Update app.py

app.py

@@ -3,6 +3,7 @@ import requests
 from io import BytesIO
 import base64
 import streamlit as st
+import requests
 
 AUTH_TOKEN = st. secrets["AUTH_TOKEN"]
 
@@ -14,47 +15,44 @@ 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!")
+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.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)
+        st.warning("Please upload a resume!")