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/agents-llamaindex

@d9d759e

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

  • 4 files
  • 28.2 KB
  • MIT
  • Updated 9 months ago
  • GitHub

Use this Skill: https://skilld.dev/gh/davila7/claude-code-templates/agents-llamaindex

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referencesdata_connectors.md

≈577 tokens on demand. Your agent reads this file only when SKILL.md points to it.

LlamaIndex Data Connectors Guide

300+ data connectors via LlamaHub.

Built-in loaders

SimpleDirectoryReader

from llama_index.core import SimpleDirectoryReader

# Load all files
documents = SimpleDirectoryReader("./data").load_data()

# Filter by extension
documents = SimpleDirectoryReader(
    "./data",
    required_exts=[".pdf", ".docx", ".txt"]
).load_data()

# Recursive
documents = SimpleDirectoryReader("./data", recursive=True).load_data()

Web pages

from llama_index.readers.web import SimpleWebPageReader, BeautifulSoupWebReader

# Simple loader
reader = SimpleWebPageReader()
documents = reader.load_data(["https://example.com"])

# Advanced (BeautifulSoup)
reader = BeautifulSoupWebReader()
documents = reader.load_data(urls=[
    "https://docs.python.org",
    "https://numpy.org"
])

PDF

from llama_index.readers.file import PDFReader

reader = PDFReader()
documents = reader.load_data("paper.pdf")

GitHub

from llama_index.readers.github import GithubRepositoryReader

reader = GithubRepositoryReader(
    owner="facebook",
    repo="react",
    filter_file_extensions=[".js", ".jsx"],
    verbose=True
)

documents = reader.load_data(branch="main")

LlamaHub connectors

Visit https://llamahub.ai for 300+ connectors:

  • Notion, Google Docs, Confluence
  • Slack, Discord, Twitter
  • PostgreSQL, MongoDB, MySQL
  • S3, GCS, Azure Blob
  • Stripe, Shopify, Salesforce

Install from LlamaHub

pip install llama-index-readers-notion
from llama_index.readers.notion import NotionPageReader

reader = NotionPageReader(integration_token="your-token")
documents = reader.load_data(page_ids=["page-id"])

Custom loader

from llama_index.core.readers.base import BaseReader
from llama_index.core import Document

class CustomReader(BaseReader):
    def load_data(self, file_path: str):
        # Your custom loading logic
        with open(file_path) as f:
            text = f.read()
        return [Document(text=text, metadata={"source": file_path})]

reader = CustomReader()
documents = reader.load_data("data.txt")

Resources

Source: SKILL.md on GitHub

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Signed by skilld at d9d759e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 14 hours ago.

Activeupdated 9 months ago
version
1.0.0
author
Orchestra Research
dependencies
[
  "llama-index",
  "openai",
  "anthropic"
]
Other metadata
tags
[
  "Agents",
  "LlamaIndex",
  "RAG",
  "Document Ingestion",
  "Vector Indices",
  "Query Engines",
  "Knowledge Retrieval",
  "Data Framework",
  "Multimodal",
  "Private Data",
  "Connectors"
]

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