Create new readme file (#558)

* fixes * New README --------- Co-authored-by: Harish Mohan Raj <[email protected]>
airtai · Nov 12, 2024 · a46ee63 · a46ee63
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diff --git a/README.md b/README.md
diff --git a/docs/docs/en/example.md b/docs/docs/en/example.md
@@ -0,0 +1,176 @@
+## Quick Start
+
+### Project setup
+
+We **strongly recommend** using [**Cookiecutter**](../cookiecutter/index.md) for setting up a FastAgency project. It creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"} for development.
+
+1. Install Cookiecutter with the following command:
+    ```console
+    pip install cookiecutter
+    ```
+
+2. Run the `cookiecutter` command:
+    ```console
+    cookiecutter https://github.com/airtai/cookiecutter-fastagency.git
+    ```
+
+3. Assuming that you used the default values, you should get the following output:
+    ```console
+    [1/4] project_name (My FastAgency App):
+    [2/4] project_slug (my_fastagency_app):
+    [3/4] Select app_type
+        1 - fastapi+mesop
+        2 - mesop
+        3 - nats+fastapi+mesop
+        Choose from [1/2/3] (1): 1
+    [4/4] Select python_version
+        1 - 3.12
+        2 - 3.11
+        3 - 3.10
+        Choose from [1/2/3] (1):
+    [5/5] Select authentication
+        1 - none
+        2 - google
+        Choose from [1/2] (1):
+    ```
+
+4. To run LLM-based applications, you need an API key for the LLM used. The most commonly used LLM is [OpenAI](https://platform.openai.com/docs/models). To use it, create an [OpenAI API Key](https://openai.com/index/openai-api/) and set it as an environment variable in the terminal using the following command:
+
+    ```console
+    export OPENAI_API_KEY=openai_api_key_here
+    ```
+
+5. Open the generated project in [Visual Studio Code](https://code.visualstudio.com/){target="_blank"} with the following command:
+    ```console
+    code my_fastagency_app
+    ```
+
+6. Once the project is opened, you will get the following option to reopen it in a devcontainer:
+
+    <img src="https://fastagency.ai/0.3/user-guide/getting-started/images/reopen-in-container.png" width="600" class="center">
+
+7. After reopening the project in devcontainer, you can verify that the setup is correct by running the provided tests with the following command:
+
+    ```console
+    pytest -s
+    ```
+
+    You should get the following output if everything is correctly setup.
+    ```console
+    =================================== test session starts ===================================
+    platform linux -- Python 3.12.7, pytest-8.3.3, pluggy-1.5.0
+    rootdir: /workspaces/my_fastagency_app
+    configfile: pyproject.toml
+    plugins: asyncio-0.24.0, anyio-4.6.2.post1
+    asyncio: mode=Mode.STRICT, default_loop_scope=None
+    collected 1 item
+
+    tests/test_workflow.py .                                                            [100%]
+
+    ==================================== 1 passed in 1.02s ====================================
+    ```
+-----
+
+### Workflow Development
+
+#### Define the Workflow
+
+You need to define the workflow that your application will use. This is where you specify how the agents interact and what they do. Here's a simple example of a workflow definition as it is generated by the cookie cutter under `my_fastagency_app/workflow.py`:
+
+```python
+import os
+from typing import Any
+
+from autogen.agentchat import ConversableAgent
+from fastagency import UI
+from fastagency.runtimes.autogen import AutoGenWorkflows
+
+llm_config = {
+    "config_list": [
+        {
+            "model": "gpt-4o-mini",
+            "api_key": os.getenv("OPENAI_API_KEY"),
+        }
+    ],
+    "temperature": 0.8,
+}
+
+wf = AutoGenWorkflows()
+
+
+@wf.register(name="simple_learning", description="Student and teacher learning chat")  # type: ignore[misc]
+def simple_workflow(ui: UI, params: dict[str, Any]) -> str:
+    initial_message = ui.text_input(
+        sender="Workflow",
+        recipient="User",
+        prompt="I can help you learn about mathematics. What subject you would like to explore?",
+    )
+
+    student_agent = ConversableAgent(
+        name="Student_Agent",
+        system_message="You are a student willing to learn.",
+        llm_config=llm_config,
+    )
+    teacher_agent = ConversableAgent(
+        name="Teacher_Agent",
+        system_message="You are a math teacher.",
+        llm_config=llm_config,
+    )
+
+    chat_result = student_agent.initiate_chat(
+        teacher_agent,
+        message=initial_message,
+        summary_method="reflection_with_llm",
+        max_turns=3,
+    )
+
+    return str(chat_result.summary)
+```
+
+This code snippet sets up a simple learning chat between a student and a teacher. It defines the agents and how they should interact and specify how the conversation should be summarized.
+
+#### Run and Debug the Workflow
+
+To ensure that the workflow we have defined is working properly, we can test it locally using MesopUI. The code below can be found under `my_fastagency_app/local/main_mesop.py` and imports the defined workflow and sets up MesopUI.
+
+You can run the Mesop application locally with the following command on Linux and MacOS:
+
+```console
+gunicorn my_fastagency_app.local.main_mesop:app
+```
+
+On Windows, please use the following command:
+```console
+waitress-serve --listen=0.0.0.0:8000 my_fastagency_app.local.main_mesop:app
+```
+
+Open the MesopUI URL [http://localhost:8000](http://localhost:8000) in your browser. You can now use the graphical user interface to start, run, test and debug the autogen workflow manually.
+
+![Initial message](https://fastagency.ai/latest/user-guide/getting-started/images/chat-init.png)
+
+
+## Deployment
+
+### Building the Docker Image
+
+If you created the project using Cookiecutter, then building the Docker image is as simple as running the provided script, as shown below:
+
+```console
+./scripts/build_docker.sh
+```
+
+### Running the Docker Image
+
+Similarly, running the Docker container is as simple as running the provided script, as shown below:
+
+```console
+./scripts/run_docker.sh
+```
+
+### Deploying to Fly.io
+
+If you created the project using Cookiecutter, there is a built-in script to deploy your workflow to [**Fly.io**](https://fly.io/). Run it as shown below:
+
+```console
+./scripts/deploy_to_fly_io.sh
+```
diff --git a/docs/docs/en/features.md b/docs/docs/en/features.md
@@ -11,6 +11,8 @@ search:
   boost: 10
 ---
 
