From 9b15c21d48a004f7870497b9effe0afe2a3c7cab Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Thu, 31 Jul 2025 17:29:23 +0100
Subject: [PATCH 01/10] Replace connectors with adaptors

---
 healthchain/io/__init__.py                    |  10 +-
 healthchain/io/base.py                        |  67 +++++--
 healthchain/io/cdaadapter.py                  | 186 ++++++++++++++++++
 healthchain/io/cdsfhiradapter.py              | 133 +++++++++++++
 healthchain/pipeline/base.py                  |  68 +------
 healthchain/pipeline/medicalcodingpipeline.py |  67 ++++---
 healthchain/pipeline/summarizationpipeline.py |  67 ++++---
 7 files changed, 462 insertions(+), 136 deletions(-)
 create mode 100644 healthchain/io/cdaadapter.py
 create mode 100644 healthchain/io/cdsfhiradapter.py

diff --git a/healthchain/io/__init__.py b/healthchain/io/__init__.py
index 1e0272e6..1a7e9fda 100644
--- a/healthchain/io/__init__.py
+++ b/healthchain/io/__init__.py
@@ -1,15 +1,21 @@
 from .containers import DataContainer, Document, Tabular
-from .base import BaseConnector
+from .base import BaseConnector, BaseAdapter
 from .cdaconnector import CdaConnector
 from .cdsfhirconnector import CdsFhirConnector
+from .cdaadapter import CdaAdapter
+from .cdsfhiradapter import CdsFhirAdapter
 
 __all__ = [
     # Containers
     "DataContainer",
     "Document",
     "Tabular",
-    # Connectors
+    # Connectors (legacy)
     "BaseConnector",
     "CdaConnector",
     "CdsFhirConnector",
+    # Adapters (new)
+    "BaseAdapter",
+    "CdaAdapter",
+    "CdsFhirAdapter",
 ]
diff --git a/healthchain/io/base.py b/healthchain/io/base.py
index b13b02dd..fc67eedc 100644
--- a/healthchain/io/base.py
+++ b/healthchain/io/base.py
@@ -1,40 +1,77 @@
 from abc import ABC, abstractmethod
-from typing import Generic, TypeVar
-from healthchain.io.containers import DataContainer
+from typing import Generic, TypeVar, Optional, Any
+from healthchain.io.containers import Document
 
-T = TypeVar("T")
+RequestType = TypeVar("RequestType")
+ResponseType = TypeVar("ResponseType")
 
 
-class BaseConnector(Generic[T], ABC):
+class BaseAdapter(Generic[RequestType, ResponseType], ABC):
     """
-    Abstract base class for all connectors in the pipeline.
+    Abstract base class for all adapters in HealthChain.
 
-    This class should be subclassed to create specific connectors.
-    Subclasses must implement the input and output methods.
+    Adapters handle conversion between external healthcare data formats
+    (CDA, CDS Hooks, etc.) and HealthChain's internal Document objects.
+
+    This class should be subclassed to create specific adapters.
+    Subclasses must implement the parse and format methods.
     """
 
+    def __init__(self, engine: Optional[Any] = None):
+        """
+        Initialize BaseAdapter with optional interop engine.
+
+        Args:
+            engine (Optional[Any]): Optional interoperability engine for format conversions.
+                                   Only used by adapters that require format conversion (e.g., CDA).
+        """
+        self.engine = engine
+
     @abstractmethod
-    def input(self, data: DataContainer[T]) -> DataContainer[T]:
+    def parse(self, request: RequestType) -> Document:
         """
-        Convert input data to the pipeline's internal format.
+        Parse external format data into HealthChain's internal Document format.
 
         Args:
-            data (DataContainer[T]): The input data to be converted.
+            request (RequestType): The external format request to be parsed.
 
         Returns:
-            DataContainer[T]: The converted data.
+            Document: The parsed data as a Document object.
         """
         pass
 
     @abstractmethod
-    def output(self, data: DataContainer[T]) -> DataContainer[T]:
+    def format(self, document: Document) -> ResponseType:
         """
-        Convert pipeline's internal format to output data.
+        Format HealthChain's internal Document into external format response.
 
         Args:
-            data (DataContainer[T]): The data to be converted for output.
+            document (Document): The Document object to be formatted.
 
