extension ExtPose

Screener Transcript Helper

CRX id

dhblhhdhopbjbodknlkaajhbjefaoogf-

Description from extension meta

Adds a button to ask questions about PDF transcripts found on Screener.in.

Image from store Screener Transcript Helper
Description from store This project is a sophisticated AI-powered tool designed to enhance the user experience on the `screener.in` website by allowing users to "chat" with financial documents. The system consists of two main components: a frontend Chrome Extension and a backend Python API deployed on the cloud. ### Key Features * **Integrated UI**: Injects a sleek, modern sidebar directly into the `screener.in` webpage, creating a seamless user experience. * **Automatic Document Detection**: Automatically finds the 10 most recent "Concall" transcripts on the page and populates them in a dropdown for easy selection. * **AI-Powered Chat**: Allows users to ask questions in natural language about the selected transcript and receive answers generated by the GPT-4 model. * **Suggested Questions**: Provides users with one-click suggested questions to initiate the conversation with the document. * **Cloud-Native Backend**: The API is designed to be deployed as a serverless function on Vercel for scalability and reliability. ### Frontend (Chrome Extension) The frontend is a Chrome Extension built with JavaScript that modifies the `screener.in` website. Its core logic resides in `content.js`, which is responsible for injecting the sidebar UI, finding the relevant transcripts, handling user input from the chat interface, and communicating with the backend API. While it includes files for a browser popup (`popup.html`, `popup.js`), the primary interface is the sidebar. ### Backend (AI API) The backend is a Python API built using the FastAPI framework. It exposes a single `/ask` endpoint that performs the following actions: 1. Receives a PDF URL and a question from the frontend. 2. Downloads the PDF content into memory. 3. Uses the `PyMuPDF` library (`fitz`) to extract text from the in-memory data. 4. Constructs a prompt containing the transcript text and the user's question. 5. Sends the prompt to the OpenAI GPT-4 model to generate a relevant answer. 6. Returns the answer to the frontend to be displayed in the chat window. The API includes CORS middleware to allow requests from the Chrome extension.

Statistics

Installs
Category
Rating
5.0 (3 votes)
Last update / version
2025-06-26 / 1.2
Listing languages
en

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