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new sk-python-azure-functions-chatgpt-plugin starter
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‎README.md

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- [C# Hello World](sk-csharp-hello-world): The Hello World C# console application starter for the Semantic Kernel.
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- [C# Console Chat](sk-csharp-console-chat): A console application based chat starter for the Semantic Kernel.
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- [C# Azure Functions](sk-csharp-azure-functions): The Hello World C# Azure Functions starter for the Semantic Kernel.
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- [C# Azure ChatGPT Plugin](sk-csharp-chatgpt-plugin): The Joke ChatGPT Plugin starter using C# Azure Functions for the Semantic Kernel.
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- [Python Hello World](sk-python-hello-world): The Hello World Python console application starter for the Semantic Kernel.
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- [Python Azure Functions](sk-python-azure-functions): The Hello World Python Azure Functions starter for the Semantic Kernel.
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- [Python Azure Functions ChatGPT Plugin](sk-python-azure-functions-chatgpt-plugin): The Joke ChatGPT Plugin starter using Python Azure Functions for the Semantic Kernel.
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- [Python Flask ChatGPT Plugin](sk-python-flask-chatgpt-plugin): The Joke ChatGPT Plugin starter using Python Flask for the Semantic Kernel.
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- [Typescript Console Chat](sk-typescript-console-chat): A console application based chat starter for the Semantic Kernel.
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## Contributing

‎sk-python-azure-functions-chatgpt-plugin/.env.example

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OPENAI_API_KEY=""
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OPENAI_ORG_ID=""
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AZURE_OPENAI_DEPLOYMENT_NAME=""
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AZURE_OPENAI_ENDPOINT=""
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AZURE_OPENAI_API_KEY=""

‎sk-python-azure-functions-chatgpt-plugin/.funcignore

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.git*
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.vscode
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__azurite_db*__.json
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__blobstorage__
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__queuestorage__
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local.settings.json
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test
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.venv

‎sk-python-azure-functions-chatgpt-plugin/.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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pip-wheel-metadata/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don’t work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# celery beat schedule file
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celerybeat-schedule
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# Azure Functions artifacts
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bin
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obj
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appsettings.json
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# Azurite artifacts
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__blobstorage__
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__queuestorage__
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__azurite_db*__.json
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.python_packages

‎sk-python-azure-functions-chatgpt-plugin/.vscode/extensions.json

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{
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"recommendations": [
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"ms-azuretools.vscode-azurefunctions",
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"ms-python.python",
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"azurite.azurite",
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"ms-semantic-kernel.semantic-kernel",
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]
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}

‎sk-python-azure-functions-chatgpt-plugin/.vscode/launch.json

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{
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"version": "0.2.0",
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"configurations": [
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{
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"name": "Attach to Python Functions",
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"type": "python",
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"request": "attach",
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"port": 9091,
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"preLaunchTask": "func: host start"
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}
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]
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}

‎sk-python-azure-functions-chatgpt-plugin/.vscode/settings.json

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{
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"azureFunctions.deploySubpath": ".",
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"azureFunctions.scmDoBuildDuringDeployment": true,
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"azureFunctions.pythonVenv": ".venv",
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"azureFunctions.projectLanguage": "Python",
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"azureFunctions.projectRuntime": "~4",
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"debug.internalConsoleOptions": "neverOpen",
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"azureFunctions.projectLanguageModel": 2
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}

‎sk-python-azure-functions-chatgpt-plugin/.vscode/tasks.json

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{
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"version": "2.0.0",
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"tasks": [
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{
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"type": "func",
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"label": "func: host start",
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"command": "host start",
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"problemMatcher": "$func-python-watch",
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"isBackground": true,
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"dependsOn": "pip install (functions)"
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},
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{
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"label": "create venv",
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"type": "shell",
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"command": "python -m venv .venv || echo 0",
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"group": {
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"kind": "build",
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"isDefault": true
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}
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},
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{
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"label": "pip install (functions)",
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"type": "shell",
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"osx": {
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"command": "${config:azureFunctions.pythonVenv}/bin/python -m pip install -r requirements.txt"
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},
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"windows": {
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"command": "${config:azureFunctions.pythonVenv}\\Scripts\\python -m pip install -r requirements.txt"
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},
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"linux": {
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"command": "${config:azureFunctions.pythonVenv}/bin/python -m pip install -r requirements.txt"
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},
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"problemMatcher": [],
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"dependsOn": "create venv"
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}
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]
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}

‎sk-python-azure-functions-chatgpt-plugin/.well-known/ai-plugin.json

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{
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"schema_version": "v1",
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"name_for_human": "Fun Plugin",
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"name_for_model": "FunPlugin",
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"description_for_human": "Execute fun skills such as jokes, excuses and limericks.",
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"description_for_model": "A plugin for using semantic kernel fun skills.",
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"auth": {
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"type": "none"
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},
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"api": {
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"type": "openapi",
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"url": "http://localhost:7071/openapi.yaml"
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},
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"logo_url": "http://localhost:7071/logo.png",
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"contact_email": "[email protected]",
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"legal_info_url": "http://example.com/legal"
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}

‎sk-python-azure-functions-chatgpt-plugin/README.md

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# Semantic Kernel Python Azure Functions Starter
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The `sk-python-azure-functions` application demonstrates how to execute a semantic function within an Azure Function.
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## Prerequisites
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- [Python](https://www.python.org/downloads/) >=3.8 and <3.11
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- [Azure Functions](https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-azurefunctions)
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- [Azurite](https://marketplace.visualstudio.com/items?itemName=Azurite.azurite). Run the services from the VS Code status bar.
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- [Semantic Kernel Tools](https://marketplace.visualstudio.com/items?itemName=ms-semantic-kernel.semantic-kernel)
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## Configuring the starter
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The starter can be configured with a `.env` file in the project which holds api keys and other secrets and configurations.
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Make sure you have an
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[Open AI API Key](https://openai.com/api/) or
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[Azure Open AI service key](https://learn.microsoft.com/azure/cognitive-services/openai/quickstart?pivots=rest-api)
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Copy the `.env.example` file to a new file named `.env`. Then, copy those keys into the `.env` file:
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```
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OPENAI_API_KEY=""
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OPENAI_ORG_ID=""
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AZURE_OPENAI_DEPLOYMENT_NAME=""
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AZURE_OPENAI_ENDPOINT=""
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AZURE_OPENAI_API_KEY=""
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```
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## Running the starter
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To run the console application within Visual Studio Code, run Azurite from the status bar or command pallette, then just hit `F5`.
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As configured in `launch.json` and `tasks.json`, Visual Studio Code will create a virtual environment at `.venv` and run `pip install requirements.txt`.
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To run from command line, run the following:
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```
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python -m venv .venv
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.venv\Scripts\python -m pip install -r requirements.txt # Location of python within venv depends on OS
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.venv\Scripts\activate
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func host start
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```
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## Using the starter
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In your browser, visit `http://localhost:7071/api/skills/{skill_name/functions/{function_name}` to execute a skill.
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For example, `http://localhost:7071/api/skills/FunSkill/functions/Joke` will execute the example Joke function in the FunSkill skill.
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To provide input, send a POST request with a JSON body, e.g. provide this as input to the Joke function:
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`{"input": "time traveling to dinosaur age", "style": "deadpan"}`

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