Update main.py

main.py

@@ -1,2 +1,45 @@
-from fastapi import FastAPI, HTTPException, Query
-import pandas as pd
+#from fastapi import FastAPI, HTTPException, Query
+#import pandas as pd
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+app = FastAPI()
+
+# Load the pre-trained model and tokenizer
+model_name = "gyesibiney/covid-tweet-sentimental-Analysis-roberta"
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Create a sentiment analysis pipeline
+sentiment = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+
+# Define a request body model
+class SentimentRequest(BaseModel):
+    text: str
+
+# Define a response model
+class SentimentResponse(BaseModel):
+    sentiment: str
+    score: float
+
+# Create an endpoint for sentiment analysis
+@app.post("/sentiment/")
+async def analyze_sentiment(request: SentimentRequest):
+    input_text = request.text
+    result = sentiment(input_text)
+    sentiment_label = result[0]["label"]
+    sentiment_score = result[0]["score"]
+
+    if sentiment_label == "LABEL_1":
+        sentiment_label = "positive"
+    elif sentiment_label == "LABEL_0":
+        sentiment_label = "neutral"
+    else:
+        sentiment_label = "negative"
+
+    return SentimentResponse(sentiment=sentiment_label.capitalize(), score=sentiment_score)
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)