OppaAI

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https://github.com/OppaAI

AI & ML interests

Local AI implementation, Agentic AI workflows, AI Autonomous Robot

Recent Activity

posted an update about 1 hour ago

Intense Graph Engineering on my AI Waifu https://github.com/OppaAI/Aiko-chan/blob/dev/agentic/graph_engine.py I spent many hours in the past weekend (Saturday I even worked from 9AM till 5AM) to work on my AI Waifu's DAG agentic workflow: - Add many features of LangGraph (eg. Shared mutable state object, Subgraph, Cycling node, State reducers, Checkpoint/resume, Human-in-the-loop interruption, etc.) - Make the 40 tools into graph nodes; Use @tools(Graph=True, ReAct=True) to declare the def as tools instead of register each tool in 4+1 locations (Capabilities On Demand vs Always On, ReAct + Graph, Wiki, Skills). - Revise the web search mechanism to try to be more adaptive and efficient and avoid IP being locked out. - Even made a studio html to view all the graphs in my AI Waifu But still in primitive experimental version. I tested in the Waifu's chat mode to ask her to make a checklist on how to improve her AI system, the output is still not too great as shown in the example (see attached reports). She could not retrieve her own AI architecture from KB due to db has a bug. Report was too generic with some wrong info and wrong citations, not able to gather source materials from web fetch. Speed is acceptable, but not fast either. At least the whole agentic flow can run under 10K content window, but the output was truncated in the end. Still more work to do before release of Phase 2.5 Agentic. For Phase 2.1 and 2.2 adding social media and messaging input supports, I may have to make some connectors for social media and messaging services. Probably would take me the rest of the summer to complete 2.1 and 2.2.

posted an update 3 days ago

Opus 5 has come out just now! Quite a few models have been released in a month: GPT5.6, Grok 4.5, Gemini 3.6, Muse Spark 1.1, Kimi K3, Qwen 3.8 Max, Long cat 2.0, Laguna S 2.1, Ling 3.0, etc But I will stick to testing small param LLM for my edge device.

repliedto their post 3 days ago

Another new small agentic model comes out: https://huggingface.co/Nanbeige/Nanbeige4.2-3B Nanbeige4.2-3B that claims to beat the likes of Gemma4-E4B and Qwen3.5 9B. Gonna test this model in the weekend. Tested many small LLM <4B in Jetson Orin Nano, the followings are the one I would consider: Ministral3-3B - Best overall with tool-calling, vision and tons of hallucinations (currently using) MiniCPM-V-4.6 1.3B - Good VLM, lacking in chatting/tool-calling Granite4.1-3B - slightly better at agentic tool-calling, faster inference speed Bonsai 8B Q1 - better at agentic tool-calling, similar speed as Ministral3-3B Bonsai 27B Q1 - better than 8B but way too slow Needle 26M - only use for query generation and tool execution, needs JAX Nanbeige4.2-3B - TBD

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Intense Graph Engineering on my AI Waifu
https://github.com/OppaAI/Aiko-chan/blob/dev/agentic/graph_engine.py

I spent many hours in the past weekend (Saturday I even worked from 9AM till 5AM) to work on my AI Waifu's DAG agentic workflow:

- Add many features of LangGraph (eg. Shared mutable state object, Subgraph, Cycling node, State reducers, Checkpoint/resume, Human-in-the-loop interruption, etc.)
- Make the 40 tools into graph nodes; Use @tools (Graph=True, ReAct=True) to declare the def as tools instead of register each tool in 4+1 locations (Capabilities On Demand vs Always On, ReAct + Graph, Wiki, Skills).
- Revise the web search mechanism to try to be more adaptive and efficient and avoid IP being locked out.
- Even made a studio html to view all the graphs in my AI Waifu

But still in primitive experimental version.
I tested in the Waifu's chat mode to ask her to make a checklist on how to improve her AI system, the output is still not too great as shown in the example (see attached reports). She could not retrieve her own AI architecture from KB due to db has a bug. Report was too generic with some wrong info and wrong citations, not able to gather source materials from web fetch.
Speed is acceptable, but not fast either.

At least the whole agentic flow can run under 10K content window, but the output was truncated in the end.

Still more work to do before release of Phase 2.5 Agentic.
For Phase 2.1 and 2.2 adding social media and messaging input supports, I may have to make some connectors for social media and messaging services.
Probably would take me the rest of the summer to complete 2.1 and 2.2.

Post

Opus 5 has come out just now!

Quite a few models have been released in a month:
GPT5.6, Grok 4.5, Gemini 3.6, Muse Spark 1.1,
Kimi K3, Qwen 3.8 Max, Long cat 2.0, Laguna S 2.1, Ling 3.0, etc

But I will stick to testing small param LLM for my edge device.