         Returns:
-            DataContainer[T]: The converted output data.
+            ResponseType: The formatted response in external format.
+        """
+        pass
+
+
+# Legacy connector class for backwards compatibility
+class BaseConnector(Generic[RequestType], ABC):
+    """
+    DEPRECATED: Use BaseAdapter instead.
+
+    Abstract base class for legacy connectors.
+    """
+
+    @abstractmethod
+    def input(self, data: RequestType) -> Document:
+        """
+        DEPRECATED: Use BaseAdapter.parse() instead.
+        """
+        pass
+
+    @abstractmethod
+    def output(self, data: Document) -> ResponseType:
+        """
+        DEPRECATED: Use BaseAdapter.format() instead.
         """
         pass
diff --git a/healthchain/io/cdaadapter.py b/healthchain/io/cdaadapter.py
new file mode 100644
index 00000000..4dd7b709
--- /dev/null
+++ b/healthchain/io/cdaadapter.py
@@ -0,0 +1,186 @@
+import logging
+from typing import Optional
+
+from healthchain.io.containers import Document
+from healthchain.io.base import BaseAdapter
+from healthchain.interop import create_engine, FormatType, InteropEngine
+from healthchain.models.requests.cdarequest import CdaRequest
+from healthchain.models.responses.cdaresponse import CdaResponse
+from healthchain.fhir import (
+    create_bundle,
+    set_problem_list_item_category,
+    create_document_reference,
+    read_content_attachment,
+)
+from fhir.resources.condition import Condition
+from fhir.resources.medicationstatement import MedicationStatement
+from fhir.resources.allergyintolerance import AllergyIntolerance
+from fhir.resources.documentreference import DocumentReference
+
+log = logging.getLogger(__name__)
+
+
+class CdaAdapter(BaseAdapter[CdaRequest, CdaResponse]):
+    """
+    CdaAdapter class for handling CDA (Clinical Document Architecture) documents.
+
+    This adapter facilitates parsing CDA documents into Document objects and formatting
+    Document objects back into CDA responses. It uses the InteropEngine to convert
+    between CDA and FHIR formats, preserving clinical content while allowing for
+    manipulation of the data within HealthChain pipelines.
+
+    Attributes:
+        engine (InteropEngine): The interoperability engine for CDA conversions.
+        If not provided, the default engine is used.
+        original_cda (str): The original CDA document for use in output.
+        note_document_reference (DocumentReference): Reference to the note document
+                                                    extracted from the CDA.
+
+    Methods:
+        parse: Parses a CDA document and extracts clinical data into a Document.
+        format: Converts a Document back to CDA format and returns a CdaResponse.
+    """
+
+    def __init__(self, engine: Optional[InteropEngine] = None):
+        """
+        Initialize CdaAdapter with optional interop engine.
+
+        Args:
+            engine (Optional[InteropEngine]): Custom interop engine for CDA conversions.
+                                            If None, creates a default engine.
+        """
+        # Initialize engine with default if not provided
+        initialized_engine = engine or create_engine()
+        super().__init__(engine=initialized_engine)
+        self.engine = initialized_engine
+        self.original_cda = None
+        self.note_document_reference = None
+
+    def parse(self, cda_request: CdaRequest) -> Document:
+        """
+        Parse a CDA document and extract clinical data into a HealthChain Document object.
+
+        This method takes a CdaRequest object as input, parses it using the InteropEngine to convert
+        CDA to FHIR resources, and creates a Document object with the extracted data. It creates a
+        DocumentReference for the original CDA XML and extracts clinical data (problems, medications,
+        allergies) into FHIR resources.
+
+        Args:
+            cda_request (CdaRequest): Request object containing the CDA XML document to process.
+
+        Returns:
+            Document: A Document object containing:
+                - The extracted note text as the document data
+                - FHIR resources organized into appropriate lists:
+                  - problem_list: List of Condition resources
+                  - medication_list: List of MedicationStatement resources
+                  - allergy_list: List of AllergyIntolerance resources
+                - DocumentReference resources for the original CDA and extracted notes
+
+        Note:
+            If a DocumentReference resource is found in the converted FHIR resources,
+            it is assumed to contain the note text and is stored for later use.
+        """
+        # Store original CDA for later use
+        self.original_cda = cda_request.document
+
+        # Convert CDA to FHIR using the InteropEngine
+        fhir_resources = self.engine.to_fhir(
+            self.original_cda, src_format=FormatType.CDA
+        )
+
+        # Create a FHIR DocumentReference for the original CDA document
+        cda_document_reference = create_document_reference(
+            data=self.original_cda,
+            content_type="text/xml",
+            description="Original CDA Document processed by HealthChain",
+            attachment_title="Original CDA document in XML format",
+        )
+
+        # Extract any DocumentReference resources for notes
+        note_text = ""
+        doc = Document(data=note_text)  # Create document with empty text initially
+
+        # Create FHIR Bundle and add documents
+        doc.fhir.bundle = create_bundle()
+        doc.fhir.add_document_reference(cda_document_reference)
+
+        problem_list = []
+        medication_list = []
+        allergy_list = []
+
+        for resource in fhir_resources:
+            if isinstance(resource, Condition):
+                problem_list.append(resource)
+                set_problem_list_item_category(resource)
+            elif isinstance(resource, MedicationStatement):
+                medication_list.append(resource)
+            elif isinstance(resource, AllergyIntolerance):
+                allergy_list.append(resource)
+            elif isinstance(resource, DocumentReference):
+                if (
+                    resource.content
+                    and resource.content[0].attachment
+                    and resource.content[0].attachment.data is not None
+                ):
+                    content = read_content_attachment(resource)
+                    if content is not None:
+                        note_text = content[0]["data"]
+                        self.note_document_reference = resource
+                    else:
+                        log.warning(
+                            f"No content found in DocumentReference: {resource.id}"
+                        )
+
+        doc.fhir.problem_list = problem_list
+        doc.fhir.medication_list = medication_list
+        doc.fhir.allergy_list = allergy_list
+
+        # Update document text
+        doc.data = note_text
+
+        # Add the note document reference
+        if self.note_document_reference is not None:
+            doc.fhir.add_document_reference(
+                self.note_document_reference, parent_id=cda_document_reference.id
+            )
+
+        return doc
+
+    def format(self, document: Document) -> CdaResponse:
+        """
+        Convert a Document object back to CDA format and return the response.
+
+        This method takes a Document object containing FHIR resources (problems,
+        medications, allergies) and converts them back to CDA format using the
