swarm-models 0.0.5

Swarm Models - Pytorch

Swarms Models

Leverage LLM APIs with Unparalleled Speed, Security, and Reliability

Why Swarm Models?

• Multi-Provider Support: Effortlessly integrate APIs from various providers into your projects.

• Bleeding-Edge Speed: Experience lightning-fast performance optimized for efficiency.

• Robust Security: Built with top-notch security protocols to protect your data and API keys.

• Ease of Use: Simple initialization and execution with intuitive .run(task) and __call__ methods.

• Scalability: Designed to handle everything from small scripts to large-scale applications.

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Code Example

from swarm_models import OpenAIChat
import os

# Get the OpenAI API key from the environment variable
api_key = os.getenv("OPENAI_API_KEY")

# Create an instance of the OpenAIChat class
model = OpenAIChat(openai_api_key=api_key, model_name="gpt-4o-mini")

# Query the model with a question
out = model(
   "What is the best state to register a business in the US for the least amount of taxes?"
)

# Print the model's response
print(out)

How It Works

Swarm Models simplifies the way you interact with different APIs by providing a unified interface for all models.

1. Install Swarm Models

$ pip3 install swarm-models

2. Set Your Keys

OPENAI_API_KEY="your_openai_api_key"
GROQ_API_KEY="your_groq_api_key"
ANTHROPIC_API_KEY="your_anthropic_api_key"
AZURE_OPENAI_API_KEY="your_azure_openai_api_key"

3. Initialize a Model

Import the desired model from the package and initialize it with your API key or necessary configuration.

from swarm_models import YourDesiredModel

model = YourDesiredModel(api_key='your_api_key', *args, **kwargs)

4. Run Your Task

Use the .run(task) method or simply call the model like model(task) with your task.

task = "Define your task here"
result = model.run(task)

# Or equivalently
#result = model(task)

5. Enjoy the Results

print(result)

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Get Started Now

Ready to streamline your API integrations and boost your application's performance?

1. Install the Package

   $ pip install swarm-models
   

2. Explore the Documentation

   Dive into our comprehensive Documentation to learn more about the available models and features.

3. Join the Community

   Connect with other developers on our GitHub and contribute to the project.

Download Now | Documentation | GitHub

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Available Models

Model Name	Description
OpenAIChat	Chat model for OpenAI's GPT-3 and GPT-4 APIs.
Anthropic	Model for interacting with Anthropic's APIs.
AzureOpenAI	Azure's implementation of OpenAI's models.
Dalle3	Model for generating images from text prompts.
NvidiaLlama31B	Llama model for causal language generation.
Fuyu	Multi-modal model for image and text processing.
Gemini	Multi-modal model for vision and language tasks.
Vilt	Vision-and-Language Transformer for question answering.
TogetherLLM	Model for collaborative language tasks.
FireWorksAI	Model for generating creative content.
ReplicateChat	Chat model for replicating conversations.
HuggingfaceLLM	Interface for Hugging Face models.
CogVLMMultiModal	Multi-modal model for vision and language tasks.
LayoutLMDocumentQA	Model for document question answering.
GPT4VisionAPI	Model for analyzing images with GPT-4 capabilities.
LlamaForCausalLM	Causal language model from the Llama family.

Frequently Asked Questions

Q: Which providers are supported?

A: Swarm Models supports a wide range of API providers. Check out the documentation for a full list.

Q: How do I secure my API keys?

A: We recommend using environment variables or a secure key management system. Swarm Models ensures your keys are handled securely within the package.

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