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import openai
import numpy as np
import pandas as pd
from sentence_transformers import SentenceTransformer
import re
import gradio as gr
import json
# Calculate the cosine similarity
def cos_sim(vector1, vector2):
cosine_similarity = np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
return cosine_similarity
def sim_search(df, query, n=3, dot=False):
embedding = model.encode(query)
if dot:
df['similarities'] = df.embeddings.apply(lambda x: x@embedding)
print("using dot product")
else:
df['similarities'] = df.embeddings.apply(lambda x: cos_sim(x, embedding))
print("using cosine similarity")
res = df.sort_values('similarities', ascending=False).head(n)
return res
def create_prompt(context, question):
return f"""
Context information is below.
---------------------
{context}
---------------------
Given the context information and not prior knowledge, answer the query.
Query: {question}
Answer: \
"""
def answer_question(question, model="gpt-3.5-turbo",n=3):
r = sim_search(df, question,n=n)
context = "\n\n".join(r.chunks)
prompt = create_prompt(context, question)
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant answering questions in german. You answer only in german. If you do not know an answer you say it. You do not fabricate answers."},
{"role": "user", "content": prompt},
]
)
return response.choices[0].message.content
df = pd.read_csv("carotid_embeddings_sentence_transformers.csv")
df["embeddings"] = df.embeddings.apply(json.loads)
model = SentenceTransformer('thenlper/gte-base')
def gradio_answer(input):
return answer_question(input)
demo = gr.Interface(fn=gradio_answer, inputs=gr.Textbox(lines=1, placeholder="Frage hier...", label="Frage"), outputs=gr.Textbox(lines=4, placeholder="Antwort hier...", label="Antwort"), title="S3 Leitlinie Carotis Stenose", examples=["In welchen Intervallen ist eine Nachuntersuchung nach CAS angezeigt?", "Ist eine ambulante Therapie der Carotisstenose mittels CEA oder CAS möglich und sinnvoll?", "Was sollte man als Bradykardie-Therapie bei Nachdilatation eines Stents einsetzen?"])
demo.launch() |