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| import os | |
| import requests | |
| from io import BytesIO | |
| import base64 | |
| import streamlit as st | |
| AUTH_TOKEN = st. secrets["AUTH_TOKEN"] | |
| headers = {"Authorization": f"Bearer {AUTH_TOKEN}"} | |
| st.set_page_config(page_title="Image Similarity", page_icon="🎆🎇") | |
| 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("Document Uploader and Chatbot Trainer") | |
| st.header("Upload Documents") | |
| # Upload evergreen document | |
| evergreen_file = st.file_uploader("Choose an Evergreen Document", type=['txt', 'pdf', 'doc', 'docx']) | |
| if evergreen_file: | |
| files = {'file': evergreen_file.getvalue()} | |
| response = requests.post(f'{CHAT_API}upload/evergreen/', files=files, headers=headers) | |
| if response.json().get("success"): | |
| st.success("Evergreen document uploaded successfully!") | |
| else: | |
| st.error("Failed to upload evergreen document!") | |
| # Upload dynamic document | |
| dynamic_file = st.file_uploader("Choose a Dynamic Document", type=['txt', 'pdf', 'doc', 'docx']) | |
| if dynamic_file: | |
| files = {'file': dynamic_file.getvalue()} | |
| response = requests.post(f'{CHAT_API}upload/dynamic/', files=files, headers=headers) | |
| if response.json().get("success"): | |
| st.success("Dynamic document uploaded successfully!") | |
| else: | |
| st.error("Failed to upload dynamic document!") | |
| # Train bot button | |
| # if st.button("Train Bot"): | |
| # response = requests.post('http://your_fastapi_endpoint/train/') | |
| # bot_url = response.json().get("bot_url") | |
| # if bot_url: | |
| # st.success(f"Bot trained successfully! Access the bot at {bot_url}") | |
| # else: | |
| # st.error("Failed to train the bot!") | |
| # Chat with bot | |
| st.header("Chat with Bot") | |
| user_input = st.text_input("Ask your question:") | |
| # Assuming you have an endpoint to send user questions and get responses | |
| data = { | |
| "text": user_input, | |
| "top_k": 5, | |
| } | |
| response = requests.post(f'{CHAT_API}/query/', json=data) | |
| bot_response = response.json().get("answer") | |
| st.text_area("Bot's Response:", value=bot_response) |