Flight Insight AI is a chatbot system designed to provide intelligent insights and analysis of airline reviews. Using natural language processing and machine learning techniques, Flight Insight AI offers users a seamless interface to query and understand airline experiences based on real customer reviews. Try it Here!
- Frontend: A React application providing a responsive and interactive user interface.
- Backend: A FastAPI server that handles real-time communication and orchestrates the AI components.
- Vector Database: Pinecone is used for efficient similarity search of review embeddings.
- Language Model: Google's Gemini Flash for natural language understanding and generation.
- Data Processing: Several scripts to get and clean the data.
- User Input: The user types the query into the Frontend interface.
- Query Transmission: The Frontend sends this query to the FastAPI Backend via a WebSocket connection.
- Airline Extraction:
- The Gemini Flash model for airline extraction identifies the airline in question.
- Query Embedding:
- The processed query is sent to the Query Embedder. The Query Embedder converts the text query into a vector embedding, similar to how the reviews were embedded.
- Relevant Review Retrieval:
- The Retriever takes this query embedding and searches the Pinecone Vector DB for similar review embeddings. It retrieves the TOP_K relevant reviews similar to the user query.
- Prompt Generation:
-
The Prompt Generator receives:
- The original query
- The relevant reviews from the Retriever
-
It combines this information into a structured prompt for the language model.
- Response Generation:
- The generated prompt is sent to the Gemini Flash model for response generation. This model processes the prompt and generates a comprehensive response based on the relevant reviews.
- Response Delivery:
- The generated response is sent back to the Frontend via the WebSocket connection. The Frontend streams this response to the user.
- Output Streaming: Utilizes WebSocket for streaming AI responses, providing a dynamic and engaging user experience.
- Intelligent Review Analysis: Leverages a RAG (Retrieval-Augmented Generation) system to provide insights based on relevant customer reviews.
- Dynamic Airline Information: Automatically detects airline mentioned and responds based on that.
- Vector Search: Pinecone DB is used for efficient similarity search of review embeddings, ensuring fast and relevant retrievals.
- LLM: Integrates Google's Gemini Flash for high-quality natural language processing and generation.
- Frontend: React, Tailwind CSS
- Backend: FastAPI
- Vector Database: Pinecone
- Language Model: Google Gemini Flash
- Embedding Model: SentenceTransformer
- Deployment: Vercel, Render (https://flight-insight-ai.vercel.app/)