diff --git a/.github/workflows/a b/.github/workflows/a new file mode 100644 index 000000000..e69de29bb diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index b4aad9943..971b1105c 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -1,41 +1,82 @@ name: ML Pipeline CI on: - # push: - # branches: [ main, master ] + push: + branches: [ main, master ] pull_request: branches: [ main, master ] +permissions: + contents: read + actions: write + jobs: test: runs-on: ubuntu-latest + environment: BASE_ACCURACY # デプロイ先環境を 'development' に固定 steps: - uses: actions/checkout@v3 + - name: Clear environment # テスト的に追加 + run: | + env -i bash -c "env" + # ... (セットアップ、依存関係インストールなど) + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install pytest great_expectations pandas scikit-learn flake8 black mypy pytest-cov gh + if [ -f requirements.txt ]; then pip install -r requirements.txt; fi + + - name: Run model tests + run: | + echo "BASELINE_ACCURACY from vars: ${{ vars.BASELINE_ACCURACY }}" # 確認用 + echo "BASELINE_ACCURACY from env: ${{ env.BASELINE_ACCURACY }}" # 確認用 + python -c "import os; print(f'BASELINE_ACCURACY from os: {os.environ.get(\"BASELINE_ACCURACY\")}')" # 確認用 + pytest day5/演習3/tests/test_model.py -v -s + env: + BASELINE_ACCURACY: ${{ vars.BASELINE_ACCURACY }} - name: Set up Python uses: actions/setup-python@v4 with: python-version: '3.10' - - - name: Install dependencies - run: | - python -m pip install --upgrade pip - pip install pytest great_expectations pandas scikit-learn flake8 black mypy pytest-cov - if [ -f requirements.txt ]; then pip install -r requirements.txt; fi - + + - name: Lint with flake8 run: | flake8 day5/演習3 --count --select=E9,F63,F7,F82 --show-source --statistics flake8 day5/演習3 --count --exit-zero --max-complexity=10 --max-line-length=88 --statistics - + - name: Format check with black run: | black --check day5/演習3 - + - name: Run data tests run: | - pytest day5/演習3/tests/test_data.py -v - - - name: Run model tests + pytest day5/演習3/tests/test_data.py -v -s + + - name: Run model tests and get accuracy + id: model_test + run: | + cd day5/演習3/tests + pytest test_model.py -v -s > output.log + echo "TEST_OUTPUT<> $GITHUB_OUTPUT + cat output.log >> $GITHUB_OUTPUT + echo "EOF" >> $GITHUB_OUTPUT + env: + BASELINE_ACCURACY: ${{ vars.BASELINE_ACCURACY }} # 環境変数として定義されている場合 + + - name: Update baseline accuracy (if tests passed) + if: success() run: | - pytest day5/演習3/tests/test_model.py -v + import re + accuracy_output = ${{ steps.model_test.outputs.stdout }} + current_accuracy_match = re.search(r"現在のモデルの精度\((\d+\.\d+)\)", accuracy_output) + if current_accuracy_match: + current_accuracy=$(echo "${current_accuracy_match[1]}" | awk '{printf "%.4f", $1}') + echo "Updating BASELINE_ACCURACY to: $current_accuracy" + gh variable set BASELINE_ACCURACY "$current_accuracy" + else: + echo "Could not extract current accuracy from logs." + exit 1 + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} \ No newline at end of file diff --git a/day1/01_streamlit_UI/app.py b/day1/01_streamlit_UI/app.py index dcfbe6fec..0489da909 100644 --- a/day1/01_streamlit_UI/app.py +++ b/day1/01_streamlit_UI/app.py @@ -15,48 +15,48 @@ # ============================================ # タイトルと説明 # ============================================ -st.title("Streamlit 初心者向けデモ") -st.markdown("### コメントを解除しながらStreamlitの機能を学びましょう") -st.markdown("このデモコードでは、コメントアウトされた部分を順番に解除しながらUIの変化を確認できます。") +st.title("個人情報アンケート") +st.markdown("### 