https://github.com/prcharan592/llm-driven-enterprise-assistant-for-client-support-and-queries

The enterprise chatbot using Gemini API, Flask, and Google Vertex AI to respond to client queries. Implemented dynamic response generation, safety settings, and context-aware suggestions for enhanced user experience.
https://github.com/prcharan592/llm-driven-enterprise-assistant-for-client-support-and-queries

css gemini-api html5 javascript python3

Last synced: about 1 month ago
JSON representation

The enterprise chatbot using Gemini API, Flask, and Google Vertex AI to respond to client queries. Implemented dynamic response generation, safety settings, and context-aware suggestions for enhanced user experience.

• Host: GitHub
• URL: https://github.com/prcharan592/llm-driven-enterprise-assistant-for-client-support-and-queries
• Owner: prcharan592
• Created: 2025-01-09T17:16:31.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2025-01-17T05:55:52.000Z (4 months ago)
• Last Synced: 2025-02-09T04:40:53.820Z (3 months ago)
• Topics: css, gemini-api, html5, javascript, python3
• Language: JavaScript
• Homepage:
• Size: 14.6 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# LLM-Driven-Enterprise-Assistant-for-Client-Support-and-Queries

This project is a Flask-based web application that integrates Google Vertex AI’s Gemini API to create a chatbot. The chatbot is designed to answer queries related to a company’s services, technologies, mission, and more, by generating responses from a predefined context. It uses a combination of natural language processing (NLP) and generative AI to provide accurate, context-aware replies.

# Features

	•	Real-time chatbot for company-related queries.

	•	Uses Google Vertex AI’s Gemini API for generating responses.

	•	Safety settings in place to block harmful content.

	•	Customizable context for company-specific queries.

# Steps to Run this project

==>Setup the files like below

# project/

	•	app.py: Main Flask application file.

	•	static/: Directory containing frontend files:

	•	index1.html: HTML file for the chatbot interface.

	•	style1.css: CSS file for styling the UI.

	•	script1.js: JavaScript file for frontend interactivity.

	•	requirements.txt: List of required Python libraries for the project.

	•	service_account.json: Google Cloud Platform service account credentials (ensure it is stored securely).

	•	README.md: Project documentation (this file).

==>follow requirements.txt for setup API

😊You’re now ready to use the Vertex AI Gemini API!😊