# mcp/openai_utils.py | |
import openai | |
import os | |
openai.api_key = os.environ.get("OPENAI_API_KEY") | |
async def ai_summarize(text: str, prompt: str = None): | |
if not prompt: | |
prompt = "Summarize these biomedical search results, highlighting key findings and future research directions:" | |
client = openai.AsyncOpenAI(api_key=openai.api_key) | |
response = await client.chat.completions.create( | |
model="gpt-4o", | |
messages=[ | |
{"role": "system", "content": "You are an expert biomedical research assistant."}, | |
{"role": "user", "content": f"{prompt}\n{text}"} | |
], | |
max_tokens=350 | |
) | |
return response.choices[0].message.content | |
async def ai_qa(question: str, context: str = ""): | |
client = openai.AsyncOpenAI(api_key=openai.api_key) | |
response = await client.chat.completions.create( | |
model="gpt-4o", | |
messages=[ | |
{"role": "system", "content": "You are an advanced biomedical research agent."}, | |
{"role": "user", "content": f"Question: {question}\nContext: {context}"} | |
], | |
max_tokens=350 | |
) | |
return response.choices[0].message.content | |