Obsidian Reader
If youβre opening this Notebook on colab, you will probably need to install LlamaIndex π¦.
%pip install llama-index-readers-obsidian!pip install llama-index%env OPENAI_API_KEY=sk-************import loggingimport sys
logging.basicConfig(stream=sys.stdout, level=logging.INFO)logging.getLogger().addHandler(logging.StreamHandler(stream=sys.stdout))from llama_index.readers.obsidian import ObsidianReaderfrom llama_index.core import VectorStoreIndexdocuments = ObsidianReader( "/Users/hursh/vault").load_data() # Returns list of documentsindex = VectorStoreIndex.from_documents( documents) # Initialize index with documents# set Logging to DEBUG for more detailed outputsquery_engine = index.as_query_engine()res = query_engine.query("What is the meaning of life?")> [query] Total LLM token usage: 920 tokens> [query] Total embedding token usage: 7 tokensres.response'\nThe meaning of life is subjective and can vary from person to person. It is ultimately up to each individual to decide what they believe is the purpose and value of life. Some may find meaning in their faith, while others may find it in their relationships, work, or hobbies. Ultimately, it is up to each individual to decide what brings them joy and fulfillment and to pursue that path.'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/