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