forked from Archives/langchain
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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.
47 lines
1.9 KiB
Markdown
47 lines
1.9 KiB
Markdown
# Replicate
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This page covers how to run models on Replicate within LangChain.
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## Installation and Setup
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- Create a [Replicate](https://replicate.com) account. Get your API key and set it as an environment variable (`REPLICATE_API_TOKEN`)
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- Install the [Replicate python client](https://github.com/replicate/replicate-python) with `pip install replicate`
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## Calling a model
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Find a model on the [Replicate explore page](https://replicate.com/explore), and then paste in the model name and version in this format: `owner-name/model-name:version`
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For example, for this [dolly model](https://replicate.com/replicate/dolly-v2-12b), click on the API tab. The model name/version would be: `"replicate/dolly-v2-12b:ef0e1aefc61f8e096ebe4db6b2bacc297daf2ef6899f0f7e001ec445893500e5"`
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Only the `model` param is required, but any other model parameters can also be passed in with the format `input={model_param: value, ...}`
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For example, if we were running stable diffusion and wanted to change the image dimensions:
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```
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Replicate(model="stability-ai/stable-diffusion:db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf", input={'image_dimensions': '512x512'})
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```
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*Note that only the first output of a model will be returned.*
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From here, we can initialize our model:
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```python
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llm = Replicate(model="replicate/dolly-v2-12b:ef0e1aefc61f8e096ebe4db6b2bacc297daf2ef6899f0f7e001ec445893500e5")
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```
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And run it:
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```python
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prompt = """
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Answer the following yes/no question by reasoning step by step.
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Can a dog drive a car?
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"""
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llm(prompt)
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```
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We can call any Replicate model (not just LLMs) using this syntax. For example, we can call [Stable Diffusion](https://replicate.com/stability-ai/stable-diffusion):
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```python
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text2image = Replicate(model="stability-ai/stable-diffusion:db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf", input={'image_dimensions':'512x512'})
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image_output = text2image("A cat riding a motorcycle by Picasso")
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```
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