- Perspective-AI
Perspective-AI is designed to combat the echo chambers created by personalized content algorithms. It actively curates counterarguments and alternative narratives from credible sources alongside the content you usually see. Whether it’s a news article, blog post, or social media update, Perspective-AI analyzes the existing narrative and presents a balanced, in-depth counter-perspective. This approach not only challenges your current viewpoints but also helps broaden your understanding of complex issues—all in real time.
Imagine having a smart, opinionated friend who isn’t afraid to challenge your beliefs with well-articulated counterpoints—that’s Perspective-AI in a nutshell!
- Next.js UI: A sleek, responsive interface that displays content alongside counter perspectives.
- FastAPI Server: A high-performance API server handling requests, content analysis, and response delivery.
- Content Analyzer: Processes incoming articles or posts to identify the dominant narrative.
- Counter-Narrative Engine: Uses advanced AI and NLP techniques to generate alternative perspectives and reasoned analyses.
- LLM Service: Leverages large language models (e.g., OpenAI, custom models) to generate detailed counterarguments.
- LangChain & Langgraph: Frameworks to manage chains of reasoning and workflow orchestration for coherent narrative generation.
- VectorDB: A vector database for storing semantic embeddings to efficiently retrieve and compare content.
- framework: Next.js
- styling: TailwindCSS
- framework: FastAPI
- language: Python
- AI & NLP: LangChain, Langgraph, Prompt Engineering
- database: Any VectorDB
- LLM: OpenAI, Other NLP Models
- processing:Context-Aware
- What It Does: Instantly displays counterarguments to the main narrative.
- How It Works: Analyzes content to identify biases and generates alternative viewpoints.
- What It Does: Breaks down narratives into logical, connected arguments.
- How It Works: Uses chain-of-thought prompting and connected fact analysis.
- What It Does: Provides real-time updates and the latest facts along with counter-narratives.
- How It Works: Continuously pulls data from trusted sources and updates the insights.
- What It Does: Integrates effortlessly with existing news, blogs, and social media platforms.
- How It Works: Uses custom integration modules and API endpoints.
- What It Does: Generates insights instantly as you browse.
- How It Works: Employs real-time processing powered by advanced AI.
sequenceDiagram
%% Define Participants
participant U as User
participant F as Frontend
participant B as Backend
participant AI as AI Service
participant D as Data Storage
%% Interaction Flow
U->>F: Request/View Content
F->>B: Forward Request
B->>AI: Analyze Content & Generate Counter Perspective
AI->>B: Return Counter Analysis
B->>F: Deliver Results
F->>U: Display Balanced Insights
%% Notes for Clarity
Note over AI: AI generates counter analysis
Note over B: Backend processes logic
Note over F: Frontend updates UI
Setup environment variables:*
- add .env file in
/frontenddirectory. - add following environment variable in your .env file.
NEXT_PUBLIC_API_URL = http://localhost:8000
cd frontend
npm install
npm run devGet HuggingFace Access Token:
- Go to HuggingFace website and create new access token.
- copy that token
Install uv:
- install uv from https://docs.astral.sh/uv/
Setup environment variables:
- add .env file in
/backenddirectory. - add following environment variable in your .env file.
GROQ_API_KEY= <groq_api_key>
PINECONE_API_KEY = <your_pinecone_API_KEY>
PORT = 8000
SEARCH_KEY = <your_Google_custom_search_engine_API_key>
Run backend:
cd backend
uv sync # Creating virtual environment at: .venv
uv run main.py #Runs the backend servergraph TB
%% Define Subgraphs with Colors and Text Styles
subgraph Client Side
style UI fill:#FFDDC1,stroke:#FF6600,stroke-width:2px,color:#000,font-weight:bold
UI[Next.js UI]
end
subgraph Server Side
style API fill:#D1E8FF,stroke:#005BBB,stroke-width:2px,color:#000,font-weight:bold
style Analyzer fill:#D1E8FF,stroke:#005BBB,stroke-width:2px,color:#000,font-weight:bold
style CNEngine fill:#D1E8FF,stroke:#005BBB,stroke-width:2px,color:#000,font-weight:bold
style Context fill:#D1E8FF,stroke:#005BBB,stroke-width:2px,color:#000,font-weight:bold
API[FastAPI Server]
Analyzer[Content Analyzer]
CNEngine[Counter-Narrative Engine]
Context[Context Manager]
end
subgraph AI & NLP Layer
style LLM fill:#E6FFCC,stroke:#66BB66,stroke-width:2px,color:#000,font-weight:bold
style LangChain fill:#E6FFCC,stroke:#66BB66,stroke-width:2px,color:#000,font-weight:bold
style Langgraph fill:#E6FFCC,stroke:#66BB66,stroke-width:2px,color:#000,font-weight:bold
LLM[LLM Service]
LangChain[LangChain]
Langgraph[Langgraph]
end
subgraph Data Storage
style VectorDB fill:#FFDDEE,stroke:#CC3366,stroke-width:2px,color:#000,font-weight:bold
VectorDB[(Vector Database)]
end
%% Define Connections with Labels
style Browser fill:#FFFF99,stroke:#FFAA00,stroke-width:2px,color:#000,font-weight:bold
Browser -->|User Interaction| UI
UI -->|Requests| API
API -->|Process| Analyzer
Analyzer -->|Analysis| CNEngine
CNEngine -->|Generates| LLM
LLM -->|Uses| LangChain
LLM -->|Uses| Langgraph
API -->|Manages| Context
CNEngine -->|Stores| VectorDB
API -->|Responses| UI
- Less Bias in Narratives: Break out of echo chambers and question prevailing narratives.
- Wider Perspectives: Broaden your understanding of complex issues.
- Better Discourse: Enable balanced, informed discussions.
- Sharper Analysis: Improve critical thinking by comparing connected facts and counter-facts.
- Frontend Development: Experience with Next.js and modern UI frameworks.
- Backend Development: Proficiency in Python and FastAPI.
- AI & NLP: Familiarity with LangChain, Langgraph, and prompt engineering techniques.
- Database Management: Knowledge of vector databases system.