Chain of Grounded Objectives

Official implementation of the paper 'Chain-of-Grounded-Objectives: Concise-Goal-oriented-Prompting-for-Code-Generation'.

Installation

Requirements

• Python 3.10+

Setup

1. Install dependencies:

   pip install -r requirements.txt
   pip install -e third_party/expand_langchain
   pip install vllm==0.6.2

2. Run CodeExecContainer:

   source third_party/CodeExecContainer/run.sh

   At a new terminal, run the following command and keep it running.

3. Configure API keys:
   Edit api_keys.json with your API keys and endpoints.

Usage

Running Experiments

You can run experiments using the provided shell scripts or directly via run.py:

python3 run.py generator --config_path=<path_to_config.yaml> run merge_json exit

Summarizing Results

After running experiments, aggregate results with:

python3 main_result_summurize.py

Configuration

• Model configs: configs/llm/*.yaml
• Data source configs: configs/source/*.yaml
• Experiment configs: See subfolders in configs/ for each model/benchmark

API Keys

Edit api_keys.json to provide your keys and endpoints:

{
  "OPEN_WEBUI_API_KEY": "sk-your_key",
  "OLLAMA_BASE_URL": "your_path",
  "VLLM_BASE_URL": "your_path",
  "OPENAI_API_KEY": "sk-your_key",
  "CODEEXEC_ENDPOINT": "http://localhost:5097/execute"
}

License