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‎.deployment‎

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‎README.md‎

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## Prerequisites
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- [Python 3.10+](https://www.python.org/downloads/)
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- [Poetry](https://python-poetry.org/docs/#installation)
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- [GNU Make](https://www.gnu.org/software/make/)
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- [Azure OpenAI Service](https://azure.microsoft.com/ja-jp/products/ai-services/openai-service)
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- [Azure Cosmos DB](https://azure.microsoft.com/ja-jp/products/cosmos-db/)
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## Development instructions
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### Local development
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Use Makefile to run the project locally.
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```shell
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# help
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make
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# install dependencies for development
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make install-deps-dev
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# run tests
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make test
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# run CI tests
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make ci-test
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```
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### Docker development
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```shell
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# build docker image
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make docker-build
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# run docker container
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make docker-run
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# run CI tests in docker container
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make ci-test-docker
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```
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To run all the projects in this repository, you need the followings.
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To publish the docker image to Docker Hub, you need to set the following secrets in the repository settings.
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```shell
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gh secret set DOCKERHUB_USERNAME --body $DOCKERHUB_USERNAME
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gh secret set DOCKERHUB_TOKEN --body $DOCKERHUB_TOKEN
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```
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## Deployment
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### From Docker Hub
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You can run the docker image from Docker Hub.
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```shell
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# Run 2_streamlit_chat
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docker run -p 8501:8501 ks6088ts/workshop-azure-openai:latest \
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python -m streamlit run apps/2_streamlit_chat/main.py
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# Run 99_streamlit_llm_examples
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docker run -p 8501:8501 ks6088ts/workshop-azure-openai:latest \
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python -m streamlit run apps/99_streamlit_llm_examples/main.py
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```
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### App Service
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For deploying the Streamlit application to Azure App Service, you need to set the following two configurations.
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1. Go to `Settings > Configuration > Startup Command` and set startup command as `python -m streamlit run apps/4_streamlit_chat_history/main.py --server.port 8000 --server.address 0.0.0.0`
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1. Set `SCM_DO_BUILD_DURING_DEPLOYMENT` to `true`
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Notes:
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- [Python 3.10+](https://www.python.org/downloads/)
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- [Azure OpenAI Service](https://azure.microsoft.com/en-us/products/ai-services/openai-service)
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- [Azure Cosmos DB](https://azure.microsoft.com/en-us/products/cosmos-db/)
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- [Azure AI Search](https://azure.microsoft.com/en-us/products/ai-services/ai-search)
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- Update the startup command as needed. App Service listens on port 8000 by default, so `--server.port 8000` is required.
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- The default port of App Service is 8000, so `--server.port 8000` is required.
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Here are the preferred tools for development.
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#### References
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- [Poetry](https://python-poetry.org/docs/#installation)
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- [GNU Make](https://www.gnu.org/software/make/)
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- [Streamlit を Azure App Service で動かす！](https://qiita.com/takashiuesaka/items/491b21e9afb34bbb6e6d)
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- [WARNING: Could not find virtual environment directory /home/site/wwwroot/antenv](https://stackoverflow.com/a/61720957)
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- [How to deploy a streamlit application on Azure App Service (WebApp)](https://learn.microsoft.com/en-us/answers/questions/1470782/how-to-deploy-a-streamlit-application-on-azure-app)
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## Projects
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| Project | Description | Image |
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| --------------------------------------------------------------------------------- | ------------------------------------------------------- | ---------------------------------------------------------------------------------------- |
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| [1_call_azure_openai_chat](./apps/1_call_azure_openai_chat/README.md) | Call Azure OpenAI Service API from Python | No Image |
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| [2_streamlit_chat](./apps/2_streamlit_chat/README.md) | Create an Azure OpenAI Chat app using Streamlit | ![2_streamlit_chat](./docs/images/2_streamlit_chat.chat_page.png) |
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| [3_call_azure_cosmos_db](./apps/3_call_azure_cosmos_db/README.md) | Call Azure Cosmos DB from Python | No Image |
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| [4_streamlit_chat_history](./apps/4_streamlit_chat_history/README.md) | Add feature to store chat history using Azure Cosmos DB | ![4_streamlit_chat_history](./docs/images/4_streamlit_chat_history.chat_page.png) |
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| [5_streamlit_query_chat_history](./apps/5_streamlit_query_chat_history/README.md) | Search Chat History | ![5_streamlit_query_chat_history](./docs/images/5_streamlit_query_chat_history.main.png) |
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| [6_call_azure_ai_search](./apps/6_call_azure_ai_search/README.md) | Call Azure AI Search from Python | No Image |
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| [7_streamlit_chat_rag](./apps/7_streamlit_chat_rag/README.md) | Add RAG feature to Streamlit chat app | ![7_streamlit_chat_rag](./docs/images/7_streamlit_chat_rag.main.png) |
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| [99_streamlit_examples](./apps/99_streamlit_examples/README.md) | Code samples for Streamlit | ![99_streamlit_examples](./docs/images/99_streamlit_examples.explaindata.png) |

