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Getting Started with Fireworks

This section focuses on examples built entirely using Fireworks AI. These projects demonstrate the core capabilities of Fireworks without external dependencies, giving you a straightforward path to mastering Fireworks.

⚠️ Note: Repo under construction - Excuse our dust⚠️

These notebooks and projects are upcoming and scheduled! Stay tuned! Please feel free to contribute!

Inference with Fireworks

  • Project: Inference with Fireworks
  • Objective: Learn how to perform model inference using Fireworks AI.
  • Topics Covered: Loading Fireworks models, performing inference, and optimizing performance.
  • Getting Started: Detailed instructions can be found in the 1_inference directory.
  • Video Link: Watch Video

Fine-Tuning with Fireworks

  • Project: Fine-Tuning with Fireworks
  • Objective: Learn how to fine-tune models using Fireworks AI.
  • Topics Covered: Dataset preparation, model fine-tuning techniques, and evaluation.
  • Getting Started: Instructions are available in the 2_fine-tuning directory.
  • Video Link: Watch Video

Function-Calling with Fireworks

  • Project: Function-Calling with Fireworks
  • Objective: Explore Fireworks' function-calling capabilities and how to deploy function-calling LLMs.
  • Topics Covered: Function-call models, handling function requests, and workflows.
  • Getting Started: Instructions are in the 3_function-calling directory.
  • Video Link: Watch Video

RAG with Fireworks

  • Project: RAG with Fireworks
  • Objective: Learn how to build RAG systems entirely using Fireworks AI.
  • Topics Covered: Document retrieval, knowledge-base integration, and response generation.
  • Getting Started: Detailed guide available in the 4_rag directory.
  • Video Link: Watch Video

Found an Error?

If you encounter any errors or issues while working through the examples, we encourage you to open an issue. Please provide details about the problem and, if possible, steps to reproduce it. Our team is constantly improving the projects based on community feedback, and we appreciate your contributions!

Installation and Setup

To run these projects locally, follow the instructions below to set up your environment:

Step 1: Clone the Repository

Start by cloning the Fireworks repository:

git clone https://github.com/fw-ai/cookbook.git
cd examples

Step 2: Set Up a Python Virtual Environment

Creating a virtual environment ensures that dependencies are isolated from your system Python installation.

  1. Create the virtual environment:

    python3 -m venv venv

  2. Activate the virtual environment:

    • On MacOS/Linux: 
      source venv/bin/activate
    • On Windows: 
      .\venv\Scripts\activate

Step 3: Install Dependencies

Once the virtual environment is activated, install the dependencies for the project:

pip3 install -r requirements.txt

Each project may have additional dependencies specified in its own directory. After navigating to the respective project folder, install any extra requirements with:

pip3 install -r <project_folder>/requirements.txt

Step 4: Run the Projects

Now that your environment is set up, navigate to the project directory you want to run. For example, for inference:

cd 1_inference
python inference_example.py

Follow the instructions in each project’s README.md for specific details and commands.

Resources

For more resources and detailed documentation on Fireworks, visit the Fireworks Documentation or join the discussions in the Discord forum.