Create README.md for GraphNews project

Add README.md with project overview and setup instructions

Author: SimonSl07

README.md

@@ -0,0 +1,75 @@
+# GraphNews: A Multi-Agent Self-Correcting Editorial Team
+![Python Version](https://img.shields.io/badge/python-3.11%2B-blue)
+![LangGraph](https://img.shields.io/badge/Orchestration-LangGraph-orange)
+![LLM](https://img.shields.io/badge/LLM-DeepSeek--V3.2-green)
+
+**GraphNews** is a sophisticated multi-agent system built with **LangGraph** that automates the end-to-end process of news research, curation, and newsletter drafting. Unlike standard linear AI chains, this project utilizes a **Cyclic Graph** architecture to implement a "Self-Correction" loop, ensuring high-quality, factual output through autonomous peer review.
+
+## Workflow Architecture
+The system treats the editorial process as a state machine. Data flows through specialized nodes, maintaining a shared state to ensure context is preserved across the entire lifecycle:
+
+1.  **RESEARCHER:** Scours the web using **Tavily** for the top 10 .
+2.  **CURATOR:** Filters research results to select the top 5 most relevant sources.
+3.  **WRITER:** Generates a structured Markdown draft based on curated items.
+4.  **CRITIC:** Evaluates the draft. If the score is **< 8/10**, the draft is sent back to the **WRITER** with specific feedback for revision.
+5.  **FINALIZE:** Once the quality threshold is met, or we reach the 3rd draft (to avoid infinite loops), the final newsletter is saved to disk.
+
+```mermaid
+graph TD
+    Start((Start)) --> Researcher[Researcher Node]
+    Researcher --> Curator[Curator Node]
+    Curator --> Writer[Writer Node]
+    Writer --> Critic[Critic Node]
+    
+    Critic --> Decision{Score >= 8?}
+    
+    Decision -- "No (Score < 8 and draft number < 3)" --> Writer
+    Decision -- "Yes (Approved)" --> End((Save Markdown))
+
+    subgraph "The Agentic Loop"
+    Writer
+    Critic
+    Decision
+    end
+
+    style Researcher fill:#f9f,stroke:#333,stroke-width:2px
+    style Curator fill:#bbf,stroke:#333,stroke-width:2px
+    style Writer fill:#dfd,stroke:#333,stroke-width:2px
+    style Critic fill:#fdd,stroke:#333,stroke-width:2px
+    style Decision fill:#fff,stroke:#333,stroke-width:2px
+```
+
+## Tech Stack
+* **Orchestration:** LangGraph (Stateful Multi-Agent Workflows)
+* **LLM:** DeepSeek-V3.2
+* **Search Engine:** Tavily AI (Search API for LLMs)
+* **Language:** Python
+
+## Quick Start
+
+### 1. Clone & Install
+```bash
+git clone https://github.com/simonsl07/InsightLoop.git
+cd InsightLoop
+pip install -r requirements.txt
+```
+### 2. Create a .env file following the .env.example file
+```
+DEEPSEEK_API_KEY=your_key_here
+TAVILY_API_KEY=your_key_here
+```
+
+### 3. Run the system
+```bash
+python main.py
+```
+
+## Technical Challenges & Solutions
+- The "Hallucination" Brake: Implemented a max revision counter within the Critic node logic to prevent infinite loops and runaway API costs.
+- Deterministic State Control: Used LangGraph's TypedDict state to maintain a single source of truth, preventing context drift.
+
+## Roadmap
+ - Add CLI arguments to control news topic and source count.
+ - Integrate LangSmith for full-trace agent debugging and cost monitoring.
+ - Human-in-the-Loop: Add a LangGraph Checkpointer to pause for human approval before final output.
+