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| import uvicorn | |
| from llm.llm import VirtualNurseLLM | |
| from fastapi import FastAPI | |
| from fastapi.middleware.cors import CORSMiddleware | |
| from fastapi.responses import HTMLResponse | |
| from pydantic import BaseModel | |
| import os | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| # model: typhoon-v1.5x-70b-instruct | |
| nurse_llm = VirtualNurseLLM( | |
| base_url="https://api.opentyphoon.ai/v1", | |
| model="typhoon-v1.5x-70b-instruct", | |
| api_key=os.getenv("TYPHOON_CHAT_KEY") | |
| ) | |
| # model: OpenThaiGPT | |
| # nurse_llm = VirtualNurseLLM( | |
| # base_url="https://api.aieat.or.th/v1", | |
| # model=".", | |
| # api_key="dummy" | |
| # ) | |
| app = FastAPI() | |
| app.add_middleware( | |
| CORSMiddleware, | |
| allow_origins=["*"], | |
| allow_credentials=True, | |
| allow_methods=["*"], | |
| allow_headers=["*"], | |
| ) | |
| class UserInput(BaseModel): | |
| user_input: str | |
| model_name: str = "typhoon-v1.5x-70b-instruct" | |
| class NurseResponse(BaseModel): | |
| nurse_response: str | |
| class EHRData(BaseModel): | |
| ehr_data: dict | |
| current_context: str | |
| current_prompt: str | |
| current_prompt_ehr: str | |
| current_patient_response: str | |
| current_question: str | |
| class ChatHistory(BaseModel): | |
| chat_history: list | |
| def read_index(): | |
| return """ | |
| <!DOCTYPE html> | |
| <html> | |
| <head> | |
| <title>MALI_NURSE API/title> | |
| </head> | |
| <body> | |
| <h1>Welcome to MALI_NURSE API</h1> | |
| <p>This is the index page. Use the link below to access the API docs:</p> | |
| <a href="/docs">Go to Swagger Docs UI</a> | |
| </body> | |
| </html> | |
| """ | |
| def get_chat_history(): | |
| return ChatHistory(chat_history = nurse_llm.chat_history) | |
| def get_ehr_data(): | |
| return EHRData( | |
| ehr_data=nurse_llm.ehr_data, | |
| current_context=nurse_llm.current_context, | |
| current_prompt=nurse_llm.current_prompt, | |
| current_prompt_ehr=nurse_llm.current_prompt_ehr, | |
| current_patient_response=nurse_llm.current_patient_response, | |
| current_question=nurse_llm.current_question | |
| ) | |
| def toggle_debug(): | |
| nurse_llm.debug = not nurse_llm.debug | |
| return {"debug_mode": "on" if nurse_llm.debug else "off"} | |
| def data_reset(): | |
| nurse_llm.reset() | |
| print("Chat history and EHR data have been reset.") | |
| def nurse_response(user_input: UserInput): | |
| """ | |
| Models: "typhoon-v1.5x-70b-instruct (default)", "openthaigpt" | |
| """ | |
| if user_input.model_name == "typhoon-v1.5x-70b-instruct": | |
| nurse_llm.model = "typhoon-v1.5x-70b-instruct" | |
| elif user_input.model_name == "openthaigpt": | |
| nurse_llm.model = "openthaigpt" | |
| else: | |
| return {"error": "Invalid model name"} | |
| response = nurse_llm.invoke(user_input.user_input) | |
| return NurseResponse(nurse_response = response) | |
| if __name__ == "__main__": | |
| uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True) |