NERVsystems/llm9p: LLM exposed as a 9P filesystem · GitHub

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📂 **Category**:

📌 **What You’ll Learn**:

LLM access via the 9P filesystem protocol.

llm9p enables users, scripts, and AI agents to interact with Large Language Models through standard filesystem operations. Write a prompt to a file, read the response from the same file. Supports multiple backends including Anthropic API, Claude Code CLI, and local LLMs (planned).

Backend Status Description
Anthropic API Available Direct API access with your API key
Claude Code CLI Available Uses Claude Max subscription via claude command
Local LLMs (Ollama) Planned Run models locally without cloud dependencies

The pluggable backend architecture makes it easy to add new LLM providers.

9P is a simple, lightweight network filesystem protocol originally developed for Plan 9 from Bell Labs. It lets you access remote resources as if they were local files. This means you can interact with LLMs using basic file operations (cat, echo, >, <) instead of SDKs or HTTP APIs.

Why use 9P for LLM access?

  • Universal: Any language or tool that can read/write files can use it
  • Scriptable: Chain LLM calls with standard Unix pipes and shell scripts
  • Composable: Mount multiple 9P services and combine them
  • Simple: No libraries, no dependencies, just files
go install github.com/NERVsystems/llm9p/cmd/llm9p@latest

Or build from source:

git clone https://github.com/NERVsystems/llm9p
cd llm9p
go build -o llm9p ./cmd/llm9p

Option A: Using Anthropic API (requires API key)

export ANTHROPIC_API_KEY=sk-ant-...
./llm9p -addr :5640

Option B: Using Claude Max Subscription (via Claude Code CLI)

If you have a Claude Max subscription and the Claude Code CLI installed:

./llm9p -addr :5640 -backend cli

This uses your Claude Max subscription instead of API tokens. No API key required.

Requirements for CLI backend:

  • Claude Code CLI installed and authenticated (claude command available)
  • Active Claude Max subscription

There are several ways to mount the filesystem depending on your environment.

Option 1: Plan 9 from User Space (plan9port)

plan9port provides Plan 9 tools for Unix systems.

# Install on macOS
brew install plan9port

# Install on Debian/Ubuntu
sudo apt-get install 9base

# Mount using 9pfuse
mkdir -p /mnt/llm
9pfuse localhost:5640 /mnt/llm

# Or use the 9p tool directly (no mount needed)
9p -a localhost:5640 ls llm
9p -a localhost:5640 read llm/model
9p -a localhost:5640 write llm/ask "What is 2+2?"
9p -a localhost:5640 read llm/ask

Option 2: Infernode (Inferno OS)

Infernode is a hosted Inferno OS environment with native 9P support. This is an excellent way to explore 9P filesystems.

# Start infernode
cd /path/to/infernode
./emu

# Inside infernode shell, mount llm9p
# Note: Use IP address 127.0.0.1, not "localhost"
mkdir /n/llm
mount -A tcp!127.0.0.1!5640 /n/llm

# List available files
ls -l /n/llm

# Check current model
cat /n/llm/model

# Ask a question
echo 'What is the capital of France?' > /n/llm/ask
cat /n/llm/ask

# View conversation history
cat /n/llm/context

# Reset conversation
echo reset > /n/llm/new

Infernode Tips:

  • Always use 127.0.0.1 instead of localhost for the server address
  • Create the mount point with mkdir /n/llm before mounting
  • The -A flag to mount enables anonymous authentication (no auth required)
  • Use single quotes around prompts to avoid shell interpretation issues

Linux has built-in 9P filesystem support via the 9p kernel module.

# Mount via kernel 9p module
sudo mount -t 9p -o port=5640,version=9p2000 localhost /mnt/llm
# Ask a question
echo "What is 2+2?" > /mnt/llm/ask
cat /mnt/llm/ask

# View token usage
cat /mnt/llm/tokens

# Change model
echo "claude-3-haiku-20240307" > /mnt/llm/model

# Adjust temperature
echo "0.5" > /mnt/llm/temperature

# Set a system prompt (persists across conversation resets)
echo "You are a helpful coding assistant." > /mnt/llm/system

# View current system prompt
cat /mnt/llm/system

# View conversation history
cat /mnt/llm/context

# Add a system message
echo "You are a helpful coding assistant." > /mnt/llm/context

# Reset conversation
echo "" > /mnt/llm/new

# View help
cat /mnt/llm/_example
/llm/
├── ask              # Write prompt, read response (same file)
├── model            # Read/write: current model name
├── temperature      # Read/write: temperature float (0.0-2.0)
├── system           # Read/write: system prompt (persists across resets)
├── tokens           # Read-only: last response token count
├── new              # Write anything to start fresh conversation
├── context          # Read: conversation history; Write: add system message
├── _example         # Read-only: usage examples
└── stream/          # Streaming interface
    ├── ask          # Write-only: starts a streaming request
    └── chunk        # Read-only: blocks until next chunk, EOF on completion