+        InteropEngine. It combines all resources from the document's FHIR lists
+        and includes the note document reference if available.
+
+        Args:
+            document (Document): A Document object containing FHIR resources
+                                 in problem_list, medication_list, and allergy_list.
+
+        Returns:
+            CdaResponse: A response object containing the CDA document generated
+                        from the FHIR resources.
+        """
+        # Collect all FHIR resources to convert to CDA
+        resources = []
+
+        if document.fhir.problem_list:
+            resources.extend(document.fhir.problem_list)
+
+        if document.fhir.allergy_list:
+            resources.extend(document.fhir.allergy_list)
+
+        if document.fhir.medication_list:
+            resources.extend(document.fhir.medication_list)
+
+        # Add the note document reference
+        if self.note_document_reference is not None:
+            resources.append(self.note_document_reference)
+
+        # Convert FHIR resources to CDA using InteropEngine
+        response_document = self.engine.from_fhir(resources, dest_format=FormatType.CDA)
+
+        return CdaResponse(document=response_document)
diff --git a/healthchain/io/cdsfhiradapter.py b/healthchain/io/cdsfhiradapter.py
new file mode 100644
index 00000000..882071a3
--- /dev/null
+++ b/healthchain/io/cdsfhiradapter.py
@@ -0,0 +1,133 @@
+import logging
+from typing import Optional, Any
+
+from fhir.resources.documentreference import DocumentReference
+
+from healthchain.io.containers import Document
+from healthchain.io.base import BaseAdapter
+from healthchain.models.requests.cdsrequest import CDSRequest
+from healthchain.models.responses.cdsresponse import CDSResponse
+from healthchain.fhir import read_content_attachment
+from healthchain.models.hooks.prefetch import Prefetch
+
+log = logging.getLogger(__name__)
+
+
+class CdsFhirAdapter(BaseAdapter[CDSRequest, CDSResponse]):
+    """
+    CdsFhirAdapter class for handling FHIR (Fast Healthcare Interoperability Resources) documents
+    for CDS Hooks.
+
+    This adapter facilitates the conversion between CDSRequest objects and Document objects,
+    as well as the creation of CDSResponse objects from processed Documents. Unlike CdaAdapter,
+    this adapter works directly with FHIR data and does not require interop conversion.
+
+    Attributes:
+        hook_name (str): The name of the CDS Hook being used.
+        engine (Optional[Any]): Optional interoperability engine (not used by this adapter).
+
+    Methods:
+        parse: Converts a CDSRequest object into a Document object.
+        format: Converts a Document object into a CDSResponse object.
+    """
+
+    def __init__(self, hook_name: str = None, engine: Optional[Any] = None):
+        """
+        Initialize CdsFhirAdapter with hook name and optional engine.
+
+        Args:
+            hook_name (str): The name of the CDS Hook being used. Defaults to None.
+            engine (Optional[Any]): Optional interoperability engine (not used by this adapter).
+        """
+        super().__init__(engine=engine)
+        self.hook_name = hook_name
+
+    def parse(
+        self, cds_request: CDSRequest, prefetch_document_key: Optional[str] = "document"
+    ) -> Document:
+        """
+        Convert a CDSRequest object into a Document object.
+
+        Takes a CDSRequest containing FHIR resources and extracts them into a Document object.
+        The Document will contain all prefetched FHIR resources in its fhir.prefetch_resources.
+        If a DocumentReference resource is provided via prefetch_document_key, its text content
+        will be extracted into Document.data. For multiple attachments, the text content will be
+        concatenated with newlines.
+
+        Args:
+            cds_request (CDSRequest): The CDSRequest containing FHIR resources in its prefetch
+                and/or a FHIR server URL.
+            prefetch_document_key (str, optional): Key in the prefetch data containing a
+                DocumentReference resource whose text content should be extracted.
+                Defaults to "document".
+
+        Returns:
+            Document: A Document object containing:
+                - All prefetched FHIR resources in fhir.prefetch_resources
+                - Any text content from the DocumentReference in data (empty string if none found)
+                - For multiple attachments, text content is concatenated with newlines
+
+        Raises:
+            ValueError: If neither prefetch nor fhirServer is provided in cds_request
+            ValueError: If the prefetch data is invalid or cannot be processed
+            NotImplementedError: If fhirServer is provided (FHIR server support not implemented)
+        """
+        if cds_request.prefetch is None and cds_request.fhirServer is None:
+            raise ValueError(
+                "Either prefetch or fhirServer must be provided to extract FHIR data!"
+            )
+
+        if cds_request.fhirServer is not None:
+            raise NotImplementedError("FHIR server is not implemented yet!")
+
+        # Create an empty Document object
+        doc = Document(data="")
+
+        # Validate the prefetch data
+        validated_prefetch = Prefetch(prefetch=cds_request.prefetch)
+
+        # Set the prefetch resources
+        doc.fhir.prefetch_resources = validated_prefetch.prefetch
+
+        # Extract text content from DocumentReference resource if provided
+        document_resource = validated_prefetch.prefetch.get(prefetch_document_key)
+
+        if not document_resource:
+            log.warning(
+                f"No DocumentReference resource found in prefetch data with key {prefetch_document_key}"
+            )
+        elif isinstance(document_resource, DocumentReference):
+            try:
+                attachments = read_content_attachment(
+                    document_resource, include_data=True
+                )
+                for attachment in attachments:
+                    if len(attachments) > 1:
+                        doc.data += attachment.get("data", "") + "\n"
+                    else:
+                        doc.data += attachment.get("data", "")
+            except Exception as e:
+                log.warning(f"Error extracting text from DocumentReference: {e}")
+
+        return doc
+
+    def format(self, document: Document) -> CDSResponse:
+        """
+        Convert Document to CDSResponse.
+
+        This method takes a Document object containing CDS cards and actions,
+        and converts them into a CDSResponse object that follows the CDS Hooks
+        specification.
+
+        Args:
+            document (Document): The Document object containing CDS results.
+
+        Returns:
+            CDSResponse: A response object containing CDS cards and optional system actions.
+                         If no cards are found in the Document, an empty list of cards is returned.
+        """
+        if document.cds.cards is None:
+            log.warning("No CDS cards found in Document, returning empty list of cards")
+            return CDSResponse(cards=[])
+
+        return CDSResponse(cards=document.cds.cards, systemActions=document.cds.actions)
diff --git a/healthchain/pipeline/base.py b/healthchain/pipeline/base.py
index f557c80e..540017ff 100644
--- a/healthchain/pipeline/base.py
+++ b/healthchain/pipeline/base.py
@@ -19,7 +19,6 @@
 from dataclasses import dataclass, field
 from enum import Enum
 
