offgrid 0.1.0

Python client for OffGrid LLM - Run AI models completely offline

OffGrid Python Client

Python client for OffGrid LLM - Run AI models completely offline.

Installation

pip install offgrid

Quick Start

import offgrid

client = offgrid.Client()
response = client.chat("Hello!")
print(response)

Usage

Connect to Server

import offgrid

# Default: localhost:11611
client = offgrid.Client()

# Custom server
client = offgrid.Client(host="http://192.168.1.100:11611")

# With timeout
client = offgrid.Client(host="http://192.168.1.100:11611", timeout=600)

Chat

# Basic
response = client.chat("What is Python?")

# With system prompt
response = client.chat(
    "Write a poem",
    system="You are a poet",
    temperature=0.9
)

# Streaming
for chunk in client.chat("Tell me a story", stream=True):
    print(chunk, end="", flush=True)

# Full conversation
messages = [
    {"role": "system", "content": "You are helpful."},
    {"role": "user", "content": "Hello!"},
]
response = client.chat(messages=messages)

Model Management

# List installed models
for model in client.list_models():
    print(model["id"])

# Search HuggingFace
results = client.models.search("llama", ram=8)
for r in results:
    print(f"{r['id']} - {r['size_gb']}GB")

# Download
client.models.download(
    "bartowski/Llama-3.2-3B-Instruct-GGUF",
    "Llama-3.2-3B-Instruct-Q4_K_M.gguf"
)

# Delete
client.models.delete("old-model")

# USB import/export
client.models.import_usb("/media/usb")
client.models.export_usb("model-name", "/media/usb")

Knowledge Base (RAG)

# Add documents
client.kb.add("notes.txt")
client.kb.add("meeting", content="Meeting notes...")
client.kb.add_directory("./docs")

# List
for doc in client.kb.list():
    print(f"{doc['id']}: {doc['chunks']} chunks")

# Search
results = client.kb.search("deadline")

# Chat with context
response = client.chat("Summarize notes", use_kb=True)

# Remove
client.kb.remove("notes.txt")
client.kb.clear()

Embeddings

# Single
embedding = client.embed("Hello world")

# Batch
embeddings = client.embed(["Hello", "World"])

System Info

# Health check
if client.health():
    print("Server running")

# Detailed info
info = client.info()
print(f"Uptime: {info['uptime']}")

Error Handling

from offgrid import Client, OffGridError

client = Client()

try:
    response = client.chat("Hello")
except OffGridError as e:
    print(f"Error: {e.message}")

Requirements

• Python 3.8+
• OffGrid server running (offgrid serve)
• No external dependencies

Links

• OffGrid LLM
• API Reference

License

MIT License