mirror of https://github.com/hwchase17/langchain synced 2024-10-31 15:20:26 +00:00

Leonid Ganeline e2d7677526

docs: compound ecosystem and integrations (#4870 )

# Docs: compound ecosystem and integrations

**Problem statement:** We have a big overlap between the
References/Integrations and Ecosystem/LongChain Ecosystem pages. It
confuses users. It creates a situation when new integration is added
only on one of these pages, which creates even more confusion.
- removed References/Integrations page (but move all its information
into the individual integration pages - in the next PR).
- renamed Ecosystem/LongChain Ecosystem into Integrations/Integrations.
I like the Ecosystem term. It is more generic and semantically richer
than the Integration term. But it mentally overloads users. The
`integration` term is more concrete.
UPDATE: after discussion, the Ecosystem is the term.
Ecosystem/Integrations is the page (in place of Ecosystem/LongChain
Ecosystem).

As a result, a user gets a single place to start with the individual
integration.

2023-05-18 09:29:57 -07:00

1.5 KiB

Raw Blame History

Helicone

This page covers how to use the Helicone ecosystem within LangChain.

What is Helicone?

Helicone is an open source observability platform that proxies your OpenAI traffic and provides you key insights into your spend, latency and usage.

Quick start

With your LangChain environment you can just add the following parameter.

export OPENAI_API_BASE="https://oai.hconeai.com/v1"

Now head over to helicone.ai to create your account, and add your OpenAI API key within our dashboard to view your logs.

How to enable Helicone caching

from langchain.llms import OpenAI
import openai
openai.api_base = "https://oai.hconeai.com/v1"

llm = OpenAI(temperature=0.9, headers={"Helicone-Cache-Enabled": "true"})
text = "What is a helicone?"
print(llm(text))

Helicone caching docs

How to use Helicone custom properties

from langchain.llms import OpenAI
import openai
openai.api_base = "https://oai.hconeai.com/v1"

llm = OpenAI(temperature=0.9, headers={
        "Helicone-Property-Session": "24",
        "Helicone-Property-Conversation": "support_issue_2",
        "Helicone-Property-App": "mobile",
      })
text = "What is a helicone?"
print(llm(text))

Helicone property docs

1.5 KiB Raw Blame History