Comparison
py-gpt vs TradingAgents
Verdict
Pick py-gpt when license: py-gpt is Other, TradingAgents is Apache-2.0; pick TradingAgents when license: TradingAgents is Apache-2.0, py-gpt is Other.
Markdown twin · py-gpt alternatives · TradingAgents alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | py-gpt | TradingAgents |
|---|---|---|
| Maintenance | Slowing (159d since push) As of today · github_public_v1 | Very active (5d since push) As of 4d · github_public_v1 |
| Provenance | Not a fork · Personal account As of today · github_public_v1 | Not a fork · Organization account As of 4d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of today · osv@v1 | No lockfile (source not queried) As of 4d · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- py-gpt
- Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe
- TradingAgents
- Multi-Agents LLM Financial Trading Framework
Stars
- py-gpt
- 1.9k
- TradingAgents
- 92k
Forks
- py-gpt
- 333
- TradingAgents
- 18k
Open issues
- py-gpt
- 61
- TradingAgents
- 292
Language
- py-gpt
- Python
- TradingAgents
- Python
Adopt for
- py-gpt
- -
- TradingAgents
- Use TradingAgents for projects requiring a sophisticated framework to develop and deploy AI agents in financial market transactions leveraging Large Language Models. Avoid it if you need simpler tools or frameworks thatだ
Persona
- py-gpt
- -
- TradingAgents
- -
Runtime
- py-gpt
- -
- TradingAgents
- -
License
- py-gpt
- Other
- TradingAgents
- Apache-2.0
Last pushed
- py-gpt
- Feb 6, 2026
- TradingAgents
- Jul 5, 2026
Categories
- py-gpt
- AI Agents, LLM Frameworks, Vector Databases
- TradingAgents
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- py-gpt
- Slowing (36%)
- TradingAgents
- Very active (96%)
Days since push
- py-gpt
- 159d
- TradingAgents
- 5d
Open issues (now)
- py-gpt
- 61
- TradingAgents
- 292
Owner type
- py-gpt
- User
- TradingAgents
- Organization
Full report
- py-gpt
- Trust report
- TradingAgents
- Trust report
Choose py-gpt if…
- License: py-gpt is Other, TradingAgents is Apache-2.0.
- Tags unique to py-gpt: ai, ai-assistant, artificial-intelligence, autonomous-agent.
- Also covers Vector Databases.
When NOT to use py-gpt
- Last GitHub push was 159 days ago (slowing maintenance, Feb 6, 2026). Validate activity before betting a new project on py-gpt.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Choose TradingAgents if…
- License: TradingAgents is Apache-2.0, py-gpt is Other.
- Requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework..
- Tags unique to TradingAgents: agent, finance, llm, multiagent.
- When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.
When NOT to use TradingAgents
- If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead.
- When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (szczyglis-dev/py-gpt) · observed Jul 15, 2026
- GitHub forks (szczyglis-dev/py-gpt) · observed Jul 15, 2026
- Last push (szczyglis-dev/py-gpt) · observed Feb 6, 2026
- License file (Other) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
- GitHub stars (TauricResearch/TradingAgents) · observed Jul 11, 2026
- GitHub forks (TauricResearch/TradingAgents) · observed Jul 11, 2026
- Last push (TauricResearch/TradingAgents) · observed Jul 5, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: py-gpt 1.9k · TradingAgents 92k (synced Jul 15, 2026).
Common questions
- What is the difference between py-gpt and TradingAgents?
- py-gpt: Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe. TradingAgents: Multi-Agents LLM Financial Trading Framework. See the comparison table for live GitHub stats and shared categories.
- When should I choose py-gpt over TradingAgents?
- Choose py-gpt over TradingAgents when License: py-gpt is Other, TradingAgents is Apache-2.0; Tags unique to py-gpt: ai, ai-assistant, artificial-intelligence, autonomous-agent; Also covers Vector Databases.
- When should I choose TradingAgents over py-gpt?
- Choose TradingAgents over py-gpt when License: TradingAgents is Apache-2.0, py-gpt is Other; Requirements: Min 8 GB RAM; Python environment setup is required.; Deep understanding of finance and LLMs will enhance the utilization of this framework.; Tags unique to TradingAgents: agent, finance, llm, multiagent; When your project involves complex multi-agent interactions specifically in the finance domain, utilizing LLMs to manage trading strategies.
- When should I avoid py-gpt?
- Last GitHub push was 159 days ago (slowing maintenance, Feb 6, 2026). Validate activity before betting a new project on py-gpt. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
- When should I avoid TradingAgents?
- If simplicity and ease of deployment are prioritized over advanced AI capabilities; TradingAgents' complexity might introduce unnecessary overhead. When the focus is on non-financial applications or when LLM integration isn't necessary, as this framework specializes in financial market trading with a multi-agent approach.
- Is py-gpt or TradingAgents more popular on GitHub?
- TradingAgents has more GitHub stars (92,290 vs 1,851). Stars measure visibility, not whether either tool fits your constraints.
- Are py-gpt and TradingAgents open source?
- Yes - both are open-source projects on GitHub (py-gpt: Other, TradingAgents: Apache-2.0).
- Where can I find alternatives to py-gpt or TradingAgents?
- GraphCanon lists graph-backed alternatives at py-gpt alternatives and TradingAgents alternatives (py-gpt markdown twin, TradingAgents markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, py-gpt or TradingAgents?
- py-gpt: Slowing. TradingAgents: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for py-gpt and TradingAgents?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: py-gpt trust report; TradingAgents trust report.