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4 changes: 2 additions & 2 deletions 1_foundations/1_lab1.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -345,7 +345,7 @@
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"display_name": "agents",
"language": "python",
"name": "python3"
},
Expand All @@ -359,7 +359,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
"version": "3.12.12"
}
},
"nbformat": 4,
Expand Down
20 changes: 16 additions & 4 deletions 1_foundations/2_lab2.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -29,9 +29,21 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 2,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'dotenv'",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mModuleNotFoundError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 5\u001b[39m\n\u001b[32m 3\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mos\u001b[39;00m\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mjson\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m5\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mdotenv\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m load_dotenv\n\u001b[32m 6\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mopenai\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m OpenAI\n\u001b[32m 7\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01manthropic\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Anthropic\n",
"\u001b[31mModuleNotFoundError\u001b[39m: No module named 'dotenv'"
]
}
],
"source": [
"# Start with imports - ask ChatGPT to explain any package that you don't know\n",
"\n",
Expand Down Expand Up @@ -470,7 +482,7 @@
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -484,7 +496,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
"version": "3.14.3"
}
},
"nbformat": 4,
Expand Down
20 changes: 16 additions & 4 deletions 2_openai/1_lab1.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -31,9 +31,21 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 2,
"metadata": {},
"outputs": [],
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'dotenv'",
"output_type": "error",
"traceback": [
"\u001b[31m---------------------------------------------------------------------------\u001b[39m",
"\u001b[31mModuleNotFoundError\u001b[39m Traceback (most recent call last)",
"\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m 1\u001b[39m \u001b[38;5;66;03m# The imports\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mdotenv\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m load_dotenv\n\u001b[32m 4\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01magents\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m Agent, Runner, trace\n",
"\u001b[31mModuleNotFoundError\u001b[39m: No module named 'dotenv'"
]
}
],
"source": [
"# The imports\n",
"\n",
Expand Down Expand Up @@ -90,7 +102,7 @@
],
"metadata": {
"kernelspec": {
"display_name": ".venv",
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
Expand All @@ -104,7 +116,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
"version": "3.14.3"
}
},
"nbformat": 4,
Expand Down
3 changes: 3 additions & 0 deletions 3_crew/community_contributions/laundry_system/.gitignore
Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
.env
__pycache__/
.DS_Store
54 changes: 54 additions & 0 deletions 3_crew/community_contributions/laundry_system/README.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,54 @@
# LaundrySystem Crew

Welcome to the LaundrySystem Crew project, powered by [crewAI](https://crewai.com). This template is designed to help you set up a multi-agent AI system with ease, leveraging the powerful and flexible framework provided by crewAI. Our goal is to enable your agents to collaborate effectively on complex tasks, maximizing their collective intelligence and capabilities.

## Installation

Ensure you have Python >=3.10 <3.14 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.

First, if you haven't already, install uv:

```bash
pip install uv
```

Next, navigate to your project directory and install the dependencies:

(Optional) Lock the dependencies and install them by using the CLI command:
```bash
crewai install
```
### Customizing

**Add your `OPENAI_API_KEY` into the `.env` file**

- Modify `src/laundry_system/config/agents.yaml` to define your agents
- Modify `src/laundry_system/config/tasks.yaml` to define your tasks
- Modify `src/laundry_system/crew.py` to add your own logic, tools and specific args
- Modify `src/laundry_system/main.py` to add custom inputs for your agents and tasks

## Running the Project

To kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:

```bash
$ crewai run
```

This command initializes the laundry_system Crew, assembling the agents and assigning them tasks as defined in your configuration.

This example, unmodified, will run the create a `report.md` file with the output of a research on LLMs in the root folder.

## Understanding Your Crew

The laundry_system Crew is composed of multiple AI agents, each with unique roles, goals, and tools. These agents collaborate on a series of tasks, defined in `config/tasks.yaml`, leveraging their collective skills to achieve complex objectives. The `config/agents.yaml` file outlines the capabilities and configurations of each agent in your crew.

## Support

For support, questions, or feedback regarding the LaundrySystem Crew or crewAI.
- Visit our [documentation](https://docs.crewai.com)
- Reach out to us through our [GitHub repository](https://github.com/joaomdmoura/crewai)
- [Join our Discord](https://discord.com/invite/X4JWnZnxPb)
- [Chat with our docs](https://chatg.pt/DWjSBZn)

Let's create wonders together with the power and simplicity of crewAI.
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