-from healthchain.io.base import BaseConnector
 from healthchain.io.containers import DataContainer
 from healthchain.pipeline.components.base import BaseComponent
 
@@ -80,8 +79,7 @@ class BasePipeline(Generic[T], ABC):
 
     The BasePipeline class provides a framework for building modular data processing pipelines
     by allowing users to add, remove, and configure components with defined dependencies and
-    execution order. Components can be added at specific positions, grouped into stages, and
-    connected via input/output connectors.
+    execution order. Components can be added at specific positions and grouped into stages.
 
     This is an abstract base class that should be subclassed to create specific pipeline
     implementations.
@@ -90,28 +88,23 @@ class BasePipeline(Generic[T], ABC):
         _components (List[PipelineNode[T]]): Ordered list of pipeline components
         _stages (Dict[str, List[Callable]]): Components grouped by processing stage
         _built_pipeline (Optional[Callable]): Compiled pipeline function
-        _input_connector (Optional[BaseConnector[T]]): Connector for processing input data
-        _output_connector (Optional[BaseConnector[T]]): Connector for processing output data
         _output_template (Optional[str]): Template string for formatting pipeline outputs
-        _model_config (Optional[ModelConfig]): Configuration for the pipeline model
 
     Example:
-        >>> class MyPipeline(BasePipeline[str]):
+        >>> class MyPipeline(BasePipeline[Document]):
         ...     def configure_pipeline(self, config: ModelConfig) -> None:
         ...         self.add_node(preprocess, stage="preprocessing")
         ...         self.add_node(process, stage="processing")
         ...         self.add_node(postprocess, stage="postprocessing")
         ...
         >>> pipeline = MyPipeline()
-        >>> result = pipeline("input text")
+        >>> result = pipeline(document)  # Document → Document
     """
 
     def __init__(self):
         self._components: List[PipelineNode[T]] = []
         self._stages: Dict[str, List[Callable]] = {}
         self._built_pipeline: Optional[Callable] = None
-        self._input_connector: Optional[BaseConnector[T]] = None
-        self._output_connector: Optional[BaseConnector[T]] = None
         self._output_template: Optional[str] = None
         self._output_template_path: Optional[Path] = None
 
@@ -350,10 +343,9 @@ def configure_pipeline(self, model_config: ModelConfig) -> None:
         This method should be implemented by subclasses to add specific components
         and configure the pipeline according to the given model configuration.
         The configuration typically involves:
-        1. Setting up input/output connectors
-        2. Adding model components based on the model source
-        3. Adding any additional processing nodes
-        4. Configuring the pipeline stages and execution order
+        1. Adding model components based on the model source
+        2. Adding any additional processing nodes
+        3. Configuring the pipeline stages and execution order
 
         Args:
             model_config (ModelConfig): Configuration object containing:
@@ -371,17 +363,12 @@ def configure_pipeline(self, model_config: ModelConfig) -> None:
 
         Example:
             >>> def configure_pipeline(self, config: ModelConfig):
-            ...     # Add FHIR connector for input/output
-            ...     connector = FhirConnector()
-            ...     self.add_input(connector)
-            ...
             ...     # Add model component
             ...     model = self.get_model_component(config)
             ...     self.add_node(model, stage="processing")
             ...
             ...     # Add output formatting
             ...     self.add_node(OutputFormatter(), stage="formatting")
-            ...     self.add_output(connector)
         """
         raise NotImplementedError("This method must be implemented by subclasses.")
 
