JinaRanker

Ranks Documents based on their similarity to the query using Jina AI models.

Basic Information

• Type: haystack_integrations.components.rankers.jina.ranker.JinaRanker
• Components it can connect with:
  • Retrievers: JinaRanker receives documents to rank from a Retriever.
  • PromptBuilder: JinaRanker sends the re-ranked documents to PromptBuilder to be included in the prompt.

Inputs

Parameter	Type	Default	Description
query	str		Query string.
documents	List[Document]		List of Documents.
top_k	Optional[int]	None	The maximum number of Documents you want the Ranker to return.
score_threshold	Optional[float]	None	If provided only returns documents with a score above this threshold.

Outputs

Parameter	Type	Default	Description
documents	List[Document]		A dictionary with the following keys: - documents: List of Documents most similar to the given query in descending order of similarity.

Overview

JinaRanker re-ranks documents based on their relevance to a query using Jina AI reranker models. Reranking improves retrieval quality by applying a cross-encoder model that directly compares query-document pairs.

Use JinaRanker after an initial retrieval step to improve the precision of results before passing them to a generator.

Authorization

Create a secret with your Jina API key. Type JINA_API_KEY as the secret key. For detailed instructions on creating secrets, see Create Secrets.

Get your API key from Jina AI.

Usage Example

This example shows a RAG pipeline that retrieves documents, re-ranks them using Jina, and generates an answer.

components:
  InMemoryBM25Retriever:
    type: haystack.components.retrievers.in_memory.bm25_retriever.InMemoryBM25Retriever
    init_parameters:
      document_store:
        type: haystack.document_stores.in_memory.document_store.InMemoryDocumentStore
        init_parameters:
          bm25_tokenization_regex: (?u)\b\w\w+\b
          bm25_algorithm: BM25L
          bm25_parameters:
          embedding_similarity_function: dot_product
          index: 'default'
          async_executor:
      top_k: 10
  JinaRanker:
    type: haystack_integrations.components.rankers.jina.ranker.JinaRanker
    init_parameters:
      api_key:
        type: env_var
        env_vars:
        - JINA_API_KEY
        strict: false
      model: jina-reranker-v1-base-en
      top_k: 3
  PromptBuilder:
    type: haystack.components.builders.prompt_builder.PromptBuilder
    init_parameters:
      template: "Given the following documents, answer the question.\n\nDocuments:\n{% for doc in documents %}{{ doc.content }}\n{% endfor %}\n\nQuestion: {{ query }}"
  OpenAIGenerator:
    type: haystack.components.generators.openai.OpenAIGenerator
    init_parameters:
      api_key:
        type: env_var
        env_vars:
        - OPENAI_API_KEY
        strict: false
      model: gpt-4o-mini
  AnswerBuilder:
    type: haystack.components.builders.answer_builder.AnswerBuilder
    init_parameters:
      pattern:
      reference_pattern:
      last_message_only: false
      return_only_referenced_documents: true

connections:
- sender: InMemoryBM25Retriever.documents
  receiver: JinaRanker.documents
- sender: JinaRanker.documents
  receiver: PromptBuilder.documents
- sender: PromptBuilder.prompt
  receiver: OpenAIGenerator.prompt
- sender: OpenAIGenerator.replies
  receiver: AnswerBuilder.replies
- sender: JinaRanker.documents
  receiver: AnswerBuilder.documents

max_runs_per_component: 100

metadata: {}

inputs:
  query:
  - InMemoryBM25Retriever.query
  - JinaRanker.query
  - PromptBuilder.query
  - AnswerBuilder.query

outputs:
  answers: AnswerBuilder.answers

Parameters

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
api_key	Secret	Secret.from_env_var('JINA_API_KEY')	The Jina API key. It can be explicitly provided or automatically read from the environment variable JINA_API_KEY (recommended).
model	str	jina-reranker-v1-base-en	The name of the Jina model to use. Check the list of available models on https://jina.ai/reranker/
top_k	Optional[int]	None	The maximum number of Documents to return per query. If None, all documents are returned
score_threshold	Optional[float]	None	If provided only returns documents with a score above this threshold.

Run Method Parameters

These are the parameters you can configure for the component's run() method. This means you can pass these parameters at query time through the API, in Playground, or when running a job. For details, see Modify Pipeline Parameters at Query Time.

Parameter	Type	Default	Description
query	str		Query string.
documents	List[Document]		List of Documents.
top_k	Optional[int]	None	The maximum number of Documents you want the Ranker to return.
score_threshold	Optional[float]	None	If provided only returns documents with a score above this threshold.