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README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.49.1
+sdk_version: 6.0.0
 app_file: run.py
 pinned: false
 hf_oauth: true

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: sentiment_analysis\n", "### This sentiment analaysis demo takes in input text and returns its classification for either positive, negative or neutral using Gradio's Label output.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio nltk"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import nltk  # type: ignore\n", "from nltk.sentiment.vader import SentimentIntensityAnalyzer  # type: ignore\n", "\n", "nltk.download(\"vader_lexicon\")\n", "sid = SentimentIntensityAnalyzer()\n", "\n", "def sentiment_analysis(text):\n", "    scores = sid.polarity_scores(text)\n", "    del scores[\"compound\"]\n", "    return scores\n", "\n", "demo = gr.Interface(\n", "    fn=sentiment_analysis,\n", "    inputs=gr.Textbox(placeholder=\"Enter a positive or negative sentence here...\"),\n", "    outputs=\"label\",\n", "    examples=[[\"This is wonderful!\"]])\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: sentiment_analysis\n", "### This sentiment analaysis demo takes in input text and returns its classification for either positive, negative or neutral using Gradio's Label output.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio nltk"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import nltk  # type: ignore\n", "from nltk.sentiment.vader import SentimentIntensityAnalyzer  # type: ignore\n", "\n", "nltk.download(\"vader_lexicon\")\n", "sid = SentimentIntensityAnalyzer()\n", "\n", "def sentiment_analysis(text):\n", "    scores = sid.polarity_scores(text)\n", "    del scores[\"compound\"]\n", "    return scores\n", "\n", "demo = gr.Interface(\n", "    fn=sentiment_analysis,\n", "    inputs=gr.Textbox(placeholder=\"Enter a positive or negative sentence here...\"),\n", "    outputs=\"label\",\n", "    examples=[[\"This is wonderful!\"]],\n", "    api_name=\"predict\")\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -14,6 +14,7 @@ demo = gr.Interface(
     fn=sentiment_analysis,
     inputs=gr.Textbox(placeholder="Enter a positive or negative sentence here..."),
     outputs="label",
-    examples=[["This is wonderful!"]])
+    examples=[["This is wonderful!"]],
+    api_name="predict")
 
 demo.launch()