@@ -419,44 +406,6 @@ def stages(self, new_stages: Dict[str, List[Callable]]):
         """
         self._stages = new_stages
 
-    def add_input(self, connector: BaseConnector[T]) -> None:
-        """
-        Adds an input connector to the pipeline.
-
-        This method sets the input connector for the pipeline, which is responsible
-        for processing the input data before it's passed to the pipeline components.
-
-        Args:
-            connector (Connector[T]): The input connector to be added to the pipeline.
-
-        Returns:
-            None
-
-        Note:
-            Only one input connector can be set for the pipeline. If this method is
-            called multiple times, the last connector will overwrite the previous ones.
-        """
-        self._input_connector = connector
-
-    def add_output(self, connector: BaseConnector[T]) -> None:
-        """
-        Adds an output connector to the pipeline.
-
-        This method sets the output connector for the pipeline, which is responsible
-        for processing the output data after it has passed through all pipeline components.
-
-        Args:
-            connector (Connector[T]): The output connector to be added to the pipeline.
-
-        Returns:
-            None
-
-        Note:
-            Only one output connector can be set for the pipeline. If this method is
-            called multiple times, the last connector will overwrite the previous ones.
-        """
-        self._output_connector = connector
-
     def add_node(
         self,
         component: Union[
@@ -771,15 +720,10 @@ def resolve_dependencies():
         ordered_components = resolve_dependencies()
 
         def pipeline(data: Union[T, DataContainer[T]]) -> DataContainer[T]:
-            if self._input_connector:
-                data = self._input_connector.input(data)
-
             if not isinstance(data, DataContainer):
                 data = DataContainer(data)
 
             data = reduce(lambda d, comp: comp(d), ordered_components, data)
-            if self._output_connector:
-                data = self._output_connector.output(data)
 
             return data
 
diff --git a/healthchain/pipeline/medicalcodingpipeline.py b/healthchain/pipeline/medicalcodingpipeline.py
index eb70fc16..301ab1a0 100644
--- a/healthchain/pipeline/medicalcodingpipeline.py
+++ b/healthchain/pipeline/medicalcodingpipeline.py
@@ -1,36 +1,24 @@
-from healthchain.io.cdaconnector import CdaConnector
 from healthchain.pipeline.base import BasePipeline, ModelConfig
 from healthchain.pipeline.mixins import ModelRoutingMixin
 
 
 class MedicalCodingPipeline(BasePipeline, ModelRoutingMixin):
     """
-    A pipeline for medical coding tasks using NLP models.
-
-    This pipeline processes clinical documents using medical NLP models to extract
-    and code medical concepts. It uses CDA format for input/output handling and
-    supports named entity recognition and linking (NER+L) to medical ontologies.
-
-    The pipeline consists of the following stages:
-    1. Input: CDA connector loads clinical documents
-    2. NER+L: Medical NLP model extracts and links medical concepts
-    3. Output: Returns coded results via CDA connector
-
-    Examples:
-        >>> # Using with SpaCy/MedCAT
-        >>> pipeline = MedicalCodingPipeline.from_model_id("medcatlite", source="spacy")
-        >>> cda_response = pipeline(documents)
-        >>>
-        >>> # Using with Hugging Face
-        >>> pipeline = MedicalCodingPipeline.from_model_id(
-        ...     "bert-base-uncased",
-        ...     task="ner"
-        ... )
-        >>> # Using with LangChain
+    Pipeline for extracting and coding medical concepts from clinical documents using NLP models.
+
+    Stages:
+        1. NER+L: Extracts and links medical concepts from document text.
+
+    Usage Examples:
+        # With SpaCy
+        >>> pipeline = MedicalCodingPipeline.from_model_id("en_core_sci_sm", source="spacy")
+
+        # With Hugging Face
+        >>> pipeline = MedicalCodingPipeline.from_model_id("bert-base-uncased", task="ner")
+
+        # With LangChain
         >>> chain = ChatPromptTemplate.from_template("Extract medical codes: {text}") | ChatOpenAI()
         >>> pipeline = MedicalCodingPipeline.load(chain)
-        >>>
-        >>> cda_response = pipeline(documents)
     """
 
     def __init__(self):
@@ -38,15 +26,36 @@ def __init__(self):
         ModelRoutingMixin.__init__(self)
 
     def configure_pipeline(self, config: ModelConfig) -> None:
-        """Configure pipeline with CDA connector and NER+L model.
+        """Configure pipeline with NER+L model.
 
