Add support for indexing pipelines

[tanaysoni]

The Pipelines were introduced to help build directed graphs from Haystack components to process a query.

This PR extends the Pipelines for building indexing workflows using components like file converters, preprocessors, retrievers, and document stores.

Proposed changes

1. In the YAML configuration of Pipeline, a new field type is added. This can be used in the current version to specify Query & Indexing pipelines. In the future, additional types, for example, RayQuery can be added that builds a query pipeline with the Ray framework. This new type fields allows components like the Retriever to be "polymorphic". For instance, in the case of Query, it embeds a query, while, in an Indexing pipeline, it creates embeddings for the given list of documents.

2. There can be different root nodes based on the pipeline. For example, a Query pipeline has a Query root node, while an Indexing Pipeline has a File root node. For cases where a user might want to use a text blob instead of a file, the REST API module can convert the text blob to a .txt file before passing it on to the indexing pipeline.

3. The components should allow run-time parameters, e.g., remove_numeric_tables to be also configurable during component initialization. This enables defining the default values as part of the Pipeline configuration that can later be overridden by individual requests.

Sample Indexing Pipeline

version: '0.7'

components:    
  - name: MyDPRRetriever
    type: DensePassageRetriever
    params:
      document_store: MyDocumentStore  
      query_embedding_model: facebook/dpr-question_encoder-single-nq-base
      passage_embedding_model: facebook/dpr-ctx_encoder-single-nq-base
  - name: MyDocumentStore
    type: MilvusDocumentStore
    params:
        similarity: dot_product
  - name: MyPDFToTextConverter
    type: PDFToTextConverter
    params:
      remove_numeric_tables: false
      valid_languages: ["de", "en"]
  - name: MyPreProcessor
    type: PreProcessor
    params:
      clean_whitespace: true

pipelines:
  - name: my_indexing_pipeline
    type: Indexing
    nodes:
      - name: MyPDFToTextConverter
        inputs: [File]
      - name: MyPreProcessor
        inputs: [MyPDFToTextConverter]
      - name: MyDPRRetriever
        inputs: [MyPreProcessor]
      - name: MyDocumentStore
        inputs: [MyDPRRetriever]

[tholor]

I like the design. Differentiation into pipeline types makes sense. Just not sure about the repetition of all instance attributes in the respective methods. This can create quite a mess in the long run...

[tholor]

I see why we want the option to overwrite instance attributes here, but it will create quite a mess if we apply this pattern to all potential pipeline nodes (retriever, reader ...). Maybe we can find another, cleaner workaround 🤔

[tholor]

LGTM