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221 lines
6.6 KiB
Markdown
221 lines
6.6 KiB
Markdown
# 📑 Data Contracts — Stable Interfaces for RAG & Agents
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Everything WFGY touches is JSON-first and versioned. These “contracts” make pipelines observable, reproducible, and easy to debug.
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> **Quick Nav**
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> [Retrieval Playbook](./retrieval-playbook.md) ·
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> [Traceability](./retrieval-traceability.md) ·
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> [Eval](./eval/README.md) ·
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> [Ops](./ops/README.md) ·
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> Patterns: [SCU](./patterns/pattern_symbolic_constraint_unlock.md) ·
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> [Memory Desync](./patterns/pattern_memory_desync.md)
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---
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## 0) Envelope (required for all records)
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```json
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{
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"schema_version": "1.0.0",
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"event": "ingest.write | retrieve.run | rerank.run | answer.decide",
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"ts": "2025-08-13T10:22:59Z",
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"trace_id": "uuid",
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"agent_id": "scout|medic|engineer|retriever|system",
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"mem_rev": "r42",
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"mem_hash": "sha256:..."
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}
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````
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* `mem_rev`/`mem_hash` prevent **memory overwrite** and **desync**.
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* Use the same envelope for logs and datasets.
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---
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## 1) Chunk record
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**Purpose:** atomic, traceable text unit for retrieval.
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```json
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{
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"$schema": "https://wfgy.dev/schemas/chunk-1.0.json",
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"chunk_id": "c_00123",
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"doc_id": "d_wfgy_paper",
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"section_id": "s_intro",
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"span": {"line_start": 120, "line_end": 154},
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"lang": "en",
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"text": "Delta-S measures semantic stress ...",
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"hash": "sha256:...",
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"embedding": {
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"model": "sentence-transformers/all-MiniLM-L6-v2",
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"dim": 384,
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"vector": [0.012, -0.044, ...],
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"normalized": true,
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"metric": "cosine"
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},
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"anchors": ["ΔS", "semantic stress"]
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}
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```
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**Rules**
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* Keep **original text** + **normalized text** (case/punctuation) if you apply normalization downstream.
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* Always store `metric` and `normalized`.
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---
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## 2) Query record
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```json
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{
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"$schema": "https://wfgy.dev/schemas/query-1.0.json",
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"q_id": "q_2025_08_13_0001",
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"text": "How does ΔS detect retrieval failure?",
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"lang": "en",
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"hyde": "Generate a canonical query about ... (optional)",
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"tokens": {"count": 12, "analyzer": "icu"},
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"hints": {"doc_id": ["d_wfgy_paper"], "section_id": []}
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}
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```
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---
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## 3) Retrieval result (candidate)
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```json
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{
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"$schema": "https://wfgy.dev/schemas/retrieved-1.0.json",
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"q_id": "q_2025_08_13_0001",
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"ranker": "dense|bm25|hybrid",
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"k": 50,
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"items": [
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{
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"chunk_id": "c_00123",
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"doc_id": "d_wfgy_paper",
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"score": 0.812, // retriever-native score
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"cosine": 0.91, // optional explicit cosine
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"ΔS_q_ctx": 0.36, // optional, if ground anchor available
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"source": "dense",
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"features": {"bm25": 8.3, "dense": 0.91}
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}
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]
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}
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```
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---
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## 4) Rerank result
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```json
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{
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"$schema": "https://wfgy.dev/schemas/rerank-1.0.json",
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"q_id": "q_2025_08_13_0001",
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"model": "BAAI/bge-reranker-base",
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"k_in": 60,
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"k_out": 8,
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"items": [
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{
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"chunk_id": "c_00123",
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"pre_score": {"dense": 0.91, "bm25": 8.3},
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"post_score": {"ce": 0.82},
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"reason": "mentions ΔS definition and failure threshold",
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"selected": true
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}
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]
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}
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```
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---
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## 5) Prompt frame (schema-locked)
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```json
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{
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"$schema": "https://wfgy.dev/schemas/prompt-frame-1.0.json",
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"system": "You are a grounded assistant. Cite before you explain.",
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"task": "Answer the user's question using ONLY the cited snippets.",
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"constraints": ["No cross-source merging", "Cite line spans"],
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"citations": [
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{"id": "c_00123", "doc_id": "d_wfgy_paper", "section_id": "s_intro", "span": [120,154]}
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],
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"question": "How does ΔS detect retrieval failure?"
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}
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```
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---
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## 6) Answer + trace
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```json
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{
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"$schema": "https://wfgy.dev/schemas/answer-1.0.json",
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"q_id": "q_2025_08_13_0001",
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"answer_text": "ΔS measures the semantic gap ...",
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"cited_chunks": ["c_00123", "c_00987"],
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"λ_observe": "→",
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"metrics": {"ΔS_q_ctx": 0.38, "latency_ms": 922}
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}
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```
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---
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## 7) Metrics pack (for CI)
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```json
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{
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"$schema": "https://wfgy.dev/schemas/metrics-1.0.json",
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"dataset": "goldset_v1",
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"recall@50": 0.91,
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"nDCG@10": 0.62,
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"ΔS_mean": 0.41,
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"ΔS_p95": 0.58,
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"λ_convergent_rate": 0.82
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}
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```
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---
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## Acceptance checklist
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* ✅ All records include **envelope** (schema\_version, event, ts, trace\_id, mem\_rev/hash).
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* ✅ Chunks persist **metric** and **normalized** flags.
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* ✅ Prompts are **schema-locked** (cite → explain).
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* ✅ Answers store **cited chunk IDs** and **λ state**.
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* ✅ Metrics committed per PR (goldset.jsonl).
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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|------|------|--------------|
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| Engine | [WFGY 1.0](/legacy/README.md) | Original PDF based tension engine |
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| Engine | [WFGY 2.0](/core/README.md) | Production tension kernel and math engine for RAG and agents |
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| Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine, 131 S class set |
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| Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure checklist and fix map |
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| Map | [Problem Map 2.0](/ProblemMap/rag-architecture-and-recovery.md) | RAG focused recovery pipeline |
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| Map | [Problem Map 3.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card, image as a debug protocol layer |
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| Map | [Semantic Clinic](/ProblemMap/SemanticClinicIndex.md) | Symptom to family to exact fix |
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| Map | [Grandma’s Clinic](/ProblemMap/GrandmaClinic/README.md) | Plain language stories mapped to Problem Map 1.0 |
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| Onboarding | [Starter Village](/StarterVillage/README.md) | Guided tour for newcomers |
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| App | [TXT OS](/OS/README.md) | TXT semantic OS, fast boot |
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| App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q and A built on TXT OS |
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| App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image with semantic control |
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| App | [Blow Blow Blow](/OS/BlowBlowBlow/README.md) | Reasoning game engine and memory demo |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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