Files
fastapi-sqlalchemy-asyncpg/app/services/llm.py
T

51 lines
1.9 KiB
Python

"""Streaming client for OpenAI-compatible chat completion endpoints."""
from collections.abc import AsyncIterator
import httpx2
import orjson
class StreamLLMService:
"""Send prompts to an LLM endpoint and yield newline-delimited JSON events."""
def __init__(self, base_url: str = "http://localhost:11434/v1") -> None:
"""Configure the endpoint and default model."""
self.base_url = base_url
self.model = "llama3.2"
async def stream_chat(self, prompt: str) -> AsyncIterator[bytes]:
"""Yield the prompt followed by streamed model response chunks."""
user_msg = {
"role": "user",
"content": prompt,
}
yield orjson.dumps(user_msg) + b"\n"
async with httpx2.AsyncClient(base_url=self.base_url) as client:
async with client.stream(
"POST",
"/chat/completions",
json={
"model": self.model,
"messages": [{"role": "user", "content": prompt}],
"stream": True,
},
timeout=60.0,
) as response:
async for line in response.aiter_lines():
if line.startswith("data: ") and line != "data: [DONE]":
data = orjson.loads(line.removeprefix("data: "))
choices = data.get("choices", [])
if not choices:
continue
content = choices[0].get("delta", {}).get("content", "")
if content:
model_msg = {"role": "model", "content": content}
yield orjson.dumps(model_msg) + b"\n"
def get_llm_service(base_url: str | None = None) -> StreamLLMService:
"""Build the service using the supplied URL or its local default."""
return StreamLLMService(base_url=base_url or "http://localhost:11434/v1")