Test pipeline scenarios against a saved bank of test cases. Leverage LLMs to score output so with each iteration, you move closer to the desired output.

Bulk quantitative testing

Test pipeline scenarios against a saved bank of test cases. Leverage LLMs to score output so with each iteration, you move closer to the desired output.

Shared
workspace

Iterate on pipeline scenarios together with a cross-functional team.

Shared workspace

Iterate on pipeline scenarios together with a cross-functional team.

History
tracking

Each scenario and associated outputs are saved so that you can revisit during your iteration cycles.

History tracking

Each scenario and associated outputs are saved so that you can revisit during your iteration cycles.

How it works

1
Start
with  a template
Start by selecting a pipeline you want to optimize.
2
Connect
data
Optionally, add additional pipeline scenarios with different prompts, parameters, architectures, and models.
3
Intuitive drag and drop builder
Create or upload test cases to run your scenarios against.
4
Customize & deploy  to end users
Run scenarios against test cases and further iterate!

1
Start
with  a template
Start by selecting a pipeline you want to optimize.
2
Connect
data
Optionally, add additional pipeline scenarios with different prompts, parameters, architectures, and models.
3
Intuitive drag and drop builder
Create or upload test cases to run your scenarios against.
4
Customize & deploy  to end users
Run scenarios against test cases and further iterate!

1
Start
with  a template
Start by selecting a pipeline you want to optimize.
2
Connect
data
Optionally, add additional pipeline scenarios with different prompts, parameters, architectures, and models.
3
Intuitive drag and drop builder
Create or upload test cases to run your scenarios against.
4
Customize & deploy  to end users
Run scenarios against test cases and further iterate!

1
Start
with  a template
Start by selecting a pipeline you want to optimize.
2
Connect
data
Optionally, add additional pipeline scenarios with different prompts, parameters, architectures, and models.
3
Intuitive drag and drop builder
Create or upload test cases to run your scenarios against.
4
Customize & deploy  to end users
Run scenarios against test cases and further iterate!

VectorShift Docs

Unlock advanced features and detailed guides in our extensive documentation.

Browse documentation

pipeline_setup.py

from vectorshift.node import *

from vectorshift.pipeline import *

file_node = InputNode(name='file_input', input_type='file')

model_text_node = TextNode(text='Describe this file to me.')

llm_node = OpenAI_LLMNode(

model='gpt-4.0-turbo',

system_input=model_text_node.output(),

prompt_input=fileloader_node.output()

)

output_node = OutputNode(

name='my_output',

output_type='text',