Swarm is an experimental educational framework by OpenAI for exploring multi-agent orchestration. It focuses on agent coordination using Python and the Chat Completions API. The project is in an active development state, with ongoing improvements and documentation updates.
Katia Gil Guzman (katia-openai)
README.md
.Greg Admin (greg-admin)
README.md
.Ilan Bigio (ibigio)
README.md
.Shyamal H Anadkat (shyamal-anadkat)
Nate Nowack (zzstoatzz)
Colin Jarvis (colin-openai)
README.md
.Charu Jaiswal (charuj)
James Hills (jhills20)
README.md
.Timespan | Opened | Closed | Comments | Labeled | Milestones |
---|---|---|---|---|---|
7 Days | 8 | 0 | 5 | 8 | 1 |
30 Days | 8 | 0 | 5 | 8 | 1 |
90 Days | 9 | 3 | 5 | 9 | 1 |
All Time | 11 | 3 | - | - | - |
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 |
---|---|---|---|---|---|---|
Ilan Bigio | 1 | 1/1/0 | 6 | 139 | 3670 | |
Charu Jaiswal | 1 | 0/0/0 | 1 | 150 | 1832 | |
Shyamal H Anadkat | 1 | 0/0/0 | 4 | 6 | 55 | |
greg-admin | 1 | 0/0/0 | 3 | 1 | 14 | |
nate nowack | 1 | 2/2/0 | 2 | 2 | 13 | |
James Hills | 1 | 0/0/0 | 1 | 1 | 3 | |
Colin Jarvis | 1 | 0/0/0 | 1 | 1 | 3 | |
katia-openai | 1 | 0/0/0 | 1 | 1 | 1 | |
Will Dembinski (wi-ski) | 0 | 1/0/0 | 0 | 0 | 0 | |
Yuga Sun (yugasun) | 0 | 1/0/0 | 0 | 0 | 0 | |
Pengfei Ni (feiskyer) | 0 | 1/0/0 | 0 | 0 | 0 | |
citizenhicks (Arrabonae) | 0 | 1/0/0 | 0 | 0 | 0 | |
Ikko Eltociear Ashimine (eltociear) | 0 | 1/0/0 | 0 | 0 | 0 | |
Lutz Roeder (lutzroeder) | 0 | 1/0/0 | 0 | 0 | 0 | |
Derek Deming (derekdeming) | 0 | 1/0/0 | 0 | 0 | 0 | |
None (thanos-wandb) | 0 | 1/0/0 | 0 | 0 | 0 | |
METACOGNITIVE (METACOGNITIVE) | 0 | 1/0/0 | 0 | 0 | 0 | |
Eric Burke (eburke-openai) | 0 | 0/0/1 | 0 | 0 | 0 | |
Travis Fischer (transitive-bullshit) | 0 | 1/0/0 | 0 | 0 | 0 |
PRs: created by that dev and opened/merged/closed-unmerged during the period
Risk | Level (1-5) | Rationale |
---|---|---|
Delivery | 4 | The project faces significant delivery risks due to unresolved issues and a backlog that could impact timelines. The legal threat in issue #50 poses a substantial risk, and missing functionality in issue #49 could delay progress. The lack of milestones and structured planning further exacerbates these risks. |
Velocity | 4 | Velocity is at risk due to bottlenecks in the review process, as evidenced by the low number of merged pull requests. The focus on minor documentation updates rather than substantial development work suggests minimal progress towards core project goals. |
Dependency | 3 | Dependency risks are moderate. While the project specifies Python 3.10+ requirements, which could impact users on older versions, there are no major unresolved dependency issues reported. However, interoperability challenges in issue #54 and potential overlaps with similar projects (issue #42) need attention. |
Team | 3 | Team risks are moderate, with limited engagement in issue discussions suggesting possible communication challenges. The varied commit activity indicates some team members are more active than others, which could lead to uneven workload distribution and potential burnout. |
Code Quality | 3 | Code quality risks are moderate due to the focus on minor typo corrections and documentation updates. While type hints and security policies have been added, the lack of substantial functional improvements may affect maintainability and robustness. |
Technical Debt | 3 | Technical debt is a concern due to the backlog of unresolved issues and the focus on superficial changes. However, efforts like addressing mutable default arguments (PR #37) show some attention to reducing debt. |
Test Coverage | 4 | Test coverage is at risk as installation issues (#40, #36) hinder user adoption and testing. While new examples (PR #48) enhance coverage, the lack of comprehensive automated testing remains a concern. |
Error Handling | 3 | Error handling risks are moderate. The addition of a security policy is positive, but the README lacks emphasis on error handling practices, indicating potential gaps in catching and reporting errors. |
Recent GitHub issue activity for the openai/swarm project shows a mix of technical and legal concerns. Notably, issues #50 and #54 highlight non-technical challenges, such as potential legal threats and collaboration opportunities with other groups. Technical issues like #49 and #40 indicate missing components and version conflicts, respectively.
