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Recent GitHub Issues Activity

_{Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.}

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PR#17 - [doc] Add readme-zh for Chinese usersopen

3_/5

从零开始学AI (mahone3297)Created: 2024-04-15

This pull request introduces a new README file in Chinese, which is a useful addition for Chinese-speaking users, enhancing accessibility and inclusivity. However, the PR is relatively minor in scope as it primarily involves documentation changes without any code modifications or significant feature additions. The PR has been open for a considerable time due to pending major updates to the repository, which slightly diminishes its immediate relevance. Overall, while the effort is commendable, the impact of the change is moderate, justifying an average rating.

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PR#17 - [doc] Add readme-zh for Chinese usersopen

3_/5

从零开始学AI (mahone3297)Created: 2024-04-15

The pull request adds a Chinese version of the README file, which is a useful but not groundbreaking contribution. It enhances accessibility for Chinese-speaking users but does not involve complex coding or significant changes to the functionality of the project. The addition is straightforward and well-executed, aligning with documentation improvements. However, it lacks the depth or complexity that would warrant a higher rating.

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PR#192 - Changes made in the article_generation.py and storm_dataclass.py to a…open

3_/5

slightlyarrogantCreated: 2024-10-01

The pull request addresses a specific issue related to NoneType errors in two Python files, which is a necessary maintenance task. The changes are minor and focused on stability, with testing done on 10 generations, suggesting some level of reliability. However, the PR lacks significant innovation or complexity, and the impact appears limited to error handling improvements rather than introducing new features or major enhancements. The addition of several JSON and text files seems unrelated to the core changes and could clutter the repository. Overall, it's an average PR that resolves a specific problem but doesn't stand out in terms of broader impact or technical challenge.

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PR#264 - Update article_polish.pyopen

3_/5

The smpl Ai Guy (smpl-ai)Created: 2024-12-07

The pull request improves the documentation by expanding the docstring to include parameter types and expected return values. This is a positive change as it enhances code readability and maintainability. However, the change is relatively minor, affecting only a small portion of the code without altering functionality or fixing bugs. The update is important for clarity but does not significantly impact the overall project, thus warranting an average rating.

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PR#268 - Set azure_api_key as optional parameteropen

3_/5

jaydeep-mbarcCreated: 2024-12-16

The pull request makes a minor but useful change by making the azure_api_key parameter optional in the init_openai_model function. This enhances flexibility in scenarios where the API key is not always needed. However, the change is relatively small, affecting only one line of code and having minimal impact on the overall functionality. It does not introduce any significant new features or improvements, nor does it address any major issues. Therefore, it is considered average and unremarkable, fitting a rating of 3.

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PR#155 - Multiple retriever systems.open

4_/5

AMMAS1Created: 2024-08-31

The pull request introduces a significant enhancement by allowing the STORM system to utilize multiple retrievers, which can improve the flexibility and effectiveness of information retrieval. The changes are well-documented, with clear descriptions and nicknames for each retriever. The code modifications are substantial, affecting multiple files and adding a new example script. However, there are some minor issues, such as unused parameters in constructors and some redundant comments, which prevent it from being rated as excellent. Overall, it's a quite good PR that adds meaningful functionality.

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Recent Activity Analysis

The recent activity on the GitHub repository for the STORM project shows a moderate level of engagement with 45 open issues. Notably, there is a mix of feature requests, bug reports, and questions from users, indicating active participation from the community. Several issues have been closed recently, demonstrating ongoing maintenance and responsiveness from the development team.

Anomalies and Themes

• Missing Information: Issue #270 highlights a lack of detailed documentation on the ENCODER-API_Type, which could be crucial for users encountering errors.
• Unaddressed Urgent Issues: Issue #262 involves an uncaught exception that seems critical but has not been updated recently, suggesting it might need more immediate attention.
• Common Themes: Many issues relate to integration with various language models and retrieval systems, such as requests for support for open-source alternatives (e.g., Issue #272) and questions about using local models like Ollama (Issue #217).
• Feature Requests: There are multiple requests for new features or enhancements, such as multilingual support (Issue #170) and integration with specific APIs like gpt4free (Issue #245).
• Bug Reports: Several bug reports indicate issues with existing functionalities, such as citation generation inconsistencies (Issue #168) and problems with specific retrieval modules (Issue #231).

