plano/function_resolver/app/main.py

50 lines
1.5 KiB
Python

import json
from fastapi import FastAPI, Response
from bolt_handler import BoltHandler
from arch_handler import ArchHandler
from common import ChatMessage
import logging
from openai import OpenAI
import os
ollama_endpoint = os.getenv("OLLAMA_ENDPOINT", "localhost")
ollama_model = os.getenv("OLLAMA_MODEL", "Bolt-Function-Calling-1B:Q4_K_M")
logger = logging.getLogger('uvicorn.error')
logger.info(f"using model: {ollama_model}")
logger.info(f"using ollama endpoint: {ollama_endpoint}")
app = FastAPI()
bolt_handler = BoltHandler()
arch_handler = ArchHandler()
client = OpenAI(
base_url='http://{}:11434/v1/'.format(ollama_endpoint),
# required but ignored
api_key='ollama',
)
@app.get("/healthz")
async def healthz():
return {
"status": "ok"
}
@app.post("/v1/chat/completions")
async def chat_completion(req: ChatMessage, res: Response):
logger.info("starting request")
if ollama_model.startswith("Bolt"):
handler = bolt_handler
else:
handler = arch_handler
tools_encoded = handler._format_system(req.tools)
# append system prompt with tools to messages
messages = [{"role": "system", "content": tools_encoded}]
for message in req.messages:
messages.append({"role": message.role, "content": message.content})
logger.info(f"request model: {ollama_model}, messages: {json.dumps(messages)}")
resp = client.chat.completions.create(messages=messages, model=ollama_model, stream=False)
logger.info(f"response: {resp.to_json()}")
return resp