A minimalist and powerful interface for the OpenAI API with multimodal and history management support.
Project description
oiaapi (OpenAI API Python Interface)
A minimalist yet powerful Python interface for the OpenAI API, designed for structured conversation management and advanced multimodal interactions.
Features
- Centralized Client: Use a single
Clientto manage your connection and spawn multiple chat sessions. - Variadic Chat Interface: Send multiple message components directly:
chat.chat("Text", Image("local.png"), "More text"). - Node-Based History: Every interaction is a node with an incremental ID.
- Context Control: Activate or deactivate conversation nodes by their ID to manage the model's window.
- Enhanced Metrics: Track token usage, models, and active nodes per request with built-in Pandas integration.
- Multimodal Support: Handle local images (auto-base64 encoding) and remote URLs seamlessly.
- State Persistence: Save
Chatstates and load them via theClientto resume sessions. - Deep Copy: Create independent clones of your chat session.
Installation
# Via Pip (once published)
pip install oiaapi
# From source
git clone https://github.com/artitzco/openai-api.git
cd openai-api
pip install .
Quick Start
from oiaapi import Client, Image
# Initialize the main client
client = Client(api_key="your-api-key") # or use OPENAI_API_KEY env var
# Start a new chat session
chat = client.chat(model="gpt-4o-mini", system_prompt="You are a helpful assistant.")
# Basic Chat
response = chat.chat("Hello! What can you do?")
print(response)
# Multimodal Chat (Local and URL)
chat.chat(
"Analyze these images:",
Image("path/to/local_image.png"),
"and also this one:",
Image("https://example.com/image.jpg")
)
# Manage History
df_history = chat.history.to_dataframe()
chat.history.toggle(node_id=1, active=False) # Context management
# Persistence
chat.save("my_session.json")
new_chat_recovered = client.load_chat("my_session.json")
Project Structure
src/oiaapi/: Core library modules.__init__.py: Contains theClientfactory and exports.core.py: Contains theChatsession manager.history.py: Logic for node-based conversation management.metrics.py: Token usage and request tracking.content.py: Multimodal data builders (Images, etc.).
notebooks/: Interactive guides and testing playgrounds.img/: Storage for sample assets.output/: Default location for saved session JSONs.
License
MIT
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