Metadata-Version: 2.4
Name: stocklens-sdk
Version: 1.0.1
Summary: AI-Powered Stock Sentiment and Trend Analysis SDK
Home-page: https://github.com/karthikrajesh10/stocklens_sdk
Author: Karthik R S
Author-email: karthikrajesh9010@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: textblob
Requires-Dist: requests
Requires-Dist: flask
Requires-Dist: flask-cors
Requires-Dist: gtts
Requires-Dist: pandas
Requires-Dist: yfinance
Requires-Dist: scikit-learn
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
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Dynamic: summary


# 📊 StockLens SDK

StockLens SDK is an AI-powered Python toolkit designed for stock sentiment analysis, news summarization, and trend prediction.  
It enables traders, analysts, and developers to extract, analyze, and interpret financial insights from real-time market data using natural language processing (NLP) and machine learning.

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## 🚀 Features

- 📰 Fetch and analyze stock market news sentiment via NLP (TextBlob)  
- 🧠 Generate summaries using transformer-based models (Hugging Face BART)  
- 🔊 Convert summaries to speech with gTTS for auditory insights  
- 📈 Compute technical indicators like RSI, MACD, and Bollinger Bands  
- ⚙️ Predict short-term stock trends using combined sentiment and technical signals  

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## 🧩 Installation


pip install stocklens-sdk


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## 💻 Usage Example


from stocklens_sdk import analyze_sentiment, generate_summary, generate_audio

# Example text
text = "Apple reported strong quarterly earnings with increased iPhone sales."

# Analyze and summarize
summary = generate_summary([{"headline": "Apple Q2 Results", "summary": text}])
audio = generate_audio(summary, "AAPL")

print("Summary:", summary)
print("Audio File:", audio)


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## 🧠 Modules Overview

| Module | Description |
|---------|--------------|
| news_fetcher.py | Fetches latest stock news via n8n webhook |
| sentiment_utils.py | Performs sentiment scoring using TextBlob |
| summarizer.py | Generates AI-powered natural summaries |
| tts_generator.py | Converts summaries to speech (MP3 format) |
| indicators.py | Computes RSI, MACD, and Bollinger Bands for trend insight |

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## 🏗 Architecture Overview


Frontend or Marketfeed API Call
          ↓
     Flask Backend
          ↓
     StockLens SDK
          ├── Fetch News
          ├── Analyze Sentiment
          ├── Summarize Text
          ├── Generate Audio
          ↓
  Returns JSON + Audio Summary


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## 🧾 Acknowledgment

This project, StockLens – AI-Powered Stock Sentiment and Trend Analyzer, was developed with the guidance and support of the Centre of Excellence, Artificial Intelligence and Robotics (AIR).  


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## 🧑‍💻 Developer Notes

The SDK can be integrated with web platforms like Marketfeed as a modular AI plugin.  
It can process financial data, summarize insights, and output both text and speech results.  
For enterprise-scale usage, batch or async processing can be enabled.

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## 📜 License

MIT License © 2025 — Developed by Karthik R S

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## 🌐 Project Links

- PyPI: [https://pypi.org/project/stocklens-sdk/](https://pypi.org/project/stocklens-sdk/)
- GitHub: [https://github.com/karthikrajesh10/stocklens_sdk](https://github.com/karthikrajesh10/stocklens_sdk)
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