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| name: "Code_Flow" | |
| description: |2- | |
| Given a problem description, generate code directly. | |
| # ~~~ Input interface specification ~~~ | |
| input_interface_non_initialized: # Applied when constructing the first user message. | |
| - "problem_description" | |
| - "io_description" | |
| - "constraints" | |
| - "python_stub" | |
| input_interface_initialized: # Applied when constructing all subsequent user messages. | |
| - "query" | |
| # ~~~ Output interface specification ~~~ | |
| output_interface: | |
| - "api_output" | |
| # ~~~ Flow specification ~~~ | |
| backend: | |
| _target_: aiflows.backends.llm_lite.LiteLLMBackend | |
| api_infos: ??? | |
| model_name: | |
| openai: "gpt-4" | |
| azure: "azure/gpt-4" | |
| n: 1 | |
| max_tokens: 3000 | |
| temperature: 0.3 | |
| top_p: 0.2 | |
| frequency_penalty: 0 | |
| presence_penalty: 0 | |
| system_message_prompt_template: | |
| _target_: aiflows.prompt_template.JinjaPrompt | |
| template: |2- | |
| Your goal is to provide executable Python code that solves a coding interview 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 | |
| - example test cases | |
| - the constraints of the problem | |
| The user will provide you with a task and an output format that you will strictly follow. | |
| input_variables: [] | |
| human_message_prompt_template: | |
| _target_: aiflows.prompt_template.JinjaPrompt | |
| template: "{{query}}" | |
| input_variables: | |
| - "query" | |
| init_human_message_prompt_template: | |
| _target_: aiflows.prompt_template.JinjaPrompt | |
| template: |2- | |
| # Problem statement | |
| {{problem_description}} | |
| {{io_description}} | |
| # Constraints | |
| {{constraints}} | |
| Return Python code that solves the problem. The code should extend the following stub: | |
| ```python | |
| {{python_stub}} | |
| ``` | |
| without changing the method signatures. | |
| Reply in the following format: | |
| ```python | |
| {{code_placeholder}} | |
| ``` | |
| input_variables: | |
| - "problem_description" | |
| - "io_description" | |
| - "constraints" | |
| - "python_stub" | |
| partial_variables: | |
| code_placeholder: "{{python_code}}" | |