Fix Dockerfile build issue

making.sh

@@ -0,0 +1,67 @@
+#!/bin/bash
+
+PROJECT_DIR="../projects/example_01"
+CONFIG_DIR="$PROJECT_DIR/config"
+RAW_DATA_DIR="$PROJECT_DIR/raw_data"
+
+# TIMESTAMP=$(date +"%Y%m%d_%H%M")
+PARSE_DIR="$PROJECT_DIR/parse"
+CHUNK_DIR="$PROJECT_DIR/chunk"
+
+mkdir -p "$PARSE_DIR" "$CHUNK_DIR";
+
+# ----------------------------------------------------------------------- #
+echo "1️⃣ Parsing PDF 문서 시작..."
+python3 -c "
+from autorag.parser import Parser
+parser = Parser(data_path_glob='$RAW_DATA_DIR/*.pdf', project_dir='$PARSE_DIR')
+parser.start_parsing('$CONFIG_DIR/parse.yaml')
+"
+echo "✅ Parse 데이터 생성 완료"
+# ----------------------------------------------------------------------- #
+echo "2️⃣ Chunking 데이터 생성 시작..."
+python3 -c "
+from autorag.chunker import Chunker
+chunker = Chunker.from_parquet(parsed_data_path='$PARSE_DIR/parsed_result.parquet', project_dir='$CHUNK_DIR')
+chunker.start_chunking('$CONFIG_DIR/chunk.yaml')
+"
+echo "✅ Chunk 데이터 생성 완료"
+# ----------------------------------------------------------------------- #
+QA_SIZE=20
+echo "3️⃣ QA 데이터 생성 시작..."
+python3 -c "
+import os
+import pandas as pd
+from autorag.data.qa.filter.dontknow import dontknow_filter_rule_based
+from autorag.data.qa.generation_gt.llama_index_gen_gt import (
+    make_basic_gen_gt,
+    make_concise_gen_gt,
+)
+from autorag.data.qa.query.llama_gen_query import factoid_query_gen
+from autorag.data.qa.sample import random_single_hop
+from autorag.data.qa.schema import Raw, Corpus
+from dotenv import load_dotenv
+from llama_index.llms.openai import OpenAI
+
+load_dotenv()
+print('API Key:', os.getenv('OPENAI_API_KEY'))
+
+llm = OpenAI(model='gpt-4o-mini')
+
+initial_raw = Raw(pd.read_parquet('$PARSE_DIR/parsed_result.parquet', engine='pyarrow'))
+initial_corpus = Corpus(pd.read_parquet('$CHUNK_DIR/0.parquet', engine='pyarrow'), initial_raw)
+
+qa = (
+    initial_corpus
+    .sample(random_single_hop, n=$QA_SIZE)
+    .map(lambda df: df.reset_index(drop=True))
+    .make_retrieval_gt_contents()
+    .batch_apply(factoid_query_gen, llm=llm, lang='ko')
+    .batch_apply(make_basic_gen_gt, llm=llm, lang='ko')
+    .batch_apply(make_concise_gen_gt, llm=llm, lang='ko')
+    .filter(dontknow_filter_rule_based, lang='ko')
+)
+
+qa.to_parquet('$PROJECT_DIR/qa.parquet', '$PROJECT_DIR/corpus.parquet')
+"
+echo "✅ QA 데이터 생성 완료"