Create app.py and requirements.txt

app.py

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+import streamlit as st
+import os
+import requests
+
+
+@st.cache_data
+def query(text):
+    API_URL = "https://api-inference.huggingface.co/models/j-hartmann/emotion-english-distilroberta-base"
+    headers = {"Authorization": "Bearer " + os.environ["HF_API_KEY"]}
+    payload = {"inputs": text}
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()
+
+
+# Initialize the `prompts` session state
+if "prompts" not in st.session_state:
+    st.session_state.prompts = []
+
+col1, col2 = st.columns(2)
+
+with col1:
+    if st.button("Add query"):
+        st.session_state.prompts.append("")
+    if st.button("Remove query"):
+        st.session_state.prompts.pop(0)
+
+
+def card(index: int):
+    def on_change():
+        # Update the `prompts[index]` session state with the value from the text input which is specified by the key, `f"prompt_{index}"`.
+        st.session_state.prompts[index] = st.session_state[f"prompt_{index}"]
+    st.text_input("Prompt:", key=f"prompt_{index}", value=st.session_state.prompts[index], on_change=on_change)
+
+    prompt = st.session_state.prompts[index]
+
+    # This `query` function is cached, so it will only be re-run if the input `prompt` changes.
+    result = query(prompt)
+
+    st.write(f'Prompt: "{prompt}"')
+    st.json(result)
+
+
+with col2:
+    for index in range(len(st.session_state.prompts)):
+        card(index)

requirements.txt

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+requests