New App : Speak With CSV File - Stremlit Audio Input

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**:rocket: Streamlit GenAI Voice-Interactive With CSV: **

Check My app : GenAI CSV Voice-Interactive

:wave: I’m thrilled to introduce my latest project: That enables seamless voice-driven data analysis through the integration of large language models (LLMs) and intuitive, user-friendly design.

openai streamlit pandas llms ai multipage

:star2: Give a project star on GitHub to help others discover it.

Speak With Data
Speak With Data3838×1567 203 KB

:star2: What Makes This App Unique?

The app combines advanced LLM capabilities with voice interaction, allowing users to upload CSV files and, through simple voice commands, gain valuable insights from their data.

:key: Key Features and Innovations

  • :brain: LLM-Powered Data Analysis: At the core of this app is OpenAI’s sophisticated language model, capable of analyzing structured data and delivering contextual insights based on extensive language understanding.

  • :microphone: Voice-Driven Interaction with Whisper: OpenAI’s Whisper model transforms spoken queries into text, making it easy for users to interact with their data conversationally.

  • :desktop_computer: Streamlined User Interface: Built with Streamlit, the app provides a smooth, intuitive experience for uploading CSVs, issuing voice commands, and viewing instant analysis results, all within a single platform.

  • :bar_chart: Automatic Data Insight Generation: From uploaded CSV files, the app generates tailored summaries and analytical insights, making data interpretation simple and straightforward.

:honeybee: The Power Behind the App: Swarm Framework

At the heart of this app is the Custom Swarm framework :honeybee:, a robust toolkit designed to support scalable, multi-agent systems. Swarm’s lightweight structure enables complex tasks to be broken down into manageable agents, each with specialized instructions and tools for specific functions. This setup is perfect for scenarios that demand flexibility and coordination among various capabilities.

:gear: Highlights of the Custom Swarm Setup

  • :card_file_box: Single-File Simplicity: The core GenAI code is elegantly encapsulated in under 390 lines, ensuring maintainability and ease of use.

  • :chart_with_upwards_trend: Pandas DataFrame Support: With built-in Pandas integration, the app seamlessly handles data for quick and efficient analysis.

  • :open_file_folder: Base64 Encoding for File Flexibility: The app allows any file to be uploaded as a context variable through Base64 encoding, adding further versatility.

  • :twisted_rightwards_arrows: Multi-LLM Compatibility: Designed to work with a range of LLMs compatible with OpenAI’s API, including Ollama, Mistral, Llama 3.2, and more, ensuring adaptability for different project needs.

:computer: Technology Stack

  • :jigsaw: OpenAI for GenAI services, driving the intelligence behind our LLM and voice interactions.
  • :honeybee:Custom Swarm Framework for building and managing a multi-agent system.
  • :parrot: Streamlit for a simple yet powerful frontend interface.
  • :bar_chart: Pandas for robust data analysis and manipulation.
  • :hammer_and_wrench: Pydantic for data validation, ensuring reliability and security.
  • :whale: Docker for seamless development and deployment across environments.
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Amazing Work!

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Thank you.
Please star on GitHub to help others discover it.

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Wonderfull , I like idea to use Swarm agent and also include Streamlit audio input.

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Hey, hi! We’re excited to introduce our new product, Super Engineer!

Super Engineer is an AI-powered platform designed for both developers and non-developers to turn app ideas into working applications quickly and easily. Just share your idea, and Super Engineer’s Requirement Agents will refine it with you, asking questions to clarify your needs.

Key Features:

  • Automated Code Generation: Instantly generates code based on your requirements, with a preview hosted on Heroku.
  • Expectation Agent: Iteratively refine the app to meet your expectations, with the flexibility to choose between Claude and OpenAI agents.
  • Error Resolution: Easily fix errors with a single click, sending issues directly to the agent for correction.
  • Data Integration: Build apps based on data from CSV, PostgreSQL, or BigQuery files.
  • Version Control: Track changes with Git-style versioning to easily revert or manage updates.

Visit our website to get started and join our Discord community to stay connected!

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Very thankfully for your comment.

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Done!

1 Like