CCFlows / CF_CodeCritic.yaml
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name: "CodeCritic_Flow"
description: |2-
Given a problem description and a solution candidate, provide useful feedback concerning the correctness of the solution candidate.
# ~~~ Input interface specification ~~~
input_interface_non_initialized:
- "problem_description"
- "input_description"
- "output_description"
- "io_examples_and_explanation"
- "code"
input_interface_initialized:
- "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 identify potential issues with a competitive programming solution attempt.
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
- a Python solution attempt
Crucially, your goal is to correctly identify potential issues with the solution attempt, and not to provide the code implementation yourself.
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}}
# Input description
{{input_description}}
# Output description
{{output_description}}
{{io_examples_and_explanation}}
# Python solution attempt:
```python
{{code}}
```
Consider the problem statement and the solution attempt. Are there any issues with the proposed solution or it is correct? Explain your reasoning very concisely, and do not provide code.
input_variables:
- "problem_description"
- "input_description"
- "output_description"
- "io_examples_and_explanation"
- "code"