Dria-Agent-a-7B is a large language model trained on the Qwen2.5-Coder series, specializing in agent applications. It utilizes a Pythonic function calling approach, offering advantages such as simultaneous multipurpose function calls, free-form reasoning and actions, and instant complex solution generation compared to traditional JSON function calls. The model has demonstrated excellent performance across various benchmarks, including the Berkeley Function Calling Leaderboard (BFCL), MMLU-Pro, and the Dria-Pythonic-Agent-Benchmark (DPAB). With 7.62 billion parameters and employing BF16 tensor type, it supports text generation tasks. Its key benefits include powerful programming assistance, efficient function calling methods, and high accuracy in specific domains. The model is suitable for applications requiring complex logic processing and multi-step task execution, such as automated programming and intelligent agents. Currently, it is available for free use on the Hugging Face platform.