TxtAI MCP Server

# Entity   The Entity pipeline applies a token classifier to text and extracts entity/label combinations. ## Example The following shows a simple example using this pipeline. ```python from txtai.pipeline import Entity # Create and run pipeline entity = Entity() entity("Canada's last fully intact ice shelf has suddenly collapsed, " \ "forming a Manhattan-sized iceberg") # Extract entities using a GLiNER model which supports dynamic labels entity = Entity("gliner-community/gliner_medium-v2.5") entity("Canada's last fully intact ice shelf has suddenly collapsed, " \ "forming a Manhattan-sized iceberg", labels=["country", "city"]) ``` See the link below for a more detailed example. | Notebook | Description | | |:----------|:-------------|------:| | [Entity extraction workflows](https://github.com/neuml/txtai/blob/master/examples/26_Entity_extraction_workflows.ipynb) | Identify entity/label combinations | [](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/26_Entity_extraction_workflows.ipynb) | | [Parsing the stars with txtai](https://github.com/neuml/txtai/blob/master/examples/72_Parsing_the_stars_with_txtai.ipynb) | Explore an astronomical knowledge graph of known stars, planets, galaxies | [](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/72_Parsing_the_stars_with_txtai.ipynb) | ## Configuration-driven example Pipelines are run with Python or configuration. Pipelines can be instantiated in [configuration](../../../api/configuration/#pipeline) using the lower case name of the pipeline. Configuration-driven pipelines are run with [workflows](../../../workflow/#configuration-driven-example) or the [API](../../../api#local-instance). ### config.yml ```yaml # Create pipeline using lower case class name entity: # Run pipeline with workflow workflow: entity: tasks: - action: entity ``` ### Run with Workflows ```python from txtai import Application # Create and run pipeline with workflow app = Application("config.yml") list(app.workflow("entity", ["Canada's last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg"])) ``` ### Run with API ```bash CONFIG=config.yml uvicorn "txtai.api:app" & curl \ -X POST "http://localhost:8000/workflow" \ -H "Content-Type: application/json" \ -d '{"name":"entity", "elements": ["Canadas last fully intact ice shelf has suddenly collapsed, forming a Manhattan-sized iceberg"]}' ``` ## Methods Python documentation for the pipeline. ### ::: txtai.pipeline.Entity.__init__ ### ::: txtai.pipeline.Entity.__call__