hjimi-openai 0.1.0

A demo package for OpenAI integration with conversation management and multiple output formats

hjimi_openai

An AI conversation management tool based on LangChain, supporting multi-session management, streaming output, automatic saving and backup, and other features. Focused on providing flexible and powerful conversation management solutions.

Key Features

• Multi-Session Management

  • Support for managing multiple independent conversation sessions
  • Automatic session saving and recovery
  • Flexible session configuration system
  • Session history management support

• Multiple Output Format Support

  • Markdown format output
  • JSON format output
  • Plain text (TXT) output
  • HTML format output

• Automation Features

  • Automatic conversation history saving
  • Periodic backup functionality
  • Automatic history length management

• Input/Output Processing

  • Support for streaming output
  • Support for batch loading questions from files
    • JSON format support
    • TXT format support
  • Flexible output formatting

• System Features

  • Complete logging system
  • Error handling and recovery
  • Environment variable configuration
  • Session state management

Installation Requirements

• Python 3.8 or higher
• Required dependencies:
  • langchain-openai>=0.0.3
  • langchain-core>=0.1.4
  • langchain-community>=0.0.6
  • langchain>=0.1.0

Quick Start

1. Install Package

pip install hjimi-openai

2. Set Environment Variables

# Set API Key
export DASHSCOPE_API_KEY="your_api_key_here"

3. Basic Usage

from hjimi_openai import AIConversationManager, ConversationConfig

# Create configuration
config = ConversationConfig(
    output_dir="output",
    model_name="qwen-plus",
    temperature=0.7
)

# Initialize manager
manager = AIConversationManager(config)

# Process single question
response = manager.process_conversation("What is artificial intelligence?")
print(response)

Configuration Options

Basic Configuration

• model_name: Model name to use (default: "qwen-plus")
• temperature: Temperature parameter (default: 0.0)
• max_tokens: Maximum tokens (default: 1024)
• streaming: Enable streaming output (default: True)
• output_dir: Output directory (default: "output")
• output_format: Output format (supports markdown/json/txt/html)

Advanced Configuration

• system_prompt: System prompt
• api_base: API base URL
• api_key_env: API key environment variable name
• save_interval: Auto-save interval
• max_history_length: Maximum history length
• backup_enabled: Enable backup
• session_id_prefix: Session ID prefix

Advanced Usage

Multi-Session Management

# Create multiple sessions
sessions = {
    "ai_basics": [
        "What is machine learning?",
        "What's the difference between deep learning and machine learning?"
    ],
    "python_tips": [
        "What are Python decorators?",
        "How to use generators to improve performance?"
    ]
}

manager.process_questions(sessions)

Loading Questions from File

# JSON format example
questions_json = {
    "session1": {
        "title": "AI Basics",
        "questions": [
            "What are neural networks?",
            "What is backpropagation?"
        ]
    }
}

# Load from file
manager.process_questions("questions.json")

Custom Output Format

from hjimi_openai import ConversationConfig, OutputFormat

config = ConversationConfig(
    output_format=OutputFormat.MARKDOWN,
    markdown_template="""
# {title}
## Q&A Records
{content}
"""
)

manager = AIConversationManager(config)

Basic Conversation Example

# Create manager instance
manager = AIConversationManager()

# Simple conversation
questions = [
    "What's the difference between lists and tuples in Python?",
    "How to handle exceptions in Python?"
]

for question in questions:
    response = manager.process_conversation(question)
    print(f"Question: {question}")
    print(f"Answer: {response}\n")

Batch Processing Example

# Prepare batch questions
batch_questions = {
    "programming": {
        "title": "Programming Basics",
        "questions": [
            "What is object-oriented programming?",
            "What are design patterns?",
            "What is functional programming?"
        ]
    },
    "database": {
        "title": "Database Basics",
        "questions": [
            "What is database indexing?",
            "What's the difference between SQL and NoSQL?"
        ]
    }
}

# Batch processing
manager.process_questions(batch_questions)

Custom Configuration Example

config = ConversationConfig(
    model_name="qwen-plus",
    temperature=0.7,
    max_tokens=2048,
    streaming=True,
    output_dir="custom_output",
    output_format=OutputFormat.MARKDOWN,
    system_prompt="You are a professional programming assistant. Please answer questions concisely.",
    save_interval=3,
    max_history_length=100,
    backup_enabled=True
)

manager = AIConversationManager(config)

Version History

0.1.0 (Current)

• Initial release
• Multi-session management support
• Multiple output format support
• Streaming output support
• Automatic saving and backup support
• File-based question loading support

Contributing

Issues and Pull Requests are welcome to help improve the project.

License

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

Author

wenquanshan ([e-mail])

Contact

• GitHub: https://github.com/zidanewenqsh/openai_demo
• Email: [e-mail]
• Bug Reports: https://github.com/zidanewenqsh/openai_demo/issues