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https://huggingface.co/spaces/decodingdatascience/newrag-pine
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# 📞 Telecom Customer Support LLM with Groq API
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This project demonstrates how to build a fast, production-grade AI-powered telecom customer support assistant using the **Groq API** and optimized GenAI configurations.
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## 📌 Project Overview
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A step-by-step guide to:
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- Sending POST requests using **Postman**
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- Connecting to the **Groq API**
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- Testing default vs. optimized GenAI configurations
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- Applying structured **prompt templates**
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- Deploying a simple LLM-powered support API
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## 🔧 Tech Stack
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| Layer | Tool/Tech |
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|---------------|-------------------------|
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| LLM | [Groq API](https://groq.com/) |
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| API Platform | FastAPI / Postman |
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| Prompt Design | Custom templates |
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| Deployment | Localhost / Cloud (optional) |
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## 🧠 AI Configuration
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| Parameter | Description |
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|---------------------|--------------------------------------|
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| `temperature` | Controls randomness (default: 0.7) |
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| `top_p` | Nucleus sampling |
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| `max_tokens` | Max tokens to generate |
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| `frequency_penalty` | Repetition control |
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| `presence_penalty` | Topic diversity |
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## 🔄 Experiment Setup
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### 1. No Prompt Template + Default Config
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- Basic user input
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- Uses Groq defaults
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- For benchmarking
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### 2. With Prompt Template + Tuned Config
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- Structured input (e.g., role, intent, constraints)
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- Custom temperature and token limits
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- Optimized for domain-specific responses
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## 🚀 Quickstart
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### Step 1: Clone the repo
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```bash
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git clone https://github.com/your-username/telecom-support-llm.git
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cd telecom-support-llm
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