add github code #4

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mschoi merged 52 commits from impl_code_review into main 2025-01-09 16:20:38 +09:00
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mschoi added 1 commit 2024-12-31 00:48:21 +09:00
add github test
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mschoi added 1 commit 2024-12-31 00:49:54 +09:00
remake wrong test file
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mschoi added 1 commit 2024-12-31 01:01:33 +09:00
change test values
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mschoi added 1 commit 2024-12-31 01:11:14 +09:00
fix json directory
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mschoi added 1 commit 2024-12-31 01:12:02 +09:00
fix typo 'index' to 'label'
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mschoi added 1 commit 2025-01-08 09:51:11 +09:00
update test
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mschoi added 1 commit 2025-01-08 10:48:19 +09:00
parse diff into chunk
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mschoi added 1 commit 2025-01-08 10:49:50 +09:00
update code review yml
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mschoi added 1 commit 2025-01-08 10:50:43 +09:00
comment action tag until finish development
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mschoi added 1 commit 2025-01-08 10:56:19 +09:00
update pattern
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mschoi added 1 commit 2025-01-08 11:36:55 +09:00
update pattern
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mschoi added 1 commit 2025-01-08 11:39:58 +09:00
add exclude option
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mschoi added 1 commit 2025-01-08 11:43:09 +09:00
update exclude pattern format
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mschoi added 1 commit 2025-01-08 11:53:57 +09:00
change to use fnmatch
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mschoi added 1 commit 2025-01-08 11:58:44 +09:00
update pip dependencies
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mschoi added 1 commit 2025-01-08 18:26:49 +09:00
add single chunk comments
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mschoi added 1 commit 2025-01-08 18:28:25 +09:00
test real data
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mschoi added 1 commit 2025-01-08 18:34:30 +09:00
fix api method format
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mschoi added 1 commit 2025-01-08 18:35:09 +09:00
fix system argument
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mschoi added 1 commit 2025-01-08 18:37:40 +09:00
test claude message
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mschoi added 1 commit 2025-01-08 18:39:29 +09:00
test claude response
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mschoi added 1 commit 2025-01-08 18:43:21 +09:00
update parser
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mschoi added 1 commit 2025-01-09 08:41:06 +09:00
deepseek api test
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mschoi added 1 commit 2025-01-09 08:43:15 +09:00
resolve system prompt parameter
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mschoi added 1 commit 2025-01-09 09:07:41 +09:00
update deepseek base url
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mschoi added 1 commit 2025-01-09 09:30:48 +09:00
update json parsing
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mschoi added 1 commit 2025-01-09 09:35:13 +09:00
change secrets
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mschoi added 1 commit 2025-01-09 10:15:46 +09:00
remove access_token
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mschoi added 1 commit 2025-01-09 10:18:49 +09:00
test google gemini
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mschoi added 1 commit 2025-01-09 10:23:04 +09:00
update google system prompt
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mschoi added 1 commit 2025-01-09 10:28:47 +09:00
update cache and parsing algorithm
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mschoi added 1 commit 2025-01-09 10:32:25 +09:00
remove cache
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mschoi added 1 commit 2025-01-09 10:33:24 +09:00
update strip
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mschoi added 1 commit 2025-01-09 10:36:15 +09:00
test for gpt
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mschoi added 1 commit 2025-01-09 12:49:57 +09:00
test full context response
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mschoi added 1 commit 2025-01-09 12:51:16 +09:00
fix url parsing structure
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mschoi added 1 commit 2025-01-09 12:53:13 +09:00
fix / to %2F
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mschoi added 1 commit 2025-01-09 12:55:56 +09:00
fix base url for api
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mschoi added 1 commit 2025-01-09 13:07:10 +09:00
fix url
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mschoi added 1 commit 2025-01-09 13:13:39 +09:00
remove o1 because I cannot use it
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mschoi added 1 commit 2025-01-09 13:21:06 +09:00
reduce max token
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mschoi added 1 commit 2025-01-09 13:24:34 +09:00
add instruction
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mschoi added 1 commit 2025-01-09 13:29:09 +09:00
improve prompt
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mschoi added 1 commit 2025-01-09 14:05:49 +09:00
restrict start message
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mschoi added 1 commit 2025-01-09 14:06:48 +09:00
add code block restriction
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mschoi added 1 commit 2025-01-09 14:09:37 +09:00
strict restriction for give code
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mschoi added 1 commit 2025-01-09 14:27:29 +09:00
test mock review
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mschoi added 1 commit 2025-01-09 14:28:22 +09:00
add access token for write permission
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mschoi reviewed 2025-01-09 14:33:55 +09:00
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This is a mock full context response.

