Tr/pypi

[mrT23]

see https://test.pypi.org/project/pr-agent/

Type

enhancement, documentation

---

Description

• Updated MANIFEST.in to include necessary files for PyPI distribution.
• Enhanced README.md with updated project aims, improved visuals, and revised supported commands section.
• Prepared pyproject.toml for PyPI packaging with updated project information, dependencies, and packaging configurations.
• Updated dependencies in requirements.txt for better compatibility and stability.

---

Changes walkthrough

	Relevant files
Configuration changes	MANIFEST.in Update Package Manifest for PyPI Distribution                        MANIFEST.in Include all .toml files in the pr_agent package. Exclude .secrets.toml files from the pr_agent package. +2/-0      pyproject.toml Prepare `pyproject.toml` for Enhanced PyPI Packaging          pyproject.toml Changed the project name to pr-agent and updated version to 0.2.0. Updated the authors and maintainers list. Revised the project description to align with the README changes. Updated the package keywords and license information. Enabled include-package-data for better package data management. Updated dependencies and project URLs. +14/-14
Documentation	README.md Enhance README with Updated Information and Visuals            README.md Updated the logo image to be visible in both light and dark modes. Revised the project's aim for clarity and added AI feedbacks and suggestions. Updated the supported commands and tools section with new icons. +33/-32
Dependencies	requirements.txt Update Dependencies for Better Compatibility                          requirements.txt Updated pinecone-client to version 3.2.0. Updated pinecone-datasets to version 0.6.1. +2/-2

---

✨ PR-Agent usage:
Comment /help on the PR to get a list of all available PR-Agent tools and their descriptions

[codiumai-pr-agent-pro]

CI Failure Feedback

(Checks updated until commit dab033c)

Action: build-and-test

Failed stage: Build dev docker [❌]

Failure summary: The action failed due to a dependency conflict between two packages, lancedb and pr-agent, which indirectly caused by conflicting version requirements for pyarrow by pinecone-datasets and pylance. Specifically: pinecone-datasets 0.6.1 requires pyarrow version to be between 11.0.0 and 12.0.0 (inclusive on the lower bound, exclusive on the upper bound). pylance 0.9.7 requires pyarrow version 12 or newer. This conflict makes it impossible for pip to resolve a set of package versions that satisfies all dependencies, leading to a ResolutionImpossible error during the package installation process in the Docker build step.

Relevant error logs: 1: ##[group]Operating System 2: Ubuntu ... 1144: #11 15.52 INFO: pip is looking at multiple versions of dynaconf to determine which version is compatible with other requirements. This could take a while. 1145: #11 15.52 INFO: pip is looking at multiple versions of boto3 to determine which version is compatible with other requirements. This could take a while. 1146: #11 15.52 INFO: pip is looking at multiple versions of azure-identity to determine which version is compatible with other requirements. This could take a while. 1147: #11 15.52 INFO: pip is looking at multiple versions of azure-devops to determine which version is compatible with other requirements. This could take a while. 1148: #11 15.52 INFO: pip is looking at multiple versions of atlassian-python-api to determine which version is compatible with other requirements. This could take a while. 1149: #11 15.52 INFO: pip is looking at multiple versions of aiohttp to determine which version is compatible with other requirements. This could take a while. 1150: #11 15.52 INFO: pip is looking at multiple versions of <Python from Requires-Python> to determine which version is compatible with other requirements. This could take a while. 1151: #11 15.52 INFO: pip is looking at multiple versions of pr-agent to determine which version is compatible with other requirements. This could take a while. 1152: #11 15.52 ERROR: Cannot install lancedb and pr-agent because these package versions have conflicting dependencies. ... 1154: #11 15.52 The conflict is caused by: 1155: #11 15.52 pinecone-datasets 0.6.1 depends on pyarrow<12.0.0 and >=11.0.0 1156: #11 15.52 pylance 0.9.7 depends on pyarrow>=12 1157: #11 15.52 1158: #11 15.52 To fix this you could try to: 1159: #11 15.52 1. loosen the range of package versions you've specified 1160: #11 15.52 2. remove package versions to allow pip attempt to solve the dependency conflict 1161: #11 15.52 1162: #11 15.52 ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts 1163: #11 15.53 1164: #11 15.53 [notice] A new release of pip is available: 23.0.1 -> 24.0 1165: #11 15.53 [notice] To update, run: pip install --upgrade pip 1166: #11 ERROR: process "/bin/sh -c pip install . && rm pyproject.toml requirements.txt" did not complete successfully: exit code: 1 1167: ------ 1168: > [base 5/5] RUN pip install . && rm pyproject.toml requirements.txt: 1169: 15.52 pylance 0.9.7 depends on pyarrow>=12 1170: 15.52 1171: 15.52 To fix this you could try to: 1172: 15.52 1. loosen the range of package versions you've specified 1173: 15.52 2. remove package versions to allow pip attempt to solve the dependency conflict 1174: 15.52 1175: 15.52 ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/topics/dependency-resolution/#dealing-with-dependency-conflicts ... 1180: Dockerfile:6 1181: -------------------- 1182: 4 | ADD pyproject.toml . 1183: 5 | ADD requirements.txt . 1184: 6 | >>> RUN pip install . && rm pyproject.toml requirements.txt 1185: 7 | ENV PYTHONPATH=/app 1186: 8 | 1187: -------------------- 1188: ERROR: failed to solve: process "/bin/sh -c pip install . && rm pyproject.toml requirements.txt" did not complete successfully: exit code: 1 1189: ##[error]buildx failed with: ERROR: failed to solve: process "/bin/sh -c pip install . && rm pyproject.toml requirements.txt" did not complete successfully: exit code: 1

