https://github.com/project-ryoma/ryoma
Common AI agent framework solving your data problems
https://github.com/project-ryoma/ryoma
ai data-science llm
Last synced: about 2 months ago
JSON representation
Common AI agent framework solving your data problems
- Host: GitHub
- URL: https://github.com/project-ryoma/ryoma
- Owner: project-ryoma
- License: apache-2.0
- Created: 2023-07-07T06:45:07.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2025-04-29T07:07:02.000Z (about 2 months ago)
- Last Synced: 2025-04-29T07:27:40.480Z (about 2 months ago)
- Topics: ai, data-science, llm
- Language: Python
- Homepage: https://project-ryoma.github.io/ryoma/
- Size: 5.15 MB
- Stars: 276
- Watchers: 10
- Forks: 46
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md
Awesome Lists containing this project
- awesome-LangGraph - Ryoma - powered data agent framework for data analysis, engineering, and visualization, combining LangChain, Reflex, Apache Arrow, and more.  (Community Projects / Development & Tools)
README
# Ryoma
AI Powered Data Agent framework, a comprehensive solution for data analysis, engineering, and visualization.
[](https://github.com/project-ryoma/ryoma/actions/workflows/build.yml?query=workflow%3Abuild)
[](https://pypi.org/project/ryoma/)
[](https://github.com/project-ryoma/ryoma/pulls?utf8=%E2%9C%93&q=is%3Apr%20author%3Aapp%2Fdependabot)
[](https://github.com/psf/black)
[](https://github.com/PyCQA/bandit)
[](https://github.com/project-ryoma/ryoma/blob/main/.pre-commit-config.yaml)
[](https://github.com/project-ryoma/ryoma/blob/main/LICENSE)
[](https://github.com/project-ryoma/ryoma/blob/main/assets/images/coverage.svg)
## Tech Stack
Our platform leverages a combination of cutting-edge technologies and frameworks:
- **[Langchain](https://www.langchain.com/)**: Facilitates the seamless integration of language models into application workflows, significantly enhancing AI interaction capabilities.
- **[Reflex](https://reflex.dev/)**: An open-source framework for quickly building beautiful, interactive web applications in pure Python
- **[Apache Arrow](https://arrow.apache.org/)**: A cross-language development platform for in-memory data that specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware like CPUs and GPUs.
- **[Jupyter Ai Magics](https://github.com/jupyterlab/jupyter-ai)**: A JupyterLab extension that provides a set of magics for working with AI models.
- **[Amundsen](https://www.amundsen.io/)**: A data discovery and metadata platform that helps users discover, understand, and trust the data they use.
- **[Ibis](https://ibis-project.org/)**: A Python data analysis framework that provides a pandas-like API for analytics on large datasets.
- **[Feast](https://feast.dev/)**: An operational feature store for managing and serving machine learning features to models in production.
## Installation
Simply install the package using pip:
```shell
pip install ryoma_ai
```
Or with extra dependencies:
```shell
pip install ryoma_ai[snowflake]
```
## Basic Example
Below is an example of using SqlAgent to connect to a postgres database and ask a question.
You can read more details in the [documentation](https://ryoma-1.gitbook.io/ryoma/).