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[GPT-REVIEW] This is a mock comment.

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mschoi reviewed 2025-01-09 14:35:52 +09:00
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mschoi reviewed 2025-01-09 14:36:20 +09:00
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[GPT-REVIEW] This is a mock comment.

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mschoi reviewed 2025-01-09 14:40:24 +09:00
@@ -0,0 +2,4 @@
import os
import re
import fnmatch
import json
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Hello

Hello
mschoi reviewed 2025-01-09 14:42:56 +09:00
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This is a mock full context response.

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[GPT-REVIEW] This is a mock comment.

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mschoi reviewed 2025-01-09 14:43:17 +09:00
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mschoi reviewed 2025-01-09 14:51:02 +09:00
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mschoi reviewed 2025-01-09 15:53:29 +09:00
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mschoi reviewed 2025-01-09 15:55:56 +09:00
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This is a mock full context response.

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@@ -25,4 +25,3 @@
- name: Run Code Review
env:
GITEA_TOKEN: ${{ secrets.GITEA_TOKEN }}
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[GPT-REVIEW] This is a mock comment.

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mschoi reviewed 2025-01-09 15:56:19 +09:00
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This is a mock full context response.

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@@ -27,3 +27,2 @@
env:
GITEA_TOKEN: ${{ secrets.GITEA_TOKEN }}
CLAUDE_API_KEY: ${{ secrets.CLAUDE_API_KEY }}
CLAUDE_API_KEY: ${{ secrets.ANTHROPIC_API_KEY }}
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[GPT-REVIEW] This is a mock comment.

[GPT-REVIEW] This is a mock comment.
mschoi added 1 commit 2025-01-09 16:00:05 +09:00
final e2e test
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mschoi added 1 commit 2025-01-09 16:07:32 +09:00
add access token
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mschoi reviewed 2025-01-09 16:08:08 +09:00
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Code Structure & Architecture

The code is structured into multiple functions and classes, which is a good practice for modularity. However, there are some areas that could be improved for better organization and readability:

  • Separation of Concerns: The main function in both code_review.py and github_code.py scripts is handling multiple responsibilities, such as reading event data, fetching diffs, and posting comments. Consider breaking down these responsibilities into smaller, more focused functions.

  • Class Usage: The PRDetails class is used to encapsulate pull request details. However, it could be beneficial to add methods to this class that handle related operations, such as fetching the diff or posting comments, to encapsulate behavior as well as data.

Refactoring Opportunities

  • Repeated Code: There is a significant amount of repeated logic between the two scripts, particularly in handling API requests and parsing diffs. Consider creating utility functions or a helper module to avoid code duplication.

  • Error Handling: The current error handling strategy is to print errors and continue execution. This could be improved by implementing a more robust error handling mechanism that can retry operations or fail gracefully.

  • Environment Variable Access: Accessing environment variables multiple times can be inefficient. Consider loading them once at the start of the script and storing them in a configuration object or dictionary.

Potential Future Problems

  • Scalability: The use of synchronous HTTP requests (requests.get) could become a bottleneck if the system needs to handle a large number of pull requests concurrently. Consider using asynchronous requests or a task queue to improve scalability.

  • Dependency Management: The code relies on several external libraries (e.g., openai, anthropic, requests). Ensure that these dependencies are properly managed and versioned to avoid compatibility issues in the future.

  • Security: Sensitive information such as API keys is being accessed directly from environment variables. Ensure that these are stored securely and consider using a secrets management tool to handle them.

Example Refactoring

Here's an example of how you might refactor the main function to improve separation of concerns:

def main():
    pr_details = get_pr_details()
    event_data = load_event_data()

    if event_data["action"] not in ["opened", "synchronize"]:
        print("Unsupported event.")
        return

    diff = fetch_diff(pr_details, event_data)
    if not diff:
        print("No diff found.")
        return

    parsed_diff = parse_diff(diff)
    comments = analyze_code(parsed_diff, pr_details)
    if comments:
        create_review_comment(pr_details.owner, pr_details.repo, pr_details.pull_number, comments)

def load_event_data() -> dict:
    with open(GITHUB_EVENT_PATH, "r") as f:
        return json.load(f)

def fetch_diff(pr_details: PRDetails, event_data: dict) -> Optional[str]:
    if event_data["action"] == "opened":
        return get_diff(pr_details.owner, pr_details.repo, pr_details.pull_number)
    elif event_data["action"] == "synchronize":
        return get_synchronized_diff(pr_details, event_data)
    return None

This refactoring separates the loading of event data and fetching of diffs into their own functions, making the main function easier to read and maintain.

