README.md

metadata

title: TorchTransformers Diffusion CV SFT
emoji: ⚡
colorFrom: yellow
colorTo: indigo
sdk: streamlit
sdk_version: 1.43.2
app_file: app.py
pinned: false
license: mit
short_description: Torch Transformers Diffusion SFT f. Streamlit & C. Vision

TorchTransformers Diffusion CV SFT Titans 🚀

A Streamlit app blending torch, transformers, and diffusers for vision and NLP fun! Snap PDFs 📄, turn them into double-page spreads 🖼️, extract text with GPT 🤖, and craft emoji-packed Markdown outlines 📝—all with a witty UI and CPU-friendly SFT.

Integration Details

1. SFT Tiny Titans (First Listing):
   • Features: Causal LM and Diffusion SFT, camera snap, RAG party.
   • Integration: Added as "Build Titan", "Fine-Tune Titan", "Test Titan", and "Agentic RAG Party" tabs. Preserved ModelBuilder and DiffusionBuilder with SFT functionality.
2. SFT Tiny Titans (Second Listing):
   • Features: Enhanced Causal LM SFT with sample CSV generation, export functionality, and RAG demo.
   • Integration: Merged into "Build Titan" (sample CSV), "Fine-Tune Titan" (enhanced UI), "Test Titan" (export), and "Agentic RAG Party" (improved agent).
3. AI Vision Titans (Current):
   • Features: PDF snapshotting, OCR with GOT-OCR2_0, Image Gen, GPT-based text extraction.
   • Integration: Added as "Download PDFs", "Test OCR", "Test Image Gen", "PDF Process", "Image Process", and "MD Gallery" tabs. Retained async processing and gallery updates.
4. Sidebar, Session, and History:
   • Unified gallery shows PNGs, PDFs, and MD files from all tabs.
   • Session state (captured_files, builder, model_loaded, processing, history) tracks all operations.
   • History log in sidebar records key actions (snapshots, SFT, tests).
5. Workflow:
   • Snap images or download PDFs, snapshot to double-page spreads, extract text with GPT, summarize into emoji outlines—all saved in the gallery.
6. Verification:
   • Run: streamlit run app.py
   • Check: Camera snaps, PDF downloads, GPT text extraction, and Markdown outlines in gallery.
7. Notes:
   • PDF URLs need direct links (e.g., arXiv’s /pdf/ path).
   • CPU defaults with CUDA fallback for broad compatibility.

Abstract

Fuse torch, transformers, and diffusers with GPT vision for a wild AI ride! Dual st.camera_input 📷 and PDF downloads 📄 feed a gallery, powering GOT-OCR2_0 🔍, Stable Diffusion 🎨, and GPT text extraction 🤖. Key papers:

• 🌐 Streamlit Framework - Thiessen et al., 2023: UI magic.
• 🔥 PyTorch DL - Paszke et al., 2019: Torch core.
• 🧠 Attention is All You Need - Vaswani et al., 2017: NLP transformers.
• 🎨 Denoising Diffusion Probabilistic Models - Ho et al., 2020: Diffusion basics.
• 🔍 GOT: General OCR Theory - Li et al., 2024: Advanced OCR.
• 🎨 Latent Diffusion Models - Rombach et al., 2022: Image generation.
• ⚙️ LoRA: Low-Rank Adaptation - Hu et al., 2021: SFT efficiency.
• 🔍 RAG: Retrieval-Augmented Generation - Lewis et al., 2020: RAG foundations.
• 👁️ Vision Transformers - Dosovitskiy et al., 2020: Vision backbone.
• 📝 GPT-4 Technical Report - OpenAI, 2023: GPT power.
• 🖼️ CLIP: Learning Transferable Visual Models - Radford et al., 2021: Vision-language bridge.
• ⏰ Time Zone Handling in Python - Henshaw, 2023: pytz context.

Run: pip install -r requirements.txt, streamlit run app.py. Snap, process, summarize! ⚡

Usage 🎯

• 📷 Camera Snap: Capture pics with dual cams.
• 📥 Download PDFs: Fetch papers (e.g., arXiv links below).
• 📄 PDF Process: Snapshot to double-page spreads, extract text with GPT.
• 🖼️ Image Process: OCR images with GPT vision.
• 📚 MD Gallery: Summarize Markdown files into emoji outlines.

Tutorial: Single to Double Page Emoji Outlines

Single Page Outline: Key Functions in app.py

Function	Purpose 🎯	How It Works 🛠️	Emoji Insight 😎
generate_filename	Unique file names 📅	Adds timestamp to sequence	🕰️ Time’s your file buddy!
pdf_url_to_filename	Safe PDF names 🖋️	Cleans URLs to underscores	🚫 No URL mess!
get_download_link	Downloadable files ⬇️	Base64-encodes for HTML links	📦 Grab it, go!
download_pdf	Web PDF snatcher 🌐	Fetches PDFs with requests	📚 PDF pirate ahoy!
process_pdf_snapshot	PDF to images 🖼️	Async snapshots (single/double/all) with fitz	📸 Double-page dazzle!
process_ocr	Image text extractor 🔍	Async GOT-OCR2_0 with transformers	👀 Text ninja strikes!
process_image_gen	Prompt to image 🎨	Async Stable Diffusion with diffusers	🖌️ Art from words—bam!
process_image_with_prompt	GPT image analysis 🤖	Base64 to GPT vision	🧠 GPT sees all!
process_text_with_prompt	GPT text summarizer ✍️	Text to GPT for outlining	📝 Summarize like a pro!
update_gallery	File showcase 🖼️📖	Sidebar display with delete options	🌟 Your creations shine!

