Initial commit.

Basic docker deployment with Local LLM integration and simple game state.

architecture.md

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+# Text-Based LLM Interaction System Architecture
+
+## Overview
+This document outlines the architecture for a text-based system that allows users to interact with an LLM running on LM Studio.
+
+## Components
+
+### 1. User Interface Layer
+- **Text Input Handler**: Captures user input from terminal
+- **Text Output Display**: Shows LLM responses to user
+- **Session Manager**: Manages conversation history
+
+### 2. Communication Layer
+- **LLM Client**: Handles HTTP communication with LM Studio
+- **API Interface**: Formats requests/responses according to LM Studio's API
+
+### 3. Core Logic Layer
+- **Message Processor**: Processes user input and LLM responses
+- **Conversation History**: Maintains context between messages
+
+## Data Flow
+
+```mermaid
+graph TD
+    A[User] --> B[Text Input Handler]
+    B --> C[Message Processor]
+    C --> D[LLM Client]
+    D --> E[LM Studio Server]
+    E --> D
+    D --> C
+    C --> F[Text Output Display]
+    F --> A
+```
+
+## Technical Details
+
+### LM Studio API
+- Endpoint: http://10.0.0.200:1234/v1/chat/completions
+- Method: POST
+- Content-Type: application/json
+
+### Request Format
+```json
+{
+  "model": "model_name",
+  "messages": [
+    {"role": "user", "content": "user message"}
+  ],
+  "temperature": 0.7,
+  "max_tokens": -1
+}
+```
+
+### Response Format
+```json
+{
+  "id": "chatcmpl-123",
+  "object": "chat.completion",
+  "created": 1677652288,
+  "model": "model_name",
+  "choices": [
+    {
+      "index": 0,
+      "message": {
+        "role": "assistant",
+        "content": "response message"
+      },
+      "finish_reason": "stop"
+    }
+  ]
+}
+```
+
+## Project Structure
+```
+text_adventure/
+├── main.py              # Entry point
+├── config.py             # Configuration settings
+├── llm_client.py         # LLM communication
+├── interface.py          # Text input/output
+└── conversation.py       # Conversation history management
+```
+
+## Implementation Plan
+1. Create basic text input/output interface
+2. Implement LLM client for LM Studio communication
+3. Add conversation history management
+4. Integrate components
+5. Test functionality