### Code Structure & Architecture The code is structured into multiple functions and classes, which is a good practice for modularity. However, there are some areas that could be improved for better organization and readability: - **Separation of Concerns**: The `main` function in both `code_review.py` and `github_code.py` scripts is handling multiple responsibilities, such as reading event data, fetching diffs, and posting comments. Consider breaking down these responsibilities into smaller, more focused functions. - **Class Usage**: The `PRDetails` class is used to encapsulate pull request details. However, it could be beneficial to add methods to this class that handle related operations, such as fetching the diff or posting comments, to encapsulate behavior as well as data. ### Refactoring Opportunities - **Repeated Code**: There is a significant amount of repeated logic between the two scripts, particularly in handling API requests and parsing diffs. Consider creating utility functions or a helper module to avoid code duplication. - **Error Handling**: The current error handling strategy is to print errors and continue execution. This could be improved by implementing a more robust error handling mechanism that can retry operations or fail gracefully. - **Environment Variable Access**: Accessing environment variables multiple times can be inefficient. Consider loading them once at the start of the script and storing them in a configuration object or dictionary. ### Potential Future Problems - **Scalability**: The use of synchronous HTTP requests (`requests.get`) could become a bottleneck if the system needs to handle a large number of pull requests concurrently. Consider using asynchronous requests or a task queue to improve scalability. - **Dependency Management**: The code relies on several external libraries (e.g., `openai`, `anthropic`, `requests`). Ensure that these dependencies are properly managed and versioned to avoid compatibility issues in the future. - **Security**: Sensitive information such as API keys is being accessed directly from environment variables. Ensure that these are stored securely and consider using a secrets management tool to handle them. ### Example Refactoring Here's an example of how you might refactor the `main` function to improve separation of concerns: ```python def main(): pr_details = get_pr_details() event_data = load_event_data() if event_data["action"] not in ["opened", "synchronize"]: print("Unsupported event.") return diff = fetch_diff(pr_details, event_data) if not diff: print("No diff found.") return parsed_diff = parse_diff(diff) comments = analyze_code(parsed_diff, pr_details) if comments: create_review_comment(pr_details.owner, pr_details.repo, pr_details.pull_number, comments) def load_event_data() -> dict: with open(GITHUB_EVENT_PATH, "r") as f: return json.load(f) def fetch_diff(pr_details: PRDetails, event_data: dict) -> Optional[str]: if event_data["action"] == "opened": return get_diff(pr_details.owner, pr_details.repo, pr_details.pull_number) elif event_data["action"] == "synchronize": return get_synchronized_diff(pr_details, event_data) return None ``` This refactoring separates the loading of event data and fetching of diffs into their own functions, making the `main` function easier to read and maintain.
@@ -0,0 +55,4 @@
self.owner = owner
self.repo = repo
self.pull_number = pull_number
self.title = title
Author
Owner

[REVIEW] The ACCESS_TOKEN is being retrieved from the environment variables without any validation or error handling. Consider adding a check to ensure that the token is not empty and handle the case where it might be missing.

[REVIEW] The `ACCESS_TOKEN` is being retrieved from the environment variables without any validation or error handling. Consider adding a check to ensure that the token is not empty and handle the case where it might be missing.
@@ -0,0 +71,4 @@
FULL_CONTEXT_MODEL = os.getenv("FULL_CONTEXT_MODEL", "o1")
SINGLE_CHUNK_MODEL = os.getenv("SINGLE_CHUNK_MODEL", "claude-3-5-sonnet-20241022")
Author
Owner

[REVIEW] The GITHUB_EVENT_PATH is used directly without checking if the environment variable is set or if the file exists. Consider adding error handling to manage cases where the file might not be found or the environment variable is not set.

[REVIEW] The `GITHUB_EVENT_PATH` is used directly without checking if the environment variable is set or if the file exists. Consider adding error handling to manage cases where the file might not be found or the environment variable is not set.
@@ -0,0 +127,4 @@
)
elif any(key in model for key in ["deepseek"]):
deepseek = OpenAI(api_key=DEEPSEEK_API_KEY, base_url="https://api.deepseek.com")
return (
Author
Owner

[REVIEW] The parse_provider function uses tuple unpacking with Callable, but the return type annotation should be tuple[Callable[[str], Any], Callable[[Any], str]] for better clarity and type safety.