+<!-- README starts here -->
+
 # FastAgency
 
 
@@ -70,7 +72,7 @@ search:
 For start, FastAgency is not yet another agentic AI framework. There are many such
 frameworks available today, the most popular open-source ones being [**AutoGen**](https://github.com/microsoft/autogen){target="_blank"}, [**CrewAI**](https://www.crewai.com/){target="_blank"}, [**Swarm**](https://github.com/openai/swarm){target="_blank"} and [**LangGraph**](https://github.com/langchain-ai/langgraph){target="_blank"}. FastAgency provides you with a unified programming interface for deploying agentic workflows written in above agentic frameworks in both development and productional settings (current version supports [**AutoGen**](https://github.com/microsoft/autogen){target="_blank"} only, but other frameworks will be supported very soon). With only a few lines of code, you can create a web chat application or REST API service interacting with agents of your choice. If you need to scale-up your workloads, FastAgency can help you deploy a fully distributed system using internal message brokers coordinating multiple machines in multiple datacenters with just a few lines of code changed from your local development setup.
 
-**FastAgency** is an open-source framework designed to accelerate the transition from prototype to production for multi-agent AI workflows. For developers who use the AutoGen framework, FastAgency enables you to seamlessly scale Jupyter notebook prototypes into fully functional, production-ready applications. With multi-framework support, a unified programming interface, and powerful API integration capabilities, FastAgency streamlines the deployment process, saving time and effort while maintaining flexibility and performance.
+**FastAgency** is an open-source framework designed to accelerate the transition from prototype to production for multi-agent AI workflows. For developers who use the AutoGen framework, FastAgency enables you to seamlessly scale Jupyter notebook prototypes into a fully functional, production-ready applications. With multi-framework support, a unified programming interface, and powerful API integration capabilities, FastAgency streamlines the deployment process, saving time and effort while maintaining flexibility and performance.
 
