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Upload 5 files
Browse files- app.py +30 -0
- branding.json +26 -0
- profile-of-hereandnowai.txt +116 -0
- requirements.txt +3 -0
- text_rag.py +42 -0
app.py
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import gradio as gr
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from text_rag import get_response
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import json
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import os
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with open(os.path.abspath(os.path.join(os.path.dirname(__file__), "branding.json"))) as f:
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brand_info = json.load(f)["brand"]
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with gr.Blocks(theme="default", title=brand_info["organizationName"]) as rag_bot:
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gr.HTML(f"""
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<div style="display: flex; justify-content:center; margin-bottom:20px">
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<img src="{brand_info["logo"]["title"]}" alt="{brand_info["organizationName"]} Logo" style="width:200px;height:40px">
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</div> """)
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gr.ChatInterface(
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fn=get_response,
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chatbot=gr.Chatbot(height=500, avatar_images=(None, brand_info["chatbot"]["avatar"]), type="messages"),
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title=brand_info["organizationName"],
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description=brand_info["slogan"],
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type="messages",
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examples=[
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["Who is the CEO of Here and Now AI?"],
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["What is the mission of Here and Now AI?"],
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["Tell me about the team behind Here and Now AI."]
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]
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)
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if __name__ == "__main__":
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rag_bot.launch()
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branding.json
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{
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"brand":
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{
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"organizationName": "HERE AND NOW AI",
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"website": "https://hereandnowai.com",
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"email": "info@hereandnowai.com",
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"mobile": "+91 996 296 1000",
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"slogan": "designed with passion for innovation",
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"colors": {"primary": "#FFDF00", "secondary": "#004040"},
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"logo":
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{
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"title": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/logo-of-here-and-now-ai.png",
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"favicon": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/favicon-logo-with-name.png"}, "chatbot": {"avatar": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/caramel.jpeg", "face": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/caramel-face.jpeg"
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},
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"socialMedia":
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{
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"blog": "https://hereandnowai.com/blog",
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"linkedin": "https://www.linkedin.com/company/hereandnowai/",
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"instagram": "https://instagram.com/hereandnow_ai",
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"github": "https://github.com/hereandnowai",
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"x": "https://x.com/hereandnow_ai",
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"youtube": "https://youtube.com/@hereandnow_ai"
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}
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}
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}
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profile-of-hereandnowai.txt
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# PASTE THE CLEANED PLAIN TEXT OF YOUR PROSPECTUS HERE
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# Example snippet:
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About HERE AND NOW AI
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HERE AND NOW AI is Indiaβs leading autonomous Artificial Intelligence Research Institute, dedicated to transforming the way AI is taught, researched, and applied. It is a brainchild of Deepti Balagopal and Ruthran Raghavan, who envisioned a future where AI education is not limited to coders but accessible to every learner β whether theyβre from engineering, business, science, or the arts.
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Born from the success of HERE AND NOW β The Language Institute (est. 2011), which redefined language learning in India, HERE AND NOW AI was founded in 2018 with a mission to disrupt traditional education through AI innovation. Our core initiatives lie in:
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* AI Education: Delivering industry-ready, practical AI programs for students
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* Research & Innovation: Exploring cutting-edge LLMs, RAG frameworks, and autonomous agents
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* Automation: Building intelligent systems that power real-world enterprises and academic institutions
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We believe that every college in India can be an AI-powered campus, and we are on a mission to make that happen.
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Vision & Mission
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Our Vision
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To build a generation of AI-native graduates and researchers empowered with real-world skills and global exposure, through Indiaβs first fully autonomous AI professor.
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Our Mission
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* Deliver AI education to 1 lakh students by 2030
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* Sign MoUs with 100+ colleges for long-term collaboration
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* Build AI as a Service (AIaaS) solutions for corporates using student talent
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* Create open-access tools that empower learners and educators with AI
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HERE AND NOW AI stands for innovation with inclusivity. Whether you're from an arts stream or an engineering background β we are here to level the playing field with AI.
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Value-Added Courses Overview
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We proudly offer two high-impact AI programs designed for value addition in colleges. These are flexible, certification-backed, and tailored to academic timetables.
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1. Business Analytics with AI
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For: Non-technical students β BBA, BCom, BA, BSc, MBA, MCA, ME
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Prerequisites: None
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This course introduces students to the world of data-driven business intelligence through Python, visualization tools, and cutting-edge AI platforms like ChatGPT, Claude, and Gemini.
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Students will learn:
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* How to clean and analyze data using Python
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* How to interpret and visualize insights with Pandas, Matplotlib
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* How AI can enhance decision-making in HR, Finance, Marketing
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* Real-world project: Creating a dashboard or report powered by AI tools
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Why this course matters: In the modern job market, even non-tech graduates are expected to have basic data literacy. This course bridges that gap while giving them an AI edge.
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2. Full-Stack AI Developer Program
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For: Technical students β BE, BTech, BCA, MCA, MSc IT, ME
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Prerequisites: Basic familiarity with programming logic
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This project-oriented course teaches students to build AI-powered applications end-to-end using the latest in LLM technology.
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Students will explore:
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* Python fundamentals + API development (Flask, FastAPI)
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* Working with OpenAI, Claude, Gemini through API integration
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* RAG (Retrieval-Augmented Generation), LangChain, Vector DBs
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* Deploying AI apps on cloud platforms (GCP, Vercel)
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* Final Capstone: Build your own AI Chatbot or Assistant
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Why this course matters: Students not only learn AI concepts β they deploy real applications. It builds confidence, improves resumes, and gives them a head start in interviews or internships.
