From 18e585b9e06b77063157fbf06df891735b19bd16 Mon Sep 17 00:00:00 2001
From: Cole Medin <47287758+coleam00@users.noreply.github.com>
Date: Sun, 23 Jun 2024 15:14:49 -0500
Subject: [PATCH] Initial commit
---
.gitattributes | 2 +
1-first-agent/.env.example | 20 +++++
1-first-agent/agents.py | 144 +++++++++++++++++++++++++++++++++
1-first-agent/requirements.txt | 3 +
LICENSE | 21 +++++
README.md | 80 ++++++++++++++++++
6 files changed, 270 insertions(+)
create mode 100644 .gitattributes
create mode 100644 1-first-agent/.env.example
create mode 100644 1-first-agent/agents.py
create mode 100644 1-first-agent/requirements.txt
create mode 100644 LICENSE
create mode 100644 README.md
diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..dfe0770
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+# Auto detect text files and perform LF normalization
+* text=auto
diff --git a/1-first-agent/.env.example b/1-first-agent/.env.example
new file mode 100644
index 0000000..1be90a0
--- /dev/null
+++ b/1-first-agent/.env.example
@@ -0,0 +1,20 @@
+# Rename this file to .env once you have filled in the below environment variables!
+
+# Get your Open AI API Key by following these instructions -
+https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key
+OPENAI_API_KEY=
+
+# See all Open AI models you can use here -
+# https://platform.openai.com/docs/models
+# A good default to go with here is gpt-4o
+OPENAI_MODEL=
+
+# Get your personal Asana access token through the developer console in Asana.
+# Feel free to follow these instructions -
+# https://developers.asana.com/docs/personal-access-token
+ASANA_ACCESS_TOKEN=
+
+# The Asana project ID is in the URL when you visit a project in the Asana UI.
+# If your URL is https://app.asana.com/0/123456789/1212121212, then your
+# Asana project ID is 123456789
+ASANA_PROJECT_ID=
\ No newline at end of file
diff --git a/1-first-agent/agents.py b/1-first-agent/agents.py
new file mode 100644
index 0000000..05b74e9
--- /dev/null
+++ b/1-first-agent/agents.py
@@ -0,0 +1,144 @@
+import asana
+from asana.rest import ApiException
+from openai import OpenAI
+from dotenv import load_dotenv
+from datetime import datetime
+import json
+import os
+
+load_dotenv()
+
+client = OpenAI()
+model = os.getenv('OPENAI_MODEL', 'gpt-4o')
+
+configuration = asana.Configuration()
+configuration.access_token = os.getenv('ASANA_ACCESS_TOKEN', '')
+api_client = asana.ApiClient(configuration)
+
+tasks_api_instance = asana.TasksApi(api_client)
+
+def create_asana_task(task_name, due_on="today"):
+ """
+ Creates a task in Asana given the name of the task and when it is due
+
+ Example call:
+
+ create_asana_task("Test Task", "2024-06-24")
+ Args:
+ task_name (str): The name of the task in Asana
+ due_on (str): The date the task is due in the format YYYY-MM-DD. If not given, the current day is used
+ Returns:
+ str: The API response of adding the task to Asana or an error message if the API call threw an error
+ """
+ if due_on == "today":
+ due_on = str(datetime.now().date())
+
+ task_body = {
+ "data": {
+ "name": task_name,
+ "due_on": due_on,
+ "projects": [os.getenv("ASANA_PROJECT_ID", "")]
+ }
+ }
+
+ try:
+ api_response = tasks_api_instance.create_task(task_body, {})
+ return json.dumps(api_response, indent=2)
+ except ApiException as e:
+ return f"Exception when calling TasksApi->create_task: {e}"
+
+def get_tools():
+ tools = [
+ {
+ "type": "function",
+ "function": {
+ "name": "create_asana_task",
+ "description": "Creates a task in Asana given the name of the task and when it is due",
+ "parameters": {
+ "type": "object",
+ "properties": {
+ "task_name": {
+ "type": "string",
+ "description": "The name of the task in Asana"
+ },
+ "due_on": {
+ "type": "string",
+ "description": "The date the task is due in the format YYYY-MM-DD. If not given, the current day is used"
+ },
+ },
+ "required": ["task_name"]
+ },
+ },
+ }
+ ]
+
+ return tools
+
+def prompt_ai(messages):
+ # First, prompt the AI with the latest user message
+ completion = client.chat.completions.create(
+ model=model,
+ messages=messages,
+ tools=get_tools()
+ )
+
+ response_message = completion.choices[0].message
+ tool_calls = response_message.tool_calls
+
+ # Second, see if the AI decided it needs to invoke a tool
+ if tool_calls:
+ # If the AI decided to invoke a tool, invoke it
+ available_functions = {
+ "create_asana_task": create_asana_task
+ }
+
+ # Add the tool request to the list of messages so the AI knows later it invoked the tool
+ messages.append(response_message)
+
+ # Next, for each tool the AI wanted to call, call it and add the tool result to the list of messages
+ for tool_call in tool_calls:
+ function_name = tool_call.function.name
+ function_to_call = available_functions[function_name]
+ function_args = json.loads(tool_call.function.arguments)
+ function_response = function_to_call(**function_args)
