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Documentation Index

Fetch the complete documentation index at: https://docs.obiguard.ai/llms.txt

Use this file to discover all available pages before exploring further.

Instead of building and maintaining separate integrations for each multimodal LLM, you can use a single, unified API to access models from OpenAI, Anthropic, Meta, Cohere, Mistral, and over 100 models across 15+ providers.

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Obiguard Uses the OpenAI API Standard

The Obiguard API leverages its robust open-source AI Gateway to translate all incoming requests into the OpenAI API format, ensuring responses are fully OpenAI-compatible.

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Seamlessly Switch Between Providers

from obiguard import Obiguard

# Calling OpenAI
client = Obiguard(
  provider = "openai",
  Authorization = "sk-xxxxx"
)

response = obiguard.chat.completions.create(
  messages = [{ "role": 'user', "content": 'Hello' }],
  model = 'gpt-4'
)

# Switching to Anthropic
client = Obiguard(
  provider = "anthropic",
  Authorization = "sk-ant-xxxxx"
)

response = obiguard.chat.completions.create(
  messages = [{ "role": 'user', "content": 'Hello' }],
  model = 'claude-3-opus-20240229'
)

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Integrating Local or Private Models

Obiguard can connect to and monitor your locally or privately hosted LLMs, provided the model is compatible with one of the 15+ providers supported by Obiguard and its URL is accessible. Just set the custom_host parameter along with the provider name, and Obiguard will manage communication with your local model.
When using custom_host, make sure to include the version segment (e.g., /v1) in the URL. Obibuard will automatically add the correct endpoint path (/chat/completions, /completions, or /embeddings).For Ollama models, this process is different. See documentation for details.

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Multimodality

Obiguard offers seamless integration with multimodal models using the same unified API, enabling support for vision, audio, image generation, and additional advanced capabilities across multiple providers. Multimodal Capabilities