Add notebooks for Muhammad Qasim Sheikh in community-contributions

community-contributions/muhammad_qasim_sheikh/Week 2/day1/readme.md

@@ -0,0 +1,47 @@
+# Multi-Agent Conversation Simulator (OpenAI + Ollama)
+
+## Project Overview
+
+This project is an experimental **multi-agent conversational simulation** built with **OpenAI GPT models** and a locally-hosted **Ollama LLM (Llama 3.2)**. It demonstrates how multiple AI personas can participate in a shared conversation, each with distinct roles, perspectives, and behaviors — producing a dynamic, evolving debate from different angles.
+
+The script orchestrates a **three-way dialogue** around a single topic (“Why did the chicken cross the road?”) between three agents, each powered by a different model and persona definition:
+
+- **Athena (OpenAI GPT-4o):** A strategic thinker who looks for deeper meaning, long-term consequences, and practical wisdom.
+- **Loki (Ollama Llama 3.2):** A sarcastic trickster who mocks, questions, and challenges the others with wit and irony.
+- **Orion (OpenAI GPT-4o):** A data-driven realist who grounds the discussion in facts, statistics, or logical deductions.
+
+## What’s Happening in the Code
+
+1. **Environment Setup**  
+   - Loads the OpenAI API key from a `.env` file.  
+   - Initializes OpenAI’s Python client and configures a local Ollama endpoint.
+
+2. **Persona System Prompts**  
+   - Defines system prompts for each agent to give them unique personalities and communication styles.  
+   - These prompts act as the “character definitions” for Athena, Loki, and Orion.
+
+3. **Conversation Initialization**  
+   - Starts with a single conversation topic provided by the user.  
+   - All three agents are aware of the discussion context and prior messages.
+
+4. **Conversation Loop**  
+   - The conversation runs in multiple rounds (default: 5).  
+   - In each round:
+     - **Athena (GPT)** responds first with a strategic viewpoint.
+     - **Loki (Ollama)** replies next, injecting sarcasm and skepticism.
+     - **Orion (GPT)** follows with a fact-based or analytical perspective.
+   - Each response is appended to the conversation history so future replies build on previous statements.
+
+5. **Dynamic Context Sharing**  
+   - Each agent receives the **entire conversation so far** as context before generating a response.  
+   - This ensures their replies are relevant, coherent, and responsive to what the others have said.
+
+6. **Output Rendering**  
+   - Responses are displayed as Markdown in a readable, chat-like format for each speaker, round by round.
+
+## Key Highlights
+
+- Demonstrates **multi-agent orchestration** with different models working together in a single script.
+- Uses **OpenAI GPT models** for reasoning and **Ollama (Llama 3.2)** for local, cost-free inference.
+- Shows how **system prompts** and **context-aware message passing** can simulate realistic dialogues.
+- Provides a template for experimenting with **AI characters**, **debate simulations**, or **collaborative agent systems**.