個人情報を打ち込んで、整理しましょう") +st.markdown("このサイトでは、個人情報を入力していくことで、他の個人情報を入力する場面での入力をスムーズにします。") # ============================================ # サイドバー # ============================================ -st.sidebar.header("デモのガイド") -st.sidebar.info("コードのコメントを解除して、Streamlitのさまざまな機能を確認しましょう。") +st.sidebar.header("サイトのガイド") +st.sidebar.info("個人情報を入力していくことで、他の個人情報を入力する場面での入力をスムーズにしましょう。") # ============================================ # 基本的なUI要素 # ============================================ -st.header("基本的なUI要素") +st.header("個人情報入力欄") # テキスト入力 -st.subheader("テキスト入力") +st.subheader("個人情報は大切にしてください") name = st.text_input("あなたの名前", "ゲスト") st.write(f"こんにちは、{name}さん！") # ボタン -# st.subheader("ボタン") -# if st.button("クリックしてください"): -# st.success("ボタンがクリックされました！") +st.subheader("個人情報を入力しちゃうんですか？") +if st.button("はい"): + st.success("変わってますね！") # チェックボックス -# st.subheader("チェックボックス") -# if st.checkbox("チェックを入れると追加コンテンツが表示されます"): -# st.info("これは隠れたコンテンツです！") +st.subheader("個人情報を入力することに躊躇いがある") +if st.checkbox("当てはまる場合はチェックを入れてください"): + st.info("なぜこんなサイトを訪れたんですか？") # スライダー -# st.subheader("スライダー") -# age = st.slider("年齢", 0, 100, 25) -# st.write(f"あなたの年齢: {age}") +st.subheader("自身の年齢にスライダーを合わせてください") +age = st.slider("年齢", 0, 100, 25) +st.write(f"あなたの年齢は{age}歳です！覚えておいてくださいね！") # セレクトボックス -# st.subheader("セレクトボックス") -# option = st.selectbox( -# "好きなプログラミング言語は?", -# ["Python", "JavaScript", "Java", "C++", "Go", "Rust"] -# ) -# st.write(f"あなたは{option}を選びました") +st.subheader("性別") +option = st.selectbox( + "あなたの性別は?", + [ "男", "女", "その他"] + ) +st.write(f"あなたは{option}です。わかりましたか？") # ============================================ # レイアウト @@ -82,10 +82,10 @@ # st.write("これは第2タブの内容です") # エクスパンダー -# st.subheader("エクスパンダー") -# with st.expander("詳細を表示"): -# st.write("これはエクスパンダー内の隠れたコンテンツです") -# st.code("print('Hello, Streamlit！')") +st.subheader("その他") +with st.expander("詳細を表示"): + st.write("もう入力するのは終わりです、、、") + st.code("print('お疲れ様でした')") # ============================================ # データ表示 @@ -93,11 +93,11 @@ # st.header("データの表示") # サンプルデータフレームを作成 -# df = pd.DataFrame({ -# '名前': ['田中', '鈴木', '佐藤', '高橋', '伊藤'], -# '年齢': [25, 30, 22, 28, 33], -# '都市': ['東京', '大阪', '福岡', '札幌', '名古屋'] -# }) +df = pd.DataFrame({ + '名前': ['田中', '鈴木', '佐藤', '高橋', '伊藤'], + '年齢': [25, 30, 22, 28, 33], + '都市': ['東京', '大阪', '福岡', '札幌', '名古屋'] + }) # データフレーム表示 # st.subheader("データフレーム") @@ -183,21 +183,21 @@ # ============================================ # デモの使用方法 # ============================================ -st.divider() -st.subheader("このデモの使い方") -st.markdown(""" -1. コードエディタでコメントアウトされた部分を見つけます（#で始まる行） -2. 確認したい機能のコメントを解除します（先頭の#を削除） -3. 変更を保存して、ブラウザで結果を確認します -4. 様々な組み合わせを試して、UIがどのように変化するか確認しましょう -""") +# st.divider() +# st.subheader("このデモの使い方") +# st.markdown(""" +# 1. コードエディタでコメントアウトされた部分を見つけます（#で始まる行） +# 2. 確認したい機能のコメントを解除します（先頭の#を削除） +# 3. 変更を保存して、ブラウザで結果を確認します +#4. 様々な組み合わせを試して、UIがどのように変化するか確認しましょう +# """) -st.code(""" +# st.code(""" # コメントアウトされた例: # if st.button("クリックしてください"): # st.success("ボタンがクリックされました！") # コメントを解除した例: -if st.button("クリックしてください"): - st.success("ボタンがクリックされました！") -""") \ No newline at end of file +# if st.button("クリックしてください"): +# st.success("ボタンがクリックされました！") +# """) diff --git a/day1/day1_practice.ipynb b/day1/day1_practice.ipynb index a1dec3a9e..a22d326f7 100644 --- a/day1/day1_practice.ipynb +++ b/day1/day1_practice.ipynb @@ -115,11 +115,38 