 Whether you're orchestrating complex AI agents or integrating external APIs into workflows, FastAgency provides the tools necessary to quickly transition from concept to production, reducing development cycles and allowing you to focus on optimizing your multi-agent systems.
 
@@ -80,7 +82,7 @@ Whether you're orchestrating complex AI agents or integrating external APIs into
 
 - [**Unified Programming Interface Across UIs**](user-guide/ui/index.md): FastAgency features a **common programming interface** that enables you to develop your core workflows once and reuse them across various user interfaces without rewriting code. This includes support for both **console-based applications** via `ConsoleUI` and **web-based applications** via `MesopUI`. Whether you need a command-line tool or a fully interactive web app, FastAgency allows you to deploy the same underlying workflows across environments, saving development time and ensuring consistency.
 
-- [**Seamless External API Integration**](user-guide/api/index.md): One of FastAgency's standout features is its ability to easily integrate external APIs into your agent workflows. With just a **single line of code**, you can import an OpenAPI specification, and in only one more line, you can connect it to your agents. This dramatically simplifies the process of enhancing AI agents with real-time data, external processing, or third-party services. For example, you can easily integrate a weather API to provide dynamic, real-time weather updates to your users, making your application more interactive and useful with minimal effort.
+- [**Seamless External API Integration**](user-guide/api/index.md): One of FastAgency's standout features is its ability to easily integrate external APIs into your agent workflows. With just a **few lines of code**, you can import an OpenAPI specification, and in only one more line, you can connect it to your agents. This dramatically simplifies the process of enhancing AI agents with real-time data, external processing, or third-party services. For example, you can easily integrate a weather API to provide dynamic, real-time weather updates to your users, making your application more interactive and useful with minimal effort.
 
 - [**Tester Class for Continuous Integration**](user-guide/testing/index.md): FastAgency also provides a **Tester Class** that enables developers to write and execute tests for their multi-agent workflows. This feature is crucial for maintaining the reliability and robustness of your application, allowing you to automatically verify agent behavior and interactions. The Tester Class is designed to integrate smoothly with **continuous integration (CI)** pipelines, helping you catch bugs early and ensure that your workflows remain functional as they scale into production.
 
@@ -115,6 +117,7 @@ support the following network adapters:
 - [**NATS.io**](https://nats.io/){target="_blank"} via [**FastStream**](https://github.com/airtai/faststream){target="_blank"}: Utilize the [**`NatsAdapter`**](../api/fastagency/adapters/nats/NatsAdapter.md) to use [**NATS.io MQ**](https://nats.io/){target="_blank"} message broker for highly-scalable, production-ready setup. This interface is suitable for setups in VPN-s or, in combination with the [**`FastAPIAdapter`**](../api/fastagency/adapters/fastapi/FastAPIAdapter.md) to serve public workflows in an authenticated, secure manner.
 
 
+<!-- README insert example here -->
 
 ## Future Plans
 

diff --git a/docs/docs/en/user-guide/adapters/fastapi/index.md b/docs/docs/en/user-guide/adapters/fastapi/index.md
@@ -180,7 +180,7 @@ This section provides [**high-level architecture**](https://en.wikipedia.org/wik
 
 ## Installation
 
-We **strongly recommend** using [**Cookiecutter**](../cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
+We **strongly recommend** using [**Cookiecutter**](../../../user-guide/cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
 
 You can setup the project using Cookiecutter by following the [**project setup guide**](../../../user-guide/cookiecutter/index.md).
 

diff --git a/docs/docs/en/user-guide/adapters/fastapi_nats/index.md b/docs/docs/en/user-guide/adapters/fastapi_nats/index.md
@@ -84,7 +84,7 @@ Now, it's time to see the [**`FastAPIAdapter`**](../../../api/fastagency/adapter
 
