File size: 1,942 Bytes
7183e08 df724f2 7183e08 9d82eed 7183e08 14577ec 7183e08 | 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 | # Parlay — Windows-oriented Makefile (GNU Make from Git Bash or Chocolatey).
# Uses venv/Scripts/ paths. On Windows, clean uses cmd.exe.
.PHONY: setup setup-train run run-env run-mcp test clean train-data train-sft train-grpo evaluate
ifeq ($(OS),Windows_NT)
SHELL := cmd.exe
.SHELLFLAGS := /C
endif
setup:
python -m venv venv
venv\Scripts\python -m pip install --upgrade pip -q
venv\Scripts\pip install -r requirements.txt -q
if not exist .env copy .env.example .env
venv\Scripts\python scripts\init_db.py
setup-train:
python -m venv venv-train
venv-train\Scripts\python -m pip install --upgrade pip -q
venv-train\Scripts\pip install -r requirements.txt -q
venv-train\Scripts\pip install -r requirements-train.txt
run:
venv\Scripts\uvicorn main:app --host 0.0.0.0 --port 8000 --reload
run-env:
venv\Scripts\python -m parlay_env.server
run-mcp:
venv\Scripts\python -m mcp_server.server stdio
test:
venv\Scripts\pytest tests/ -v
train-data:
# hackathon budget default; override with EPISODES=N
venv-train\Scripts\python -m training.generate_data --episodes 80 --output data/episodes.jsonl
train-sft:
venv-train\Scripts\python -m training.sft_train --model Qwen/Qwen2.5-7B-Instruct --data data/episodes.jsonl --output models/parlay-sft --threshold 0.30
train-grpo:
venv-train\Scripts\python -m training.grpo_train --model models/parlay-sft --data data/episodes.jsonl --output models/parlay-grpo --steps 500
evaluate:
venv-train\Scripts\python -m training.evaluate --base Qwen/Qwen2.5-7B-Instruct --sft models/parlay-sft --grpo models/parlay-grpo --data data/episodes.jsonl --output results/eval_results.json
test-keyless:
venv\Scripts\pytest tests\test_keyless.py -v
docker-test:
docker build -t parlay-test . && docker run -p 7860:7860 --env-file .env parlay-test
clean:
if exist venv rd /s /q venv
if exist venv-train rd /s /q venv-train
for /r . %%d in (__pycache__) do @if exist "%%d" rd /s /q "%%d"
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