BurmeseGPT is a Burmese-first AI ecosystem package, including Padauk, an agentic small language model built for tool use, function calling, and local deployment.
Project description
BurmeseGPT
BurmeseGPT is an open Burmese-first AI ecosystem created by Dr. Wai Yan Nyein Naing. This Python package is the main package for BurmeseGPT projects, including Padauk, a practical agentic small language model built for Burmese language understanding, tool use, function calling, and local or edge deployment.
Why BurmeseGPT
Burmese is still a low-resource language in AI, and practical Burmese AI tooling remains limited for many real developer workflows. BurmeseGPT focuses on useful, production-minded, and developer-friendly Burmese AI systems that can run locally and integrate with modern agent and API patterns.
Related projects
- Padauk - Burmese-first agentic language model.
- Burmese-Coder - Burmese coding and technical AI direction.
- Future tools and integrations under the BurmeseGPT ecosystem.
Installation
# Core package (download + info)
pip install burmesegpt
# Local OpenAI-compatible server runtime
pip install "burmesegpt[server]"
# OpenAI Python SDK integration helpers
pip install "burmesegpt[openai]"
# Full install (recommended)
pip install "burmesegpt[full]"
downloadandinfowork with core install.serveandrun(without--base-url) requireburmesegpt[server].smoke-test --client openairequiresburmesegpt[openai].
Real model run (recommended)
pip install "burmesegpt[full]"
burmesegpt download --quant q8_0
burmesegpt serve --quant q8_0 --host 127.0.0.1 --port 8000
Developer/CI smoke test (no model download)
burmesegpt serve --test-mode --port 8000
burmesegpt smoke-test --base-url http://127.0.0.1:8000/v1 --model padauk-agent
burmesegpt smoke-test --client openai --base-url http://127.0.0.1:8000/v1 --model padauk-agent
OpenAI-compatible Python usage
from openai import OpenAI
client = OpenAI(base_url="http://127.0.0.1:8000/v1", api_key="sk-no-key-required")
response = client.chat.completions.create(
model="padauk-agent",
messages=[{"role": "user", "content": "မင်္ဂလာပါ"}],
)
print(response.choices[0].message.content)
OpenAI Agents SDK usage
pip install openai-agents
import asyncio
from openai import AsyncOpenAI
from agents import Agent, Runner, set_default_openai_api, set_default_openai_client, set_tracing_disabled
set_tracing_disabled(True)
set_default_openai_api("chat_completions")
set_default_openai_client(
AsyncOpenAI(base_url="http://127.0.0.1:8000/v1", api_key="sk-no-key-required")
)
padauk = Agent(
name="Padauk Assistant",
model="padauk-agent",
instructions="You are Padauk, a Burmese-first assistant. Reply in Burmese by default.",
)
async def main() -> None:
result = await Runner.run(padauk, input="မင်္ဂလာပါ")
print(result.final_output)
asyncio.run(main())
Padauk system prompt note
model/Modelfile includes a Burmese custom SYSTEM prompt for Padauk, but this package currently serves GGUF directly with llama_cpp.server and does not automatically inject that SYSTEM block. If you need strict persona behavior, provide a system message (or Agent.instructions) from your client.
CLI commands
burmesegpt download- Download and checksum-verify a quantized GGUF artifact.burmesegpt serve- Start a local OpenAI-compatible API server.burmesegpt run- Interactive chat (boots local server or uses--base-url).burmesegpt smoke-test- Validate/modelsand/chat/completions.burmesegpt info- Print package/model configuration as JSON.
Useful options:
--quant:q4_k_m(default),q5_k_m,q8_0--repo-id,--revision,--cache-dir,--hf-token(orHF_TOKEN)- Shared options work both before and after subcommands.
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