 ## Installation
 
-We **strongly recommend** using [**Cookiecutter**](../cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
+We **strongly recommend** using [**Cookiecutter**](../../../user-guide/cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
 
 You can setup the project using Cookiecutter by following the [**project setup guide**](../../../user-guide/cookiecutter/index.md).
 

diff --git a/docs/docs/en/user-guide/adapters/nats/index.md b/docs/docs/en/user-guide/adapters/nats/index.md
@@ -40,7 +40,7 @@ Now, it's time to see the Nats Adapter using FastAgency in action. Let's dive in
 
 ## Installation
 
-We **strongly recommend** using [**Cookiecutter**](../cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
+We **strongly recommend** using [**Cookiecutter**](../../../user-guide/cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
 
 You can setup the project using Cookiecutter by following the [**project setup guide**](../../../user-guide/cookiecutter/index.md).
 

diff --git a/docs/docs/en/user-guide/api/openapi/index.md b/docs/docs/en/user-guide/api/openapi/index.md
@@ -11,7 +11,7 @@ In this example, we'll use a simple [weather API](https://weather.tools.fastagen
 
 ## Install
 
-We **strongly recommend** using [**Cookiecutter**](../cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
+We **strongly recommend** using [**Cookiecutter**](../../../user-guide/cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
 
 You can setup the project using Cookiecutter by following the [**project setup guide**](../../../user-guide/cookiecutter/index.md).
 

diff --git a/docs/docs/en/user-guide/cookiecutter/index.md b/docs/docs/en/user-guide/cookiecutter/index.md
@@ -30,6 +30,10 @@ Cookiecutter creates projects from cookiecutters (project templates), e.g. Pytho
             2 - 3.11
             3 - 3.10
             Choose from [1/2/3] (1):
+        [5/5] Select authentication
+            1 - none
+            2 - google
+            Choose from [1/2] (1):
         ```
 
         This command installs FastAgency with support for both the Console and Mesop interfaces for AutoGen workflows.
@@ -48,6 +52,10 @@ Cookiecutter creates projects from cookiecutters (project templates), e.g. Pytho
             2 - 3.11
             3 - 3.10
             Choose from [1/2/3] (1):
+        [5/5] Select authentication
+            1 - none
+            2 - google
+            Choose from [1/2] (1):
         ```
 
         This command installs FastAgency with support for both the Console and Mesop interfaces for AutoGen workflows, with FastAPI handling input requests and workflow execution.
@@ -66,6 +74,10 @@ Cookiecutter creates projects from cookiecutters (project templates), e.g. Pytho
             2 - 3.11
             3 - 3.10
             Choose from [1/2/3] (1):
+        [5/5] Select authentication
+            1 - none
+            2 - google
+            Choose from [1/2] (1):
         ```
 
         This command installs FastAgency with support for both the Console and Mesop interfaces for AutoGen workflows, with FastAPI serving input and independent workers communicating over the NATS.io protocol workflows. This is the most scable setup, recommended for large production workloads.

diff --git a/docs/docs/en/user-guide/runtimes/autogen/index.md b/docs/docs/en/user-guide/runtimes/autogen/index.md
@@ -6,7 +6,7 @@ In this example, we will create a simple weather [**chatbot**](https://en.wikipe
 
 ## Installation
 
-We **strongly recommend** using [**Cookiecutter**](../cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
+We **strongly recommend** using [**Cookiecutter**](../../../user-guide/cookiecutter/index.md) for setting up the project. Cookiecutter creates the project folder structure, default workflow, automatically installs all the necessary requirements, and creates a [devcontainer](https://code.visualstudio.com/docs/devcontainers/containers){target="_blank"} that can be used with [Visual Studio Code](https://code.visualstudio.com/){target="_blank"}.
 
 You can setup the project using Cookiecutter by following the [**project setup guide**](../../../user-guide/cookiecutter/index.md).