$schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
environment:
  python_requirements_txt: requirements.txt
inputs:
  text_chunk:
    type: string
    is_chat_input: false
    default: Prompt flow is a suite of development tools designed to streamline the
      end-to-end development cycle of LLM-based AI applications, from ideation,
      prototyping, testing, evaluation to production deployment and monitoring.
      It makes prompt engineering much easier and enables you to build LLM apps
      with production quality.
outputs:
  question:
    type: string
    reference: ${validate_question.output.question}
  suggested_answer:
    type: string
    reference: ${validate_suggested_answer.output.suggested_answer}
  debug_info:
    type: string
    reference: ${generate_debug_info.output}
nodes:
- name: score_text_chunk_prompt
  type: prompt
  source:
    type: code
    path: score_text_chunk_prompt.jinja2
  inputs:
    context: ${inputs.text_chunk}
  use_variants: false
- name: validate_question_prompt
  type: prompt
  source:
    type: code
    path: validate_question_prompt.jinja2
  inputs:
    question: ${generate_question.output}
    context: ${inputs.text_chunk}
  use_variants: false
- name: generate_question_prompt
  type: prompt
  source:
    type: code
    path: generate_question_prompt.jinja2
  inputs:
    context: ${inputs.text_chunk}
  use_variants: false
- name: generate_suggested_answer_prompt
  type: prompt
  source:
    type: code
    path: generate_suggested_answer_prompt.jinja2
  inputs:
    context: ${inputs.text_chunk}
    question: ${validate_question.output.question}
  use_variants: false
- name: generate_question
  type: python
  source:
    type: code
    path: generate_question.py
  inputs:
    connection: ""
    context: ${validate_text_chunk.output.context}
    temperature: 0.2
    generate_question_prompt: ${generate_question_prompt.output}
  use_variants: false
- name: validate_question
  type: python
  source:
    type: code
    path: validate_question.py
  inputs:
    connection: ""
    temperature: 0.2
    generated_question: ${generate_question.output}
    validate_question_prompt: ${validate_question_prompt.output}
  use_variants: false
- name: generate_suggested_answer
  type: python
  source:
    type: code
    path: generate_suggested_answer.py
  inputs:
    connection: ""
    context: ${inputs.text_chunk}
    generate_suggested_answer_prompt: ${generate_suggested_answer_prompt.output}
    question: ${validate_question.output.question}
    temperature: 0.2
  use_variants: false
- name: generate_debug_info
  type: python
  source:
    type: code
    path: generate_debug_info.py
  inputs:
    text_chunk: ${inputs.text_chunk}
    validate_suggested_answer_output: ${validate_suggested_answer.output}
    text_chunk_validation_res: ${validate_text_chunk.output.validation_res}
    validate_question_output: ${validate_question.output}
- name: validate_suggested_answer_prompt
  type: prompt
  source:
    type: code
    path: validate_suggested_answer_prompt.jinja2
  inputs:
    answer: ${generate_suggested_answer.output}
- name: validate_suggested_answer
  type: python
  source:
    type: code
    path: validate_suggested_answer.py
  inputs:
    connection: ""
    suggested_answer: ${generate_suggested_answer.output}
    validate_suggested_answer_prompt: ${validate_suggested_answer_prompt.output}
    temperature: 0.2
- name: validate_text_chunk
  type: python
  source:
    type: code
    path: validate_text_chunk.py
  inputs:
    connection: ""
    score_text_chunk_prompt: ${score_text_chunk_prompt.output}
    context: ${inputs.text_chunk}
    score_threshold: 4
    temperature: 0.2