Issue Details

Most Recently Created Issues

1. #274: Storm

   • Priority: Not specified
   • Status: Open
   • Created: 1 day ago

2. #272: Integration of an Open source alternative to Open Ai's canvas/ Claude Artifacts

   • Priority: Not specified
   • Status: Open
   • Created: 1 day ago

3. #270: question

   • Priority: Not specified
   • Status: Open
   • Created: 7 days ago

Most Recently Updated Issues

1. #217: Want to run fully locally using OLLAMA and SEARXNG

   • Priority: Not specified
   • Status: Open
   • Created: 80 days ago
   • Updated: 1 day ago

2. #262: [BUG] Uncaught Exception

   • Priority: Not specified
   • Status: Open
   • Created: 32 days ago
   • Updated: 17 days ago

3. #267: About Plans to Open Source the Frontend Code

   • Priority: Not specified
   • Status: Open
   • Created: 17 days ago
   • Updated: 14 days ago

Overall, the STORM project is actively maintained with regular updates and community interaction. However, some critical issues may require more immediate attention to ensure smooth functionality and user satisfaction.

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Analysis of Pull Requests for Stanford-Oval/Storm

Open Pull Requests

#268: Set azure_api_key as optional parameter

• State: Open
• Created: 17 days ago
• Description: This PR modifies the azure_api_key function to make its parameter optional, enhancing flexibility in function calls.
• Key Changes: Adjusts the init_openai_model definition to make azure_api_key optional.
• Notable: The change is minimal but crucial for flexibility, especially when the API key is not always required.

#264: Update article_polish.py

• State: Open
• Created: 27 days ago
• Description: Expands docstring to include parameter types and expected return values.
• Notable: While this is a documentation enhancement, it improves code readability and maintainability.

#192: Changes made in the article_generation.py and storm_dataclass.py to avoid various Nonetype related errors

• State: Open
• Created: 93 days ago
• Description: This PR addresses NoneType errors in article_generation.py and storm_dataclass.py.
• Notable: The PR has been open for a significant time (93 days), indicating potential issues with review or integration.

#155: Multiple retriever systems

• State: Open
• Created: 124 days ago
• Description: Introduces functionality to run STORM with multiple retrievers.
• Notable: This PR has been open for a long time (124 days) and represents a significant enhancement in functionality. It may require more attention to move forward.

#17: [doc] Add readme-zh for Chinese users

• State: Open
• Created: 262 days ago, edited 100 days ago
• Description: Adds a README file in Chinese.
• Comments: The PR is on hold due to potential major updates to the repository. It remains open for reference.

Closed Pull Requests

Notable Closed PRs

#236: [SerperRM Bug]

• State: Closed (Merged)
• Created/Closed: Created 68 days ago, closed 67 days ago
• Description: Fixes a bug where valid_url_to_snippets.get(url, {}) returns None.
• Comments: Required code formatting before merging. Successfully merged after corrections.

#218: fix broken readme link

• State: Closed (Merged)
• Created/Closed: Created and closed 80 days ago
• Description: Corrected a broken link in the README file.

#198: [New RM] Add AzureAISearch

• State: Closed (Merged)
• Created/Closed: Created 87 days ago, closed 75 days ago
• Description: Introduced support for Azure AI Search, allowing use of custom datasets via Azure AI Search.

#183: [New RM] Add GoogleSearch

• State: Closed (Merged)
• Created/Closed: Created and closed 100 days ago
• Description: Added Google Search as a new retrieval module.

#181: 174 pylint alerts corrections

• State: Closed (Merged)
• Created/Closed: Created 100 days ago, closed 97 days ago
• Description: Addressed various Pylint alerts to improve code quality.

Not Merged PRs

#254: Storm updates

• State: Closed (Not Merged)
• Created/Closed: Created and closed 44 days ago
• Description: Included various updates but was not merged. The reasons for closure without merging are not detailed but could indicate issues with the proposed changes or conflicts with ongoing development.

Summary

The STORM project shows active development with several open pull requests addressing both minor enhancements and significant feature additions. Notably, some PRs have been open for extended periods (#192 and #155), which might need prioritization or additional resources to resolve. The recently closed PRs indicate ongoing efforts to integrate new features like Azure AI Search and Google Search while maintaining code quality through linting corrections. The project also demonstrates responsiveness to community contributions, as seen in the quick closure of some PRs after necessary adjustments.

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Source Code Assessment

File: knowledge_storm/rm.py

Structure and Quality:

• The file implements multiple retrieval modules, each encapsulated in a class. These modules are responsible for fetching data from various sources like You.com, Bing, Qdrant, and others.
• Each class inherits from dspy.Retrieve, ensuring a consistent interface across different retrieval methods.
• Error handling is implemented using try-except blocks, logging errors when exceptions occur. This is crucial for debugging and maintaining robustness.
• API keys are managed through environment variables or direct input, with checks to ensure they are provided.
• The use of backoff for retrying requests is a good practice for handling transient network issues.
• The code is modular and well-organized, with clear separation of concerns between different retrieval methods.

Potential Improvements:

• Consider centralizing common functionalities (e.g., API key validation) to reduce redundancy.
• Enhance logging by including more contextual information to aid in troubleshooting.
• Add type hints for return values in methods to improve code readability and maintainability.

