3. Passage Augmenter¶
🔎 Definition¶
Passage augmenter is a node that augments passages. As opposed to the passage filter node, this is a node that adds passages
🤸 Benefits¶
The primary benefit of passage augmenter is that it allows users to fetch additional passages.
Node Parameters¶
Top_k
Description: The
top_k
parameter is used at the node level to define the top ‘k’ results to be retrieved from corpus.📌 Note: The number of
top_k
must be same or less than the number of “retrieval
node parametertop_k
”.
embedding_model
Description: The embedding model name to be used for calculating the cosine similarity between the query and the augmented passages.
Example config.yaml file¶
node_lines:
- node_line_name: retrieve_node_line # Arbitrary node line name
nodes:
- node_type: passage_augmenter
strategy:
metrics: [ retrieval_f1, retrieval_recall, retrieval_precision ]
speed_threshold: 5
embedding_model: openai
top_k: 5
modules:
- module_type: pass_passage_augmenter
- module_type: prev_next_augmenter
mode: next
What is pass_passage_augmenter?
Its purpose is to test the performance that ‘not using’ any passage augmenter module. Because it can be the better option that not using passage augmenter node. So with this module, you can automatically test the performance without using any passage augmenter module.