How To Connect Llama3 to CrewAI [Groq + Ollama]
TLDRIn this informative video, the host guides viewers on how to utilize Llama 3 with Crew AI for creating Instagram content, specifically for advertising a smart thermos. The video is divided into three main sections: an introduction to Llama 3, its comparison with other language models, and a live demo; a tutorial on running a Crew using Llama 3 locally with Olama; and an exploration of enhancing the Crew's performance with Gro, accessing the more powerful 7 billion parameter version of Llama 3. The host also provides a source code for free, invites viewers to join a supportive AI development community, and concludes with a demonstration of the Crew's ability to generate compelling Instagram posts and images using Llama 3, showcasing its capabilities in content creation and efficiency.
Takeaways
- 🚀 **Introduction to Llama 3**: The video introduces Llama 3, the third generation of Meta's open-source large language model, and compares it to other models like Chat GPT 4.
- 🔍 **Context Window Enhancement**: Llama 3 has doubled the context window to 8,000 tokens, making it more comparable to other advanced models.
- 🤖 **Cooperative Model Behavior**: Newer versions of Llama are more cooperative and user-friendly, willing to engage in tasks that previous models might refuse.
- 📈 **Parameter Versions**: Llama 3 comes in two versions: an 8 billion parameter model suitable for local running and a 70 billion parameter model for more complex tasks.
- 💻 **Local Deployment with Ollama**: The video demonstrates how to run Llama 3 locally using Ollama, allowing for free and private use of the model on your own computer.
- 🌐 **Internet Access for Agents**: The Crew AI agents used in the video can search the internet and Instagram to gather information for tasks such as creating marketing content.
- 🎨 **Content Creation with Crew AI**: The video showcases how to use Crew AI to generate Instagram posts, including text and mid-journey descriptions for image creation.
- ⚙️ **Switching to Groq**: The tutorial explains how to switch the model used by Crew AI from Llama 3 local to Groq, which allows for faster processing and access to the larger 70 billion parameter model of Llama 3.
- 📊 **Performance Comparison**: Llama 3 is shown to be faster than Chat GPT 4 in terms of tokens per second, with the 8 billion parameter model being particularly quick for local tasks.
- 🚧 **Rate Limiting**: When using Groq with Llama 3's larger model, the video addresses rate limiting issues and provides a workaround by adjusting the requests per minute.
- 📚 **Community and Source Code**: The creator offers a community for support and free source code for those following the tutorial, making it easier to set up and start experimenting.
Q & A
What is the main topic of the video?
-The main topic of the video is teaching viewers how to use Llama 3 with Crew AI to run their AI crews completely for free.
What are the three major parts covered in the video?
-The three major parts covered in the video are: an introduction to Llama 3 and its comparison to other language models, a live demo of Llama 3, running a Crew using Llama 3 locally on a personal computer with Ollama, and updating the crew to work with Gro for faster processing.
What is Llama 3?
-Llama 3 is the third generation of Meta's open-source large language model known as Llama. It has seen significant improvements such as a doubled context window and a more cooperative model behavior.
How does Llama 3 compare to other language models?
-Llama 3, particularly the 8 billion parameter model, performs well on most fronts when compared to other models like MISTOL and JIMMA. The 70 billion parameter model is also highly competitive, showing intelligence and speed that rivals Chat GPT 4.
What is the purpose of the Instagram post generating crew?
-The purpose of the Instagram post generating crew is to create text and images for an Instagram post to advertise a product, in this case, a smart thermos that keeps coffee hot all day.
How can one access the source code mentioned in the video?
-The source code is available for free. Interested individuals can find the download link in the video description.
What is the benefit of using Gro with Llama 3?
-Using Gro with Llama 3 allows for faster processing of tasks and access to the larger 7 billion parameter version of Llama 3, which provides more complex and intelligent responses.
What is Ollama and how is it used in the video?
-Ollama is a tool that allows users to run large language models like Llama 3 locally on their own computer for free, keeping their data private. In the video, it's used to set up and run a custom Llama 3 model specialized for working with Crew AI.
How does the video presenter handle issues that viewers might encounter?
-The presenter has created a school community where viewers can post problems they're having with their code, along with screenshots, and receive help from the presenter or other developers in the community.
What is the importance of large language models as demonstrated in the video?
-Large language models are important because they can process and generate human-like text, making them useful for a variety of applications, such as creating content for social media posts, which is the focus of the video.
What is the rate limit issue and how is it resolved in the video?
-The rate limit issue occurs when using Gro, where there is a maximum number of tokens that can be used per minute. In the video, the presenter resolves this by setting the maximum number of requests per minute (RPM Max) to two, which is a temporary workaround to avoid getting rate-limited.