---

✨ CI feedback usage guide:

---

The CI feedback tool (/checks) automatically triggers when a PR has a failed check.
The tool analyzes the failed checks and provides several feedbacks:

• Failed stage
• Failed test name
• Failure summary
• Relevant error logs

In addition to being automatically triggered, the tool can also be invoked manually by commenting on a PR:

/checks "https://github.com/{repo_name}/actions/runs/{run_number}/job/{job_number}"

where {repo_name} is the name of the repository, {run_number} is the run number of the failed check, and {job_number} is the job number of the failed check.

Configuration options

• enable_auto_checks_feedback - if set to true, the tool will automatically provide feedback when a check is failed. Default is true.
• excluded_checks_list - a list of checks to exclude from the feedback, for example: ["check1", "check2"]. Default is an empty list.
• enable_help_text - if set to true, the tool will provide a help message with the feedback. Default is true.
• persistent_comment - if set to true, the tool will overwrite a previous checks comment with the new feedback. Default is true.
• final_update_message - if persistent_comment is true and updating a previous checks message, the tool will also create a new message: "Persistent checks updated to latest commit". Default is true.

See more information about the checks tool in the docs.

[codiumai-pr-agent-pro]

PR Description updated to latest commit (d1fc6c6)

• Copy walkthrough table to "Files Changed" Tab

[codiumai-pr-agent-pro]

PR Review

⏱️ Estimated effort to review [1-5]	2, because the changes are mostly configuration and documentation updates, which are straightforward to review. The complexity is low, and the changes are well-documented and structured.
🏅 Score	85
🧪 Relevant tests	No
🔍 Possible issues	Dependency Version Locking: The explicit version locking in requirements.txt for pinecone-client and pinecone-datasets might lead to compatibility issues in the future if not regularly updated.
🔒 Security concerns	No
🔀 Multiple PR themes	Sub-PR theme: Update project packaging configuration for PyPI Relevant files: MANIFEST.in pyproject.toml
	Sub-PR theme: Enhance README with updated project information and visuals Relevant files: README.md
	Sub-PR theme: Update dependencies for better compatibility and stability Relevant files: requirements.txt

---

✨ 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:

[pr_reviewer]
some_config1=...
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 review tool is: pr_commands = ["/review", ...] meaning the review tool will run automatically on every PR, with the default configuration. Edit this field to enable/disable the tool, or to change the used configurations

Auto-labels The review tool can auto-generate two specific types of labels for a PR: a possible security issue label, that detects possible security issues (enable_review_labels_security flag) a Review effort [1-5]: x label, where x is the estimated effort to review the PR (enable_review_labels_effort flag)

Extra sub-tools The review tool provides a collection of possible feedbacks about a PR. It is recommended to review the possible options, and choose the ones relevant for your use case. Some of the feature that are disabled by default are quite useful, and should be considered for enabling. For example: require_score_review, require_soc2_ticket, require_can_be_split_review, and more.

