File size: 2,258 Bytes
80b7188 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | # DeepCoder Programming Agent Example
This example demonstrates training and running [DeepCoder](https://pretty-radio-b75.notion.site/DeepCoder-A-Fully-Open-Source-14B-Coder-at-O3-mini-Level-1cf81902c14680b3bee5eb349a512a51), a code reasoning LLM fine-tuned from DeepSeek-R1-Distill-Qwen-14B on coding competition problems with RL. The model achieves 60.6% Pass@1 accuracy on LiveCodeBench v5, representing an 8% improvement over the base model.
## Overview
The DeepCoder examples demonstrate:
- How to use rLLM's CompetitionCodingAgent for programming tasks
- How to train agents with iterative context lengthening (16K -> 32K)
- How to evaluate coding performance on LiveCodeBench
## Quick Start
### Setup Coding Data
First, prepare your coding datasets:
```bash
cd examples/deepcoder
python prepare_deepcoder_data.py
```
### Model Hosting
Start a model server (choose one option):
**Option 1: Using vLLM**
```bash
python -m vllm.entrypoints.openai.api_server \
--model agentica-org/DeepCoder-14B-Preview \
--host 0.0.0.0 \
--port 30000 \
--dtype bfloat16 \
--max-model-len 32768
```
**Option 2: Using SGLang**
```bash
python -m sglang_router.launch_server \
--model-path agentica-org/DeepCoder-14B-Preview \
--dp-size 1 \
--dtype bfloat16
```
### Run DeepCoder Agent
Execute the coding agent for evaluation:
```bash
python evaluate_deepcoder.py
```
### Train DeepCoder Agent
Train your own DeepCoder agent with iterative context lengthening:
```bash
# Train with 16K context
bash train_deepcoder_16k.sh
# Train with 32K context (modify MODEL_PATH to 16k checkpoint)
bash train_deepcoder_32k.sh
```
## Code Reference
### Code Agent Evaluator
Main script for evaluating coding performance:
```python title="examples/deepcoder/run_deepcoder.py"
--8<-- "examples/deepcoder/run_deepcoder.py"
```
### Training Script
DeepCoder training configuration:
```python title="examples/deepcoder/train_deepcoder.py"
--8<-- "examples/deepcoder/train_deepcoder.py"
```
For detailed setup instructions, see the [README](https://github.com/rllm-org/rllm/blob/main/examples/deepcoder/README.md) in the deepcoder example directory.
|