Initial commit

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto

1-first-agent/.env.example

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+# 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=

1-first-agent/agents.py

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+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()

1-first-agent/requirements.txt

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+asana==5.0.0
+openai==1.10.0
+python-dotenv==0.13.0

LICENSE

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+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.

README.md

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+<div align="center">
+  <a href="https://www.youtube.com/channel/UCMwVTLZIRRUyyVrkjDpn4pA">
+    <img alt="AI Agents Masterclass" src="https://i.imgur.com/8Gr2pBA.png">
+    <h1 align="center">AI Agents Masterclass</h1>
+  </a>
+</div>
+
+<p align="center">
+  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.
+</p>
+
+<p align="center" style="margin-top: 25px">
+  <a href="#what-are-ai-agents"><strong>What are AI Agents?</strong></a> ·
+  <a href="#how-this-repo-works"><strong>How this Repo Works</strong></a> ·
+  <a href="#instructions-to-follow-along"><strong>Instructions to Follow Along</strong></a>
+</p>
+<br/>
+
+## 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:
+
+<div align="center" style="margin-top: 25px;margin-bottom:25px">
+<img width="700" alt="Trainers Ally LangGraph graph" src="https://i.imgur.com/ChRoV8W.png">
+</div>
+
+<br/>
+
+## 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.
+
+<br/>
+
+## 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
+```