User description
…wise ChatGPT makes infinte stream (?). For example in 'generate ai tests', for problem 80 - optimal insertion
Type
Enhancement
Description
- This PR introduces the
frequency_penalty parameter to various toml configuration files in the alpha_codium/settings directory.
- The addition of this parameter is aimed at preventing infinite stream generation by ChatGPT.
Changes walkthrough
| Relevant files |
|---|
| Configuration changes | 10 files
choose_best_solution_direct.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/choose_best_solution_direct.toml
|
+1/-0 |
code_contests_prompt_analyze_and_fix.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompt_analyze_and_fix.toml
|
+1/-0 |
code_contests_prompt_analyze_and_fix_direct.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompt_analyze_and_fix_direct.toml
|
+1/-0 |
code_contests_prompt_analyze_failure.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompt_analyze_failure.toml
|
+1/-0 |
code_contests_prompts_baseline.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompts_baseline.toml
|
+1/-0 |
code_contests_prompts_fix_solution.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompts_fix_solution.toml
|
+1/-0 |
code_contests_prompts_generate_ai_tests.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompts_generate_ai_tests.toml
|
+1/-0 |
code_contests_prompts_generate_possible_solutions.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompts_generate_possible_solutions.toml
|
+1/-0 |
code_contests_prompts_solve.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompts_solve.toml
|
+1/-0 |
code_contests_prompts_solve_direct.tomlAddition of `frequency_penalty` parameter
alpha_codium/settings/code_contests_prompts_solve_direct.toml
|
+1/-0 |
|
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PR Description updated to latest commit (https://github.com/Codium-ai/AlphaCodium/commit/de4566f45ad54edf91de6c7c017ab07ac678f2f8)
PR Analysis
- 🎯 Main theme: Addition of
frequency_penalty parameter to toml configuration files
- 📝 PR summary: This PR adds the
frequency_penalty parameter to various toml configuration files in the alpha_codium/settings directory. The addition of this parameter is aimed at preventing infinite stream generation by ChatGPT.
- 📌 Type of PR: Enhancement
- 🧪 Relevant tests added: No
- ⏱️ Estimated effort to review [1-5]: 1, because the changes are straightforward and involve only the addition of a parameter to configuration files.
- 🔒 Security concerns: No
PR Feedback
💡 General suggestions: The changes seem to be fine. However, it would be beneficial to add comments explaining the purpose of the frequency_penalty parameter in the toml files for future reference.
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PR Code Suggestions
| Suggestions |
|---|
| enhancement |
Add a comment to explain the frequency_penalty parameter.
Consider adding a comment to explain the purpose of the frequency_penalty parameter.
alpha_codium/settings/choose_best_solution_direct.toml [3]
[code_contests_prompts_choose_best_solution_direct]
temperature = 0.3
+# frequency_penalty reduces the likelihood of frequently used tokens appearing in the output
frequency_penalty = 0.1
|
|
| performance |
Adjust the frequency_penalty value based on specific setting requirements.
Consider adjusting the frequency_penalty value based on the specific requirements of the
code_contests_prompt_analyze_and_fix setting.
alpha_codium/settings/code_contests_prompt_analyze_and_fix.toml [3]
[code_contests_prompt_analyze_and_fix]
temperature = 0.2
-frequency_penalty = 0.1
+# Adjusted frequency_penalty to 0.2 for better performance in this specific setting
+frequency_penalty = 0.2
|
Adjust the frequency_penalty value based on specific setting requirements.
Consider adjusting the frequency_penalty value based on the specific requirements of the
code_contests_prompts_baseline setting.
alpha_codium/settings/code_contests_prompts_baseline.toml [3]
[code_contests_prompts_baseline]
temperature = 0.3
-frequency_penalty = 0.1
+# Adjusted frequency_penalty to 0.15 for better performance in this specific setting
+frequency_penalty = 0.15
|
|
| maintainability |
Add a comment to explain the frequency_penalty value in the code_contests_prompt_analyze_failure setting.