[REVIEW] The `parse_provider` function uses tuple unpacking with `Callable`, but the return type annotation should be `tuple[Callable[[str], Any], Callable[[Any], str]]` for better clarity and type safety.
@@ -0,0 +181,4 @@
def parse_diff(diff: str) -> list[dict[str, Any]]:
"""Parse diff into list of dicts
Author
Owner

[REVIEW] The get_diff function uses print for error messages, which might not be suitable for production code. Consider using a logging framework to handle different log levels and outputs.

[REVIEW] The `get_diff` function uses `print` for error messages, which might not be suitable for production code. Consider using a logging framework to handle different log levels and outputs.
@@ -0,0 +184,4 @@
Args:
diff: str, code difference between base and head
Author
Owner

[REVIEW] The get_diff function checks the status code after calling raise_for_status(), which will already raise an exception for non-200 status codes. This check is redundant and can be removed.

[REVIEW] The `get_diff` function checks the status code after calling `raise_for_status()`, which will already raise an exception for non-200 status codes. This check is redundant and can be removed.
@@ -0,0 +1,19 @@
import json
import os
print(os.getenv("GITHUB_EVENT_PATH"))
Author
Owner

[REVIEW] Consider handling the case where GITHUB_EVENT_PATH is not set or the file does not exist to avoid potential runtime errors.

[REVIEW] Consider handling the case where `GITHUB_EVENT_PATH` is not set or the file does not exist to avoid potential runtime errors.
@@ -0,0 +3,4 @@
print(os.getenv("GITHUB_EVENT_PATH"))
with open(os.getenv("GITHUB_EVENT_PATH"), "r") as f:
Author
Owner

[REVIEW] It's advisable to check if GITHUB_EVENT_PATH is set before attempting to open the file to prevent TypeError.

[REVIEW] It's advisable to check if `GITHUB_EVENT_PATH` is set before attempting to open the file to prevent `TypeError`.
@@ -0,0 +7,4 @@
event_data = json.load(f)
print(os.getenv("GITEA_TOKEN"))
print(os.getenv("CLAUDE_API_KEY"))
Author
Owner

[REVIEW] Printing sensitive information such as tokens (GITEA_TOKEN, CLAUDE_API_KEY, OPENAI_API_KEY, DEEPSEEK_API_KEY) is a security risk. Consider removing these print statements or masking the output.

[REVIEW] Printing sensitive information such as tokens (`GITEA_TOKEN`, `CLAUDE_API_KEY`, `OPENAI_API_KEY`, `DEEPSEEK_API_KEY`) is a security risk. Consider removing these print statements or masking the output.
@@ -0,0 +11,4 @@
print(os.getenv("OPENAI_API_KEY"))
print(os.getenv("DEEPSEEK_API_KEY"))
print(event_data)
Author
Owner

[REVIEW] Accessing dictionary keys like event_data["pull_request"] without checking if they exist can lead to KeyError. Consider using get() method or checking the keys' existence first.

[REVIEW] Accessing dictionary keys like `event_data["pull_request"]` without checking if they exist can lead to `KeyError`. Consider using `get()` method or checking the keys' existence first.
github_code.py Outdated
@@ -0,0 +5,4 @@
from openai import OpenAI
import requests
import re
Author
Owner

[REVIEW] The OpenAI import is incorrect. The correct import should be from openai import OpenAI or import openai if using the OpenAI Python client.

[REVIEW] The `OpenAI` import is incorrect. The correct import should be `from openai import OpenAI` or `import openai` if using the OpenAI Python client.
github_code.py Outdated
@@ -0,0 +90,4 @@
response = openai.chat.completions.create(
model=OPENAI_API_MODEL,
messages=[
{"role": "system", "content": prompt}
Author
Owner

[REVIEW] The openai.chat.completions.create method is incorrect. The correct method should be openai.Completion.create or openai.ChatCompletion.create depending on the OpenAI API version.

[REVIEW] The `openai.chat.completions.create` method is incorrect. The correct method should be `openai.Completion.create` or `openai.ChatCompletion.create` depending on the OpenAI API version.
github_code.py Outdated
@@ -0,0 +183,4 @@
if __name__ == "__main__":
try:
main()
except Exception as e:
Author
Owner

[REVIEW] The regular expression in re.finditer is incomplete and will cause a syntax error. Ensure the pattern is correctly defined and closed.

