add dynamic project naming

requirements.txt

@@ -2,4 +2,6 @@ fastapi==0.111.0
 requests==2.31.0
 huggingface_hub==0.23.4
 uvicorn[standard]==0.29.0
-autotrain-advanced==0.8.12
+autotrain-advanced==0.8.12
+yaml
+datetime

src/backup.yaml

@@ -0,0 +1,39 @@
+task: llm-sft
+base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
+project_name: llama
+log: tensorboard
+backend: local
+
+data:
+  path: baryshych/platma
+  train_split: train
+  valid_split: null
+  chat_template: null
+  column_mapping:
+    text_column: text
+
+params:
+  block_size: 1024
+  lr: 1e-4
+  warmup_ratio: 0.1
+  weight_decay: 0.01
+  epochs: 1
+  batch_size: 2
+  gradient_accumulation: 8
+  mixed_precision: fp16
+  peft: True
+  quantization: null
+  lora_r: 16
+  lora_alpha: 32
+  lora_dropout: 0.05
+  unsloth: False
+  optimizer: paged_adamw_8bit
+  target_modules: all-linear
+  padding: right
+  optimizer: paged_adamw_8bit
+  scheduler: cosine
+
+hub:
+  username: baryshych
+  token: ${HF_ACCESS_TOKEN}
+  push_to_hub: True

src/main.py

@@ -3,6 +3,8 @@ import requests
 from typing import Optional
 import uvicorn
 from subprocess import Popen
+import yaml
+import datetime
 
 from fastapi import FastAPI, Header, BackgroundTasks
 from fastapi.responses import FileResponse
@@ -51,7 +53,15 @@ async def post_webhook(
 def schedule_retrain(payload: WebhookPayload):
     # Create the autotrain project
     try:
-        result = Popen(['autotrain', '--config', os.path.join(os.getcwd(), "src/config.yaml")])
+        yaml_path = os.path.join(os.getcwd(), "config.yaml")
+        with open(yaml_path) as f:
+            list_doc = yaml.safe_load(f)
+            list_doc['project_name'] = datetime.datetime.now().isoformat()
+
+        with open(yaml_path) as f:
+            yaml.dump(list_doc, f, default_flow_style=False)
+
+        result = Popen(['autotrain', '--config', yaml_path])
     # project = AutoTrain.create_project(payload)
     # AutoTrain.add_data(project_id=project["id"])
     # AutoTrain.start_processing(project_id=project["id"])