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "bvEowFfg5lrq" - }, - "outputs": [], + "execution_count": 4, + "metadata": { + "id": "bvEowFfg5lrq", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "fb6acecb-d475-4b34-e90c-7f673140fe6a" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting python-dotenv\n", + " Downloading python_dotenv-1.1.0-py3-none-any.whl.metadata (24 kB)\n", + "Downloading python_dotenv-1.1.0-py3-none-any.whl (20 kB)\n", + "Installing collected packages: python-dotenv\n", + "Successfully installed python-dotenv-1.1.0\n", + "/content/lecture-ai-engineering/day1\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "True" + ] + }, + "metadata": {}, + "execution_count": 4 + } + ], "source": [ "!pip install python-dotenv\n", "from dotenv import load_dotenv, find_dotenv\n", @@ -141,11 +168,23 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "S28XgOm0ELSM" - }, - "outputs": [], + "execution_count": 5, + "metadata": { + "id": "S28XgOm0ELSM", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "c8086931-df0a-4d1b-b471-7806a0dc0268" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "/content/lecture-ai-engineering/day1/01_streamlit_UI\n" + ] + } + ], "source": [ "%cd /content/lecture-ai-engineering/day1/01_streamlit_UI" ] @@ -161,7 +200,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "id": "nBe41LFiELSN" }, @@ -182,11 +221,23 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "aYw1q0iXELSN" - }, - "outputs": [], + "execution_count": 7, + "metadata": { + "id": "aYw1q0iXELSN", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "40578aa1-2a46-46ef-c376-c986614e0f79" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Authtoken saved to configuration file: /root/.config/ngrok/ngrok.yml\n" + ] + } + ], "source": [ "!ngrok authtoken $$NGROK_TOKEN" ] @@ -204,9 +255,68 @@ "cell_type": "code", "execution_count": null, "metadata": { - "id": "f-E7ucR6ELSN" - }, - "outputs": [], + "id": "f-E7ucR6ELSN", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "c85d6711-55e6-4787-abe6-aa66510bcb93" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "公開URL: https://a54b-35-233-225-230.ngrok-free.app\n", + "\n", + "Collecting usage statistics. To deactivate, set browser.gatherUsageStats to false.\n", + "\u001b[0m\n", + "\u001b[0m\n", + "\u001b[34m\u001b[1m You can now view your Streamlit app in your browser.\u001b[0m\n", + "\u001b[0m\n", + "\u001b[34m Local URL: \u001b[0m\u001b[1mhttp://localhost:8501\u001b[0m\n", + "\u001b[34m Network URL: \u001b[0m\u001b[1mhttp://172.28.0.12:8501\u001b[0m\n", + "\u001b[34m External URL: \u001b[0m\u001b[1mhttp://35.233.225.230:8501\u001b[0m\n", + "\u001b[0m\n", + "2025-04-25 04:08:15.825 Script compilation error\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/lib/python3.11/dist-packages/streamlit/runtime/scriptrunner/script_runner.py\", line 549, in _run_script\n", + " code = self._script_cache.get_bytecode(script_path)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/lib/python3.11/dist-packages/streamlit/runtime/scriptrunner/script_cache.py\", line 72, in get_bytecode\n", + " filebody = magic.add_magic(filebody, script_path)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/lib/python3.11/dist-packages/streamlit/runtime/scriptrunner/magic.py\", line 46, in add_magic\n", + " tree = ast.parse(code, script_path, \"exec\")\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/lib/python3.11/ast.py\", line 50, in parse\n", + " return