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name: "Plan_Flow" |
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description: |2- |
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Given a problem description, generate a high-level solution strategy. |
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input_interface_non_initialized: |
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- "problem_description" |
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- "input_description" |
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- "output_description" |
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- "io_examples_and_explanation" |
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input_interface_initialized: |
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- "query" |
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output_interface: |
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- "api_output" |
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model_name: |
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openai: "gpt-4" |
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azure: "azure/gpt-4" |
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n: 1 |
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max_tokens: 3000 |
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temperature: 0.3 |
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top_p: 0.2 |
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frequency_penalty: 0 |
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presence_penalty: 0 |
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system_message_prompt_template: |
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_target_: flows.prompt_template.JinjaPrompt |
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template: |2- |
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Your goal is to provide a high-level conceptual solution that, if implemented, will solve a given competitive programming problem. |
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The user will specify the problem by providing you with: |
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- the problem statement |
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- input description |
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- output description |
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- example test cases |
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- (optional) explanation of the test cases |
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The proposed algorithm should be computationally efficient, logically correct and handle all corner cases. |
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The user will provide you with a task and an output format that you will strictly follow. |
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input_variables: [] |
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human_message_prompt_template: |
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_target_: flows.prompt_template.JinjaPrompt |
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template: "{{query}}" |
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input_variables: |
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- "query" |
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init_human_message_prompt_template: |
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_target_: flows.prompt_template.JinjaPrompt |
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template: |2- |
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# Problem statement |
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{{problem_description}} |
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{{input_description}} |
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{{output_description}} |
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{{io_examples_and_explanation}} |
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Return a high-level conceptual solution that would solve the problem. Be very concise, and do not provide code. |
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Reply in the following format: |
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{{plan_placeholder}} |
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input_variables: |
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- "problem_description" |
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- "input_description" |
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- "output_description" |
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- "io_examples_and_explanation" |
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partial_variables: |
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plan_placeholder: "{{conceptual_solution}}" |
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