MistralAI Embeddings
If youβre opening this Notebook on colab, you will probably need to install LlamaIndex π¦.
%pip install llama-index-embeddings-mistralai!pip install llama-index# importsfrom llama_index.embeddings.mistralai import MistralAIEmbedding# get API key and create embeddingsapi_key = "YOUR API KEY"model_name = "mistral-embed"embed_model = MistralAIEmbedding(model_name=model_name, api_key=api_key)
embeddings = embed_model.get_text_embedding("La Plateforme - The Platform")print(f"Dimension of embeddings: {len(embeddings)}")Dimension of embeddings: 1024embeddings[:5][-0.0299224853515625, -0.0028362274169921875, 0.0282745361328125, -0.034759521484375, -0.0017366409301757812]Note for AI agents: this documentation is built for programmatic access.
- Overview of all docs: https://developers.llamaindex.ai/llms.txt
- Any page is available as raw Markdown by appending index.md to its URL β e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md
- Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ β search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters.
- A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/