Domain Specific Language - Structured Pipeline Agent
DSL-SPA is an open-source Python library for connecting LLM Agents to ETL and other common tasks. With this tool, you can connect LLM Agents to complex Data Pipelines.
Key Features of DSL-SPA
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Building SQL Queries - construct sql queries from fields extracted by Agents
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Applying Data Transformations - selectively apply data transformations based on Agent instructions
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Generating Unstructured Text Summaries - generate summaries of query results and data transformations
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Generating Visualizations - generate vega-lite visualizations of query results and data transformations
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Executing Commands - generate command sequences or execute python fucntions
For some interactive demos of what you can do with dsl-spa sdk check out the streamlit demo.
Getting Started
Get started with dsl-spa by installing the Python library via pip
pip install dsl-spa
The semantic cache pipelines need an embedding model client, which is not part of the base install. To use OpenAISemanticCachePipeline (or any OpenAI-compatible embedding endpoint), install the semantic-cache extra:
pip install dsl-spa[semantic-cache]
To see some example pipelines checkout these jupyter notebooks.
For more details on constructing a pipeline, reference Building a Pipeline.
For more details on the flow of Semantic Caching using DSL-SPA, refer to Semantic Cache Flow
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Release files for dsl-spa 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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| dsl_spa-0.5.0.tar.gz | 40.1 kB | Details |
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|---|---|---|---|---|
| dsl_spa-0.5.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 72.8 kB
Release files / dsl_spa-0.5.0.tar.gz
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