A Python library for text-based AI interactions
Project description
multiai
multiai
is a Python library and command-line tool designed to interact with text-based generative AI models from the following providers:
AI Provider | Web Service | Models Available |
---|---|---|
OpenAI | ChatGPT | GPT Models |
Anthropic | Claude | Claude Models |
Gemini | Gemini Models | |
Perplexity | Perplexity | Perplexity Models |
Mistral | Mistral | Mistral Models |
Key Features
- Interactive Chat: Communicate with AI directly from your terminal.
- Multi-Line Input: Supports multi-line prompts for complex queries.
- Pager for Long Responses: View lengthy responses conveniently using a pager.
- Continuation Handling: Automatically handle and request continuations if responses are cut off.
- Automatic Chat Logging: Automatically save your chat history for future reference.
Usage
Install multiai
, then configure your API keys for your chosen AI providers as environment variables or in a user-setting file. Once that's done, you can start interacting with the AI.
-
To send a simple query:
ai hi
You should see a response like:
gpt-4o-mini> Hello! How can I assist you today?
-
For an interactive session, enter interactive mode:
ai
In this mode, you can continue the conversation:
user> hi gpt-4o-mini> Hello! How can I assist you today? user> how are you gpt-4o-mini> I'm just a program, so I don't have feelings, but I'm here and ready to help you! How about you? How are you doing? user>
To see a list of all command-line options, use:
ai -h
For more detailed documentation, you can open the manual in a web browser with:
ai -d
Using multiai
as a Python Library
multiai
can also be used as a Python library. Here’s a simple example:
import multiai
# Initialize the client
client = multiai.Prompt()
client.set_model('openai', 'gpt-4o') # Set model
client.temperature = 0.5 # Set temperature
# Send a prompt and get a response
answer = client.ask('hi')
print(answer)
# Continue the conversation with context
answer = client.ask('how are you')
print(answer)
# Clear the conversation context
client.clear()
The manual includes the following sample codes:
- A script that translates a text file into English.
- A local chat app that allows you to easily select from various AI models provided by different providers and engage in conversations with them.
Project details
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