CodeGenerator.yaml

name: "CodeGenerator"
verbose: True
description: "A simple demonstration flow that outputs python code"

model_name: "gpt-4"
generation_parameters:
  n: 1
  max_tokens: 3000
  temperature: 0.3

  model_kwargs:
    top_p: 0.2
    frequency_penalty: 0
    presence_penalty: 0

system_message_prompt_template:
  _target_: langchain.PromptTemplate
  template: |2-
    Your goal is to provide executable Python code that solves a problem described by the user.
    The user will provide you with an output format that you will strictly follow.
  input_variables: []
  template_format: jinja2

human_message_prompt_template:
  _target_: langchain.PromptTemplate
  template: "{{query}}"
  input_variables:
    - "query"
  template_format: jinja2

query_message_prompt_template:
  _target_: langchain.PromptTemplate
  template: |2-
    # Problem statement
    {{problem_description}}

    Return Python code that solves the problem. Reply in the following format:
    ```python
    {{code_placeholder}}
    ```
  input_variables:
    - "problem_description"
  partial_variables:
    code_placeholder: "{{python_code}}"
  template_format: jinja2

input_data_transformations: []
input_keys:
  - "problem_description"

output_data_transformations:
  - _target_: flows.data_transformations.RegexFirstOccurrenceExtractor
    regex: '(?<=```python)([\s\S]*?)(?=```)'
    regex_fallback: '(?<=```)([\s\S]*?)(?=```)'
    input_key: "raw_response"
    output_key: "code"
    strip: True
    assert_unique: True
    verbose: True
output_keys:
  - "code"