| name: "Code_Flow" |
| description: "ToDO: add description" |
|
|
| model_name: "gpt-4" |
| generation_parameters: |
| n: 1 |
| max_tokens: 3000 |
| temperature: 0 |
|
|
| model_kwargs: |
| top_p: 1 |
| 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 competitive programming problem. The code should correctly handle all corner cases in order to pass the hidden test cases, which are used to evaluate the correctness of the solution. |
| |
| The user will specify the problem by providing you with: |
| - the problem statement |
| - input description |
| - output description |
| - example test cases |
| - (optional) explanation of the test cases |
|
|
| The user will provide you with a task and 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}} |
| |
| |
| {{input_description}} |
|
|
| |
| {{output_description}} |
|
|
| {{io_examples_and_explanation}} |
|
|
|
|
| The input should be read from the standard input and the output should be passed to the standard output. |
| Return Python code that solves the problem. Reply in the following format: |
| ```python |
| {{code_placeholder}} |
| ``` |
| input_variables: |
| - "problem_description" |
| - "input_description" |
| - "output_description" |
| - "io_examples_and_explanation" |
| partial_variables: |
| code_placeholder: "{{python_code}}" |
| template_format: jinja2 |
|
|
| input_data_transformations: [] |
| input_keys: |
| - "problem_description" |
| - "input_description" |
| - "output_description" |
| - "io_examples_and_explanation" |
|
|
| 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 |
|
|
| output_keys: |
| - "code" |
|
|