amir-mohseni / ai-response-evaluation Goto Github PK

This project evaluates the quality of responses generated by different AI models, specifically GPT-4o and Gemini, for a set of user questions. The evaluation is based on a predefined prompt that scores the responses on a scale of 1 to 4, considering the relevance, completeness, and helpfulness of the answers.

1. Install Dependencies: Ensure you have all necessary packages installed. Use the following command to install dependencies:

   %pip install -r requirements.txt

2. Load Environment Variables: Ensure that the .env file contains the necessary API keys for OpenAI and Google Gemini:

   OPENAI_API_KEY=your_openai_api_key
   GOOGLE_API_KEY=your_google_api_key
   

1. Load Data: Load the dataset containing the questions and answers from both AI models.

2. Clean Data: Drop rows with missing questions to ensure the dataset is complete.

3. Evaluate Responses: Evaluate the responses using a predefined prompt template.

4. Review and Rate: Generate reviews and ratings for both GPT-4o and Gemini responses. Iterate through the dataset, evaluate each response, and store the reviews.

5. Calculate Ratings: Extract ratings from the reviews by parsing the review text.

6. Save Evaluated Data: Save the evaluated dataset to a CSV file for further analysis.

7. Visualize Results: Plot the average ratings by category to compare the performance of GPT-4o and Gemini.

8. Analyze Low Ratings: Identify questions with low ratings and save them for further review.

• Eval: This script is used for the evaluation of a single model's responses.
• Pairwise_eval: This script compares responses from two models, providing a direct comparison of their performance.

• The Question Set directory contains the gathered question set, with Q4 containing the latest problems.
• The evaluated responses along with the ratings and reviews are stored in QuestionSet/Q4_evaluated.csv.

The evaluation produced the following key statistics:

• Average Ratings:

  • GPT-4o: Mean rating of 3.81 with a standard deviation of 0.58. The ratings indicate reliable consistency with few low ratings.
  • Gemini: Mean rating of 3.61 with a standard deviation of 0.84. The ratings show more variability with noticeable frequencies across all rating levels.

• Observations:

  • GPT-4o has a slightly higher mean rating compared to Gemini, suggesting generally better performance.
  • The standard deviation for Gemini’s ratings is higher, indicating more variability in the quality of responses.

• Expanded Dataset: Increase the size and diversity of the question set to include more varied topics and difficulty levels.
• Addition of other models: Add more models for a more complete automated benchmark.