README.md

metadata

title: Falcon
emoji: 🔥
colorFrom: indigo
colorTo: yellow
sdk: docker
pinned: false

Falcon: Fake News Analysis and Language Comprehension for Online Neutrality

Falcon is an advanced Gen AI-powered system designed to analyze, verify, and classify online claims to promote digital content neutrality. Leveraging state-of-the-art language models, it classifies user-submitted text, detects tone and intent, verifies facts using multiple data sources, and generates an informed verdict about claim credibility.

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Features

• Claim Classification: Classifies input text into categories like Factual Claim, Opinion, Irrelevant Talk, or Vague/Incomplete.
• Tone and Intent Detection: Analyzes the emotional tone and intent behind the claim (e.g., neutral, persuasive, humorous).
• Fact Verification: Verifies factual claims by searching reliable sources like Google (via Serper API) and Wikipedia.
• Verdict Generation: Produces a clear verdict on the claim’s truthfulness based on gathered evidence and reasoning.
• Fallback Language Model: Uses OpenAI’s GPT-4 as the primary LLM and automatically switches to Deepseek as a fallback model to ensure high availability and robustness.
• Simple Web Interface: Easy-to-use frontend using HTML, CSS, and JavaScript for seamless user interaction.
• FastAPI Backend: Fast, lightweight API server handling all processing with asynchronous endpoints.

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Tech Stack

• Backend: FastAPI (Python)
• Frontend: HTML, CSS, JavaScript
• Language Models: OpenAI GPT-4 (primary), Deepseek (fallback)
• APIs: Serper API (Google Search), Wikipedia API
• Prompt Engineering: Carefully crafted templates for accurate and reliable results
• Deployment: Docker containerization (optional)

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Project Structure

falcon/
├── backend/
│   ├── api/
│   │   ├── claims.py           # Claim classification logic
│   │   ├── fact_check.py       # Fact verification logic
│   │   ├── tone_intent.py      # Tone and intent detection logic
│   ├── langchain_tools.py      # LangChain prompt templates and LLM wrappers
│   ├── config.py               # API keys and config variables
│   └── main.py                 # FastAPI app entry point
├── frontend/
│   ├── index.html              # Main UI page
│   ├── assets/                 # CSS, JS, images
├── Dockerfile                  # Docker container definition (optional)
└── README.md                   # This file

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Setup Instructions

Prerequisites

• Python 3.9+
• FastAPI
• Uvicorn (ASGI server)
• OpenAI API key
• Serper API key
• Deepseek API key (for fallback)

Installation

1. Clone the repository:

git clone https://github.com/yourusername/falcon.git
cd falcon

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Configure API keys in backend/config.py:

OPENAI_API_KEY = "your_openai_api_key"
SERPER_API_KEY = "your_serper_api_key"
DEEPSEEK_API_KEY = "your_deepseek_api_key"

5. Run the FastAPI server:

uvicorn backend.main:app --port 8000

6. Open your browser and visit http://localhost:8000 to use the Falcon app.

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Usage

• Enter a claim or statement in the input form.
• The system classifies the claim, detects tone and intent, performs fact verification if applicable, and returns a detailed verdict with supporting evidence.
• The fallback model Deepseek is automatically used if GPT-4 is unavailable, ensuring consistent performance.