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Business Analytics with AI: Curriculum
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Total Duration: 30 hours | Mode: Online/Offline/Hybrid
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Eligibility: Any UG/PG student (non-tech or mixed)
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Module Breakdown:
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1. Getting Started with Python β No coding experience? No problem. We begin at zero.
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2. Data Analysis with Pandas & NumPy β Learn how to work with datasets, filter and prepare reports
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3. Data Visualization β Turn raw data into stunning graphs using Matplotlib and Seaborn
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4. Statistics for Business β Descriptive & Inferential Statistics for smarter decision-making
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5. AI for Business Users β Use ChatGPT, Copilot, Claude for content, reports, and insights
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6. Mini Project β Create a business report powered by AI tools
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Full-Stack AI Developer: Curriculum
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Total Duration: 30 hours | Mode: Project-Based | Eligibility: Tech Background Students
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Module Breakdown:
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1. Python + Git + IDE Setup β Get started with clean development workflow
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2. API Development β Build backend endpoints using Flask or FastAPI
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3. LLM Integration β Learn to work with Gemini, ChatGPT, Claude via API
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4. LangChain & Vector Databases β Implement memory in AI using RAG
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5. Cloud Deployment β Launch your app on GCP, Vercel with CI/CD basics
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6. Capstone Project β Build your own AI product and present it
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Delivery Format & Certification
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Mode of Delivery:
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* Live Classes (Online or On-Campus)
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* AI-Powered LMS with recordings, quizzes, code labs
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* Mentorship & Peer Discussion Forums
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Certification:
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* Joint Certificate from HERE AND NOW AI + Partner College
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* Certificate includes project link and GitHub portfolio
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Add-Ons:
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* Career Guide PDFs, Resume Templates
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* Code Snippets, Prompt Libraries
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* Exclusive access to internship/freelance opportunities
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Placement & Career Assistance
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Job Readiness:
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* Business English Training (Add-On)
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* Soft Skills & Interview Prep (Add-On)
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* Resume & LinkedIn Profile Optimization (Free)
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Technical Readiness:
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* GitHub Portfolio Guidance
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* LeetCode Problem Solving (Add-On Module)
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* Mock Interview Rounds
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Network Readiness:
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* LinkedIn Strategy: Personal Branding + Connection Funnels
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* Monthly AI Industry Talk Sessions
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Leadership Team
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Ruthran RAGHAVAN β CEO & Chief AI Scientist
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Visionary leader and AI educator. Invented the 108-day Business French Immersion Program. Now building India's first Autonomous AI Professor and leading AI evangelism nationwide.
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Deepti BALAGOPAL β COO
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Academic strategist managing operations, course quality, and outreach. She is the backbone of all institutional collaborations and program execution.
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Balaji KAMALAKKANNAN β CTO
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Expert in cloud, open-source LLMs, and full-stack deployment. Balaji leads all technical R&D and product integration for HERE AND NOW AI.
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Gopalakrishnan KANNAN β CMO
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Marketing genius with deep experience in youth outreach and digital campaigns. Gopal ensures the AI movement reaches every corner of India.
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Contact & Collaboration
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HERE AND NOW AI β Artificial Intelligence Research Institute
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Chennai, Tamil Nadu, India
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Website: www.hereandnowai.com
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Email: info@hereandnowai.com
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Phone: +91 99629 61000
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Course Fee Structure:
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* Business Analytics with AI: βΉ5,925 / student / semester
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* Full-Stack AI Developer Program: βΉ9,925 / student / semester
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Letβs Build the Future Together
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We look forward to collaborating with your institution. Together, letβs lead India into the AI-powered future.
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requirements.txt
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openai
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python-dotenv
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gradio
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text_rag.py
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from openai import OpenAI
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from dotenv import load_dotenv
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import os
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import requests
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load_dotenv()
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api_key = os.getenv("GEMINI_API_KEY")
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model = "gemini-2.5-flash-lite"
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base_url = "https://generativelanguage.googleapis.com/v1beta/openai/"
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client = OpenAI(base_url=base_url, api_key=api_key)
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url="https://raw.githubusercontent.com/hereandnowai/vac/refs/heads/master/prospectus-context.txt"
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response = requests.get(url)
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script_dir = os.path.dirname(os.path.abspath(__file__))
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file_path = os.path.join(script_dir, "profile-of-hereandnowai.txt")
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with open(file_path, "wb") as f:
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f.write(response.content)
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text_path =file_path
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try:
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with open(text_path, "r",encoding="utf-8") as file:
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text_lines = file.readlines()
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text_content = "\n".join([line.strip() for line in text_lines if line.strip()])
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except Exception as e:
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print(f"Error reading the text file: {e}")
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text_content = "Error extracting text from text file."
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system_prompt =f"""You are Caramel AI, ai assistant build by Here and Now AI.Answer the user's question based only on the following context:\n\n{text_content}"""
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def get_response(message, history):
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messages = [{"role": "system", "content": system_prompt}]
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messages.extend(history)
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messages.append({"role": "user", "content": message})
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response = client.chat.completions.create(model=model, messages=messages)
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ai_response = response.choices[0].message.content
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return ai_response
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print(get_response("who is the ceo of here and now ai?", []))
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