Legal and Interoperability Concerns: Issue #50 involves a legal threat over trademark usage, which could potentially disrupt project progress if not addressed. Conversely, issue #54 suggests collaboration with external groups, indicating a positive opportunity for interoperability.
Technical Gaps: Issue #49 reports a missing class in the codebase, suggesting incomplete implementation. This is critical as it affects functionality in demos.
Dependency Management: Issue #40 highlights a version downgrade problem during installation, which can lead to compatibility issues.
Installation Challenges: Issue #36 discusses problems with SSH-based installation, pointing to documentation or access rights issues.
Related Projects: Issue #42 references a similar project, GPTSwarm, suggesting potential overlaps or opportunities for integration.
#54: Complementary to the LFAI and Data group's work on Interoperability
#50: Notorious namesquatter is threatening legal action
#49: The class create_triage_agent from the swarm.agents module is missing
#35: Hugging face and langchain models support
#36: The ssh install command won't work
These issues reflect both strategic challenges (e.g., legal threats) and operational hurdles (e.g., missing code components), impacting the project's development trajectory.
#53: nit: typo in personal_shopper example
personal_shopper
example.#52: docs: update README.md
#51: [Nit] Fix a typo
airline
example configuration.#48: updated with llama examples including ollama wrapper
llama
, including an ollama
wrapper.#47: docs: fix typo
#46: Allow setting client for run_demo_loop()
run_demo_loop()
.#44: adding type hints to functions
#43: Update function example in README call greet instead of print_hello
#41: fix requires openai==1.33
#39: fix: readme typo
#38: indicate python 3.10+ required and alternate git install
#37: remove mutable default in run_demo_loop
#34: Rename all instances of Assistant to Agent
#22: Add post_execute call
Overall, the project appears active with ongoing improvements and refinements, particularly in terms of documentation accuracy and expanding functionality through new examples and features.
swarm/repl/repl.py
run_demo_loop
is placed at the end, which is logical as it likely utilizes the helper functions defined above it.process_and_print_streaming_response
and pretty_print_messages
handle streaming responses and message formatting, respectively. They use ANSI escape codes for colored terminal output, enhancing readability.run_demo_loop
orchestrates the interaction loop, managing user input and agent responses.examples/customer_service_streaming/src/swarm/swarm.py
Swarm
is clearly defined with methods for deploying tasks and managing engines.AssistantsEngine
and LocalEngine
) with conditional logic to initialize and deploy tasks.load_tasks
.examples/customer_service_streaming/configs/prompts.py
swarm/core.py
Swarm
class handles chat completions, tool calls, and agent interactions.get_chat_completion
and handle_tool_calls
are central to its operation.match-case
) effectively for handling different result types.debug_print
to aid debugging without cluttering output in production mode.swarm/util.py
debug_print
, merge_fields
, and function_to_json
provide essential utilities such as debugging support, data merging, and function serialization.function_to_json
ensures robustness against unexpected function signatures.Overall, the codebase demonstrates good practices in terms of structure, readability, and functionality. Adding type hints and improving documentation would further enhance maintainability and developer experience.
README.md
.README.md
involving small changes.README.md
. Initial commit included significant additions across multiple files.util.py
, core.py
, and tool.py
. Made multiple changes to README.md
.README.md
.README.md
.README.md
.Frequent README Updates: Several team members focused on updating the README.md
, indicating an emphasis on documentation clarity and accuracy.
Security and Initial Setup Enhancements: Ilan Bigio's contributions included adding a security policy and initial setup files, suggesting foundational improvements were prioritized recently.
Collaborative Documentation Efforts: Ilan Bigio and Shyamal H Anadkat collaborated on README updates, reflecting teamwork in refining project documentation.
Codebase Expansion by Charu Jaiswal: Significant additions by Charu Jaiswal expanded the project's examples and configurations, enhancing its educational value.
Focus on Minor Fixes and Requirements Updates: Nate Nowack addressed specific technical details like mutable defaults and Python version requirements, ensuring technical precision.
Limited Active Branches and PR Activity: Most recent activities occurred on the main branch with minimal pull request activity, indicating a centralized development approach.