compile(source, filename, mode, flags,\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/content/lecture-ai-engineering/day1/01_streamlit_UI/app.py\", line 39\n", + " st.subheader(\"ボタン\")\n", + "IndentationError: unexpected indent\n", + "2025-04-25 04:08:15.829 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n", + "2025-04-25 04:08:23.075 Script compilation error\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/lib/python3.11/dist-packages/streamlit/runtime/scriptrunner/script_runner.py\", line 549, in _run_script\n", + " code = self._script_cache.get_bytecode(script_path)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/lib/python3.11/dist-packages/streamlit/runtime/scriptrunner/script_cache.py\", line 72, in get_bytecode\n", + " filebody = magic.add_magic(filebody, script_path)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/lib/python3.11/dist-packages/streamlit/runtime/scriptrunner/magic.py\", line 46, in add_magic\n", + " tree = ast.parse(code, script_path, \"exec\")\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/lib/python3.11/ast.py\", line 50, in parse\n", + " return compile(source, filename, mode, flags,\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/content/lecture-ai-engineering/day1/01_streamlit_UI/app.py\", line 39\n", + " st.subheader(\"ボタン\")\n", + "IndentationError: unexpected indent\n", + "2025-04-25 04:08:23.077 Thread 'MainThread': missing ScriptRunContext! This warning can be ignored when running in bare mode.\n", + "2025-04-25 04:08:56.234 Received event for non-watched file: /content/lecture-ai-engineering/day1/01_streamlit_UI/app.py\n" + ] + } + ], "source": [ "from pyngrok import ngrok\n", "\n", @@ -215,6 +325,18 @@ "!streamlit run app.py" ] }, + { + "cell_type": "code", + "source": [ + "from google.colab import drive\n", + "drive.mount('/content/drive')" + ], + "metadata": { + "id": "OSCJrRYSTrgo" + }, + "execution_count": null, + "outputs": [] + }, { "cell_type": "markdown", "metadata": { @@ -391,7 +513,9 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "id": "-N8qKmC6HrJ7" + }, "source": [ "アプリケーションの機能としては、チャット機能や履歴閲覧があります。\n", "\n", @@ -567,4 +691,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} +} \ No newline at end of file diff --git "a/day5/\346\274\224\347\277\2221/models/titanic_model.pkl" "b/day5/\346\274\224\347\277\2221/models/titanic_model.pkl" index 6fec87e47..7288555cb 100644 Binary files "a/day5/\346\274\224\347\277\2221/models/titanic_model.pkl" and "b/day5/\346\274\224\347\277\2221/models/titanic_model.pkl" differ diff --git "a/day5/\346\274\224\347\277\2222/black_check.py" "b/day5/\346\274\224\347\277\2222/black_check.py" index 3158f952d..910a40c3a 100644 --- "a/day5/\346\274\224\347\277\2222/black_check.py" +++ "b/day5/\346\274\224\347\277\2222/black_check.py" @@ -1,7 +1,18 @@ +def say_hello(name): + print("Hello," + name + "!") # greet + + +def say_hello(name): + print("Hello," + name + "!") # greet + + +def add(a, b): + return a + b + + +def add(a, b): + return a + b + -def say_hello(name):print("Hello,"+name+"!") # greet -def say_hello(name):print("Hello," + name +"!") # greet -def add( a,b):return a+b -def add( a , b ):return a+b def add(a, b): - return a+b \ No newline at end of file + return a + b diff --git "a/day5/\346\274\224\347\277\2223/tests/test_model.py" "b/day5/\346\274\224\347\277\2223/tests/test_model.py" index e11a19a5c..4006e75aa 100644 --- "a/day5/\346\274\224\347\277\2223/tests/test_model.py" +++ "b/day5/\346\274\224\347\277\2223/tests/test_model.py" @@ -171,3 +171,25 @@ def test_model_reproducibility(sample_data, preprocessor): assert np.array_equal( predictions1, predictions2 ), "モデルの予測結果に再現性がありません" + + +def test_model_performance_against_baseline(train_model): + """現在のモデルの精度がベースライン以上であることを検証""" + model, X_test, y_test = train_model + + # 予測と精度計算 + y_pred = model.predict(X_test) + current_accuracy = accuracy_score(y_test, y_pred) + + # 環境変数からベースライン精度を取得 + baseline_accuracy_str = os.environ.get("BASELINE_ACCURACY") + if baseline_accuracy_str is None: + pytest.fail("環境変数 BASELINE_ACCURACY が設定されていません") + try: + baseline_accuracy = float(baseline_accuracy_str) + except ValueError: + pytest.fail("環境変数 BASELINE_ACCURACY の値が float に変換できません") + + assert ( + current_accuracy >= baseline_accuracy + ), f"現在のモデルの精度({current_accuracy:.4f})がベースライン({baseline_accuracy:.4f})を下回っています" diff --git "a/\347\254\2543\345\233\236\350\252\262\351\241\214.ipynb" "b/\347\254\2543\345\233\236\350\252\262\351\241\214.ipynb" new file mode 100644 index 000000000..a3875d6aa --- /dev/null +++ "b/\347\254\2543\345\233\236\350\252\262\351\241\214.ipynb" @@ -0,0 +1,10987 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e4EN4GmtStsN" + }, + "source": [ + "# 演習の方針\n", + "\n", + "1. **ベースラインモデル評価** \n", + " 素のモデルで回答を生成し、講義内容との整合性の低さを観察する。これにより、特別な学習なしでのモデルの限界を確認する。\n", + "\n", + "2. **作成したテキストの活用** \n", + " リサーチを行い作成したテキストをモデルに学習させ、RAGを導入する。\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PPI1pj4mFavt" + }, + "source": [ + "## 扱う質問\n", + "\n", + "「NintetndoSwich2」に関する質問を取り扱う\n", + "\n", + "## 扱うモデル\n", + "\n", + "「google/gemma-2-2b-jpn-it」を使用する。このモデルは、リリース時期の関係上、「Switch2」が発表される前に訓練されており、このトピックに関する知識を持たないと想定される\n", + "- この特性を活かし、純粋なベースライン評価から各手法の効果を観察する" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bla6WHyQStsO" + }, + "source": [ + "### 演習環境の準備" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "vM50WAI7GXwC", + "outputId": "233491c5-6fa7-4d7f-f96b-e9189d67a355", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "collapsed": true + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: transformers in /usr/local/lib/python3.11/dist-packages (4.51.3)\n", + "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from transformers) (3.18.0)\n", + "Requirement already satisfied: huggingface-hub<1.0,>=0.30.0 in /usr/local/lib/python3.11/dist-packages (from transformers) (0.31.1)\n", + "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.11/dist-packages (from transformers) (2.0.2)\n", + "Requirement already satisfied: packaging>=20.0 in 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nvidia-curand-cu12\n", + " Found existing installation: nvidia-curand-cu12 10.3.6.82\n", + " Uninstalling nvidia-curand-cu12-10.3.6.82:\n", + " Successfully uninstalled nvidia-curand-cu12-10.3.6.82\n", + " Attempting uninstall: nvidia-cufft-cu12\n", + " Found existing installation: nvidia-cufft-cu12 11.2.3.61\n", + " Uninstalling nvidia-cufft-cu12-11.2.3.61:\n", + " Successfully uninstalled nvidia-cufft-cu12-11.2.3.61\n", + " Attempting uninstall: nvidia-cuda-runtime-cu12\n", + " Found existing installation: nvidia-cuda-runtime-cu12 12.5.82\n", + " Uninstalling nvidia-cuda-runtime-cu12-12.5.82:\n", + " Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82\n", + " Attempting uninstall: nvidia-cuda-nvrtc-cu12\n", + " Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82\n", + " Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:\n", + " Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82\n", + " Attempting uninstall: nvidia-cuda-cupti-cu12\n", + " Found existing installation: nvidia-cuda-cupti-cu12 12.5.82\n", + " Uninstalling nvidia-cuda-cupti-cu12-12.5.82:\n", + " Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82\n", + " Attempting uninstall: nvidia-cublas-cu12\n", + " Found existing installation: nvidia-cublas-cu12 12.5.3.2\n", + " Uninstalling nvidia-cublas-cu12-12.5.3.2:\n", + " Successfully uninstalled nvidia-cublas-cu12-12.5.3.2\n", + " Attempting uninstall: nvidia-cusparse-cu12\n", + " Found existing installation: nvidia-cusparse-cu12 12.5.1.3\n", + " Uninstalling nvidia-cusparse-cu12-12.5.1.3:\n", + " Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3\n", + " Attempting uninstall: nvidia-cudnn-cu12\n", + " Found existing installation: nvidia-cudnn-cu12 9.3.0.75\n", + " Uninstalling nvidia-cudnn-cu12-9.3.0.75:\n", + " Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75\n", + " Attempting uninstall: nvidia-cusolver-cu12\n", + " Found existing installation: nvidia-cusolver-cu12 11.6.3.83\n", + " Uninstalling nvidia-cusolver-cu12-11.6.3.83:\n", + " Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83\n", + "Successfully installed bitsandbytes-0.45.5 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127\n" + ] + } + ], + "source": [ + "!pip install --upgrade transformers\n", + "!pip install google-colab-selenium\n", + "!pip install bitsandbytes" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "id": "V2PStE0uqM03", + "outputId": "4d13378a-89af-4e6e-d18a-4a85885c1664", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Cloning into 'lecture-ai-engineering'...\n", + "remote: Enumerating objects: 81, done.\u001b[K\n", + "remote: Total 81 (delta 0), reused 0 (delta 0), pack-reused 81 (from 2)\u001b[K\n", + "Receiving objects: 100% (81/81), 1.34 MiB | 2.45 MiB/s, done.\n", + "Resolving deltas: 100% (12/12), done.\n" + ] + } + ], + "source": [ + "# 演習用のコンテンツを取得\n", + "!git clone https://github.com/matsuolab/lecture-ai-engineering.git" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "zXo_kFASXlvp", + "outputId": "2ebf93f7-0d85-477f-9711-f9be816cd3d2", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 17, + "referenced_widgets": [ + "4d4745f884854cbd909c4b044cb59947", + "e3c87e236f20452285575db1a7748d5e", + "4ea10de1d02f4e8d9052a297fa721081", + "509fd6d2ea734d0c80d12d2beae9fc3e", + "3c34a5efd89b4d99b339e92504701eea", + "86bb28abe8534878bd99e402917ff577", + "a7db570f80c240e1963d794da050f29b", + "3caa4ccd3036473f87fe96575c2d3f58", + "af790bd7473c4c4cbc85aac7acd7c90a", + "aea8f7ffbcbd4e96a420ac9e6218a7fe", + "4eab33d690164aa7896cb014eaebcf33", + 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\")\n", + " ]\n", + "\n", + " outputs = model.generate(\n", + " input_ids,\n", + " max_new_tokens=256,\n", + " eos_token_id=terminators,\n", + " do_sample=False,\n", + " # temperature=0.6, # If do_sample=True\n", + " # top_p=0.9, # If do_sample=True\n", + " )\n", + "\n", + " response = outputs[0][input_ids.shape[-1]:]\n", + " return tokenizer.decode(response, skip_special_tokens=True)" + ], + "metadata": { + "id": "huDNYbXW3lOm" + }, + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "NBUZ3o6dhMlC", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "8d954419-91b1-407b-b062-73237193d0e8" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "質問: Nintendo Switch2の国内専用本体価格はいくらですか\n", + "回答: 残念ながら、Nintendo Switch 2の国内専用本体価格はまだ発表されていません。