v1.empty()) { + return 0.0; + } + + double dot_product = 0.0; + double norm1 = 0.0; + double norm2 = 0.0; + + for (size_t i = 0; i < v1.size(); ++i) { + dot_product += v1[i] * v2[i]; + norm1 += v1[i] * v1[i]; + norm2 += v2[i] * v2[i]; + } + + if (norm1 == 0.0 || norm2 == 0.0) { + return 0.0; + } + + return dot_product / (std::sqrt(norm1) * std::sqrt(norm2)); +} + +double ReviewerSuggester::jaccardSimilarity(const std::vector& s1, const std::vector& s2) { + std::set set1(s1.begin(), s1.end()); + std::set set2(s2.begin(), s2.end()); + + std::vector intersection; + std::set_intersection(set1.begin(), set1.end(), + set2.begin(), set2.end(), + std::back_inserter(intersection)); + + std::vector union_set; + std::set_union(set1.begin(), set1.end(), + set2.begin(), set2.end(), + std::back_inserter(union_set)); + + if (union_set.empty()) { + return 0.0; + } + + return static_cast(intersection.size()) / static_cast(union_set.size()); +} + +double ReviewerSuggester::calculateSimilarity(const PRRepresentation& pr1, const PRRepresentation& pr2) { + double text_sim = cosineSimilarity(pr1.text_embedding, pr2.text_embedding); + double file_sim = jaccardSimilarity(pr1.changed_files, pr2.changed_files); + + // Weighted average: prioritize text similarity for OpenMP PRs + return 0.7 * text_sim + 0.3 * file_sim; +} + +PRRepresentation ReviewerSuggester::createPRRepresentation(const json& prData, PRParser& parser) { + PRRepresentation pr; + + try { + pr.number = prData.value("number", 0); + + // Use safe string extraction + std::string title = prData.value("title", std::string("")); + std::string body = prData.value("body", std::string("")); + + // Handle null values + if (prData["title"].is_null()) title = "No title"; + if (prData["body"].is_null()) body = "No description"; + + pr.title = title; + pr.body = body; + pr.author = prData["user"].value("login", std::string("unknown")); + pr.created_at = prData.value("created_at", std::string("")); + + // Generate text embedding with safe concatenation + std::string combined_text = pr.title + " " + pr.body; + if (combined_text.length() > 3) { // Only generate if we have meaningful text + pr.text_embedding = parser.generateEmbedding(combined_text); + } else { + pr.text_embedding = std::vector(384, 0.0f); // Zero embedding for empty text + } + + } catch (const std::exception& e) { + std::cerr << "Error creating PR representation: " << e.what() << std::endl; + // Return a default PR representation + pr.title = "Error loading PR"; + pr.body = "Error loading PR"; + pr.author = "unknown"; + pr.text_embedding = std::vector(384, 0.0f); + } + + return pr; +} + + +std::vector ReviewerSuggester::extractReviewers(const json& prData) { + std::vector reviewers; + + try { + if (prData.contains("requested_reviewers")) { + for (const auto& reviewer : prData["requested_reviewers"]) { + if (reviewer.contains("login")) { + reviewers.push_back(reviewer["login"]); + } + } + } + } catch (const std::exception& e) { + std::cerr << "Error extracting reviewers: " << e.what() << std::endl; + } + + return reviewers; +} + +std::vector ReviewerSuggester::suggestReviewers( + const PRRepresentation& currentPR, + const std::vector& historicalPRs, + PRParser& parser, + int topCount) { + + std::map reviewer_scores; + + // Calculate similarity with each historical PR and accumulate scores for reviewers + for (const auto& historicalPR : historicalPRs) { + double similarity = calculateSimilarity(currentPR, historicalPR); + + // Weight by recency (newer PRs get higher weight) + double recency_weight = 1.0; // Could be enhanced with actual date parsing + + for (const auto& reviewer : historicalPR.reviewers) { + if (reviewer != currentPR.author) { // Don't suggest the author as a reviewer + reviewer_scores[reviewer] += similarity * recency_weight; + } + } + } + + // Convert to vector and sort by score + std::vector suggestions; + for (const auto& pair : reviewer_scores) { + suggestions.emplace_back(pair.first, pair.second); + } + + std::sort(suggestions.begin(), suggestions.end(), + [](const ReviewerSuggestion& a, const ReviewerSuggestion& b) { + return a.score > b.score; + }); + + // Return top suggestions + if (suggestions.size() > static_cast(topCount)) { + suggestions.resize(topCount); + } + + return