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LLM Observability in Agenta
LLM Observability in Agenta

Product Update

4 Mins Read

Introducing Open-Source LLM Observability with Agenta

Introducing Open-Source LLM Observability with Agenta

Agenta introduces open-source LLM observability and LLM monitoring for LLM applications. It allows you to trace inputs, outputs, and meta-data with two-lines of code. It is OpenTelemetry compliant and comes with many integrations out of the box (OpenAI, LiteLLM, LangChain, Instructor and more).

Agenta introduces open-source LLM observability and LLM monitoring for LLM applications. It allows you to trace inputs, outputs, and meta-data with two-lines of code. It is OpenTelemetry compliant and comes with many integrations out of the box (OpenAI, LiteLLM, LangChain, Instructor and more).

Mahmoud Mabrouk

Nov 13, 2024

Get to know

Frequently

asked

questions

Create robust LLM apps in record time. Focus on your core business logic and leave the rest to us.

Star Us On Github

Do I need to know how to code to create LLM applications with agenta?

Can I use agenta with a self-hosted fine-tuned model such as Llama or Falcon?

How can I limit hallucinations and improve the accuracy of my LLM apps?

Is it possible to use vector embeddings and retrieval-augmented generation with Agenta?

How it works

Frequently

asked

questions

Create robust LLM apps in record time. Focus on your core business logic and leave the rest to us.

Star Us On Github

Do I need to know how to code to create LLM applications with agenta?

Can I use agenta with a self-hosted fine-tuned model such as Llama or Falcon?

How can I limit hallucinations and improve the accuracy of my LLM apps?

Is it possible to use vector embeddings and retrieval-augmented generation with Agenta?

How it works

Frequently

asked

questions

Create robust LLM apps in record time. Focus on your core business logic and leave the rest to us.

Star Us On Github

Do I need to know how to code to create LLM applications with agenta?

Can I use agenta with a self-hosted fine-tuned model such as Llama or Falcon?

How can I limit hallucinations and improve the accuracy of my LLM apps?

Is it possible to use vector embeddings and retrieval-augmented generation with Agenta?