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Mem-LLM v1.3.3 - Streaming, REST API & Web UI

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@devemree devemree released this 09 Nov 16:01
· 71 commits to main since this release
v1.3.3
4ea2c39

🎉 What's New

⚡ Streaming Response

  • Real-time streaming support for all LLM backends (Ollama, LM Studio, Gemini)
  • ChatGPT-style typing effect
  • chat_stream() method added to MemAgent and all clients
  • Example: examples/17_streaming_example.py

🌐 REST API Server

  • FastAPI-based API server with full endpoints
  • WebSocket support for real-time streaming
  • SSE (Server-Sent Events) streaming
  • Interactive API docs at /docs
  • CORS and security middleware included

💻 Web UI (3 Pages)

Chat Page (index.html)

  • Real-time streaming chat interface
  • Backend selection (Ollama/LM Studio)
  • Dynamic model configuration
  • Memory and Knowledge Base settings

Memory Page (memory.html)

  • View conversation history
  • Search in memories
  • User profile management
  • Export/clear memory

Metrics Page (metrics.html)

  • Real-time system statistics
  • Usage charts (last 7 days)
  • Backend performance metrics
  • Active users list
  • Auto-refresh every 30s

🚀 Easy Launch

# Windows
start_web_ui.bat

# Cross-platform
python start_web_ui.py

🌍 Full English Localization

  • All UI components translated to English
  • Documentation updated
  • Better accessibility for global community

📦 Installation

pip install mem-llm --upgrade

🎯 Quick Start

from mem_llm import MemAgent

agent = MemAgent(model="granite4:3b", backend="ollama")

# Streaming response
for chunk in agent.chat_stream("Hello!"):
    print(chunk, end="", flush=True)

🔧 Breaking Changes

None - Fully backward compatible!

📝 Full Changelog

  • Added chat_stream() method to all LLM clients
  • Integrated streaming into MemAgent
  • Created FastAPI server (api_server.py)
  • Built 3-page Web UI (Chat, Memory, Metrics)
  • Added WebSocket and SSE streaming support
  • Translated all files to English
  • Cleaned up redundant test files
  • Added launcher scripts (start_web_ui.bat, start_web_ui.py)

📚 Documentation

🙏 Contributors

Thanks to everyone who contributed to this release!

Full Code: https://github.com/emredeveloper/Mem-LLM
PyPI Package: https://pypi.org/project/mem-llm/

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