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| 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 | |
| {{input_description}} | |
| # Output 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" | |