Text Runtime

This page covers the text-facing command families: chat, code generation, embeddings, and PII anonymization.

Public surface

• mere.run text chat
• mere.run text code
• mere.run text embed
• mere.run text anonymize

Model families

Chat

• text-chat-gemma4
• text-chat-q35
• text-chat-q35-nano
• text-agent-deepseek-v4-flash (API/agent serving)
• text-chat-mebot
• text-chat-psi-agent

Code

• text-code-qwen3

Embeddings

• text-embed-qwen3-0.6b

Anonymization

• text-anonymize-privacy-filter

Typical workflows

Local chat

swift run mere.run text chat \
  --stream \
  --model text-chat-gemma4 \
  --prompt "Summarize diffusion models in one paragraph."

Local code generation

swift run mere.run text code \
  --prompt "Write a Swift function that reverses a string."

Embeddings

swift run mere.run text embed \
  "semantic search query" \
  --pretty

PII anonymization

swift run mere.run text anonymize \
  "My name is Alice Smith and my email is alice@example.com"

Runtime entrypoints

CLI

• Sources/MereRunCLI/Commands/TextChatCommand.swift
• Sources/MereRunCLI/Commands/TextCodeCommand.swift
• Sources/MereRunCLI/Commands/TextEmbedCommand.swift
• Sources/MereRunCLI/Commands/TextAnonymizeCommand.swift

Chat families

• Sources/MereRunCore/Q35/
• Sources/MereRunCore/Gemma4/
• Sources/MereRunCore/Psi/
• Sources/MereRunCore/MeBot/

Code generation

mere.run text code uses the vendored llama.cpp runtime via vendor/llama.xcframework and the matching support code in MereRunCore.

Embeddings

• Sources/MereRunCore/Embeddings/

Anonymization

• Sources/MereRunCore/PrivacyFilter/

Practical distinctions

mere.run text chat

Use this for local assistant-style generation. It supports prompt/system control, token limits, token streaming with --stream, and the chat-oriented model families.

mere.run text code

Use this when you want a GGUF-backed coding path through the vendored llama.cpp runtime.

mere.run text embed

Use this for vector generation, semantic search prep, and other representation tasks. It is not a generative command.

mere.run text anonymize

Use this for local PII detection and redaction. It runs the OpenAI Privacy Filter token-classification model through the native MLX runtime and can emit plain redacted text or structured JSON spans.

Reading the code

If you want to understand the text stack:

1. start at the matching CLI command
2. follow model resolution through MereRunModelManifest and ModelResolver
3. jump to the family-specific runtime in MereRunCore

For repo orientation, pair this page with CLI and Runtime Internals.