name: "Plan_Flow" description: |2- Given a problem description, generate a high-level solution strategy. # ~~~ Input interface specification ~~~ input_interface_non_initialized: # Applied when constructing the first user message. - "problem_description" - "input_description" - "output_description" - "io_examples_and_explanation" input_interface_initialized: # Applied when constructing all subsequent user messages. - "query" # ~~~ Output interface specification ~~~ output_interface: - "api_output" # ~~~ Flow specification ~~~ 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_: flows.prompt_template.JinjaPrompt template: |2- Your goal is to provide a high-level conceptual solution that, if implemented, will solve a given competitive programming problem. 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 proposed algorithm should be computationally efficient, logically correct and handle all corner cases. The user will provide you with a task and an output format that you will strictly follow. input_variables: [] human_message_prompt_template: _target_: flows.prompt_template.JinjaPrompt template: "{{query}}" input_variables: - "query" init_human_message_prompt_template: _target_: flows.prompt_template.JinjaPrompt template: |2- # Problem statement {{problem_description}} # Input description {{input_description}} # Output description {{output_description}} {{io_examples_and_explanation}} Return a high-level conceptual solution that would solve the problem. Be very concise, and do not provide code. Reply in the following format: # Conceptual solution {{plan_placeholder}} input_variables: - "problem_description" - "input_description" - "output_description" - "io_examples_and_explanation" partial_variables: plan_placeholder: "{{conceptual_solution}}"