mirror of
https://github.com/hwchase17/langchain
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481d3855dc
- `llm(prompt)` -> `llm.invoke(prompt)`
- `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`)
- `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt,
config={"callbacks": callbacks})`
- `llm(prompt, **kwargs)` -> `llm.invoke(prompt, **kwargs)`
54 lines
1.8 KiB
Plaintext
54 lines
1.8 KiB
Plaintext
# 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://www.helicone.ai/signup) 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_openai 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.invoke(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_openai 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.invoke(text))
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```
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[Helicone property docs](https://docs.helicone.ai/advanced-usage/custom-properties)
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