File: knowledge_storm/lm.py

Structure and Quality:

• This file defines several wrapper classes for integrating various language models (e.g., OpenAI, DeepSeek, Azure).
• Each class manages API interactions, including token usage logging and error handling using backoff strategies.
• The use of threading locks for managing shared state (e.g., token usage) demonstrates attention to thread safety.
• Classes are well-documented with docstrings explaining their purpose and usage.

Potential Improvements:

• Consider abstracting common patterns across different model wrappers to reduce code duplication.
• Ensure all external dependencies (e.g., anthropic, google.generativeai) are clearly documented in the setup or requirements files.

File: setup.py

Structure and Quality:

• The setup script uses setuptools to define package metadata and dependencies.
• It reads long descriptions and requirements from external files (README.md, requirements.txt), which is a good practice for maintainability.

Potential Improvements:

• Ensure that the versioning follows semantic versioning principles for clarity on updates and changes.
• Consider adding more classifiers to provide additional metadata about the package (e.g., intended audience, topics).

File: requirements.txt

Structure and Quality:

• Lists project dependencies with specific versions where applicable, ensuring reproducibility of the environment.

Potential Improvements:

• Regularly update dependencies to their latest stable versions to benefit from security patches and new features.
• Consider specifying more precise versions or version ranges to avoid compatibility issues.

File: knowledge_storm/storm_wiki/modules/article_generation.py

Structure and Quality:

• Implements the article generation module using a class-based approach with clear separation of logic into methods.
• Utilizes concurrent processing via ThreadPoolExecutor to improve performance when generating sections concurrently.
• The code is well-documented with comments explaining the purpose of key sections.

Potential Improvements:

• Consider adding more detailed logging within concurrent operations to track progress and diagnose potential issues.
• Review thread management to ensure optimal resource utilization without overwhelming the system.

File: knowledge_storm/collaborative_storm/modules/co_storm_agents.py

Structure and Quality:

• Defines several agent classes that participate in collaborative discourse within the Co-STORM framework.
• Each agent class encapsulates specific behaviors and interactions, adhering to the single responsibility principle.
• Uses type annotations extensively, enhancing code clarity and aiding in static analysis.

Potential Improvements:

• Evaluate the complexity of similarity calculations within the Moderator class for potential optimization opportunities.
• Enhance documentation around complex logic, particularly where multiple embeddings and similarities are computed.

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Development Team and Recent Activity

Team Members and Activities

1. Yijia Shao (shaoyijia)

   • Recent commits include upgrading the version of Python package build tooling and bumping up the PyPI version.
   • Previously involved in fixing format issues, integrating new retrieval modules like AzureAISearch, and marking certain modules for internal use only.
   • Frequently merges pull requests from other contributors.

2. Yucheng Jiang

   • Worked on resolving issues raised in the repository, such as updating requirements.txt and fixing typos.
   • Involved in restructuring directories, updating documentation, and enhancing module compatibility.
   • Collaborated with other contributors by merging their pull requests.

3. Eminem (zhoucheng89)

   • Addressed bugs related to SerperRM by fixing value handling and formatting code.

4. Patrick (patrick@cryptolock.ai)

   • Contributed to adding Azure AI Search support and updating related imports and requirements.

5. Adam Montgomery (montasaurus)

   • Fixed broken links in the README file.

6. Hagen Hübel (itinance)

   • Corrected typographical errors in the codebase.

7. 宋小北 (xiaobeicn)

   • Worked on encoder documentation and added instance dumping in example scripts.

8. Evidencebp

   • Focused on code refactoring to improve readability and maintainability without altering functionality.

9. Ikko Eltociear Ashimine (eltociear)

   • Made minor updates to rm.py for typo corrections.

10. Abrahan N. (zenith110)

    • Added new retrieval modules like Tavily search and DuckDuckGoRM.
    • Updated examples to align with main branch styles.

11. Hanly De Los Santos (hdelossantos)

    • Added support for SearXNG retrieval module.

12. Kevin Jiang (kevindragon)

    • Supported the integration of Brave search into the project.

13. Ray (rmcc3)

    • Supported DeepSeek language models integration into the STORM Wiki pipeline.

Patterns, Themes, and Conclusions

• The team is actively involved in maintaining and enhancing the STORM project by integrating new features, fixing bugs, and improving existing functionalities.
• Collaboration among team members is evident through frequent merging of pull requests and addressing issues raised by others.
• There is a strong focus on improving code quality through refactoring, formatting, and documentation updates.
• The project sees contributions from various developers, indicating an open-source community involvement.
• Recent activities show a trend towards expanding retrieval module support and ensuring compatibility with different language models.
• The development process appears to be well-organized with regular updates, reflecting a commitment to keeping the project up-to-date with user needs and technological advancements.