         Args:
             config (ModelConfig): Configuration for the NER+L model
         """
-        cda_connector = CdaConnector()
         config.task = "ner"  # set task if hf
         model = self.get_model_component(config)
 
-        self.add_input(cda_connector)
         self.add_node(model, stage="ner+l")
-        self.add_output(cda_connector)
+
+    def process_request(self, request, adapter=None):
+        """
+        Process a CDA request and return CDA response using an adapter.
+
+        Args:
+            request: CdaRequest object
+            adapter: Optional CdaAdapter instance
+
+        Returns:
+            CdaResponse: Processed response
+
+        Example:
+            >>> pipeline = MedicalCodingPipeline.from_model_id("en_core_sci_sm", source="spacy")
+            >>> response = pipeline.process_request(cda_request)  # CdaRequest → CdaResponse
+        """
+        if adapter is None:
+            from healthchain.io import CdaAdapter
+
+            adapter = CdaAdapter()
+
+        doc = adapter.parse(request)
+        doc = self(doc)
+        return adapter.format(doc)
diff --git a/healthchain/pipeline/summarizationpipeline.py b/healthchain/pipeline/summarizationpipeline.py
index d13091de..fd3eb21f 100644
--- a/healthchain/pipeline/summarizationpipeline.py
+++ b/healthchain/pipeline/summarizationpipeline.py
@@ -2,34 +2,23 @@
 from healthchain.pipeline.components import CdsCardCreator
 from healthchain.pipeline.modelrouter import ModelConfig
 from healthchain.pipeline.mixins import ModelRoutingMixin
-from healthchain.io import CdsFhirConnector
 
 
 class SummarizationPipeline(BasePipeline, ModelRoutingMixin):
     """
-    A pipeline for text summarization tasks using NLP models.
-
-    This pipeline processes clinical documents using a summarization model to generate
-    concise summaries. It uses CDS FHIR format for input/output handling and creates
-    CDS Hooks cards containing the generated summaries.
-
-    The pipeline consists of the following stages:
-    1. Input: CDS FHIR connector loads clinical documents
-    2. Summarization: NLP model generates summaries
-    3. Card Creation: Formats summaries into CDS Hooks cards
-    4. Output: Returns cards via CDS FHIR connector
-
-    Examples:
-        >>> # Using with GPT model
-        >>> pipeline = SummarizationPipeline.from_model_id("gpt-4o", source="openai")
-        >>> cds_response = pipeline(documents)
-        >>>
-        >>> # Using with Hugging Face
-        >>> pipeline = SummarizationPipeline.from_model_id(
-        ...     "facebook/bart-large-cnn",
-        ...     task="summarization"
-        ... )
-        >>> cds_response = pipeline(documents)
+    Pipeline for generating summaries from clinical documents using NLP models.
+
+    Stages:
+        1. Summarization: Generates summaries from document text.
+        2. Card Creation: Formats summaries into CDS Hooks cards.
+
+    Usage Examples:
+        # With Hugging Face
+        >>> pipeline = SummarizationPipeline.from_model_id("facebook/bart-large-cnn", source="huggingface")
+
+        # With LangChain
+        >>> chain = ChatPromptTemplate.from_template("Summarize: {text}") | ChatOpenAI()
+        >>> pipeline = SummarizationPipeline.load(chain)
     """
 
     def __init__(self):
@@ -37,16 +26,14 @@ def __init__(self):
         ModelRoutingMixin.__init__(self)
 
     def configure_pipeline(self, config: ModelConfig) -> None:
-        """Configure pipeline with FHIR connector and summarization model.
+        """Configure pipeline with summarization model and card creator.
 
         Args:
             config: Model configuration for the summarization model
         """
-        cds_fhir_connector = CdsFhirConnector(hook_name="encounter-discharge")
         config.task = "summarization"
         model = self.get_model_component(config)
 
-        self.add_input(cds_fhir_connector)
         self.add_node(model, stage="summarization")
         self.add_node(
             CdsCardCreator(
@@ -58,4 +45,28 @@ def configure_pipeline(self, config: ModelConfig) -> None:
             ),
             stage="card-creation",
         )
-        self.add_output(cds_fhir_connector)
+
+    def process_request(self, request, hook_name=None, adapter=None):
+        """
+        Process a CDS request and return CDS response using an adapter.
+
+        Args:
+            request: CDSRequest object
+            hook_name: CDS hook name for the adapter
+            adapter: Optional CdsFhirAdapter instance
+
+        Returns:
+            CDSResponse: Processed CDS response with cards
+
+        Example:
+            >>> pipeline = SummarizationPipeline.from_model_id("facebook/bart-large-cnn", source="huggingface")
+            >>> response = pipeline.process_request(cds_request)  # CDSRequest → CDSResponse
+        """
+        if adapter is None:
+            from healthchain.io import CdsFhirAdapter
+
+            adapter = CdsFhirAdapter(hook_name=hook_name)
+
+        doc = adapter.parse(request)
+        doc = self(doc)
+        return adapter.format(doc)

From e0384518493191bfd867786c2bbbbffb6f272f3c Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Thu, 31 Jul 2025 17:29:49 +0100
Subject: [PATCH 02/10] Update tests

---
 tests/pipeline/conftest.py                    | 41 ++++++++++
 tests/pipeline/prebuilt/test_medicalcoding.py | 73 +++++++++++-------
 tests/pipeline/prebuilt/test_summarization.py | 77 +++++++++++++------
 tests/pipeline/test_pipeline.py               | 19 -----
 4 files changed, 138 insertions(+), 72 deletions(-)

diff --git a/tests/pipeline/conftest.py b/tests/pipeline/conftest.py
index 349b5a62..45299a6d 100644
--- a/tests/pipeline/conftest.py
+++ b/tests/pipeline/conftest.py
@@ -137,6 +137,47 @@ def mock_cda_connector(test_document):
         yield mock
 