Auto-approve PRs By invoking: /review auto_approve The tool will automatically approve the PR, and add a comment with the approval. To ensure safety, the auto-approval feature is disabled by default. To enable auto-approval, you need to actively set in a pre-defined configuration file the following: [pr_reviewer] enable_auto_approval = true (this specific flag cannot be set with a command line argument, only in the configuration file, committed to the repository) You can also enable auto-approval only if the PR meets certain requirements, such as that the estimated_review_effort is equal or below a certain threshold, by adjusting the flag: [pr_reviewer] maximal_review_effort = 5

More PR-Agent commands To invoke the PR-Agent, add a comment using one of the following commands: /review: Request a review of your Pull Request. /describe: Update the PR title and description based on the contents of the PR. /improve [--extended]: Suggest code improvements. Extended mode provides a higher quality feedback. /ask <QUESTION>: Ask a question about the PR. /update_changelog: Update the changelog based on the PR's contents. /add_docs 💎: Generate docstring for new components introduced in the PR. /generate_labels 💎: Generate labels for the PR based on the PR's contents. /analyze 💎: Automatically analyzes the PR, and presents changes walkthrough for each component. See the tools guide for more details. To list the possible configuration parameters, add a /config comment.

See the review usage page for a comprehensive guide on using this tool.

[codiumai-pr-agent-pro]

PR Code Suggestions

Category	Suggestions
Best practice	Use more specific patterns for including .toml files. Consider using a more specific pattern for including .toml files to avoid accidentally including unnecessary .toml files in your package. If there are specific .toml files that are needed, list them explicitly or use a more restrictive pattern. MANIFEST.in [1] -recursive-include pr_agent *.toml +include pr_agent/pyproject.toml +include pr_agent/another_needed_file.toml
	Specify the minimum Python version more precisely. It's recommended to specify the minimum Python version more precisely if your package uses features introduced in a minor version. For example, if you're using features introduced in Python 3.10.2, specify it to avoid compatibility issues. pyproject.toml [19] -requires-python = ">=3.10" +requires-python = ">=3.10.2"
	Pin the versions of new dependencies for reproducibility. Pin the versions of pinecone-client and pinecone-datasets to ensure reproducible builds and avoid potential incompatibilities with future versions. Use the == operator to specify exact versions. requirements.txt [16-17] -pinecone-client==3.2.0 -pinecone-datasets==0.6.1 +pinecone-client==3.2.0 # Pin to the current working version +pinecone-datasets==0.6.1 # Pin to the current working version
Enhancement	Add a width attribute to the tag for layout stability. Ensure that the tag includes a width attribute to maintain consistency with the tags above it, and to improve the layout stability during image loading. README.md [9] -<img src="https://codium.ai/images/pr_agent/logo-light.png" alt="logo"> +<img src="https://codium.ai/images/pr_agent/logo-light.png" alt="logo" width="330">
	Add more classifiers to better categorize your package. Consider adding more classifiers to pyproject.toml to better categorize your package on PyPI. For example, adding a License classifier and Operating System classifiers can make it easier for users to find your package based on their requirements. pyproject.toml [23-26] classifiers = [ "Intended Audience :: Developers", "Programming Language :: Python :: 3", + "License :: OSI Approved :: Apache Software License", + "Operating System :: OS Independent", ]

---

✨ Improve tool usage guide:

---

Overview:
The improve tool scans the PR code changes, and automatically generates suggestions for improving the PR code. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on a PR.
When commenting, to edit configurations related to the improve tool (pr_code_suggestions section), use the following template:

/improve --pr_code_suggestions.some_config1=... --pr_code_suggestions.some_config2=...

With a configuration file, use the following template:

[pr_code_suggestions]
some_config1=...
some_config2=...

Enabling\disabling automation When you first install the app, the default mode for the improve tool is: pr_commands = ["/improve --pr_code_suggestions.summarize=true", ...] meaning the improve tool will run automatically on every PR, with summarization enabled. Delete this line to disable the tool from running automatically.

Utilizing extra instructions Extra instructions are very important for the improve tool, since they enable to guide the model to suggestions that are more relevant to the specific needs of the project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify relevant aspects that you want the model to focus on. Examples for extra instructions: [pr_code_suggestions] # /improve # extra_instructions=""" Emphasize the following aspects: - 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.

A note on code suggestions quality While the current AI for code is getting better and better (GPT-4), it's not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. Suggestions are not meant to be simplistic. Instead, they aim to give deep feedback and raise questions, ideas and thoughts to the user, who can then use his judgment, experience, and understanding of the code base. Recommended to use the 'extra_instructions' field to guide the model to suggestions that are more relevant to the specific needs of the project, or use the custom suggestions 💎 tool With large PRs, best quality will be obtained by using 'improve --extended' mode.

