Lettuce API ReferenceRoutersPipeline Routes

routers.pipeline_routes

source

The pipeline_routes.py file defines FastAPI routes for lettuce. This API provides several endpoints for different conversion workflows, including LLM-based conversion, direct database lookups, vector search, and a RAG (Retrieval Augmented Generation) pipeline.

PipelineRequest

class PipelineRequest(
  names: List[str]
  pipeline_options: PipelineOptions = Field(default_factory=PipelineOptions)
)

This class takes the format of a request to the API.

Attributes

  • name: str

    The drug name sent to a pipeline

  • pipeline_options: Optional[PipelineOptions]

    Optionally, the default values can be overridden by instantiating a PipelineOptions object. If none is supplied, default arguments are used

generate_events

async def generate_events(request: PipelineRequest)

Generate LLM output and OMOP results for a list of informal names.

Workflow

For each informal name:

  1. The first event is to Query the OMOP database for a match
  2. The second event is to fetches relevant concepts from the OMOP database
  3. Finally, the function yields results as they become available, allowing for real-time streaming.

Conditions

If the OMOP database returns a match, the LLM is not queried.

If the OMOP database does not return a match, the LLM is used to find the formal name and the OMOP database is queried for the LLM output.

Finally, the function yields the results for real-time streaming.

Parameters

  • request: PipelineRequest

    The request containing the list of informal names.

Yields

  • str JSON encoded strings of the event results. Two types are yielded:

    • llm_output: The result from the language model processing.

    • omop_output: The result from the OMOP database matching.

run_pipeline

@router.post("/")
async def run_pipeline(
  request: PipelineRequest
)

Call generate_events to run the pipeline.

Parameters

  • request: PipelineRequest

    The request containing a list of informal names

Returns

  • EventSourceResponse

    The response containing the events

run_db

@router.post("/db")
async def run_db(
  request: PipelineRequest
)

Fetch OMOP concepts for a name.

Default options can be overridden by the pipeline_options in the request.

Parameters

  • request: PipelineRequest

    An API request containing a list of informal names and the options of a pipeline

Returns

  • dict

    Details of OMOP concept(s) fetched from a database query

run_vector_search

@router.post("/vector_search")
async def run_vector_search(
  request: PipelineRequest
)

Search a vector database for a name

Default options can be overridden by pipeline_options.

A warning: if you don’t have a vector database set up under the embeddings_path, this method will build one for you. This takes a while, an hour using 2.8 GHz intel I7, 16 Gb RAM.

Parameters

  • request: PipelineRequest

    An API request containing a list of informal names and the options of a pipeline

Returns

  • list

    Details of OMOP concept(s) fetched from a vector database query

vector_llm_pipeline

@router.post("/vector_llm")
async def vector_llm_pipeline(
  request: PipelineRequest
)

Run a RAG pipeline that first checks a vector database, then uses an LLM.

This has a conditional router in it that checks whether there’s an exact match for the term. If there is an exact match, the vector search results are returned. If there is not, the vector search results are used for retrieval augmented generation.

Parameters

  • request: PipelineRequest

Returns

  • list

    Combined results from vector search and LLM processing

Routersutils