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Relevance AI

A simple chain

1. Install and login

Install:

pip install relevanceai

Log in and create a project and api key:

import relevanceai as rai
rai.login()

or if you are in an automated environment, set these environment variables:

RELEVANCE_API_KEY=XXXX

2. Getting started

chain = rai.create(
    name = "My chain",
    description = "The greatest chain"
)

3. Add steps to the chain

Create a step for the chain

step = PromptCompletion(
    prompt="Hello world",
)

You can run and test the individual step.

step.run()

Once you are comfortable with the step you can add it by

chain.add(step)

4. Run and test the chain

Run the chain

chain.run()

5. Configuring output

By default it'll return the full state and all outputs from each step. You can control it by:

chain.set_output(["answer"])

A chain with flexible inputs

1. Give your chain flexible inputs

Add input parameters

chain = rai.create(
    name = "My chain",
    description = "The greatest chain"
    parameters = {
        "name" : {"type" : "string"}
    }
)

2. Define the parameters inside a step

step = PromptCompletion(
    prompt="Hello world my name is ${name}",
)

Metadata

Release files for relevanceai-chains 1.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for relevanceai-chains 1.0.1
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relevanceai-chains-1.0.1.tar.gz 9.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for relevanceai-chains 1.0.1
File Interpreter ABI Platform
relevanceai_chains-1.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 23.8 kB

Release files / relevanceai-chains-1.0.1.tar.gz

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Release files / relevanceai_chains-1.0.1-py3-none-any.whl

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