TxtAI MCP Server

# Labels   The Labels pipeline uses a text classification model to apply labels to input text. This pipeline can classify text using either a zero shot model (dynamic labeling) or a standard text classification model (fixed labeling). ## Example The following shows a simple example using this pipeline. ```python from txtai.pipeline import Labels # Create and run pipeline labels = Labels() labels( ["Great news", "That's rough"], ["positive", "negative"] ) ``` See the link below for a more detailed example. | Notebook | Description | | |:----------|:-------------|------:| | [Apply labels with zero shot classification](https://github.com/neuml/txtai/blob/master/examples/07_Apply_labels_with_zero_shot_classification.ipynb) | Use zero shot learning for labeling, classification and topic modeling | [](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/07_Apply_labels_with_zero_shot_classification.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 labels: # Run pipeline with workflow workflow: labels: tasks: - action: labels args: [["positive", "negative"]] ``` ### Run with Workflows ```python from txtai import Application # Create and run pipeline with workflow app = Application("config.yml") list(app.workflow("labels", ["Great news", "That's rough"])) ``` ### 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":"labels", "elements": ["Great news", "Thats rough"]}' ``` ## Methods Python documentation for the pipeline. ### ::: txtai.pipeline.Labels.__init__ ### ::: txtai.pipeline.Labels.__call__