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pyspur
AI Agent Builder in Python
Stars: 2056
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PySpur is a graph-based editor designed for LLM (Large Language Models) workflows. It offers modular building blocks, node-level debugging, and performance evaluation. The tool is easy to hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies. Users can quickly set up PySpur by cloning the repository, creating a .env file, starting docker services, and accessing the portal. PySpur can also work with local models served using Ollama, with steps provided for configuration. The roadmap includes features like canvas, async/batch execution, support for Ollama, new nodes, pipeline optimization, templates, code compilation, multimodal support, and more.
README:
PySpur is an AI agent builder in Python. AI engineers use it to build agents, execute them step-by-step and inspect past runs.
https://github.com/user-attachments/assets/1ebf78c9-94b2-468d-bbbb-566311df16fe
- 🖐️ Drag-and-Drop: Build, Test and Iterate in Seconds.
- 🔄 Loops: Iterative Tool Calling with Memory.
- 📤 File Upload: Upload files or paste URLs to process documents.
- 📋 Structured Outputs: UI editor for JSON Schemas.
- 🗃️ RAG: Parse, Chunk, Embed, and Upsert Data into a Vector DB.
- 🖼️ Multimodal: Support for Video, Images, Audio, Texts, Code.
- 🧰 Tools: Slack, Firecrawl.dev, Google Sheets, GitHub, and more.
- 🧪 Evals: Evaluate Agents on Real-World Datasets.
- 🚀 One-Click Deploy: Publish as an API and integrate wherever you want.
- 🐍 Python-Based: Add new nodes by creating a single Python file.
- 🎛️ Any-Vendor-Support: >100 LLM providers, embedders, and vector DBs.
This is the quickest way to get started. Python 3.12 or higher is required.
-
Install PySpur:
pip install pyspur
-
Initialize a new project:
pyspur init my-project cd my-project
This will create a new directory with a
.env
file. -
Start the server:
pyspur serve --sqlite
By default, this will start PySpur app at
http://localhost:6080
using a sqlite database. We recommend you configure a postgres instance URL in the.env
file to get a more stable experience. -
[Optional] Customize Your Deployment: You can customize your PySpur deployment in two ways:
a. Through the app (Recommended): - Navigate to the API Keys tab in the app - Add your API keys for various providers (OpenAI, Anthropic, etc.) - Changes take effect immediately
b. Manual Configuration: - Edit the
.env
file in your project directory - It is recommended to configure a postgres database in .env for more reliability - Restart the app withpyspur serve
. Add--sqlite
if you are not using postgres
This is the recommended way for production deployments:
-
Install Docker: First, install Docker by following the official installation guide for your operating system:
-
Create a PySpur Project: Once Docker is installed, create a new PySpur project with:
curl -fsSL https://raw.githubusercontent.com/PySpur-com/pyspur/main/start_pyspur_docker.sh | bash -s pyspur-project
This will:
- Start a new PySpur project in a new directory called
pyspur-project
- Set up the necessary configuration files
- Start PySpur app automatically backed by a local postgres docker instance
- Start a new PySpur project in a new directory called
-
Access PySpur: Go to
http://localhost:6080
in your browser. -
[Optional] Customize Your Deployment: You can customize your PySpur deployment in two ways:
a. Through the app (Recommended): - Navigate to the API Keys tab in the app - Add your API keys for various providers (OpenAI, Anthropic, etc.) - Changes take effect immediately
b. Manual Configuration: - Edit the
.env
file in your project directory - Restart the services with:sh docker compose up -d
That's it! Click on "New Spur" to create a workflow, or start with one of the stock templates.
https://github.com/user-attachments/assets/6e82ad25-2a46-4c50-b030-415ea9994690
PDFs, Videos, Audio, Images, ...
https://github.com/user-attachments/assets/83ed9a22-1ec1-4d86-9dd6-5d945588fd0b
https://github.com/user-attachments/assets/c77723b1-c076-4a64-a01d-6d6677e9c60e
https://github.com/user-attachments/assets/50e5c711-dd01-4d92-bb23-181a1c5bba25
https://github.com/user-attachments/assets/6442f0ad-86d8-43d9-aa70-e5c01e55e876
https://github.com/user-attachments/assets/4dc2abc3-c6e6-4d6d-a5c3-787d518de7ae
https://github.com/user-attachments/assets/5bef7a16-ef9f-4650-b385-4ea70fa54c8a
For development, follow these steps:
-
Clone the repository:
git clone https://github.com/PySpur-com/pyspur.git cd pyspur
-
Launch using docker-compose.dev.yml:
docker compose -f docker-compose.dev.yml up --build -d
This will start a local instance of PySpur with hot-reloading enabled for development.
-
Customize your setup: Edit the
.env
file to configure your environment. By default, PySpur uses a local PostgreSQL database. To use an external database, modify thePOSTGRES_*
variables in.env
.
You can support us in our work by leaving a star! Thank you!
Your feedback will be massively appreciated. Please tell us which features on that list you like to see next or request entirely new ones.
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