File size: 1,505 Bytes
f85caf4 709f5b7 f85caf4 709f5b7 f85caf4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 | from flask import Flask, render_template, request, jsonify
import tempfile
import openai
from dotenv import load_dotenv
from postprocessing import postprocessing
load_dotenv()
app = Flask(__name__)
SYSPROMPT = """Ti si doktor medicine, specijalista za pisanje epikrize. Potrebno je od prosleđenih podataka o pacijentu da se napiše jasna, profesionalna i lepo strukturisana epikriza."""
@app.route("/")
def index():
return render_template("index.html")
@app.route("/epikriza", methods=["POST"])
def epikriza():
data = request.get_json()
if "podaci" in data:
podaci = data["podaci"]
response = openai.chat.completions.create(
model="ft:gpt-3.5-turbo-1106:labsoftdev::8ov22QMu",
temperature=0.35,
max_tokens=4096,
messages=[
{"role": "system", "content": SYSPROMPT},
{"role": "user", "content": podaci},
],
)
epikriza = response.choices[0].message.content
return jsonify(epikriza=epikriza)
return jsonify(error="No data provided"), 400
@app.route("/postprocess", methods=["POST"])
def api_postprocess():
data = request.get_json()
if "epikriza" in data:
original_text = data["epikriza"]
processed_text = postprocessing(original_text)
return jsonify(processedEpikriza=processed_text)
return jsonify(error="No transcript provided"), 400
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860, debug=True)
|