+
+ messages.append({
+ "tool_call_id": tool_call.id,
+ "role": "tool",
+ "name": function_name,
+ "content": function_response
+ })
+
+ # Call the AI again so it can produce a response with the result of calling the tool(s)
+ second_response = client.chat.completions.create(
+ model=model,
+ messages=messages,
+ )
+
+ return second_response.choices[0].message.content
+
+ return response_message.content
+
+def main():
+ messages = [
+ {
+ "role": "system",
+ "content": f"You are a personal assistant who helps manage tasks in Asana. The current date is: {datetime.now().date()}"
+ }
+ ]
+
+ while True:
+ user_input = input("Chat with AI (q to quit): ").strip()
+
+ if user_input == 'q':
+ break
+
+ messages.append({"role": "user", "content": user_input})
+ ai_response = prompt_ai(messages)
+
+ print(ai_response)
+ messages.append({"role": "assistant", "content": ai_response})
+
+
+if __name__ == "__main__":
+ main()
\ No newline at end of file
diff --git a/1-first-agent/requirements.txt b/1-first-agent/requirements.txt
new file mode 100644
index 0000000..bf0a03c
--- /dev/null
+++ b/1-first-agent/requirements.txt
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+asana==5.0.0
+openai==1.10.0
+python-dotenv==0.13.0
\ No newline at end of file
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..b05a952
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 Cole Medin
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..54388b7
--- /dev/null
+++ b/README.md
@@ -0,0 +1,80 @@
+
+
+
+ Artificial Intelligence is the #1 thing for all developers to spend their time on now.
+ The problem is, most developers aren't focusing on AI agents, which is the real way to unleash the full power of AI.
+ This is why I'm creating this AI Agents Masterclass - so I can show YOU how to use AI agents to transform
+ businesses and create incredibly powerful software like I've already done many times!
+ Click the image or link above to go to the masterclass on YouTube.
+
+
+
+ What are AI Agents? ·
+ How this Repo Works ·
+ Instructions to Follow Along
+
+
+
+## What are AI Agents?
+
+AI agents are simply Large Language Models that have been given the ability to interact with the outside world. They
+can do things like draft emails, book appointments in your CRM, create tasks in your task management software, and
+really anything you can dream of! I hope that everything I show here can really help you dream big
+and create incredible things with AI!
+
+AI agents can be very powerful without having to create a lot of code. That doesn't mean there isn't room though
+to create more complex applications to tie together many different agents to accomplish truly incredible things!
+That's where we'll be heading with this masterclass and I really look forward to it!
+
+Below is a very basic diagram just to get an idea of what an AI agent looks like:
+
+
+
+
+
+## How this Repo Works
+
+Each week there will be a new video for my AI Agents Masterclass! Each video will have its own folder
+in this repo, starting with [/1-first-agent/](/1-first-agent) for the first video in the masterclass
+where I create our very first AI agent!
+
+The code in each folder will be exactly what I used/created in the accompanying masterclass video.
+
+
+
+## Instructions to Follow Along
+
+The below instructions assume you already have Git, Python, and Pip installed. If you do not, you can install
+[Python + Pip from here](https://www.python.org/downloads/) and [Git from here](https://git-scm.com/).
+
+To follow along with any of my videos, first clone this GitHub repository, open up a terminal,
+and change your directory to the folder for the current video you are watching (example: 1st video is [/1-first-agent/](/1-first-agent)).
+
+The below instructions work on any OS - Windows, Linux, or Mac!
+
+You will need to use the environment variables defined in the .env.example file in the folder (example for the first video: [`1-first-agent/.env.example`](/1-first-agent/.env.example)) to set up your API keys and other configuration. Turn the .env.example file into a `.env` file, and supply the necessary environment variables.
+
+After setting up the .env file, run the below commands to create a Python virtual environment and install the necessary Python packages to run the code from the masterclass. Creating a virtual environment is optional but recommended! Creating a virtual environment for the entire masterclass is a one time thing. Make sure to run the pip install for each video though!
+
+```bash
+python -m venv ai-agents-masterclass
+
+On Windows: .\ai-agents-masterclass\Scripts\activate
+On MacOS/Linux: source ai-agents-masterclass/bin/activate
+
+cd 1-first-agent (or whichever folder)
+pip install -r requirements.txt
+```
+
+Then, you can execute the code in the folder with:
+
+```bash
+python [script name].py
+```
+