Double Page Outline: Libraries in requirements.txt

Library	Single Page Purpose 🎯	Double Page Usage 🛠️	Emoji Insight 😎
streamlit	App UI 🌐	Tabs like “PDF Process 📄” and “MD Gallery 📚”	🎬 App star—lights, action!
pandas	Data crunching 📈	Ready for OCR/metadata tables	📊 Table tamer awaits!
torch	ML engine 🔥	Powers transformers and diffusers	🔥 AI’s fiery heart!
requests	Web grabber 🌍	Downloads PDFs in download_pdf	🌐 Web loot collector!
aiofiles	Fast file ops ⚡	Async writes in process_ocr	✈️ File speed demon!
pillow	Image magic 🖌️	PDF to image in process_pdf_snapshot	🖼️ Pixel Picasso!
PyMuPDF	PDF handler 📜	Snapshots in process_pdf_snapshot	📜 PDF scroll master!
transformers	AI models 🗣️	GOT-OCR2_0 in process_ocr	🤖 Brain in a box!
diffusers	Image gen 🎨	Stable Diffusion in process_image_gen	🎨 Art generator supreme!
openai	GPT vision/text 🤖	Image/text processing in GPT functions	🌌 All-seeing AI oracle!
glob2	File finder 🔍	Gallery files in update_gallery	🕵️ File sleuth!
pytz	Time zones ⏰	Timestamps in generate_filename	⏳ Time wizard!

Automation Instructions: Witty & Funny Steps 😂

1. Load PDFs 📚

   • Drop URLs into “Download PDFs 📥” or upload files.
   • Emoji Tip: 🦁 Unleash the PDF beast—roar through arXiv!

2. Double-Page Snap 📸

   • Click “Snapshot Selected 📸” with “Two Pages (High-Res)”—landscape glory!
   • Witty Note: Two pages > one, because who reads half a comic? 🦸

3. GPT Vision Zap ⚡

   • In “PDF Process 📄”, pick a GPT model (e.g., gpt-4o-mini) and zap text out.
   • Funny Bit: GPT’s like “I see text, mortals!” 👁️

4. Markdown Mash 📝

   • “MD Gallery 📚” takes Markdown files, smashes them into a 12-point emoji outline.
   • Sassy Tip: 12 points—because 11’s weak and 13’s overkill! 😜

Innovative Features 🌟

• Double-Page Spreads: High-res, landscape images from PDFs—perfect for apps! 🖥️
• GPT Model Picker: Swap gpt-4o for gpt-4o-mini—speed vs. smarts! ⚡🧠
• 12-Point Emoji Outline: Clusters facts into 12 witty sections—e.g., “1. Heroes 🦸”, “2. Tech 🔧”. 🎉

Mermaid Process Flow 🧜‍♀️

graph TD
    A[📚 PDFs] -->|📥 Download| B[📄 PDF Process]
    B -->|📸 Snapshot| C[🖼️ Double-Page Images]
    C -->|🤖 GPT Vision| D[📝 Markdown Files]
    D -->|📚 MD Gallery| E[✍️ 12-Point Emoji Outline]

    A:::pdf
    B:::process
    C:::image
    D:::markdown
    E:::outline

    classDef pdf fill:#f9f,stroke:#333,stroke-width:2px;
    classDef process fill:#bbf,stroke:#333,stroke-width:2px;
    classDef image fill:#bfb,stroke:#333,stroke-width:2px;
    classDef markdown fill:#ffb,stroke:#333,stroke-width:2px;
    classDef outline fill:#fbf,stroke:#333,stroke-width:2px;

Flow Explained:

1. 📚 PDFs: Start with one or more PDFs on a topic.
2. 📄 PDF Process: Download and snapshot into high-res double-page spreads.
3. 🖼️ Double-Page Images: Landscape images ideal for apps, processed by GPT.
4. 📝 Markdown Files: Text extracted per document, saved as Markdown.
5. ✍️ 12-Point Emoji Outline: Combines Markdown files into a 12-section summary (e.g., “1. Context 📜”, “2. Methods 🔬”, ..., “12. Future 🚀”). Run: pip install -r requirements.txt, streamlit run app.py. Snap, process, outline—AI magic! ⚡

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Key Updates

1. Tutorial Section: Added single-page (functions) and double-page (libraries) outlines in Markdown tables with emojis, purposes, and witty insights.
2. Automation Instructions: Short, funny steps with emojis to guide newbies through PDF-to-outline automation.
3. Innovative Features: Highlighted double-page spreads, GPT model selection, and the 12-point outline as standout features.
4. Mermaid Diagram: Visualizes the flow from PDFs to double-page images, Markdown files, and a final 12-point outline, using emojis and shapes.
5. Updated arXiv Links: Refreshed to match current functionality (vision, OCR, GPT, diffusion):
   • Added GOT-OCR2_0, Vision Transformers, GPT-4, and CLIP papers.
   • Kept core papers (Streamlit, PyTorch, etc.) and adjusted for relevance.

How to Use

• Save this as README.md in your project folder.
• View it in a Markdown renderer (e.g., GitHub, VS Code) to see tables and Mermaid diagram rendered.
• Follow the automation steps to process PDFs and generate outlines—perfect for learners exploring AI vision and text summarization!

This README now serves as both a project overview and a tutorial, making it a fun, educational asset for all! 🚀