LocalMind

Available Models

• Gemma 3 1B (~760 MB) — fast, text-only chat
• Gemma 4 E2B (~1.5 GB) — multimodal + agent
• Gemma 4 E4B (~4.9 GB) — multimodal + agent, best quality

Gemma 4 Agent Tools

• calculate — math, percentages, conversions
• get_current_time — date/time with timezone
• store_memory — save facts to persistent memory
• search_memory — recall from stored memories
• web_search — search the web (requires API key)
• fetch_page — read a web page’s content
• set_reminder — browser notification after N minutes
• list_memories — show what’s stored in memory
• delete_memory — forget specific memories
• segment_image — segment objects in attached images (SAM)

Image Segmentation (SAM)

Gemma 4 can call SAM (Segment Anything Model) to segment objects in attached images. Choose your SAM model in Settings — loaded on first use.

• SlimSAM 50 (~10 MB) — fastest, good enough for most tasks
• SlimSAM 77 (~14 MB) — default, better accuracy
• SAM ViT-Base (~350 MB) — full quality, slower download
• SAM 3 (latest) — newest architecture

Things to try

• “Segment the main object in this image”
• “Outline the person on the left”
• “Isolate the background”
• “How many distinct objects are in this image?”

Translation works directly — Gemma 4 speaks 140+ languages natively, no tool needed.

Gemma 3 1B works as a simple chatbot — no agent tools.

Document Upload

• Text — .txt, .md, .json, .csv
• PDF — extracted via PDF.js, auto-summarized
• DOCX — extracted via mammoth.js, auto-summarized

Documents are chunked, embedded, and stored as searchable knowledge. A summary is generated on upload.

Multimodal (Gemma 4)

• 📎 Attach — images, audio, MP4 video, or documents
• 📷 Camera / 🎤 Mic / Paste / Drag & drop

Document Upload

• Text — .txt, .md, .json, .csv
• PDF — extracted via PDF.js, auto-summarized
• DOCX — extracted via mammoth.js, auto-summarized
• Folder — open a local folder to ingest all .md/.txt/.pdf files at once; re-open to sync only changed files (incremental)

Conversations

• New Chat — archives to History + starts fresh
• Clear — deletes without saving
• History — sidebar, click to resume any past chat
• Share — generate an encrypted or plain link to share any conversation; recipient opens the URL to load it

Memory browser

• Category pills — filter by fact / preference / finding / document / conversation with live counts
• Source grouping — document chunks grouped by file; bulk “Delete all” per source
• Audit — flags stale (>60 days), near-duplicates (cosine sim ≥0.92), and outliers (low avg similarity to category); bulk or per-item delete; auto-reruns after each deletion

Output & Export

• Save as MD — download any response as Markdown (or write directly to open folder if one is active)
• Code download — hover code blocks for download button
• Export / Import — in Memory panel, full data as JSON
• Auto-backup — toggle in Settings to download on New Chat

Batch Prompts

• Enter one prompt per line in the Batch panel — they run sequentially through the full agent loop
• {{previous}} — explicit placeholder substituted with the previous response text
• Auto-inject — checkbox (on by default) appends the previous response as context even without a placeholder; disabled for any prompt that already contains {{previous}}
• Stop — halts after the current generation finishes; progress shown live

Other

• Web Search — Settings → provider + API key → 🌐 button
• Thinking Mode — see chain-of-thought (collapses when done)
• Cache management — view/clear cached models in Settings
• Custom models — Settings → paste a Hugging Face ONNX repo id (causal LMs only). The validator probes the HF API, picks the best available quantisation, estimates real load size, and hard-blocks anything that exceeds the device’s WebGPU buffer limit or the 6 GB ceiling.
• Response badges — On-device / Agent / Web-enriched

JavaScript API (experimental)

Settings → tick Expose window.localmind. Same-tab only — cross-origin scripts cannot reach it. The object is frozen and non-writable; disable the toggle to detach.

Surface (v1.0)

• version · ready · model — live state getters
• listModels() — full registry incl. custom models with loaded flag
• load(idOrKey) — loads a model (short key or HF id); resolves when ready
• chat.completions.create({ messages, max_tokens, temperature, top_p, model }) — non-streaming, returns OpenAI-shaped chat.completion
• chat.completions.create({ …, stream: true }) — async iterator yielding chat.completion.chunk objects

Not exposed

• Tools / tool calling
• Memory read/write
• File system, web search, search API keys, user profile
• Multimodal input

Activity log

Every API call is logged in-memory (last 50). Click the • API chip in the toolbar or Settings → View activity log. Each call shows method, prompt length, tokens generated, duration, and outcome (ok / err / busy).

Demo

Open demo.html in the same folder. It iframes LocalMind, auto-flips the toggle, waits for the model, and runs both a non-streaming and a streaming completion against iframe.contentWindow.localmind.

Math & Conversions

What is 15% of 2450? Convert 72 Fahrenheit to Celsius Compound interest: $10K at 7% for 5 years?

Time & Reminders

What time is it in Tokyo? Remind me in 5 minutes to check the oven

Memory

Remember: I'm a software engineer on Dashboard Pro What do you know about me? Forget my preferences

Translation

Translate "Good morning" to Japanese, French, Hindi Train station directions in Spanish & German

Writing & Analysis

Write a polite meeting decline email Microservices vs monolith: pros and cons Explain WebGPU in 3 simple sentences

Documents (attach a PDF, DOCX, or text file)

Summarize the uploaded document Main conclusions from my document

Multimodal (attach an image first)

Describe this image in detail Transcribe text from this image

Web Research (requires API key)

Top tech news today Latest WebGPU browser support status AI in the browser: recent articles with sources

Coding

Sieve of Eratosthenes in Python async/await vs Promises explained