3-basic_chatbot_v1.md•1.94 kB
# 🤖 Basic Chatbot
This is the simplest form of a memory-aware chatbot.
It uses OpenAI's chat models combined with persistent history management to enable short-term context retention across turns.
The goal of this chatbot is to create a conversational loop that remembers **recent history**, personalizes replies based on **user info**, and summarizes past interactions, without advanced memory systems.
## ⚙️ Core Functionalities
### 1. 🧱 Initialization
When the `Chatbot` class is initialized, it sets up:
- ✅ **Model Configuration**
Loads model names, token limits, and paths from a configuration file.
- ✅ **Session ID Generation**
Each chat session is assigned a unique ID for tracking.
- ✅ **Components Setup**
- `SQLManager`: Connects to a local or remote database
- `UserManager`: Retrieves or stores user information
- `ChatHistoryManager`: Tracks message history and summaries
- ✅ **Chat Summary Retrieval**
Pulls the most recent conversation summary to preserve continuity in new prompts.
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### 2. 💬 Conversational Handling
When a message is received:
- 📌 **System Prompt Construction**
Dynamically builds a prompt including:
- User profile details
- A summary of earlier chats
- The last few message pairs
- 🔁 **Model Invocation**
Sends the prompt and user message to OpenAI's API and receives a reply.
- 🧠 **Chat History Update**
- Stores the conversation pair in the database
- Updates the summary if needed to stay within context length
- ⚠️ **Error Handling**
Any issues during the API request return a readable error message.
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## 🧾 Visual Overview
Here's a high-level schema showing how the basic chatbot works:
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> 🧩 This chatbot doesn't support tool usage or long-term memory.
> But it's a solid foundation for building more advanced, agentic systems.