> ## Documentation Index
> Fetch the complete documentation index at: https://fireworks.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Cookbooks

> Worked examples and application case studies for training, retrieval, and coding agents on Fireworks AI.

Explore notebooks and application case studies for building with Fireworks AI.

## Training

> [card] [VLM Training + Evals](https://huggingface.co/spaces/fireworks-ai/catalog-extract/blob/main/notebooks/01-eda-and-fine-tuning.ipynb)
>
> Beat frontier closed-source models for product catalog cleansing with vision-language model training.
>
> **Techniques:** Supervised Fine-Tuning (SFT)
>
> **Results:** 48% increase in quality from base model

## Embeddings & RAG

> [card] [Two-Stage Retrieval with Voyage Embeddings and Reranking](https://colab.research.google.com/github/fw-ai-external/cookbook/blob/main/case-studies/voyage-ai/voyage_two_stage_retrieval.ipynb)
>
> Build a retrieval pipeline that recalls candidates with vector search, then reorders them with a reranker for precision.
>
> **Techniques:** Voyage embeddings, MongoDB `$vectorSearch`, Voyage ReRank 2.5
>
> **Models:** Voyage AI embedders and rerankers on dedicated deployments

## Coding agents

> [card] [Advisor: a second-opinion code reviewer](https://github.com/fw-ai-external/cookbook/blob/main/case-studies/advisor/README.md)
>
> Add a critique-only frontier reviewer to a coding agent running on Fireworks.


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