[REVIEW] The regular expression in `re.finditer` is incomplete and will cause a syntax error. Ensure the pattern is correctly defined and closed.
mschoi added 1 commit 2025-01-09 16:16:28 +09:00
remove tests
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94f625a096
mschoi reviewed 2025-01-09 16:16:59 +09:00
mschoi left a comment
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Owner

Code Structure & Architecture

The code structure is generally organized, but there are areas that could be improved for better readability and maintainability:

  1. Modularization: The script is quite lengthy and could benefit from breaking down into smaller, more focused modules or functions. For example, the parse_provider function is handling multiple responsibilities, such as configuring different AI models and returning both a message creator and a response parser. Consider separating these concerns into distinct functions or classes.

  2. Class Usage: The PRDetails class is used to encapsulate PR information, which is a good practice. However, the rest of the script is procedural. Consider encapsulating related functionalities into classes, such as a CodeReviewer class that handles the review process.

Refactoring Opportunities

  1. Repeated Code: The parse_provider function contains repeated logic for setting up different AI models. This could be refactored to reduce redundancy. For example, the configuration of the system_prompt and max_tokens is repeated for each model type. Consider extracting this logic into a helper function.

    def configure_model(api_key, model, system_prompt, max_tokens):
        return lambda prompt: model.create(
            api_key=api_key,
            model=model,
            messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": prompt}],
            temperature=0.2,
            max_tokens=max_tokens,
            top_p=1,
            frequency_penalty=0,
            presence_penalty=0,
        )
    
  2. Error Handling: The error handling in functions like get_ai_response_single_chunk and get_ai_response_full_context is minimal. Consider adding more robust error handling and logging to aid in debugging and maintenance.

Potential Future Problems

  1. Scalability: The current implementation uses synchronous HTTP requests, which could become a bottleneck if the number of files or the size of the diffs increases. Consider using asynchronous requests or batch processing to improve performance.

  2. Environment Dependency: The script heavily relies on environment variables for configuration. While this is common in CI/CD pipelines, ensure that there is adequate validation and fallback mechanisms if these variables are not set.

  3. API Key Management: The script uses multiple API keys for different services. Consider implementing a more secure way to manage these keys, such as using a secrets manager or encrypting the keys.

By addressing these areas, the code can be made more maintainable, scalable, and easier to understand.

### Code Structure & Architecture The code structure is generally organized, but there are areas that could be improved for better readability and maintainability: 1. **Modularization**: The script is quite lengthy and could benefit from breaking down into smaller, more focused modules or functions. For example, the `parse_provider` function is handling multiple responsibilities, such as configuring different AI models and returning both a message creator and a response parser. Consider separating these concerns into distinct functions or classes. 2. **Class Usage**: The `PRDetails` class is used to encapsulate PR information, which is a good practice. However, the rest of the script is procedural. Consider encapsulating related functionalities into classes, such as a `CodeReviewer` class that handles the review process. ### Refactoring Opportunities 1. **Repeated Code**: The `parse_provider` function contains repeated logic for setting up different AI models. This could be refactored to reduce redundancy. For example, the configuration of the `system_prompt` and `max_tokens` is repeated for each model type. Consider extracting this logic into a helper function. ```python def configure_model(api_key, model, system_prompt, max_tokens): return lambda prompt: model.create( api_key=api_key, model=model, messages=[{"role": "system", "content": system_prompt}, {"role": "user", "content": prompt}], temperature=0.2, max_tokens=max_tokens, top_p=1, frequency_penalty=0, presence_penalty=0, ) ``` 2. **Error Handling**: The error handling in functions like `get_ai_response_single_chunk` and `get_ai_response_full_context` is minimal. Consider adding more robust error handling and logging to aid in debugging and maintenance. ### Potential Future Problems 1. **Scalability**: The current implementation uses synchronous HTTP requests, which could become a bottleneck if the number of files or the size of the diffs increases. Consider using asynchronous requests or batch processing to improve performance. 2. **Environment Dependency**: The script heavily relies on environment variables for configuration. While this is common in CI/CD pipelines, ensure that there is adequate validation and fallback mechanisms if these variables are not set. 3. **API Key Management**: The script uses multiple API keys for different services. Consider implementing a more secure way to manage these keys, such as using a secrets manager or encrypting the keys. By addressing these areas, the code can be made more maintainable, scalable, and easier to understand.
@@ -0,0 +1,379 @@
import base64
Author
Owner

[REVIEW] Consider organizing the imports into standard library imports, third-party imports, and local application imports for better readability.

