/cookbook

Primary LanguageJupyter NotebookMIT LicenseMIT

Mistral Cookbook

The Mistral Cookbook features examples contributed by our community and partners. If you have cool examples showcasing Mistral models, feel free to share them by submitting a PR to this repo.

Submission Guidelines:

  • File Format: Please submit your example in the .md or .ipynb format.
  • Runnable on Colab: If you're sharing a notebook example, try to make sure it's runnable on Google Colab.
  • Authorship: Kindly include your name and affiliation at the begining of the file.
  • Descriptions: Please include your notebook along with its category and descriptions in the table below.
  • Tone: Kindly maintain a neural tone and minimize any excessive marketing materials.
  • Reproducibility: To ensure others can reproduce your work, kindly tag package versions in your code.
  • Image size: If you have images, please make sure each image's size is below 500KB.
  • Copyright: Always respect copyright and intellectual property laws.

Disclaimer: Examples contributed by the community and partners do not represent Mistral's views and opinions.

Content Guidelines:

  • Originality: Is your content original and offering a fresh perspective?
  • Clear: Is your content well-structured and clearly written?
  • Value: Is your content valuable to the community? Does the community need it?

Notebook list

Notebook Category Description
prompting_capabilities.ipynb prompting Write prompts for classification, summarization, personalization, and evaluation
basic_RAG.ipynb RAG RAG from scratch with Mistral AI API
embeddings.ipynb embeddings Use Mistral embeddings API for classification and clustering
function_calling.ipynb function calling Use Mistral API for function calling
langgraph_crag_mistral.ipynb RAG Corrective RAG using self-reflection with LangGraph and Mistral with option to run locally (with Ollama).
llamaindex_agentic_rag.ipynb RAG, agent Use Mistral AI with LlamaIndex and ReAct agent
haystack_chat_with_docs.ipynb RAG, embeddings Use Mistral AI with Haystack indexing and RAG pipelines