 
+# Adapter fixtures
+
+
+@pytest.fixture
+def mock_cda_adapter():
+    with patch("healthchain.io.cdaadapter.CdaAdapter") as mock:
+        adapter_instance = mock.return_value
+
+        # Mock parse method
+        adapter_instance.parse.return_value = Document(data="Test note")
+
+        # Mock format method
+        adapter_instance.format.return_value = CdaResponse(
+            document="<xml>Updated CDA</xml>"
+        )
+
+        yield mock
+
+
+@pytest.fixture
+def mock_cds_fhir_adapter():
+    with patch("healthchain.io.cdsfhiradapter.CdsFhirAdapter") as mock:
+        adapter_instance = mock.return_value
+
+        # Mock parse method
+        adapter_instance.parse.return_value = Document(data="Test CDS data")
+
+        # Mock format method
+        adapter_instance.format.return_value = CDSResponse(
+            cards=[
+                Card(
+                    summary="Summarized discharge information",
+                    indicator="info",
+                    source={"label": "Test Source"},
+                )
+            ]
+        )
+
+        yield mock
+
+
 # NLP component fixtures
 
 
diff --git a/tests/pipeline/prebuilt/test_medicalcoding.py b/tests/pipeline/prebuilt/test_medicalcoding.py
index 05f5f205..dd3f62df 100644
--- a/tests/pipeline/prebuilt/test_medicalcoding.py
+++ b/tests/pipeline/prebuilt/test_medicalcoding.py
@@ -3,12 +3,12 @@
 from healthchain.models.responses.cdaresponse import CdaResponse
 from healthchain.pipeline.base import ModelConfig, ModelSource
 from healthchain.pipeline.medicalcodingpipeline import MedicalCodingPipeline
+from healthchain.io.containers import Document
 
 
-def test_coding_pipeline(mock_cda_connector, mock_spacy_nlp):
+def test_coding_pipeline(mock_spacy_nlp, test_document):
+    """Test pure pipeline processing (Document → Document)"""
     with patch(
-        "healthchain.pipeline.medicalcodingpipeline.CdaConnector", mock_cda_connector
-    ), patch(
         "healthchain.pipeline.mixins.ModelRoutingMixin.get_model_component",
         mock_spacy_nlp,
     ):
@@ -21,19 +21,13 @@ def test_coding_pipeline(mock_cda_connector, mock_spacy_nlp):
         )
         pipeline.configure_pipeline(config)
 
-        # Create a sample CdaRequest
-        test_cda_request = CdaRequest(document="<xml>Sample CDA</xml>")
-
-        # Process the request through the pipeline
-        cda_response = pipeline(test_cda_request)
-
-        # Assertions
-        assert isinstance(cda_response, CdaResponse)
-        assert cda_response.document == "<xml>Updated CDA</xml>"
+        # Process Document through pure pipeline
+        result_doc = pipeline(test_document)
 
-        # Verify that CdaConnector methods were called correctly
-        mock_cda_connector.return_value.input.assert_called_once_with(test_cda_request)
-        mock_cda_connector.return_value.output.assert_called_once()
+        # Assertions - pipeline should return processed Document
+        assert isinstance(result_doc, Document)
+        assert result_doc.data == "Test note"
+        assert result_doc.fhir.problem_list[0].code.coding[0].display == "Hypertension"
 
         # Verify that the Model was called
         mock_spacy_nlp.assert_called_once_with(
@@ -47,25 +41,45 @@ def test_coding_pipeline(mock_cda_connector, mock_spacy_nlp):
         )
         mock_spacy_nlp.return_value.assert_called_once()
 
-        # Verify the pipeline used the mocked input and output
-        input_doc = mock_cda_connector.return_value.input.return_value
-        assert input_doc.data == "Test note"
-        assert input_doc.fhir.problem_list[0].code.coding[0].display == "Hypertension"
-        assert (
-            input_doc.fhir.medication_list[0].medication.concept.coding[0].display
-            == "Aspirin"
-        )
-        assert (
-            input_doc.fhir.allergy_list[0].code.coding[0].display
-            == "Allergy to peanuts"
-        )
-
         # Verify stages are set correctly
         assert len(pipeline._stages) == 1
         assert "ner+l" in pipeline._stages
 
 
+def test_coding_pipeline_process_request(mock_spacy_nlp, mock_cda_adapter):
+    """Test process_request method with adapter"""
+    with patch(
+        "healthchain.pipeline.mixins.ModelRoutingMixin.get_model_component",
+        mock_spacy_nlp,
+    ), patch("healthchain.io.CdaAdapter", mock_cda_adapter):
+        pipeline = MedicalCodingPipeline()
+        config = ModelConfig(
+            source=ModelSource.SPACY,
+            pipeline_object="en_core_sci_sm",
+            path=None,
+            kwargs={},
+        )
+        pipeline.configure_pipeline(config)
+
+        # Create a sample CdaRequest
+        test_cda_request = CdaRequest(document="<xml>Sample CDA</xml>")
+
+        # Process via convenience method
+        cda_response = pipeline.process_request(test_cda_request)
+
+        # Assertions
+        assert isinstance(cda_response, CdaResponse)
+
+        # Verify adapter was used correctly
+        mock_cda_adapter.return_value.parse.assert_called_once_with(test_cda_request)
+        mock_cda_adapter.return_value.format.assert_called_once()
+
+        # Verify model was called
+        mock_spacy_nlp.return_value.assert_called_once()
+
+
 def test_full_coding_pipeline_integration(mock_spacy_nlp, test_cda_request):
+    """Test integration with process_request method"""
     with patch(
         "healthchain.pipeline.mixins.ModelRoutingMixin.get_model_component",
         mock_spacy_nlp,
@@ -74,7 +88,8 @@ def test_full_coding_pipeline_integration(mock_spacy_nlp, test_cda_request):
             "./spacy/path/to/production/model", source="spacy"
         )
 
