This pull request introduces the ability for users to submit their own questions that the model will answer in the context of generating performance reviews. This enhancement aims to provide more flexibility and customization in the review generation process, allowing users to tailor the feedback to specific areas of interest or concern.
Summary
Modified the generate_review function in src/app.py to accept an additional parameter user_questions, which is a list of questions provided by the user.
Updated the generate_prompt function to incorporate user_questions into the prompt sent to the OpenAI model, replacing the previously static set of questions.
Adjusted the call to generate_review within the Streamlit UI code to include a hardcoded list of sample questions, demonstrating how user questions can be integrated into the review generation process.
These changes enhance the application's flexibility and user interactivity by allowing custom questions to be part of the performance review generation.
Fixes #6.
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Description
This pull request introduces the ability for users to submit their own questions that the model will answer in the context of generating performance reviews. This enhancement aims to provide more flexibility and customization in the review generation process, allowing users to tailor the feedback to specific areas of interest or concern.
Summary
generate_review
function insrc/app.py
to accept an additional parameteruser_questions
, which is a list of questions provided by the user.generate_prompt
function to incorporateuser_questions
into the prompt sent to the OpenAI model, replacing the previously static set of questions.generate_review
within the Streamlit UI code to include a hardcoded list of sample questions, demonstrating how user questions can be integrated into the review generation process.Fixes #6.
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