suggestions; +} diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/src/main.cpp b/clang/tools/ai-powered-reviewer-suggestion-tool/src/main.cpp new file mode 100644 index 0000000000000..17af02cb92dec --- /dev/null +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/src/main.cpp @@ -0,0 +1,151 @@ +#include +#include +#include +#include "GitHubFetcher.h" +#include "PRParser.h" +#include "ReviewerSuggester.h" + +void printUsage(const char* programName) { + std::cout << "Usage: " << programName << " --pr --token [OPTIONS]" << std::endl; + std::cout << "Options:" << std::endl; + std::cout << " --pr PR number to analyze" << std::endl; + std::cout << " --token GitHub API token" << std::endl; + std::cout << " --max-pages Maximum pages of historical PRs to fetch (default: unlimited, GitHub max ~33)" << std::endl; + std::cout << " --top-reviewers Number of top reviewers to suggest (default: 5)" << std::endl; + std::cout << " --model-path Path to ONNX model file (default: models/all-MiniLM-L6-v2.onnx)" << std::endl; + std::cout << " --vocab-path Path to vocabulary file (default: models/vocab.txt)" << std::endl; + std::cout << " --help Show this help message" << std::endl; +} + +int main(int argc, char* argv[]) { + std::cout << "=== AI-Powered Reviewer Suggestion Tool for OpenMP PRs ===" << std::endl; + + // Default values - REMOVE CAPS + std::string prNumber; + std::string githubToken; + int maxPages = 2; // -1 means unlimited (up to GitHub's limit) + int topReviewers = 5; + std::string modelPath = "models/all-MiniLM-L6-v2.onnx"; + std::string vocabPath = "models/vocab.txt"; + + // Parse command line arguments + for (int i = 1; i < argc; i++) { + std::string arg = argv[i]; + + if (arg == "--help") { + printUsage(argv[0]); + return 0; + } else if (arg == "--pr" && i + 1 < argc) { + prNumber = argv[++i]; + } else if (arg == "--token" && i + 1 < argc) { + githubToken = argv[++i]; + } else if (arg == "--max-pages" && i + 1 < argc) { + maxPages = std::stoi(argv[++i]); + } else if (arg == "--top-reviewers" && i + 1 < argc) { + topReviewers = std::stoi(argv[++i]); + } else if (arg == "--model-path" && i + 1 < argc) { + modelPath = argv[++i]; + } else if (arg == "--vocab-path" && i + 1 < argc) { + vocabPath = argv[++i]; + } else { + std::cerr << "Unknown argument: " << arg << std::endl; + printUsage(argv[0]); + return 1; + } + } + + // Validate required arguments + if (prNumber.empty()) { + std::cerr << "Error: PR number is required" << std::endl; + printUsage(argv[0]); + return 1; + } + + if (githubToken.empty()) { + const char* envToken = std::getenv("GITHUB_TOKEN"); + if (envToken) { + githubToken = envToken; + } else { + std::cerr << "Error: GitHub token is required (use --token or set GITHUB_TOKEN environment variable)" << std::endl; + return 1; + } + } + + // Warn about unlimited pages + if (maxPages == -1) { + std::cout << "WARNING: Unlimited pages requested. This may take a long time and hit API rate limits." << std::endl; + std::cout << "GitHub Search API is limited to ~1000 results maximum (~33 pages at 30 per page)." << std::endl; + maxPages = 1000; // Set to a very high number + } + + try { + // Initialize components + std::cout << "Initializing GitHub fetcher..." << std::endl; + GitHubFetcher fetcher("llvm", "llvm-project", githubToken); + + std::cout << "Initializing PR parser with model: " << modelPath << std::endl; + PRParser parser(modelPath, vocabPath); + + std::cout << "Initializing reviewer suggester..." << std::endl; + ReviewerSuggester suggester; + + // Test embedding generation + std::cout << "Testing embedding generation..." << std::endl; + std::string testText = "This is a test sentence for OpenMP parallel processing."; + auto testEmbedding = parser.generateEmbedding(testText); + std::cout << "Test embedding size: " << testEmbedding.size() << std::endl; + + if (testEmbedding.size() == 0 || std::all_of(testEmbedding.begin(), testEmbedding.end(), [](float f){ return f == 0.0f; })) { + std::cerr << "Warning: Test embedding generation failed or returned zero vector" << std::endl; + } else { + std::cout << "Test embedding generated successfully!" << std::endl; + } + + // Get current PR + std::cout << "Fetching PR #" << prNumber << "..." << std::endl; + auto currentPR = fetcher.getPR(prNumber); + if (currentPR.title.empty()) { + std::cerr << "Error: Could not fetch PR #" << prNumber << std::endl; + return 1; + } + + std::cout << "Current PR: " << currentPR.title << std::endl; + + // Fetch historical PRs with unlimited pages + std::cout << "Fetching historical OpenMP PRs (unlimited pages, up to GitHub limit)..." << std::endl; + std::string query = "repo:llvm/llvm-project is:pr label:clang:openmp in:title,body"; + + auto historicalPRs = fetcher.searchPRs(query, maxPages); + + std::cout << "Found " << historicalPRs.size() << " historical PRs" << std::endl; + + if (historicalPRs.empty()) { + std::cerr << "Warning: No historical PRs found" << std::endl; + return 1; + } + + // Generate suggestions + std::cout << "Generating reviewer suggestions..." << std::endl; + auto suggestions = suggester.suggestReviewers(currentPR, historicalPRs, parser, topReviewers); + + // Display results + std::cout << "\n=== Suggested Reviewers for PR #" << prNumber << " ===" << std::endl; + std::cout << "PR Title: " << currentPR.title << std::endl; + std::cout << "PR Author: " << currentPR.author << std::endl; + std::cout << "\nTop " << suggestions.size() << " Reviewer Suggestions:" << std::endl; + + for (size_t i = 0; i < suggestions.size(); i++) { + std::cout << (i + 1) << ". 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a/clang/tools/ai-powered-reviewer-suggestion-tool/README.md b/clang/tools/ai-powered-reviewer-suggestion-tool/README.md index 3d0896c1a0cd2..2fc452c05a09a 100644 --- a/clang/tools/ai-powered-reviewer-suggestion-tool/README.md +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/README.md @@ -102,7 +102,7 @@ make -j$(nproc) --vocab-path ../models/vocab.txt ``` -![Demo SS]("/ai-powered-reviewer-suggestion-tool/media/demo_ss.png") +![Demo SS](https://github.com/AnanyaBhatblr/llvm-project/blob/main/clang/tools/ai-powered-reviewer-suggestion-tool/demo_ss.png) ![Demo GIF]("/ai-powered-reviewer-suggestion-tool/media/demo.gif") From 5e3c5935a606714b012d7d5f5aacd3ffd7ce9330 Mon Sep 17 00:00:00 2001 From: Aditya Verma <127381769+RamblingFlyer@users.noreply.github.com> Date: Fri, 20 Jun 2025 20:32:59 +0530 Subject: [PATCH 4/8] Add files via upload --- .../WhatsApp Image 2025-06-20 at 20.31.06.jpeg | Bin 0 -> 232571 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 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zvzu337vBk$W-n};?x)Y;!1i%716eR`2kcE$A=G;^r?85B3G&v{Rgy_!83ZSs!AU!J zP;XnMRB1FeqvRS$nELom6TMo7iFGtEi3GL~U$^Mx5*gsWf&Hr}ikrr68^m9N_B+e6 z&(r6!q2N9yZ;K~vk-(~nQUfP$5bibf{Pj>U3L|{s5_VGMGce_Z^H6i%iTQNz2auV*Re zv%RS4v$~at^QV4(fGp+5>*w}AENrASK%nO4V*kd)Rr$1W@1jPg{@D2xo%A0R_HJpv bBnGrE&jB%bPhLq9?=cne Date: Fri, 20 Jun 2025 20:38:18 +0530 Subject: [PATCH 6/8] Update README.md --- clang/tools/ai-powered-reviewer-suggestion-tool/README.md | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/clang/tools/ai-powered-reviewer-suggestion-tool/README.md b/clang/tools/ai-powered-reviewer-suggestion-tool/README.md index 2fc452c05a09a..63e3eb8046ccc 100644 --- a/clang/tools/ai-powered-reviewer-suggestion-tool/README.md +++ b/clang/tools/ai-powered-reviewer-suggestion-tool/README.md @@ -104,7 +104,13 @@ make -j$(nproc) ![Demo SS](https://github.com/AnanyaBhatblr/llvm-project/blob/main/clang/tools/ai-powered-reviewer-suggestion-tool/demo_ss.png) -![Demo GIF]("/ai-powered-reviewer-suggestion-tool/media/demo.gif") + +![Demo SS](https://github.com/AnanyaBhatblr/llvm-project/blob/main/clang/tools/ai-powered-reviewer-suggestion-tool/img1.jpeg) + + +![Demo SS](https://github.com/AnanyaBhatblr/llvm-project/blob/main/clang/tools/ai-powered-reviewer-suggestion-tool/img2.jpeg) + + ### Advanced Options From cb316571bd475c91a76d169e88dd5b92f01894f6 Mon Sep 17 00:00:00 2001 From: Aditya Verma <127381769+RamblingFlyer@users.noreply.github.com> Date: Fri, 20 Jun 2025 20:38:50 +0530 Subject: [PATCH 7/8] Add files via upload --- img1.jpeg | Bin 0 -> 232571 bytes img2.jpeg | Bin 0 -> 286683 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 img1.jpeg create mode 100644 img2.jpeg diff --git a/img1.jpeg b/img1.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..d23e6a2ad0a4515b2e60f84fb6563c4f0a28057c GIT binary patch literal 232571 zcmeEucUV))x9A1}1c(qIV9=N0%W2X>` 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