More PR-Agent commands To invoke the PR-Agent, add a comment using one of the following commands: /review: Request a review of your Pull Request. /describe: Update the PR title and description based on the contents of the PR. /improve [--extended]: Suggest code improvements. Extended mode provides a higher quality feedback. /ask <QUESTION>: Ask a question about the PR. /update_changelog: Update the changelog based on the PR's contents. /add_docs 💎: Generate docstring for new components introduced in the PR. /generate_labels 💎: Generate labels for the PR based on the PR's contents. /analyze 💎: Automatically analyzes the PR, and presents changes walkthrough for each component. See the tools guide for more details. To list the possible configuration parameters, add a /config comment.

See the improve usage page for a more comprehensive guide on using this tool.

[mrT23]

/improve

[codiumai-pr-agent-pro]

PR Code Suggestions

Category	Suggestions
Best practice	Use consistent argument naming conventions. It's recommended to use consistent argument naming conventions. In the usage examples, you have mixed --pr_url and --pr-url. Choose one format and stick with it to avoid confusion. pr_agent/cli.py [17-22] -- cli.py --pr_url=... review -- cli.py --pr_url=... describe -- cli.py --pr_url=... improve -- cli.py --pr_url=... ask "write me a poem about this PR" -- cli.py --pr_url=... reflect -- cli.py --issue_url=... similar_issue +- cli.py --pr-url=... review +- cli.py --pr-url=... describe +- cli.py --pr-url=... improve +- cli.py --pr-url=... ask "write me a poem about this PR" +- cli.py --pr-url=... reflect +- cli.py --issue-url=... similar_issue
	Use specific exceptions for clearer error handling. Instead of raising a generic Exception when required packages are not installed, raise a more specific exception like ImportError to provide clearer error handling. pr_agent/tools/pr_similar_issue.py [41] -except: - raise Exception("Please install 'pinecone' and 'pinecone_datasets' to use pinecone as vectordb") +except ImportError: + raise ImportError("Please install 'pinecone' and 'pinecone_datasets' to use pinecone as vectordb")
	Use environment variables for sensitive information. It's recommended to avoid hardcoding sensitive information such as user_token and openai_key directly in the script. Instead, consider using environment variables or a secure vault service to handle sensitive data securely. docs/docs/installation/locally.md [19-21] -user_token = "..." # GitHub user token -openai_key = "..." # OpenAI key +import os +user_token = os.getenv("GITHUB_USER_TOKEN") # GitHub user token +openai_key = os.getenv("OPENAI_KEY") # OpenAI key
	Use consistent quote styles in TOML files. Ensure consistency in the use of quotes for strings in the TOML file. It's recommended to stick to one style (either single or double quotes) throughout the file for better readability. pyproject.toml [6-43] -name = "pr-agent" -version = "0.2.0" +name = 'pr-agent' +version = '0.2.0' ... -include = ["pr_agent*"] # include pr_agent and any sub-packages it finds under it. +include = ['pr_agent*'] # include pr_agent and any sub-packages it finds under it.
	Pin versions of commented dependencies for reproducibility. Consider pinning the versions of the newly commented dependencies (pinecone-client, pinecone-datasets, lancedb, langchain) to ensure reproducibility and to avoid potential incompatibilities with future versions. requirements.txt [26-31] # Uncomment the following lines to enable the 'similar issue' tool -# pinecone-client -# pinecone-datasets @ git+https://github.com/mrT23/pinecone-datasets.git@main +# pinecone-client==<version> +# pinecone-datasets @ git+https://github.com/mrT23/pinecone-datasets.git@<commit_hash> # lancedb==0.5.1 # uncomment this to support language LangChainOpenAIHandler # langchain==0.0.349
	Pin versions of development dependencies. For poetry and twine, it's a good practice to specify the versions to avoid potential future compatibility issues or unexpected behavior due to updates. requirements-dev.txt [2-3] -poetry -twine +poetry==<version> +twine==<version>
Security	Avoid hardcoding sensitive information in the code. For security and maintainability, avoid hardcoding sensitive information like tokens directly in the code. Consider using environment variables or a secure vault service. pr_agent/cli_pip.py [10-13] +import os provider = "github" # GitHub provider -user_token = "..." # GitHub user token -openai_key = "..." # OpenAI key -pr_url = "..." # PR URL, for example 'https://github.com/Codium-ai/pr-agent/pull/809' +user_token = os.getenv("GITHUB_USER_TOKEN") # GitHub user token +openai_key = os.getenv("OPENAI_KEY") # OpenAI key +pr_url = os.getenv("PR_URL") # PR URL, for example 'https://github.com/Codium-ai/pr-agent/pull/809'
Maintainability	Move dynamic import logic to a separate function for better maintainability. To improve code readability and maintainability, consider moving the dynamic import logic to a separate function or module. This approach centralizes the handling of optional dependencies. pr_agent/tools/pr_similar_issue.py [36-41] -try: - import pinecone - from pinecone_datasets import Dataset, DatasetMetadata - import pandas as pd -except: - raise Exception("Please install 'pinecone' and 'pinecone_datasets' to use pinecone as vectordb") +def try_import_pinecone(): + try: + import pinecone + from pinecone_datasets import Dataset, DatasetMetadata + import pandas as pd + return pinecone, Dataset, DatasetMetadata, pd + except ImportError: + raise ImportError("Please install 'pinecone' and 'pinecone_datasets' to use pinecone as vectordb")
	Break down the main function for better readability. For better maintainability and readability, consider breaking down the main function into smaller functions, each handling a specific part of the setup and execution process. docs/docs/installation/locally.md [17-35] +def setup_configuration(provider, user_token, openai_key): + # Setting the configurations + ... + +def prepare_and_run_command(pr_url, command): + # Preparing the command and running it + ... + def main(): - # Fill in the following values ... - # Run the command. Feedback will appear in GitHub PR comments - cli.run(args=args) + setup_configuration(provider, user_token, openai_key) + prepare_and_run_command(pr_url, command)
Enhancement	Add detailed help messages for CLI arguments. To enhance the CLI user experience, consider adding more detailed help messages for each command argument, explaining their purpose and usage more clearly. pr_agent/cli.py [47-50] -parser.add_argument('--pr_url', type=str, help='The URL of the PR to review', default=None) -parser.add_argument('--issue_url', type=str, help='The URL of the Issue to review', default=None) -parser.add_argument('command', type=str, help='The', choices=commands, default='review') -parser.add_argument('rest', nargs=argparse.REMAINDER, default=[]) +parser.add_argument('--pr-url', type=str, help='The URL of the Pull Request to review. Example: https://github.com/user/repo/pull/123', default=None) +parser.add_argument('--issue-url', type=str, help='The URL of the Issue to analyze. Example: https://github.com/user/repo/issues/456', default=None) +parser.add_argument('command', type=str, help='The command to execute on the PR or Issue.', choices=commands, default='review') +parser.add_argument('rest', nargs=argparse.REMAINDER, help='Additional arguments for the command, if any.', default=[])

