Phidata, a framework for building AI assistants with memory and contextual knowledge, is experiencing significant issues in tool usage and model integration, potentially impacting user satisfaction and adoption.
Recent issues and pull requests (PRs) indicate ongoing challenges with tool functionality and model compatibility. Issues #1126 and #1123 highlight critical problems with incomplete responses and errors in specific models like llama3:8b. These issues suggest underlying architectural challenges that need addressing to ensure stability.
| Timespan | Opened | Closed | Comments | Labeled | Milestones |
|---|---|---|---|---|---|
| 7 Days | 3 | 1 | 1 | 3 | 1 |
| 30 Days | 10 | 7 | 21 | 10 | 1 |
| 90 Days | 41 | 29 | 77 | 41 | 1 |
| All Time | 168 | 105 | - | - | - |
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.
| Developer | Avatar | Branches | PRs | Commits | Files | Changes |
|---|---|---|---|---|---|---|
| Ashpreet |  |
4 | 2/0/1 | 26 | 77 | 5454 |
| Jacob Weiss |  |
3 | 4/4/0 | 11 | 24 | 2997 |
| William Espegren |  |
1 | 1/1/0 | 10 | 5 | 215 |
| Ayush |  |
2 | 2/1/0 | 3 | 2 | 98 |
| Manthan Gupta |  |
1 | 0/0/0 | 1 | 14 | 87 |
| Yash Pratap Solanky |  |
2 | 2/3/0 | 2 | 2 | 13 |
| gary318 |  |
1 | 1/0/1 | 1 | 1 | 6 |
| Nicolas Lenepveu |  |
1 | 1/1/0 | 1 | 1 | 3 |
| Tejas R Simha (Tlionn) | 0 | 1/0/0 | 0 | 0 | 0 | |
| None (paras55) | 0 | 1/0/0 | 0 | 0 | 0 | |
| Hansi P. (hansipie) | 0 | 0/0/2 | 0 | 0 | 0 | |
| Syed Husain (husainsyed) | 0 | 1/0/0 | 0 | 0 | 0 | |
| Samuel Devdas (SamuelDevdas) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
The Phidata project currently has 63 open issues on GitHub, with recent activity indicating a mix of bug reports and feature requests. Notably, issues related to tool usage and integration with various models (like Groq and OpenAI) are prevalent, suggesting ongoing challenges in ensuring compatibility and functionality across different setups.
Several issues exhibit common themes, particularly around tool failures and incomplete responses when using specific models. For example, issues #1126 (incomplete response after tool usage) and #1123 (run llama3:8b error) highlight critical problems that could hinder user experience if not addressed promptly. Additionally, the presence of multiple discussions around the same tools indicates a potential need for clearer documentation or improved error handling.
Issue #1126: Incomplete response after tool usage
Issue #1123: run llama3:8b error
Issue #1119: Tool use failed
Issue #1103: llama3.1:8b
Issue #1104: openrouter claude3.5 tool use failed
Issue #1119: Tool use failed
Issue #1126: Incomplete response after tool usage
Issue #1100: 'save_output_to_file = True' does not save the FULL chat history??
Issue #1098: Workspace supports custom stages
Issue #1096: Cannot use non-vectorstore retrievers in LangChainKnowledgeBase
The presence of multiple high-priority issues related to tool functionality and model integration suggests that users may face significant barriers to effectively utilizing the Phidata framework in their applications. This could impact user adoption and satisfaction if not resolved quickly. The project maintainers may need to prioritize addressing these issues through improved documentation, enhanced error handling, or more robust testing across different environments and models.
Additionally, the recurring nature of certain problems indicates that there may be underlying architectural challenges within the framework that require a more comprehensive review or refactoring to ensure stability and usability moving forward.
The dataset contains a total of 30 open pull requests (PRs) for the Phidata repository, showcasing ongoing development efforts to enhance the functionality and reliability of the software. The PRs address various issues, including bug fixes, feature additions, and improvements to existing functionalities.