\n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "質問: Nintendo Switchの本体価格はいくらですか\n", + "回答: Nintendo Switch本体の価格は、**約19,800円～21,800円**です。 \n", + "\n", + " \n", + " \n", + " \n", + " \n", + "\n", + "\n", + "\n", + "\n", + "質問: Nintendo Switch2の発売日はいつですか\n", + "回答: 残念ながら、Nintendo Switch 2の発売日は現在発表されていません。 \n", + "\n", + "\n", + " \n", + "\n", + "\n", + "\n", + "\n", + "質問: Nintendo SwitchとNintendo Switch2の違いを教えてください\n", + "回答: ## Nintendo SwitchとNintendo Switch2の違い\n", + "\n", + "残念ながら、Nintendo Switch2の具体的な情報はまだ公開されていません。 \n", + "\n", + "しかし、いくつかの噂や推測に基づいて、Switch2がどのような進化をするのかを想像してみましょう。\n", + "\n", + "**Switch2の期待される特徴:**\n", + "\n", + "* **より高性能なハードウェア:** Switch2は、Switchの性能を大幅に向上させることが期待されます。CPUやGPUの性能向上、より高速な通信、より高画質のゲームプレイを実現する可能性があります。\n", + "* **VR対応:** VR技術の進化により、Switch2ではVR対応が期待されます。\n", + "* **より高画質のゲーム:** Switch2は、より高画質のゲームをプレイできる可能性があります。\n", + "* **より進化した操作性:** Switch2では、より革新的な操作性を実現する可能性があります。例えば、より自然な手動操作や、より複雑な操作に対応する技術が導入されるかもしれません。\n", + "* **新しいゲーム体験:** Switch2では、従来のゲーム体験に加え、新しいゲーム体験を提供する可能性があります。例えば、よりリアルな世界観や、より没入感のあるゲーム体験を提供する技術が導入されるかもしれません。\n", + "* **\n", + "\n", + "質問: Nintendo Switchの発売日はいつですか\n", + "回答: Nintendo Switchの発売日は **2017年3月3日** です。 😊\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + } + ], + "source": [ + "questions = [\n", + " \"Nintendo Switch2の国内専用本体価格はいくらですか\",\n", + " \"Nintendo Switchの本体価格はいくらですか\",\n", + " \"Nintendo Switch2の発売日はいつですか\",\n", + " \"Nintendo SwitchとNintendo Switch2の違いを教えてください\",\n", + " \"Nintendo Switchの発売日はいつですか\"\n", + "]\n", + "\n", + "for question in questions:\n", + " response = generate_output(question)\n", + " print(f\"質問: {question}\")\n", + " print(f\"回答: {response}\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZSCNnRf9pJif" + }, + "source": [ + "## 結果 (ベースモデル)\n", + "\n", + "「google/gemma-2-2b-jpn-it」は「Nintendo Switch2」についての情報を知らない旨の回答をし、ハルシネーションは起こさなかった。モデルの作成時期の関係で、Switch2の情報を持たないと考えられる。\n", + "\n", + "---" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "k4R-hiKNGyJd" + }, + "source": [ + "# 2. 作成したテキストの活用" + ] + }, + { + "cell_type": "markdown", + "source": [ + "## 2.1 作成したテキストをソースとして活用 (RAG導入)\n", + "\n", + "モデルの回答の事実性を向上させるためにRetrieval Augmented Generation (RAG)技術を導入する：\n", + "\n", + "* **知識ソース**: 自身でリサーチして作成したテキスト\n", + "* **目的**: モデルに「NintendoSwitch2」に関する正確な知識と文脈を提供し、事実に基づいた回答を促す\n", + "\n", + "**初期RAG実装（ベーシックアプローチ）**:\n", + "* **ドキュメント処理**:作成したテキストを使用\n", + "* **分割方法**: 「。」（句点）で区切られた文単位でテキストを分割\n", + "* **検索手法**: シンプルな類似度ベースの検索でクエリに関連する文を抽出\n", + "* **制約条件**: モデルの入力トークン制限に収まるよう関連文のみを選択" + ], + "metadata": { + "id": "qcZCmKegHyrl" + } + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "id": "47GvcceyObAl", + "outputId": "4fdd1ee3-daf2-40de-e2cd-56d19d20e0e7", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 621, + "referenced_widgets": [ + "ee5d38eca4964aa88022ed82e5142703", + "89554d840fb740fd87bf8e1818fc70cb", + "973697c63db140b08606aa908e1425be", + "1e15782b93ee4259b175b2b156d01074", + "379179186699402594261442ce432150", + "90fff170b6b94fcaafab7d7223579682", + 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Copy a token from your Hugging Face\ntokens page and paste it below.
Immediately click login after copying\nyour token or it might be stored in plain text in this notebook file.
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