---

✨ Improve tool usage guide:

---

Overview:
The improve tool scans the PR code changes, and automatically generates suggestions for improving the PR code. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on a PR.
When commenting, to edit configurations related to the improve tool (pr_code_suggestions section), use the following template:

/improve --pr_code_suggestions.some_config1=... --pr_code_suggestions.some_config2=...

With a configuration file, use the following template:

[pr_code_suggestions]
some_config1=...
some_config2=...

Enabling\disabling automation When you first install the app, the default mode for the improve tool is: pr_commands = ["/improve --pr_code_suggestions.summarize=true", ...] meaning the improve tool will run automatically on every PR, with summarization enabled. Delete this line to disable the tool from running automatically.

Utilizing extra instructions Extra instructions are very important for the improve tool, since they enable to guide the model to suggestions that are more relevant to the specific needs of the project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify relevant aspects that you want the model to focus on. Examples for extra instructions: [pr_code_suggestions] # /improve # extra_instructions=""" Emphasize the following aspects: - 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.

A note on code suggestions quality While the current AI for code is getting better and better (GPT-4), it's not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. Suggestions are not meant to be simplistic. Instead, they aim to give deep feedback and raise questions, ideas and thoughts to the user, who can then use his judgment, experience, and understanding of the code base. Recommended to use the 'extra_instructions' field to guide the model to suggestions that are more relevant to the specific needs of the project, or use the custom suggestions 💎 tool With large PRs, best quality will be obtained by using 'improve --extended' mode.

More PR-Agent commands To invoke the PR-Agent, add a comment using one of the following commands: /review: Request a review of your Pull Request. /describe: Update the PR title and description based on the contents of the PR. /improve [--extended]: Suggest code improvements. Extended mode provides a higher quality feedback. /ask <QUESTION>: Ask a question about the PR. /update_changelog: Update the changelog based on the PR's contents. /add_docs 💎: Generate docstring for new components introduced in the PR. /generate_labels 💎: Generate labels for the PR based on the PR's contents. /analyze 💎: Automatically analyzes the PR, and presents changes walkthrough for each component. See the tools guide for more details. To list the possible configuration parameters, add a /config comment.

See the improve usage page for a more comprehensive guide on using this tool.