PR #1127: Fixes a bug in /anthropic/claude.py related to response type handling when search_knowledge=True. This PR adds type checking for TextBlock and ToolUseBlock to prevent runtime errors.
PR #1124: Addresses an issue with the updated_at column in Pgvector2, ensuring it updates correctly during upsert operations in SQLAlchemy.
PR #1121: Introduces support for Unify AI as an LLM provider, allowing users to access multiple models with a single API key. However, there are reported issues with the implementation that need addressing.
PR #1120: Proposes version 2.5.0, introducing a new Agent class. Review comments indicate some inconsistencies in naming conventions that need correction.
PR #1116: Adds a wait_until_done parameter to initialization but faces criticism regarding its placement in the code structure.
PR #1114: Enhances file handling capabilities by allowing CSV, DOCX, and text uploads alongside PDFs.
PR #1101: Fixes issues with saving chat history and UTF-8 encoding errors, ensuring complete chat history is saved without data loss.
PR #1097: Adjusts instance checks from VectorStoreRetriever to BaseRetriever, improving flexibility in the retrieval process.
PR #1095: Fixes a function call bug in the Ollama integration.
PR #1094: Adds filter functionality for assistant queries, enhancing search capabilities.
PR #1092: Implements a feature to allow setting debug mode at runtime.
PR #1086: Introduces support for DeepSeek as an LLM provider.
PR #1118: Fixed fireworks streaming issues and merged successfully.
PR #1117: Corrected default instructions not being included in the Assistant's LLM prompts; this was also merged successfully.
PR #1109: Fixed issues with Jina tools by replacing requests with httpx; merged successfully.
The current set of open pull requests reflects a diverse range of enhancements and bug fixes aimed at improving the Phidata framework's robustness and usability. Notably, several PRs focus on integrating new features or providers (e.g., Unify AI and DeepSeek), which indicates an ongoing effort to expand the capabilities of the platform. This aligns with Phidata's goal of providing versatile AI assistants that can handle various tasks across different domains.
A recurring theme among these PRs is addressing bugs and improving existing functionalities. For instance, PRs like #1127 and #1101 focus on fixing critical issues that could disrupt user experience—such as response handling errors and incomplete chat history saving. These fixes are essential for maintaining user trust and ensuring smooth operation within the framework.
Additionally, there is an evident emphasis on enhancing user interaction through improved features like file handling (#1114) and filtering capabilities (#1094). These enhancements are crucial as they directly impact how users interact with the platform and utilize its features effectively.
However, some PRs have raised concerns regarding implementation details or naming conventions (e.g., PR #1120). Such feedback highlights potential areas for improvement in code quality and consistency, which are vital for long-term maintainability. The presence of review comments across multiple PRs indicates an active engagement from contributors, which is beneficial for fostering a collaborative development environment.
Moreover, the closed pull requests demonstrate a healthy merge activity within the repository, suggesting that contributions are being recognized and integrated promptly. This is crucial for keeping the project dynamic and responsive to user needs. However, some older PRs remain open without significant updates or merges (e.g., PRs created over 100 days ago), which may indicate areas where attention is needed to avoid stagnation in development efforts.
In conclusion, while the current set of pull requests showcases active development and responsiveness to user needs, maintaining consistent engagement with all contributions—especially older ones—will be essential for Phidata's continued growth and improvement as a leading framework for building autonomous AI assistants.
Ashpreet Bedi (ashpreetbedi)
Summary
Quantified Reports
Detailed Reportsphi module.Yash Pratap Solanky (ysolanky)
pgvector2 upsert functionality.Nicolas Lenepveu (nlenepveu)
Ayush Chaurasia (Ayush0054)
Jacob Weiss (jacobweiss2305)
William Espegren (WilliamEspegren)
Guan Yixuan (gary318)
Manthan Gupta (manthanguptaa)
feat/celery-docker-app) and bug fixes (fix-updated_at-for-pgvector2-upsert).Overall, the development team demonstrates a robust collaborative environment focused on continuous improvement of the Phidata framework, ensuring both stability through bug fixes and innovation through new features.