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To add a generator component to the existing Haystack pipeline YAML configuration, you can follow these steps:

Define the generator component:

Choose the type of generator you want to use, for example, T5Generator, GPT2Generator, etc.
Define its name and parameters. For example:
yaml
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- name: Generator
  type: T5Generator
  params:
    model_name_or_path: t5-base
Add the generator component to the pipeline:

Add the generator component to the pipeline as a node after the Reader node.
Wire up the inputs and outputs appropriately. The generator needs the input passage and the question, which are the outputs of the Reader node.
Define the generator node name and input/output mapping. For example:
yaml
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- name: Generator
  inputs: [Reader.output.answer, Query]
  outputs: [answer]
Update the existing pipeline configuration:

Add the generator node to the query pipeline nodes list after the Reader node.
Define the generator node name and input/output mapping in the query pipeline. For example:
yaml
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- name: Generator
  inputs: [Reader.output.answer, Query]
  outputs: [answer]
Here is an example YAML configuration for adding a T5Generator to the Haystack pipeline:

yaml
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version: ignore

components:    # define all the building-blocks for Pipeline
  - name: DocumentStore
    type: ElasticsearchDocumentStore  # consider using MilvusDocumentStore or WeaviateDocumentStore for scaling to large number of documents
    params:
      host: localhost
  - name: Retriever
    type: DensePassageRetriever
    params:
      document_store: DocumentStore    # params can reference other components defined in the YAML
      top_k: 5
  - name: Reader       # custom-name