A test for space

app.py

@@ -1,42 +1,10 @@
 from transformers import pipeline
-import torch
+import streamlit as st
 
-device = "cuda:0" if torch.cuda.is_available() else "cpu"
+pipe = pipeline('sentiment-analysis')
+text = st.text_area('Enter some text here!')
 
-classifier = pipeline(
-    "audio-classification", model="MIT/ast-finetuned-speech-commands-v2", device=device
-)
-
-from transformers.pipelines.audio_utils import ffmpeg_microphone_live
-
-
-def launch_fn(
-    wake_word="marvin",
-    prob_threshold=0.5,
-    chunk_length_s=2.0,
-    stream_chunk_s=0.25,
-    debug=False,
-):
-    if wake_word not in classifier.model.config.label2id.keys():
-        raise ValueError(
-            f"Wake word {wake_word} not in set of valid class labels, pick a wake word in the set {classifier.model.config.label2id.keys()}."
-        )
-
-    sampling_rate = classifier.feature_extractor.sampling_rate
-
-    mic = ffmpeg_microphone_live(
-        sampling_rate=sampling_rate,
-        chunk_length_s=chunk_length_s,
-        stream_chunk_s=stream_chunk_s,
-    )
-
-    print("Listening for wake word...")
-    for prediction in classifier(mic):
-        prediction = prediction[0]
-        if debug:
-            print(prediction)
-        if prediction["label"] == wake_word:
-            if prediction["score"] > prob_threshold:
-                return True
-
-launch_fn(debug=True)
+if text:
+    out = pipe(text)
+    st.json(out)
+