RAG-Pipeline-Optimization / config /extracted_sample.yaml
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node_lines:
- node_line_name: retrieve_node_line
nodes:
- node_type: retrieval
modules:
- module_type: vectordb
embedding_model: openai
top_k: 3
strategy:
metrics:
- retrieval_f1
- retrieval_recall
- retrieval_precision
- node_line_name: post_retrieve_node_line
nodes:
- node_type: prompt_maker
modules:
- module_type: fstring
prompt: "Read the passages and answer the given question. \n Question: {query} \n Passage: {retrieved_contents} \n Answer : "
strategy:
generator_modules:
- batch: 2
llm: openai
module_type: llama_index_llm
metrics:
- bleu
- meteor
- rouge
- node_type: generator
modules:
- batch: 2
llm: openai
model: gpt-3.5-turbo-16k
module_type: llama_index_llm
strategy:
metrics:
- metric_name: bleu
- metric_name: meteor
- embedding_model: openai
metric_name: sem_score