‎apps/1_call_azure_openai_chat/README.md‎

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# Azure OpenAI Service を Python から呼び出す
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# Call Azure OpenAI Service API from Python
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Azure OpenAI Service を Python から呼び出す方法を説明します。
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This article explains how to call Azure OpenAI Service API from Python.
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## 前提条件
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## Prerequisites
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- Python 3.11+ がインストールされていること
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- Azure OpenAI Service が利用できること
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- Azure OpenAI Service の API キーが取得できていること
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- Python 3.10 or later
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- Azure OpenAI Service
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## 手順
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## Usage
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1. Azure OpenAI Service の API キーを取得する
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1. [.env.template](../../.env.template) をコピーして `.env` ファイルを作成する
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1. `.env` ファイルに API キーを設定する
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1. [main.py](./main.py) を実行する
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1. Get Azure OpenAI Service API key
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1. Copy [.env.template](../../.env.template) to `.env` in the same directory
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1. Set credentials in `.env`
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1. Run [main.py](./main.py)
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```shell
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# 仮想環境を作成してライブラリをインストールする
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python -m venv .venv
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# Create a virtual environment
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$ python -m venv .venv
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# 仮想環境を有効化する
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source .venv/bin/activate
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# Activate the virtual environment
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$ source .venv/bin/activate
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# ライブラリをインストールする
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pip install -r requirements.txt
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# Install dependencies
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$ pip install -r requirements.txt
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# スクリプトを実行する
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python apps/1_call_azure_openai/main.py
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# Run the script
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$ python apps/1_call_azure_openai/main.py
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```
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### 実行例
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### Example
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```shell
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❯ python apps/1_call_azure_openai_chat/main.py
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こんにちは！どうされましたか？何かお手伝いできることがあれば教えてください。
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$ python apps/1_call_azure_openai_chat/main.py
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{
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"id": "chatcmpl-9rHSFKIBtJDOlDheesev79CO7RNMz",
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"id": "chatcmpl-9tVzJwEczzb40cXT1gHZkk7ThX5Lm",
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"choices": [
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{
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"finish_reason": "stop",
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"index": 0,
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"logprobs": null,
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"message": {
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"content": "こんにちは！どうされましたか？何かお手伝いできることがあれば教えてください。",
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"content": "Hello! How can I assist you today?",
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"role": "assistant",
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"function_call": null,
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"tool_calls": null
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"filtered": false,
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"severity": "safe"
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},
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"protected_material_code": {
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"filtered": false,
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"detected": false
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},
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"protected_material_text": {
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"filtered": false,
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"detected": false
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},
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"self_harm": {
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"filtered": false,
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"severity": "safe"
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}
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}
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],
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"created": 1722485507,
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"created": 1723018029,
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"model": "gpt-4o-2024-05-13",
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"object": "chat.completion",
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"service_tier": null,
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"system_fingerprint": "fp_abc28019ad",
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"usage": {
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"completion_tokens": 23,
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"completion_tokens": 9,
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"prompt_tokens": 18,
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"total_tokens": 41
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"total_tokens": 27
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},
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"prompt_filter_results": [
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{
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}
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```
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## 参考資料
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## References
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- [クイックスタート: Azure OpenAI Service で GPT-35-Turbo と GPT-4 を使い始める](https://learn.microsoft.com/ja-jp/azure/ai-services/openai/chatgpt-quickstart?tabs=command-line%2Cpython-new&pivots=programming-language-python)
118+
- [Quickstart: Get started using GPT-35-Turbo and GPT-4 with Azure OpenAI Service](https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart?tabs=command-line%2Cpython-new&pivots=programming-language-python)

‎apps/1_call_azure_openai_chat/main.py‎

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from openai import AzureOpenAI
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if __name__ == "__main__":
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# .env ファイルをパースして環境変数にセット
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# Parse .env file and set environment variables
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load_dotenv()
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# Azure OpenAI API クライアントを初期化
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# Initialize AzureOpenAI client
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client = AzureOpenAI(
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api_key=getenv("AZURE_OPENAI_API_KEY"),
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api_version=getenv("AZURE_OPENAI_API_VERSION"),
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azure_endpoint=getenv("AZURE_OPENAI_ENDPOINT"),
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)
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# Chat API を呼び出して、ユーザーの入力に対する応答を取得
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# Call completion API and get a response to user input
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response = client.chat.completions.create(
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model=getenv("AZURE_OPENAI_GPT_MODEL"),
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "こんにちは"},
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{"role": "user", "content": "Hello"},
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],
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)
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# 応答を出力
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print(response.choices[0].message.content)
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# レスポンスの JSON を出力
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# Print response to console
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print(response.model_dump_json(indent=2))

