Skip to main content

A Python package for managing LLM chat conversation history

Project description

LLM Dialog Manager

A Python package for managing AI chat conversation history with support for multiple LLM providers (OpenAI, Anthropic, Google, X.AI) and convenient conversation management features.

Features

  • Support for multiple AI providers:
    • OpenAI (GPT-3.5, GPT-4)
    • Anthropic (Claude)
    • Google (Gemini)
    • X.AI (Grok)
  • Intelligent message role management (system, user, assistant)
  • Conversation history tracking and validation
  • Load balancing across multiple API keys
  • Error handling and retry mechanisms
  • Conversation saving and loading
  • Memory management options
  • Conversation search and indexing
  • Rich conversation display options

Installation

pip install llm-dialog-manager

Quick Start

Basic Usage

from llm_dialog_manager import ChatHistory

# Initialize with a system message
history = ChatHistory("You are a helpful assistant")

# Add messages
history.add_user_message("Hello!")
history.add_assistant_message("Hi there! How can I help you today?")

# Print conversation
print(history)

Using the AI Agent

from llm_dialog_manager import Agent

# Initialize an agent with a specific model
agent = Agent("claude-2.1", memory_enabled=True)

# Add messages and generate responses
agent.add_message("system", "You are a helpful assistant")
agent.add_message("user", "What is the capital of France?")
response = agent.generate_response()

# Save conversation
agent.save_conversation()

Advanced Features

Managing Multiple API Keys

from llm_dialog_manager import Agent

# Use specific API key
agent = Agent("gpt-4", api_key="your-api-key")

# Or use environment variables
# OPENAI_API_KEY_1=key1
# OPENAI_API_KEY_2=key2
# The system will automatically handle load balancing

Conversation Management

from llm_dialog_manager import ChatHistory

history = ChatHistory()

# Add messages with role validation
history.add_message("Hello system", "system")
history.add_message("Hello user", "user")
history.add_message("Hello assistant", "assistant")

# Search conversations
results = history.search_for_keyword("hello")

# Get conversation status
status = history.conversation_status()
history.display_conversation_status()

# Get conversation snippets
snippet = history.get_conversation_snippet(1)
history.display_snippet(1)

Environment Variables

Create a .env file in your project root:

# OpenAI
OPENAI_API_KEY_1=your-key-1
OPENAI_API_BASE_1=https://api.openai.com/v1

# Anthropic
ANTHROPIC_API_KEY_1=your-anthropic-key
ANTHROPIC_API_BASE_1=https://api.anthropic.com

# Google
GEMINI_API_KEY=your-gemini-key

# X.AI
XAI_API_KEY=your-x-key

Development

Running Tests

pytest tests/

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support, please open an issue in the GitHub repository or contact the maintainers.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

llm_dialog_manager-0.1.1073.tar.gz (11.6 kB view details)

Uploaded Source

Built Distribution

llm_dialog_manager-0.1.1073-py3-none-any.whl (10.2 kB view details)

Uploaded Python 3

File details

Details for the file llm_dialog_manager-0.1.1073.tar.gz.

File metadata

  • Download URL: llm_dialog_manager-0.1.1073.tar.gz
  • Upload date:
  • Size: 11.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for llm_dialog_manager-0.1.1073.tar.gz
Algorithm Hash digest
SHA256 047089ed84d97e94b8707c8c05589fcd38b05512df2d9f461cb735ae45bc86f5
MD5 d9189fddd1785735bf976d3e852a2710
BLAKE2b-256 7880384dea697f7e8f3714891d926fd91fa6cf8e2c110e72d90abcabfafd8ef4

See more details on using hashes here.

File details

Details for the file llm_dialog_manager-0.1.1073-py3-none-any.whl.

File metadata

File hashes

Hashes for llm_dialog_manager-0.1.1073-py3-none-any.whl
Algorithm Hash digest
SHA256 f39a3478fe9f524408d3a1449ba80963e06bcf5a8f35f9fdfb0a0d4f2074ba78
MD5 ffeab675bee4980e8b68d6cf7bc605ea
BLAKE2b-256 0a2b8f4f2bcfd049a8d76c65c35dc20f26377c31ee2708d3dc989e2938f91009

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page