Update app.py

app.py

@@ -7,7 +7,9 @@ import torchvision
 import nltk
 import torch
 import pandas as pd
+import streamlit as st
 import requests
+import threading
 import zipfile
 import tempfile
 from PyPDF2 import PdfReader
@@ -34,6 +36,14 @@ from safetensors.torch import safe_open
 nltk.download('punkt_tab')
 
 app = FastAPI()
+
+with open("style.css") as f:
+    st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
+# Streamlit interface
+def start_streamlit():
+    st.title("My Hugging Face App")
+    st.text_input("Ask a question:")
+    
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -652,3 +662,66 @@ if not init_success:
 if __name__ == "__main__":
     import uvicorn
     uvicorn.run(app, host="0.0.0.0", port=7860)
+
+# Chat API
+st.header("Chat API")
+chat_query = st.text_input("Enter your chat query:")
+language_code = st.selectbox("Select language", ["English", "Arabic"])
+
+if st.button("Submit Chat Query"):
+    response = requests.post(f"{BASE_URL}/api/chat", json={
+        "query": chat_query,
+        "language_code": 0 if language_code == "Arabic" else 1
+    })
+    if response.status_code == 200:
+        st.success("Response: " + response.json()['response'])
+    else:
+        st.error(f"Error: {response.status_code} - {response.text}")
+
+# Resources API
+st.header("Resources API")
+conditions = st.text_input("Enter medical conditions:")
+daily_symptoms = st.text_area("Enter daily symptoms:")
+count = st.number_input("Number of resources", min_value=1, max_value=10, value=5)
+
+if st.button("Submit Resources Query"):
+    response = requests.post(f"{BASE_URL}/api/resources", json={
+        "conditions": conditions,
+        "daily_symptoms": daily_symptoms,
+        "count": count
+    })
+    if response.status_code == 200:
+        resources = response.json()
+        st.write("Relevant Resources:")
+        for resource in resources:
+            st.markdown(f"- **{resource['title']}**: [Link]({resource['url']})")
+    else:
+        st.error(f"Error: {response.status_code} - {response.text}")
+
+# Recipes API
+st.header("Recipes API")
+recipe_conditions = st.text_input("Enter conditions for recipes:")
+recipe_symptoms = st.text_area("Enter symptoms for recipes:")
+recipe_count = st.number_input("Number of recipes", min_value=1, max_value=10, value=5)
+
+if st.button("Submit Recipes Query"):
+    response = requests.post(f"{BASE_URL}/api/recipes", json={
+        "conditions": recipe_conditions,
+        "daily_symptoms": recipe_symptoms,
+        "count": recipe_count
+    })
+    if response.status_code == 200:
+        recipes = response.json()['recipes']
+        st.write("Relevant Recipes:")
+        for recipe in recipes:
+            st.markdown(f"- **{recipe['title']}**: [Link]({recipe['url']})")
+    else:
+        st.error(f"Error: {response.status_code} - {response.text}")
+if __name__ == "__main__":
+    # Start FastAPI in a background thread
+    fastapi_thread = threading.Thread(target=run_fastapi)
+    fastapi_thread.start()
+    
+    # Start Streamlit
+    start_streamlit()
+