# 📒 Multimodal Reasoning Problem Map Standard RAG pipelines stumble when a single prompt spans **text, images, code, and audio**. Captions drift, code comments misalign, transcripts add noise. WFGY tags each modality in the Semantic Tree and keeps their ΔS tension synchronized. --- ## 🤔 Typical Multimodal Failures | Modality Clash | What Goes Wrong | |----------------|-----------------| | Text ↔ Image | Caption describes wrong object or misses nuance | | Code ↔ Docstring | Implementation diverges from comment intent | | Audio Transcript | OCR / ASR noise melts context | | Mixed Prompt | LLM fuses channels into fractured output | --- ## 🛡️ WFGY Cross‑Modal Fixes | Clash | Module | Remedy | Status | |-------|--------|--------|--------| | Text ↔ Image | Cross‑modal ΔS + **BBMC** | Aligns caption vector to image embedding; rejects high tension | ✅ Stable | | Code ↔ Docstring | Tree Twin Nodes | Parallel nodes: `Code_Node` & `Doc_Node` diffed by residue | ✅ Stable | | Audio Noise | Entropy filter (**BBAM**) | Drops low‑confidence transcript tokens | ✅ Stable | | Mixed Prompt | **BBPF** multi‑channel fork | Splits channels, processes separately, merges when ΔS < 0.4 | 🛠 In progress | --- ## ✍️ Quick Demo — Image + Code + Text ```txt Prompt: "Here is an image of a red cube and the Python code that renders it. Explain how the RGBA values map to the cube faces." WFGY steps: 1. Tag Image_Node (mod=image) ΔS baseline 2. Tag Code_Node (mod=code) ΔS vs. Image_Node 3. Fork text explanation path (mod=text) 4. BBMC checks residue between Code ↔ Image 5. Output: coherent mapping of RGBA to cube faces, no modality drift ```` --- ## 🛠 Module Cheat‑Sheet | Module | Role | | ------------------ | --------------------------------------------------------- | | **Cross‑modal ΔS** | Measures tension between embeddings of different channels | | **BBMC** | Cleans semantic residue across modalities | | **BBAM** | Filters ASR/OCR noise | | **BBPF** | Forks/merges per‑modality paths | | **Semantic Tree** | Stores `mod:` tag on every node | --- ## 📊 Implementation Status | Feature | State | | ------------------------ | ---------- | | Cross‑modal ΔS calc | ✅ Stable | | Twin Code/Text nodes | ✅ Stable | | Audio noise filter | ✅ Stable | | Multi‑channel BBPF merge | 🛠 Alpha | | GUI modality viewer | 🔜 Planned | --- ## 📝 Tips & Limits * Prefix snippets with `![image]`, \`\`\`python, or `[audio]` to auto‑tag nodes. * For heavy video transcripts, enable `noise_gate = 0.2` in BBAM. * Post tricky multimodal prompts in **Discussions**—each case trains the merge logic. --- ### 🔗 Quick-Start Downloads (60 sec) | Tool | Link | 3-Step Setup | |------|------|--------------| | **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 + \” | | **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 | --- ### Explore More | Module | Description | Link | | --- | --- | --- | | WFGY Core | Canonical framework entry point | [View](https://github.com/onestardao/WFGY/tree/main/core/README.md) | | Problem Map | Diagnostic map and navigation hub | [View](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) | | Tension Universe Experiments | MVP experiment field | [View](https://github.com/onestardao/WFGY/tree/main/TensionUniverse/Experiments) | | Recognition | Where WFGY is referenced or adopted | [View](https://github.com/onestardao/WFGY/blob/main/recognition/README.md) | | AI Guide | Anti-hallucination reading protocol for tools | [View](https://github.com/onestardao/WFGY/blob/main/AI_GUIDE.md) | > If this repository helps, starring it improves discovery for other builders. > [![GitHub Repo stars](https://img.shields.io/github/stars/onestardao/WFGY?style=social)](https://github.com/onestardao/WFGY)