Duplicate from templates/fastapi_with_streamlit

Co-authored-by: Omar Sanseviero <osanseviero@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+title: Fastapi_with_streamlit
+emoji: 🌍
+colorFrom: red
+colorTo: green
+sdk: streamlit
+sdk_version: 1.2.0
+app_file: app.py
+pinned: false
+license: mit
+duplicated_from: templates/fastapi_with_streamlit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

app.py

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+import streamlit as st
+
+import json
+import os
+import requests
+import socket
+
+def start_server():   
+    os.system("uvicorn inference_server:app --port 8080 --host 0.0.0.0 --workers 2")
+    st.session_state['server_started'] = True
+    
+def is_port_in_use(port):
+    import socket
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+        return s.connect_ex(('0.0.0.0', port)) == 0
+
+def inference(input_text):
+  req = "http://0.0.0.0:8080?input_text=" + input_text
+  res = requests.get(req)
+  st.markdown(f'## Output')
+  st.write(json.loads(res.text))
+ 
+if 'server_started' not in st.session_state:
+    st.session_state['server_started'] = False
+
+if not st.session_state['server_started']:
+  start_server()              
+
+st.title('FastAPI Demo')
+input_text = st.text_input(
+    label="Write something",
+    value="text"
+)
+inference(input_text)

inference_server.py

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+import uvicorn
+from fastapi import FastAPI
+
+app = FastAPI()
+
+# Here you can do things such as load your models
+
+@app.get("/")
+def read_root(input_text):
+    return {f"Hello {input_text}!"}

requirements.txt

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+fastapi
+uvicorn