extracted_sample.yaml

vectordb:
  - name: default
    db_type: chroma
    client_type: persistent
    embedding_model: openai
    collection_name: openai
    path: ${PROJECT_DIR}/data/chroma
node_lines:
- node_line_name: retrieve_node_line
  nodes:
  - node_type: retrieval
    modules:
    - module_type: vectordb
      vectordb: default
      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