add dev container

.devcontainer/Dockerfile

@@ -0,0 +1,23 @@
+FROM python:3.9-slim-bullseye AS base
+
+RUN set -x
+
+RUN apt-get update \
+    && apt-get -y install curl \
+    && apt-get -y install net-tools \
+    && apt-get -y install procps \
+    && apt-get -y install build-essential \
+    && apt-get -y install docker.io
+
+# specific pip version to workaround: https://github.com/conda/conda/issues/10178
+RUN pip install --upgrade pip==20.1.1
+RUN pip install ipython ipykernel
+RUN ipython kernel install --user --name aml
+
+# FROM base AS promptflow
+COPY default_requirements.txt .
+RUN pip install -r default_requirements.txt
+
+RUN set +x
+
+CMD bash

.devcontainer/README.md

@@ -0,0 +1,17 @@
+# Devcontainer for promptflow
+To facilitate your promptflow project development and empower you to work on LLM projects using promptflow more effectively, 
+we've configured the necessary environment for developing promptflow projects and utilizing flows through the dev container feature. 
+You can seamlessly initiate your promptflow project development and start leveraging flows by simply using the dev container feature via VS Code or Codespaces.
+
+# Use devcontainer
+1. Use vscode to open promptflow repo, and install vscode extension: Dev Containers and then open promptflow with dev containers.
+   ![devcontainer](./devcontainers.png)  
+   **About dev containers please refer to: [dev containers](https://code.visualstudio.com/docs/devcontainers/containers)**
+2. Use codespaces to open promptflow repo, it will automatically build the dev containers environment and open promptflow with dev containers.
+   ![codespaces](./codespaces.png)
+
+### Notes
+1. If you only want to try out promptflow without developing promptflow, you can simply install Docker and use promptflow within Docker without the need for using DevContainers functionality.
+   1. `docker build -t promptflow_container`
+   2. `docker run -it promptflow_container`
+2. When using the dev containers function, the promptflow and promptflow-tools installed in the container are the code of the current repo.

.devcontainer/default_requirements.txt

@@ -0,0 +1,5 @@
+azure-cli
+azure-identity
+opencensus-ext-azure
+promptflow[azure]
+promptflow-tools

.devcontainer/devcontainer.json

@@ -0,0 +1,25 @@
+{
+	"name": "Promptflow-Python39",
+	// "context" is the path that the Codespaces docker build command should be run from, relative to devcontainer.json
+	"context": ".",
+	"dockerFile": "Dockerfile",
+
+	// Set *default* container specific settings.json values on container create.
+	"settings": {
+		"terminal.integrated.shell.linux": "/bin/bash"
+	},
+
+	// Add the IDs of extensions you want installed when the container is created.
+	"extensions": [
+		"ms-python.python",
+		"ms-toolsai.vscode-ai",
+		"ms-toolsai.jupyter",
+		"redhat.vscode-yaml",
+		"prompt-flow.prompt-flow"
+	],
+
+	// Use 'postCreateCommand' to run commands after the container is created.
+	"postCreateCommand": "pip install -r ${containerWorkspaceFolder}/src/promptflow-tools/requirements.txt --force-reinstall;pip install -r ${containerWorkspaceFolder}/src/promptflow/dev_requirements.txt --force-reinstall;pip install -e ${containerWorkspaceFolder}/src/promptflow-tools;pip install -e ${containerWorkspaceFolder}/src/promptflow",
+
+	"runArgs": ["-v", "/var/run/docker.sock:/var/run/docker.sock"]
+}

examples/flows/standard/gen-docstring/main.py

@@ -3,14 +3,16 @@
 from diff import show_diff
 from load_code_tool import load_code
 from promptflow import PFClient
+from pathlib import Path
 
 
 if __name__ == "__main__":
+    current_folder = Path(__file__).absolute().parent
     parser = argparse.ArgumentParser(description="The code path of code that need to generate docstring.")
-    parser.add_argument("--source", help="Path for the code file", default='./azure_open_ai.py')
+    parser.add_argument("--source", help="Path for the code file", default=str(current_folder / 'azure_open_ai.py'))
     args = parser.parse_args()
 
     pf = PFClient()
     source = args.source
-    flow_result = pf.test(flow="./", inputs={"source": source})
+    flow_result = pf.test(flow=str(current_folder), inputs={"source": source})
     show_diff(load_code(source), flow_result['code'], File(source).filename)