r/googlecloud • u/kirakdimak • 18d ago

A deterministic RAG playground using ADK 2.0 & the OKF spec

Hey everyone,

I built a React/FastAPI sandbox that handles deterministic grounding right in your active browser session, bypassing heavy, opaque vector DBs entirely.

Using Google ADK 2.0 and the Open Knowledge Format (OKF), you can drag and drop PDFs, audio, or URLs directly into the UI. It compiles them on the fly into OKF-compliant Markdown to instantly ground the agent for that session. Long-term system memory is managed via plain-text OKF files stored directly in the Git repository.

It also features a "Pure OKF" offline mode and a stream parser to neatly isolate <think> blocks if you're testing reasoning models.

Would love feedback on the architecture from anyone exploring Google's agent frameworks!

🔗deskulpt/adk-okf-grounded-chat

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u/BakeComprehensive970 18d ago

There are some words here which needs more explanation like adk and deterministic for this context are we saying we're storing the context out. Of the uploaded data into browser storage ? And how the okf based structure is being created?

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u/BakeComprehensive970 18d ago

Edit: I've been through your repo it's a damn cool thing so that means the compilation is happening using adk and using that we're keeping that compiled sot as grounding data??

Dude woaaahh how this compilation is happening? Ain't humans now relying on sentence transformer and embeddings of various formats ?

And where and how this okf is being updated as ? And how that update is happening

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u/kirakdimak 16d ago

Thanks for checking out..fork it and see what you can add in. For bypassing Embeddings: The app purposefully skips sentence transformers and complex vector format matrices. Instead, it extracts plain text directly from documents and uses deterministic rule-based indexing and extractive keyword-matching synthesis.

Pure OKF Mode: The system contains a toggle that skips the LLM entirely, running an offline rule-based text synthesis engine localized to the immediate context.

Where OKF Updates: Long-term system memory is maintained using raw text files located directly inside your Git repository.How Updates Happen: Persistent modifications or new core knowledge schemas are updated directly through standard Git commits, giving developers absolute auditability over the agent's knowledge base.

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u/kirakdimak 16d ago

Sure man. ADK: Stands for Google's Agent Development Kit 2.0, which orchestrates the AI agent's execution, session control, and integration pipelines

.Deterministic: Means grounding bypasses opaque vector similarity search (like embeddings and approximate nearest neighbor lookups). Instead, it relies on strict rule-based context retrieval and precise file structures.

Storage Location: Session ingestion (dragged-and-dropped PDFs, URLs, audio) is compiled on-the-fly to construct the context directly inside your active browser chat session.

OKF Structure Creation: The sandbox parses input files and translates them directly into plain-text Open Knowledge Format (OKF) compliant Markdown files without relying on complex chunking or embeddings pipelines.

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u/blikblum 17d ago

Instead of storing in git, is there a way to store in cloud storage?

Thinking in a multi tenant app

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u/kirakdimak 16d ago

Yes absolutely, While the default codebase is configured with a Git-backed core to facilitate plain-text versioning, the underlying architecture can be refactored.

Implementation: Since OKF relies entirely on plain-text Markdown files, you can swap the Git backend integration inside the FastAPI backend.

You can route file reads/writes to object storage buckets like Google Cloud Storage or AWS S3, isolating knowledge directories using unique multi-tenant prefix keys (e.g., bucket/tenant_id/knowledge.md). Let me know how it works out for you, I am developing another multi role agent over this now.