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# 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.
54 lines
1.5 KiB
Markdown
54 lines
1.5 KiB
Markdown
# Helicone
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This page covers how to use the [Helicone](https://helicone.ai) ecosystem within LangChain.
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## What is Helicone?
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Helicone is an [open source](https://github.com/Helicone/helicone) observability platform that proxies your OpenAI traffic and provides you key insights into your spend, latency and usage.
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## Quick start
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With your LangChain environment you can just add the following parameter.
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```bash
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export OPENAI_API_BASE="https://oai.hconeai.com/v1"
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```
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Now head over to [helicone.ai](https://helicone.ai/onboarding?step=2) to create your account, and add your OpenAI API key within our dashboard to view your logs.
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## How to enable Helicone caching
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```python
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from langchain.llms import OpenAI
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import openai
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openai.api_base = "https://oai.hconeai.com/v1"
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llm = OpenAI(temperature=0.9, headers={"Helicone-Cache-Enabled": "true"})
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text = "What is a helicone?"
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print(llm(text))
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```
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[Helicone caching docs](https://docs.helicone.ai/advanced-usage/caching)
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## How to use Helicone custom properties
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```python
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from langchain.llms import OpenAI
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import openai
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openai.api_base = "https://oai.hconeai.com/v1"
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llm = OpenAI(temperature=0.9, headers={
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"Helicone-Property-Session": "24",
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"Helicone-Property-Conversation": "support_issue_2",
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"Helicone-Property-App": "mobile",
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})
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text = "What is a helicone?"
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print(llm(text))
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```
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[Helicone property docs](https://docs.helicone.ai/advanced-usage/custom-properties)
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