Awesome Ai Agents 2026
Section: Data Analysis · Chat with your data. NL to Pandas/SQL.
ActiveScore 74
Entry
PandasAI
Appears in 5 awesome lists
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Open github.comsinaptik-ai/pandas-ai
Found in these lists
Awesome Ai For Science
Section: Data Analysis & Visualization · Conversational data analysis using natural language
FreshScore 86
awesome-ChatGPT-repositories
Section: Chatbots · 4, Anthropic, VertexAI) and RAG.
FreshScore 87
Awesome Data Analysis
Section: Useful Python Tools for Data Analysis · Conversational data analysis using LLMs and RAG.
FreshScore 80
awesome-python
Section: Data Science and Analytics · Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
FreshScore 81
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AutoGen
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FastChat
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gpt4all
is an ecosystem of open-source chatbots trained on a massive collections of clean assistant data including code, stories and dialogue based on LLaMa.
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Mastra
TypeScript-native agent framework (from the Gatsby team) with 22K+ stars and 300K+ weekly npm downloads. Connects to 40+ providers through one standard interface, with built-in workflows, RAG pipelines, and agent orchestration. The @mastra/deployer handles serverless deployment, and the eval…
In 10 listsDetails
Embedchain
Universal memory layer for AI agents. Simple API to create RAG applications over any dataset with support for multiple vector stores, embedding models, and LLM providers. Apache 2.0 licensed.
In 9 listsDetails
DeepAnalyze
first agentic LLM for autonomous data science, supporting specific data tasks (data preparation, analysis, modeling, visualization, and insight) and data-oriented deep research (produce analyst-grade research reports). github
In 8 listsDetails
AnythingLLM
Open-source ChatGPT equivalent experience for both open and close source LLMs, embedders, and vector databases. Supports unlimited documents, threads, and concurrent users and management all in a very clean UI.
In 8 listsDetails