```python
from ryoma_ai.agent.sql import SqlAgent
from ryoma_ai.datasource.postgres import PostgresDataSource
# Connect to a postgres catalog
datasource = PostgresDataSource("postgresql://user:password@localhost:5432/dbname")
# Create a SQL agent
sql_agent = SqlAgent("gpt-3.5-turbo").add_datasource(datasource)
# ask question to the agent
sql_agent.stream("I want to get the top 5 customers which making the most purchases", display=True)
```
The Sql agent will try to run the tool as shown below:
```text
================================ Human Message =================================
I want to get the top 5 customers which making the most purchases
================================== Ai Message ==================================
Tool Calls:
sql_database_query (call_mWCPB3GQGOTLYsvp21DGlpOb)
Call ID: call_mWCPB3GQGOTLYsvp21DGlpOb
Args:
query: SELECT C.C_NAME, SUM(L.L_EXTENDEDPRICE) AS TOTAL_PURCHASES FROM CUSTOMER C JOIN ORDERS O ON C.C_CUSTKEY = O.O_CUSTKEY JOIN LINEITEM L ON O.O_ORDERKEY = L.L_ORDERKEY GROUP BY C.C_NAME ORDER BY TOTAL_PURCHASES DESC LIMIT 5
result_format: pandas
```
Continue to run the tool with the following code:
```python
sql_agent.stream(tool_mode=ToolMode.ONCE)
```
Output will look like after running the tool:
```text
================================== Ai Message ==================================
The top 5 customers who have made the most purchases are as follows:
1. Customer#000143500 - Total Purchases: $7,154,828.98
2. Customer#000095257 - Total Purchases: $6,645,071.02
3. Customer#000087115 - Total Purchases: $6,528,332.52
4. Customer#000134380 - Total Purchases: $6,405,556.97
5. Customer#000103834 - Total Purchases: $6,397,480.12
```
## Use Ryoma Lab
Ryoma lab is an application that allows you to interact with your data and AI models in UI.
The ryoma lab is built with [Reflex](https://reflex.dev/).
1. Create Ryoma lab configuration file `rxconfig.py` in your project:
```python
import logging
import reflex as rx
from reflex.constants import LogLevel
config = rx.Config(
app_name="ryoma_lab",
loglevel=LogLevel.INFO,
)
# Setup basic configuration for logging
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
```
2. You can start the ryoma lab by running the following command:
```shell
ryoma_lab run
```
the ryoma lab will be available at `http://localhost:3000`.
## Supported Models
Model provider are supported by jupyter ai magics. Ensure the corresponding environment variables are set before using the Ryoma agent.
| Provider | Provider ID | Environment variable(s) | Python package(s) |
|---------------------|----------------------|----------------------------|---------------------------------|
| AI21 | `ai21` | `AI21_API_KEY` | `ai21` |
| Anthropic | `anthropic` | `ANTHROPIC_API_KEY` | `langchain-anthropic` |
| Anthropic (playground) | `anthropic-playground` | `ANTHROPIC_API_KEY` | `langchain-anthropic` |
| Bedrock | `bedrock` | N/A | `boto3` |
| Bedrock (playground) | `bedrock-playground` | N/A | `boto3` |
| Cohere | `cohere` | `COHERE_API_KEY` | `cohere` |
| ERNIE-Bot | `qianfan` | `QIANFAN_AK`, `QIANFAN_SK` | `qianfan` |
| Gemini | `gemini` | `GOOGLE_API_KEY` | `langchain-google-genai` |
| GPT4All | `gpt4all` | N/A | `gpt4all` |
| Hugging Face Hub | `huggingface_hub` | `HUGGINGFACEHUB_API_TOKEN` | `huggingface_hub`, `ipywidgets`, `pillow` |
| NVIDIA | `nvidia-playground` | `NVIDIA_API_KEY` | `langchain_nvidia_ai_endpoints` |
| OpenAI | `openai` | `OPENAI_API_KEY` | `langchain-openai` |
| OpenAI (playground) | `openai-playground` | `OPENAI_API_KEY` | `langchain-openai` |
| SageMaker | `sagemaker-endpoint` | N/A | `boto3` |
## Supported Data Sources
- [x] Snowflake
- [x] Sqlite
- [x] BigQuery
- [x] Postgres
- [x] MySQL
- [x] File (CSV, Excel, Parquet, etc.)
- [ ] Redshift
- [ ] DynamoDB
## Supported Engines
- [x] Apache Spark
- [x] Apache Flink
- [ ] Presto
## 🛡 License
[](https://github.com/project-ryoma/ryoma/blob/main/LICENSE)
This project is licensed under the terms of the `Apache Software License 2.0` license. See [LICENSE](https://github.com/ryoma/ryoma/blob/master/LICENSE) for more details.