qwendr / app.py
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Update app.py
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from fastapi import FastAPI, Query, Request
from fastapi.responses import HTMLResponse
from fastapi.templating import Jinja2Templates
from fastapi.staticfiles import StaticFiles
from fastapi.middleware.cors import CORSMiddleware
from utils.vector_search import get_similar_symptoms
from utils.sql_queries import get_diseases_by_symptoms, get_related_symptoms
import sqlite3
import os
import httpx
import json
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
# Get Groq API key from environment variables
GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
app = FastAPI()
# Add CORS middleware
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # Allow all origins
allow_credentials=True,
allow_methods=["*"], # Allow all methods
allow_headers=["*"], # Allow all headers
)
templates = Jinja2Templates(directory="templates")
@app.get("/", response_class=HTMLResponse)
def index(request: Request):
return templates.TemplateResponse("index.html", {"request": request})
# Helper function to check if a symptom exists in the database
def is_valid_symptom(symptom):
conn = sqlite3.connect("disease.db")
cur = conn.cursor()
cur.execute("SELECT COUNT(*) FROM symptom WHERE name = ?", (symptom,))
count = cur.fetchone()[0]
conn.close()
return count > 0
@app.get("/search")
def search(symptom: str, selected: list[str] = Query([])):
# Get similar symptoms from vector search
similar = get_similar_symptoms(symptom)
# Check if the exact symptom exists in our database
if is_valid_symptom(symptom):
# Use the exact symptom if it exists
search_symptoms = [symptom] + selected
else:
# Otherwise, try to use the first similar symptom that exists in our database
valid_symptom_found = False
for sim in similar:
if is_valid_symptom(sim):
search_symptoms = [sim] + selected
valid_symptom_found = True
break
# If no valid symptom found, just use all similar symptoms
if not valid_symptom_found:
search_symptoms = similar + selected
# Get diseases that have ALL the selected search symptoms
diseases = get_diseases_by_symptoms(search_symptoms)
# Get related symptoms from the matching diseases, excluding already selected symptoms
suggestions = get_related_symptoms(diseases, exclude=search_symptoms)
return {
"matching_diseases": diseases,
"related_symptoms": suggestions,
"semantic_matches": similar
}
@app.get("/disease-info")
async def disease_info(name: str):
"""
Get detailed information about a disease using Groq's LLM API
"""
if not GROQ_API_KEY:
return {"info": "<p>Error: Groq API key not found in environment variables.</p>"}
try:
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.post(
"https://api.groq.com/openai/v1/chat/completions",
headers={
"Authorization": f"Bearer {GROQ_API_KEY}",
"Content-Type": "application/json"
},
json={
"model": "meta-llama/llama-4-scout-17b-16e-instruct",
"messages": [
{
"role": "system",
"content": "You are a helpful medical assistant. Provide accurate, well-structured information about diseases. Format your response in HTML paragraphs with appropriate headings using <h4> tags. Include symptoms, causes, treatments, and prevention when possible. Keep responses concise but informative."
},
{
"role": "user",
"content": f"Provide detailed information about {name}, including symptoms, causes, diagnosis, treatments, and prevention methods when applicable."
}
],
"max_tokens": 1500,
"temperature": 0.5
}
)
if response.status_code == 200:
data = response.json()
content = data["choices"][0]["message"]["content"]
return {"info": content}
else:
return {"info": f"<p>Error: Failed to fetch information. Status code: {response.status_code}</p>"}
except Exception as e:
return {"info": f"<p>Error: {str(e)}</p>"}