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import os | |
import requests | |
from io import BytesIO | |
import base64 | |
import streamlit as st | |
import requests | |
AUTH_TOKEN = st. secrets["AUTH_TOKEN"] | |
headers = {"Authorization": f"Bearer {AUTH_TOKEN}"} | |
st.set_page_config(page_title="Image Similarity", page_icon="ππ") | |
CHAT_API = "https://abhilashvj-chat-api.hf.space/" | |
# IMAGE_SIMILARITY_DEMO = "http://127.0.0.1:8000/find-similar-image-pinecone/" | |
TMP_DIR = "./tmp" | |
os.makedirs(TMP_DIR, exist_ok=True) | |
st.title("Resume Reframing App") | |
# Uploading files using Streamlit | |
resume_file = st.file_uploader("Upload Resume", type=["txt", "pdf"]) | |
template_file = st.file_uploader("Upload Template (Optional)", type=["txt", "pdf"], accept_multiple_files=False) | |
job_description_file = st.file_uploader("Upload Job Description (Optional)", type=["txt", "pdf"], accept_multiple_files=False) | |
# Inputs for QueryData | |
text_input = st.text_input("Enter your text:", "Your text here") | |
top_k = st.number_input("Top K", min_value=1, max_value=100, value=5) | |
primer = st.text_input("Enter primer:", "Your primer here") | |
if st.button("Submit"): | |
if resume_file: | |
# The URL to your FastAPI endpoint | |
url = f"{CHAT_API}/upload/" | |
# Setting up the data for the `QueryData` model | |
data = { | |
"text": text_input, | |
"top_k": top_k, | |
"primer": primer, | |
} | |
files = {"resume": resume_file.getvalue()} | |
if template_file: | |
files["template"] = template_file.getvalue() | |
if job_description_file: | |
files["job_description"] = job_description_file.getvalue() | |
# Making the POST request | |
response = requests.post(url, data=data, files=files) | |
# Displaying the response | |
st.write(response.json()) | |
else: | |
st.warning("Please upload a resume!") |