‎apps/2_streamlit_chat/README.md‎

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# Streamlit でチャットアプリを作成する
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# Create an Azure OpenAI Chat app using Streamlit
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Streamlit を使って、Azure OpenAI Service を利用したチャットアプリを作成します。
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This app demonstrates how to create a chat application using Azure OpenAI Service and Streamlit.
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## 前提条件
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## Prerequisites
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- Python 3.11+ がインストールされていること
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- Azure OpenAI Service が利用できること
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- Azure OpenAI Service の API キーが取得できていること
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- Python 3.10 or later
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- Azure OpenAI Service
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## 手順
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## Usage
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1. Azure OpenAI Service の API キーを取得する
14-
1. [.env.template](../../.env.template) をコピーして `.env` ファイルを作成する
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1. `.env` ファイルに API キーを設定する
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1. [main.py](./main.py) を実行する
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1. Get Azure OpenAI Service API key
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1. Copy [.env.template](../../.env.template) to `.env` in the same directory
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1. Set credentials in `.env`
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1. Run [main.py](./main.py)
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```shell
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# 仮想環境を作成してライブラリをインストールする
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python -m venv .venv
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# Create a virtual environment
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$ python -m venv .venv
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# 仮想環境を有効化する
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source .venv/bin/activate
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# Activate the virtual environment
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$ source .venv/bin/activate
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# ライブラリをインストールする
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pip install -r requirements.txt
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# Install dependencies
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$ pip install -r requirements.txt
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# スクリプトを実行する
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streamlit run ./apps/2_streamlit_chat/main.py
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# Run the script
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$ python -m streamlit run apps/2_streamlit_chat/main.py
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```
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### 実行例
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### Example
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http://localhost:8501 にアクセスすると、以下のような画面が表示されます。
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When you access `http://localhost:8501`, you will see the following screen.
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![Streamlit Chat](../../docs/images/2_streamlit_chat.png)
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![Streamlit Chat](../../docs/images/2_streamlit_chat.initial_page.png)
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## 補足
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To start a conversation, fill in the required fields in the sidebar and you will see the following screen.
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本アプリでは、チャットのやり取りを保持するために、`st.session_state.messages` にメッセージを保持しています。
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これはアプリケーションのプロセス側で、セッションごとにメッセージを保持するための仕組みです。セッションが終了するとメッセージは消えます。
39+
![Streamlit Chat](../../docs/images/2_streamlit_chat.chat_page.png)
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## 参考資料
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## Note
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This app uses `st.session_state.messages` to store messages for chat. This is a mechanism to store messages per session on the process side of the application. Messages will disappear when the session ends.
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## References
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- [Your LLM code playground](https://streamlit.io/generative-ai)

‎apps/2_streamlit_chat/main.py‎

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key="AZURE_OPENAI_GPT_MODEL",
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type="default",
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)
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"[Go to Azure Portal to get an Azure OpenAI API key](https://portal.azure.com/)"
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"[Go to Azure OpenAI Studio](https://oai.azure.com/resource/overview)"
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"[Azure Portal](https://portal.azure.com/)"
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"[Azure OpenAI Studio](https://oai.azure.com/resource/overview)"
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"[View the source code](https://github.com/ks6088ts-labs/workshop-azure-openai/blob/main/apps/2_streamlit_chat/main.py)"
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st.title("Streamlit Chat")
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st.title("2_streamlit_chat")
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if not azure_openai_api_key or not azure_openai_endpoint or not azure_openai_api_version or not azure_openai_gpt_model:
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st.warning("サイドバーに Azure OpenAI の設定を入力してください")
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st.warning("Please fill in the required fields at the sidebar.")
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st.stop()
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if "messages" not in st.session_state:
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st.session_state["messages"] = [
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{
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"role": "assistant",
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"content": "こんにちは、何かお手伝いできますか？",
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"content": "Hello! I'm a helpful assistant.",
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}
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]
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# 既存のメッセージを表示
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# Show chat messages
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for msg in st.session_state.messages:
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st.chat_message(msg["role"]).write(msg["content"])
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# ユーザーからの入力を受け付ける
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# Receive user input
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if prompt := st.chat_input():
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client = AzureOpenAI(
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api_key=azure_openai_api_key,
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}
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)
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st.chat_message("user").write(prompt)
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with st.spinner("考え中..."):
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with st.spinner("Thinking..."):
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response = client.chat.completions.create(
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model=azure_openai_gpt_model,
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messages=st.session_state.messages,

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