File Read Write
ask Returns last LLM response Sends prompt to LLM (sync), stores response
model Returns current model name Sets model for subsequent requests
temperature Returns current temperature Sets temperature (0.0-2.0)
system Returns current system prompt Sets system prompt (persists across resets)
tokens Returns last response token count Permission denied
new Permission denied Any write resets conversation (keeps system prompt)
context Returns JSON conversation history Appends system message to history
_example Returns usage examples Permission denied
stream/ask Permission denied Starts a streaming request
stream/chunk Blocks until next chunk, returns it Permission denied

For long responses, use the streaming interface to see output as it’s generated:

# Start a streaming request (using 9p tool)
echo "Write a poem about the moon" | 9p -a localhost:5640 write stream/ask &

# Read chunks as they arrive
while chunk=$(9p -a localhost:5640 read stream/chunk 2>/dev/null); do
  [ -z "$chunk" ] && break
  printf "%s" "$chunk"
done

With a mounted filesystem:

# Start streaming in background
echo "Explain quantum computing" > /mnt/llm/stream/ask &

# Read chunks
while read -r chunk < /mnt/llm/stream/chunk 2>/dev/null; do
  printf "%s" "$chunk"
done

Note: Start reading chunks immediately after writing to stream/ask. If you wait too long, the stream may complete and you’ll get EOF.

#!/bin/sh
# ask.sh - Simple LLM query script

if [ -z "$1" ]; then
    echo "Usage: $0 "
    exit 1
fi

echo "$1" > /mnt/llm/ask
cat /mnt/llm/ask

Flag Default Description
-addr :5640 Address to listen on
-backend api Backend: api (Anthropic API) or cli (Claude Code CLI)
-debug false Enable debug logging

Variable Required Description
ANTHROPIC_API_KEY For api backend Your Anthropic API key

  • Model: claude-sonnet-4-20250514 (API) or sonnet (CLI)
  • Temperature: 0.7
  • Max Tokens: 4096

Feature API Backend CLI Backend
Authentication API key required Claude Max subscription
Token counting Accurate Not available (always 0)
Model names Full names Aliases (opus, sonnet, haiku)
Streaming True streaming Simulated (full response)
Rate limits API limits apply Subscription limits apply

  • Go 1.21+
  • LLM backend (one of the following):
    • Anthropic API key (for api backend)
    • Claude Code CLI with Max subscription (for cli backend)
  • 9P client (one of the following):
    • plan9port – Plan 9 tools for Unix (macOS, Linux)
    • Infernode – Hosted Inferno OS with native 9P
    • Linux 9P kernel module – Built into Linux kernel
    • Native Plan 9 or Inferno OS
# Check what's using the port
lsof -i :5640

# Use a different port
./llm9p -addr :5641

Ensure the server is running and listening on the expected port:

# Start with debug logging to see connections
./llm9p -addr :5640 -debug

Infernode: “localhost” not resolving

Inferno’s DNS resolution works differently. Use the IP address directly:

# Wrong
mount -A tcp!localhost!5640 /n/llm

# Correct
mount -A tcp!127.0.0.1!5640 /n/llm

Infernode: Mount point doesn’t exist

Create the mount point before mounting:

mkdir /n/llm
mount -A tcp!127.0.0.1!5640 /n/llm

Permission denied on write

Some files are read-only by design:

  • tokens – Read-only (token count from last response)
  • _example – Read-only (usage examples)
  • stream/chunk – Read-only (streaming output)

The ask file only contains content after you write a prompt to it:

# First write a prompt
echo "Hello" > /mnt/llm/ask

# Then read the response
cat /mnt/llm/ask

Check that your API key is set and valid:

# Ensure the key is exported
export ANTHROPIC_API_KEY=sk-ant-...

# Verify it's set
echo $ANTHROPIC_API_KEY
  1. Server starts: llm9p listens for 9P connections on the specified port
  2. Client connects: A 9P client (9pfuse, Infernode, etc.) connects and negotiates the protocol
  3. Filesystem exposed: The client sees a virtual filesystem with files like ask, model, tokens
  4. Write prompt: Writing to ask sends the text to the configured LLM backend
  5. Read response: Reading from ask returns the LLM’s response
  6. State persists: Conversation history is maintained until you write to new

The 9P protocol handles all the complexity of making this look like a regular filesystem, so any tool that can read and write files can interact with the LLM.

MIT

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