RD-Agent vs llama_index
RD-Agent and llama_index share 19 technologies: pyarrow, OpenAI, Rich, matplotlib, datasets, peft, vLLM, scikit-learn, litellm, torch, tiktoken, LangChain, transformers, beautifulsoup4, pypdf, nbformat, pymupdf, Pydantic, and docker. Both are written in Python.
What they share and what sets them apart
RD-Agent
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through R&D-Agent, which lets AI drive data-driven AI. 🔗https://aka.ms/RD-Agent-Tech-Report
Python15.3kRead on November 8, 2026, at commit 484776cWhat is RD-Agent built with?Only in RD-Agent
- Flask
werkzeug
tables
- Hugging Face
- Kaggle
- flask-cors
- Streamlit
- Vite
- Vue
vue-router
furo
- sphinx-rtd-theme
seaborn
- Plotly
accelerate
- gym
- pydantic-ai-slim
- pyserini
- rank-bm25
- spaCy
trl
- MLflow
myst-parser
- genson
loguru
- Prefect
github-markdown-css
- Element
echarts
highlight.js
katex
marked
markdown-it
- markdown-it-texmath
prismjs
In common
llama_index
LlamaIndex is the document processing platform for AI
Python52.8kRead on November 5, 2026, at commit 444fdf0What is llama_index built with?Only in llama_index
starlette
- aiomysql
- aiosqlite
- async-lru
- asyncpg
- azure-search-documents
- azure-storage-blob
- ibm-db
- pgvecto-rs
pgvector
psycopg
psycopg2-binary
- pyzmq
- Redis
weaviate-client
lancedb
oracledb
- DuckDB
- pymilvus
- SQLite
- tablestore
chromadb
falkordb
- MySQL
pinecone
clickhouse-connect
- gcsfs
pyiceberg
pymochow
- pymysql
- pyobvector
- s3fs
- tcvectordb
typesense
- ElevenLabs
- anyio
- graphql-core
tornado
- AIOHTTP
- Ray
- soupsieve
- tinycss2
- ipywidgets
- matplotlib-inline
prompt-toolkit
- SQLAlchemy
- argon2-cffi
- azure-identity
google-auth-httplib2
google-auth-oauthlib
- cryptography
- pyjwt
- msal
- einops
firecrawl-py
- guardrails-ai
llama-index-core
- mem0ai
opencv-python
- PaddlePaddle
- tavily-python
- ibm-watsonx-ai
cohere
- MCP
sentence-transformers
dashscope
- fastembed
- flagembedding
nltk
- sentencepiece
- ModelScope
- Ollama
- openvino
- tritonclient
- exa-py
- flashrank
- hnswlib
langfuse
mlx
- mlx-lm
nomic
optimum
- paddleocr
presidio-analyzer
tokenizers
- bleach
markupsafe
mistune
- newspaper3k
- xlrd
pillow
- bs4
- html2text
unstructured
- defusedxml
- jinja2
lxml
- filetype
- docx2txt
- markdownify
docling
- lxml-html-clean
- markitdown
- nbconvert
- pdf2image
- pdfplumber
pypdf2
tinytag
- youtube-transcript-api
- jsonschema-specifications
marshmallow
- referencing
- rfc3339-validator
docling-core
- annotated-types
- jsonschema
- pydantic-core
- opentelemetry-api
opentelemetry-semantic-conventions
prometheus-client
psutil
- python-json-logger
- boto3
- Alibaba Cloud
- OpenTelemetry
Side by side
Frequently asked questions
Which is bigger, RD-Agent or llama_index?
Which has more GitHub stars, RD-Agent or llama_index?
The proof: run-llama/llama_index on GitHub
Which has more tests, RD-Agent or llama_index?
Which was updated more recently, RD-Agent or llama_index?
The proof: run-llama/llama_index's commits on GitHub
Which has more commits signed by AI, RD-Agent or llama_index?
See inside your code, today.
Paste your repo and see it drawn, part by part: a medium one in under a minute.
Free, no account.

