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Dockerfile

@@ -1,20 +1,27 @@
-FROM python:3.13.5-slim
-
-WORKDIR /app
-
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    git \
-    && rm -rf /var/lib/apt/lists/*
-
-COPY requirements.txt ./
-COPY src/ ./src/
-
-RUN pip3 install -r requirements.txt
-
-EXPOSE 8501
-
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
-
-ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Set environment variables to fix permissions
+ENV HOME=/tmp
+ENV STREAMLIT_CONFIG_DIR=/tmp/.streamlit
+ENV TRANSFORMERS_CACHE=/tmp/.cache
+ENV HF_HOME=/tmp/.cache/huggingface
+
+# Copy requirements and install dependencies
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application files
+COPY . .
+
+# Create necessary directories with proper permissions
+RUN mkdir -p /tmp/.streamlit && \
+    mkdir -p /tmp/.cache && \
+    chmod -R 777 /tmp
+
+# Expose port 7860 (Hugging Face Spaces default)
+EXPOSE 7860
+
+# Run the Streamlit app
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0", "--server.headless=true"]

Procfile

@@ -0,0 +1 @@
+web: streamlit run app.py --server.port $PORT --server.address 0.0.0.0 --server.headless true

README.md

@@ -1,20 +1,70 @@
----
-title: Sentext Analytics
-emoji: 🚀
-colorFrom: red
-colorTo: red
-sdk: docker
-app_port: 8501
-tags:
-- streamlit
-pinned: false
-short_description: Streamlit template space
-license: mit
----
-
-# Welcome to Streamlit!
-
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
-
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+# Sentiment Analysis App
+
+![Streamlit](https://img.shields.io/badge/Streamlit-%23FF4B4B?logo=streamlit&logoColor=white)
+![Python](https://img.shields.io/badge/Python-3.8%2B-blue)
+![License](https://img.shields.io/badge/License-MIT-green)
+
+> A clean, production-minded Streamlit app that reads text and returns generic & finance-aware sentiment labels and confidence scores.
+
+---
+
+## Why this project
+
+Market language is different: the same phrase can mean different things in finance compared to casual chat. This app is designed to:
+- prioritize clarity (human-readable outputs),
+- be resilient in deployment (tips to avoid first-run timeouts),
+- and be easy to extend (swap the model, add dashboards).
+
+---
+
+## Quick visual 
+![Demo](assets/demo.gif)  
+
+---
+
+## Project structure
+
+
+- **app.py** - main Streamlit application script  
+- **requirements.txt** - Python dependencies  
+- **setup.sh** - shell script for environment setup  
+- **runtime.txt** - runtime configuration (for deployment, e.g. Heroku)  
+- **.devcontainer/** - config for VSCode / dev container setup  
+- **Data/** - datasets, corpora, lexicons etc.  
+- **finance/** - finance-specific modules, models, tools  
+- **notebooks/**- Jupyter notebooks used during experimentation / prototyping  
+
+---
+
+## Installation & Setup
+
+Below is a typical setup for development and running locally.
+
+1. **Clone the repository**
+
+   ```bash
+   git clone https://github.com/Ani-404/Sentiment-Analysis-App.git
+   cd Sentiment-Analysis-App
+   ```
+2. **(Optional) Create & activate a virtual environment**
+
+   ```bash
+   python3 -m venv venv
+   source venv/bin/activate
+   ```
+   
+3. **Install dependencies**
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+4. **Run the application locally**
+   ```bash
+   streamlit run app.py
+   ```
+---
+
+
+   
+
+

app.py

@@ -0,0 +1,108 @@
+import os
+import tempfile
+
+# Fix Streamlit permissions issue on HF Spaces
+os.environ["STREAMLIT_CONFIG_DIR"] = tempfile.mkdtemp()
+
+import streamlit as st
+from transformers import pipeline
+import pandas as pd
+import numpy as np
+import plotly.express as px
+import yfinance as yf
+import warnings
+warnings.filterwarnings('ignore')
+
+# Configure page
+st.set_page_config(
+    page_title="SentText - Advanced Analysis",
+    page_icon="📈",
+    layout="wide",
+    initial_sidebar_state="expanded"
+)
+
+# Initialize models
+@st.cache_resource
+def load_models():
+    models = {}
+    try:
+        # Remove use_auth_token, rely on environment login
+        models['emotion'] = pipeline(
+            "text-classification",
+            model="Ani-404/emotion-model",
+            tokenizer="Ani-404/emotion-model"
+        )
+        models['financial'] = pipeline(
+            "text-classification", 
+            model="Ani-404/finbert-model",
+            tokenizer="Ani-404/finbert-model"
+        )
+    except Exception:
+        models = {}
+    return models
+
+# Prediction functions
+
+def predict_emotions_real(text, model):
+    results = model(text, return_all_scores=True)
+    scores_list = results[0]
+    top = max(scores_list, key=lambda x: x['score'])
+    return top['label'].lower(), top['score']
+
+
+def analyze_financial_real(text, model):
+    results = model(text)
+    res = results[0]
+    label = res['label'].lower()
+    confidence = res['score']
+    if 'positive' in label:
+        score = confidence
+        signal = 'BUY' if confidence>0.7 else 'HOLD'
+    elif 'negative' in label:
+        score = -confidence
+        signal = 'SELL' if confidence>0.7 else 'HOLD'
+    else:
+        score = 0; signal='HOLD'
+    return score, confidence, signal
+
+# Main UI
+
+def main():
+    st.title("SentText Analytics")
+    models = load_models()
+    tabs = st.tabs(["🎭 Emotion Analysis", "📈 Financial Analysis"])
+
+    # Emotion
+    with tabs[0]:
+        text = st.text_area("Enter text:")
+        if st.button("Analyze Emotion") and text:
+            if 'emotion' in models:
+                label, conf = predict_emotions_real(text, models['emotion'])
+                st.write(f"**Emotion**: {label} | **Confidence**: {conf:.1%}")
+            else:
+                st.error("Emotion model not loaded.")
+
+    # Financial
+    with tabs[1]:
+        col1, col2 = st.columns([1,2])
+        with col1:
+            ticker = st.text_input("Ticker:", value='AAPL')
+            if st.button("Fetch Chart"):
+                df = yf.Ticker(ticker).history(period='5d')
+                if not df.empty:
+                    fig = px.line(df, y='Close', title=f"{ticker} Closing Prices (5d)")
+                    st.plotly_chart(fig)
+                else:
+                    st.error("No data for ticker.")
+        with col2:
+            fin_text = st.text_area("Enter financial text:")
+            if st.button("Analyze Financial Sentiment") and fin_text:
+                if 'financial' in models:
+                    score, conf, signal = analyze_financial_real(fin_text, models['financial'])
+                    st.write(f"**Sentiment Score**: {score:.2f} | **Confidence**: {conf:.1%}")
+                    st.write(f"**Signal**: {signal}")
+                else:
+                    st.error("Financial model not loaded.")
+
+if __name__ == '__main__':
+    main()

runtime.txt

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+python-3.11.9

setup.sh

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+mkdir -p ~/.streamlit/
+echo "\
+[server]\n\
+headless = true\n\
+port = $PORT\n\
+enableCORS = false\n\
+\n\
+" > ~/.streamlit/config.toml