Consider adding a comment to explain why the frequency_penalty is set to 0.1 in the
code_contests_prompt_analyze_failure setting.
alpha_codium/settings/code_contests_prompt_analyze_failure.toml [3]
[code_contests_prompt_analyze_failure]
temperature = 0.3
+# Set frequency_penalty to 0.1 to balance the output diversity and relevance
frequency_penalty = 0.1
|
|
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i don't object to this, but it should be a parameter controlled from the configuration file
Thank you for reviewing the PR.
I understand your point, but the current implementation assumes that frequency_penalty (along with temperature) is set in the prompt toml:
https://github.com/Codium-ai/AlphaCodium/blob/ced8fee38b30bea2f8de00141b6976fd994565c5/alpha_codium/settings/code_contests_prompts_reflect.toml#L1-L3
https://github.com/Codium-ai/AlphaCodium/blob/ced8fee38b30bea2f8de00141b6976fd994565c5/alpha_codium/gen/coding_competitor.py#L47
Should frequency_penalty be read from configuration.toml instead? Meaning the same value for all prompts?
@Majdoddin
i initially set frequency_penalty only to stages where I saw this infinite response problem.
if you saw it also in other stages, maybe its best to add it to all stages.
so yes, read this parameter from configuration.toml and add it to the different stages
PR Review
| PR feedback | |
| ⏱️ Estimated effort to review [1-5] |
2, because the changes are mostly configuration updates and a minor logic adjustment in the Python code to handle the frequency_penalty parameter dynamically.
|
| 🧪 Relevant tests |
No
|
| 🔍 Possible issues |
- The use of
None as a default value for frequency_penalty before checking the global settings might lead to unexpected behavior if the settings retrieval fails or returns None.
- The removal of
frequency_penalty from TOML files without ensuring all use cases are covered by the global setting might affect specific stages differently than intended.
|
| 🔒 Security concerns |
No
|
Code feedback:
| relevant file | alpha_codium/gen/coding_competitor.py
|
| suggestion |
Consider initializing frequency_penalty with a default value directly from the global settings instead of setting it to None and then checking. This approach simplifies the logic and ensures frequency_penalty is always defined. [important]
|
| relevant line | frequency_penalty = None |
| relevant file | alpha_codium/gen/coding_competitor.py
|
| suggestion |
It's a good practice to explicitly check for None using is None instead of == None to avoid any unexpected behavior due to custom equality (__eq__) methods. [medium]
|
| relevant line | if frequency_penalty == None: |
| relevant file | alpha_codium/settings/configuration.toml
|
| suggestion |
Ensure that the frequency_penalty value in the global settings is appropriate for all stages. If specific stages require different values, consider maintaining those overrides in their respective TOML files. [important]
|
| relevant line | frequency_penalty=0.1 |
| relevant file | alpha_codium/gen/coding_competitor.py
|
| suggestion |
After retrieving the global frequency_penalty, validate its type and range to ensure it's a float and within an acceptable range (e.g., 0.0 to 1.0) to prevent runtime errors or unexpected behavior. [medium]
|
| relevant line | frequency_penalty = get_settings().get("config.frequency_penalty") |
✨ Review tool usage guide:
Overview:
The review tool scans the PR code changes, and generates a PR review. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on any PR.
When commenting, to edit configurations related to the review tool (pr_reviewer section), use the following template:
/review --pr_reviewer.some_config1=... --pr_reviewer.some_config2=...
With a configuration file, use the following template:
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some_config2=...
Utilizing extra instructions
The review tool can be configured with extra instructions, which can be used to guide the model to a feedback tailored to the needs of your project.
Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify the relevant sub-tool, and the relevant aspects of the PR that you want to emphasize.
Examples for extra instructions:
[pr_reviewer] # /review #
extra_instructions="""
In the 'possible issues' section, emphasize the following:
- Does the code logic cover relevant edge cases?
- Is the code logic clear and easy to understand?
- Is the code logic efficient?
...
"""
Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.
|
How to enable\disable automation
- When you first install PR-Agent app, the default mode for the
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Edit this field to enable/disable the tool, or to change the used configurations
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possible security issue label, that detects possible security issues (enable_review_labels_security flag)
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