[REVIEW] Consider organizing the imports into standard library imports, third-party imports, and local application imports for better readability.
@@ -0,0 +8,4 @@
from anthropic import Anthropic
import google.generativeai as genai
from collections import defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
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Owner

[REVIEW] The ACCESS_TOKEN is being retrieved from the environment variables without any validation. Consider adding a check to ensure it is not empty or invalid.

[REVIEW] The `ACCESS_TOKEN` is being retrieved from the environment variables without any validation. Consider adding a check to ensure it is not empty or invalid.
@@ -0,0 +24,4 @@
- Use the given description only for the overall context and only comment the code.
- IMPORTANT: NEVER suggest adding comments to the code.
"""
Author
Owner

[REVIEW] The GITHUB_EVENT_PATH environment variable is used without validation. Consider adding error handling to manage cases where the file path might be invalid or the file might not exist.

[REVIEW] The `GITHUB_EVENT_PATH` environment variable is used without validation. Consider adding error handling to manage cases where the file path might be invalid or the file might not exist.
@@ -0,0 +27,4 @@
FULL_CONTEXT_SYSTEM_PROMPT = """You are an experienced software engineer specializing in reviewing pull requests. Your task is to provide an overall code review summary for a PR. Focus on assessing the following aspects:
1. **Code Structure & Architecture:** Evaluate whether the code is well-organized, modular, and adheres to clean code principles. Suggest improvements if needed.
Author
Owner

[REVIEW] Opening a file without a context manager can lead to resource leaks. Consider using a with statement to ensure the file is properly closed after reading.

[REVIEW] Opening a file without a context manager can lead to resource leaks. Consider using a `with` statement to ensure the file is properly closed after reading.
@@ -0,0 +70,4 @@
EXCLUDE_PATTERNS = os.getenv("EXCLUDE", "").split(",")
FULL_CONTEXT_MODEL = os.getenv("FULL_CONTEXT_MODEL", "o1")
SINGLE_CHUNK_MODEL = os.getenv("SINGLE_CHUNK_MODEL", "claude-3-5-sonnet-20241022")
Author
Owner

[REVIEW] The EXCLUDE_PATTERNS is split by a comma, but there is no trimming of whitespace. Consider trimming whitespace to avoid issues with pattern matching.

[REVIEW] The `EXCLUDE_PATTERNS` is split by a comma, but there is no trimming of whitespace. Consider trimming whitespace to avoid issues with pattern matching.
@@ -0,0 +92,4 @@
model=model,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": prompt},
Author
Owner

[REVIEW] The parse_provider function uses tuple[Callable, Callable] which is not compatible with Python versions below 3.9. Consider using Tuple[Callable, Callable] from the typing module for broader compatibility.

[REVIEW] The `parse_provider` function uses `tuple[Callable, Callable]` which is not compatible with Python versions below 3.9. Consider using `Tuple[Callable, Callable]` from the `typing` module for broader compatibility.
@@ -0,0 +145,4 @@
.strip("`")
.lstrip("json")
.strip()
or "[]",
Author
Owner

[REVIEW] The get_diff function uses a type hint str | None which is not compatible with Python versions below 3.10. Consider using Optional[str] from the typing module for broader compatibility.

[REVIEW] The `get_diff` function uses a type hint `str | None` which is not compatible with Python versions below 3.10. Consider using `Optional[str]` from the `typing` module for broader compatibility.
@@ -0,0 +163,4 @@
FULL_CONTEXT_MODEL, is_full_context=True
)
SINGLE_CHUNK_MESSAGE, SINGLE_CHUNK_RESPONSE_PARSER = parse_provider(
SINGLE_CHUNK_MODEL, is_full_context=False
Author
Owner

[REVIEW] The parse_diff function's docstring mentions list[dict[str, Any]] which is not compatible with Python versions below 3.9. Consider using List[Dict[str, Any]] from the typing module for broader compatibility.

[REVIEW] The `parse_diff` function's docstring mentions `list[dict[str, Any]]` which is not compatible with Python versions below 3.9. Consider using `List[Dict[str, Any]]` from the `typing` module for broader compatibility.
mschoi added 1 commit 2025-01-09 16:16:59 +09:00
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mschoi merged commit 776e5ec5d8 into main 2025-01-09 16:20:38 +09:00
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Reference: mschoi/CodeReviewer#4