App.py andd requirements file addition

app.py

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+from pymongo import MongoClient
+
+def get_mongo_client():
+    client = MongoClient("mongodb+srv://GMP-21-03:[email protected]/?retryWrites=true&w=majority&appName=Cluster1")
+    db = client["sentiment_db"]
+    return db["tweets"]
+
+#### *3. Load and Process Dataset*
+import pandas as pd
+
+# Load dataset
+df = pd.read_csv("C:/Users/ANOOP G ZACHARIA/Downloads/archive/sentiment140.csv")
+
+#### *4. Sentiment Analysis using BERT-ROBERTA*
+
+from transformers import pipeline
+
+# Load Hugging Face model
+sentiment_pipeline = pipeline("sentiment-analysis", model="cardiffnlp/twitter-roberta-base-sentiment")
+
+# Function to analyze sentiment
+def analyze_sentiment(text):
+    return sentiment_pipeline(text)[0]['label']
+
+df["sentiment"] = df["text"].apply(analyze_sentiment)
+
+# Save results to MongoDB
+collection = get_mongo_client()
+collection.insert_many(df.to_dict("records"))
+
+#### *5. Build Streamlit Dashboard*
+import streamlit as st
+
+st.title("Sentiment Analysis Dashboard")
+
+if st.button("Show Data"):
+    st.write(df)
+
+if st.button("Show MongoDB Data"):
+    data = list(collection.find({}, {"_id": 0}))
+    st.write(pd.DataFrame(data))

requirements.txt

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+pandas==1.5.3
+pandasai==1.4.1
+pymongo==4.3.3
+transformers==4.37.0
+torch==2.1.0
+streamlit==1.30.0
+sentencepiece==0.1.99
+scipy==1.10.1
+huggingface_hub==0.20.3
+pydantic==1.10.13
+typing-extensions>=4.0