Python SDK for Laminar AI
Project description
Python SDK for Laminar AI
Example use:
from lmnr import Laminar
l = Laminar('<YOUR_PROJECT_API_KEY>')
result = l.run(
endpoint = 'my_endpoint_name',
inputs = {'input_node_name': 'some_value'},
env = {'OPENAI_API_KEY': 'sk-some-key'},
metadata = {'session_id': 'your_custom_session_id'}
)
Resulting in:
>>> result
EndpointRunResponse(outputs={'output': {'value': [ChatMessage(role='user', content='hello')]}}, run_id='53b012d5-5759-48a6-a9c5-0011610e3669')
CLI for code generation
Basic usage
lmnr pull <pipeline_name> <pipeline_version_name> --project-api-key <PROJECT_API_KEY>
Read more here on how to get PROJECT_API_KEY
.
To import your pipeline
# submodule with the name of your pipeline will be generated in lmnr_engine.pipelines
from lmnr_engine.pipelines.my_custom_pipeline import MyCustomPipeline
pipeline = MyCustomPipeline()
res = pipeline.run(
inputs={
"instruction": "Write me a short linked post about dev tool for LLM developers which they'll love"
},
env={
"OPENAI_API_KEY": <OPENAI_API_KEY>,
}
)
print(f"RESULT:\n{res}")
Current functionality
- Supports graph generation for graphs with Input, Output, and LLM nodes only
- For LLM nodes, it only supports OpenAI and Anthropic models and doesn't support structured output
Project details
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