Outlines
🚀 Introduction to Llama 3 and Crew AI
The video introduces Llama 3, a third-generation large language model by Meta, and its integration with Crew AI for running AI-driven tasks. It outlines the video's agenda, which includes understanding Llama 3, comparing it with other models, a live demo, and using it with Crew AI to generate Instagram posts for a smart thermos product. The presenter also mentions the availability of the source code for free and invites viewers to join a community for support.
📚 Llama 3 Overview and Setup with Ollama
This paragraph provides an overview of Llama 3, discussing its improvements over the previous version, such as a doubled context window and a more cooperative model behavior. It also covers the two versions of Llama 3: the 8 billion parameter model suitable for local use and the 70 billion parameter model for more complex tasks. The presenter guides viewers on how to download and set up Ollama, a tool for running Llama 3 locally, and emphasizes the importance of choosing the right model size for one's computer capabilities.
🤖 Customizing Llama 3 for Crew AI
The presenter explains how to customize Llama 3 to work with Crew AI by creating a model file that defines specific properties for the custom large language model. It details the process of setting up parameters for the model to listen for the keyword 'stop'. The video then demonstrates how to create a new, specialized Llama 3 model for the Crew using a command in the terminal. The presenter also shows how to set up the environment and build the Crew in Visual Studio Code.
🔧 Setting Up and Running the Crew
The video describes setting up the environment for the Crew project using the 'poetry' tool to manage dependencies and create a Python virtual environment. It outlines the structure of the 'main.py' file, which includes setting up agents and tasks for the Crew. The agents are responsible for internet and Instagram searches, market analysis, and copywriting for Instagram ads. The presenter also explains how to use Llama 3 with Crew AI by updating the LLM property in the agents' class to reference the local Llama 3 model.
🚀 Enhancing Crew Performance with Gro
The presenter demonstrates how to enhance the Crew's performance by using Gro, a platform that allows running large language models on specialized chipsets. It shows the process of switching the LLM from the local Llama 3 to Gro's Llama 3 model. The video also covers how to obtain a Gro API key and use it within the Crew setup. It discusses the rate-limiting issue that arises when using Gro and provides a workaround by setting a maximum number of requests per minute for the Crew to execute.
🎨 Generating Content with the 7B Parameter Model
The video concludes with the presenter showing the results generated by the Crew using the 70 billion parameter model of Llama 3. It presents the copy and mid-journey descriptions created for the smart coffee mug Instagram post. The presenter is impressed with the AI-generated content and emphasizes the capability of reusing the Crew for multiple runs with AI doing the work. The video ends with an invitation to explore more AI content on the channel and to seek help through comments or the provided community.
Mindmap
Keywords
💡Llama 3
💡Crew AI
💡Ollama
💡Groq
💡Instagram Post Generation
💡Mid-Journey Descriptions
💡Parameter Version
💡Context Window
💡Rate Limiting
💡Token
💡Local Language Model
Highlights
Llama 3 is the third generation of Meta's open-source large language model, with significant improvements over Llama 2.
Llama 3 features a doubled context window of 8,000 tokens, making it comparable to Chat GPT 4.
The new model of Llama 3 is more cooperative and user-friendly than its predecessor.
Two versions of Llama 3 are available: an 8 billion parameter model for local use and a 70 billion parameter model for more complex tasks.
Llama 3 outperforms other language models like MISTOL and JIMMA in various evaluations.
The 8 billion parameter model of Llama 3 is suitable for running locally and is faster than Chat GPT.
The 70 billion parameter model of Llama 3 is larger, slower, but smarter and can be accessed using Gro.
Gro, in combination with Llama 3, offers significant speed improvements over using Llama 3 locally.
The video provides a live demo of Llama 3 showcasing its capabilities in generating smart content.
A local crew is demonstrated to generate Instagram posts for a smart thermos product using Llama 3 with Ollama.
The crew generates catchy taglines and mid-journey descriptions for marketing purposes.
The source code for the demo is available for free, allowing viewers to skip setup and start experimenting.
A community has been created for support and collaboration among developers interested in AI.
The video covers how to download and set up Ollama for local language model deployment.
A custom large language model is created for specialized tasks using a model file with specific parameters.
The process of setting up environment and building Crews with Llama 3 is detailed in the video.
Llama 3 is effective for smaller, quick tasks but may fall short for larger, more complex projects.
The video demonstrates the integration of Gro for faster and smarter execution of complex tasks with Llama 3.
A workaround for rate limiting when using Gro with Llama 3 is provided to ensure uninterrupted operation.
The final output includes generated Instagram post copy and mid-journey descriptions for a smart coffee mug product.