-        cda_response = pipeline(test_cda_request)
+        # Use process_request for end-to-end processing
+        cda_response = pipeline.process_request(test_cda_request)
 
         assert isinstance(cda_response, CdaResponse)
 
diff --git a/tests/pipeline/prebuilt/test_summarization.py b/tests/pipeline/prebuilt/test_summarization.py
index 392cb984..a98aa00e 100644
--- a/tests/pipeline/prebuilt/test_summarization.py
+++ b/tests/pipeline/prebuilt/test_summarization.py
@@ -2,19 +2,16 @@
 from healthchain.models.responses.cdsresponse import CDSResponse
 from healthchain.pipeline.base import ModelConfig, ModelSource
 from healthchain.pipeline.summarizationpipeline import SummarizationPipeline
+from healthchain.io.containers import Document
 
 
 def test_summarization_pipeline(
-    mock_cds_fhir_connector,
     mock_hf_transformer,
     mock_cds_card_creator,
-    test_cds_request,
-    test_condition,
+    test_document,
 ):
+    """Test pure pipeline processing (Document → Document)"""
     with patch(
-        "healthchain.pipeline.summarizationpipeline.CdsFhirConnector",
-        mock_cds_fhir_connector,
-    ), patch(
         "healthchain.pipeline.mixins.ModelRoutingMixin.get_model_component",
         mock_hf_transformer,
     ), patch(
@@ -31,19 +28,11 @@ def test_summarization_pipeline(
         )
         pipeline.configure_pipeline(config)
 
-        # Process the request through the pipeline
-        cds_response = pipeline(test_cds_request)
+        # Process Document through pure pipeline
+        result_doc = pipeline(test_document)
 
-        # Assertions
-        assert isinstance(cds_response, CDSResponse)
-        assert len(cds_response.cards) == 1
-        assert cds_response.cards[0].summary == "Summarized discharge information"
-
-        # Verify that CdsFhirConnector methods were called correctly
-        mock_cds_fhir_connector.return_value.input.assert_called_once_with(
-            test_cds_request
-        )
-        mock_cds_fhir_connector.return_value.output.assert_called_once()
+        # Assertions - pipeline should return processed Document
+        assert isinstance(result_doc, Document)
 
         # Verify that the LLM was called
         mock_hf_transformer.assert_called_once_with(
@@ -65,20 +54,59 @@ def test_summarization_pipeline(
             delimiter="\n",
         )
 
-        # Verify the pipeline used the mocked input and output
-        input_data = mock_cds_fhir_connector.return_value.input.return_value
-
-        assert input_data.fhir.get_prefetch_resources("problem") == test_condition
-
         # Verify stages are set correctly
         assert len(pipeline._stages) == 2
         assert "summarization" in pipeline._stages
         assert "card-creation" in pipeline._stages
 
 
+def test_summarization_pipeline_process_request(
+    mock_hf_transformer,
+    mock_cds_card_creator,
+    mock_cds_fhir_adapter,
+    test_cds_request,
+):
+    """Test process_request method with adapter"""
+    with patch(
+        "healthchain.pipeline.mixins.ModelRoutingMixin.get_model_component",
+        mock_hf_transformer,
+    ), patch(
+        "healthchain.pipeline.summarizationpipeline.CdsCardCreator",
+        mock_cds_card_creator,
+    ), patch(
+        "healthchain.io.CdsFhirAdapter",
+        mock_cds_fhir_adapter,
+    ):
+        pipeline = SummarizationPipeline()
+        config = ModelConfig(
+            source=ModelSource.HUGGINGFACE,
+            pipeline_object="llama3",
+            task="summarization",
+            path=None,
+            kwargs={},
+        )
+        pipeline.configure_pipeline(config)
+
+        # Process via convenience method
+        cds_response = pipeline.process_request(test_cds_request)
+
+        # Assertions
+        assert isinstance(cds_response, CDSResponse)
+
+        # Verify adapter was used correctly
+        mock_cds_fhir_adapter.return_value.parse.assert_called_once_with(
+            test_cds_request
+        )
+        mock_cds_fhir_adapter.return_value.format.assert_called_once()
+
+        # Verify model was called
+        mock_hf_transformer.return_value.assert_called_once()
+
+
 def test_full_summarization_pipeline_integration(
     mock_hf_transformer, test_cds_request, tmp_path
 ):
+    """Test integration with process_request method"""
     # Use mock LLM object for now
     with patch(
         "healthchain.pipeline.mixins.ModelRoutingMixin.get_model_component",
@@ -100,7 +128,8 @@ def test_full_summarization_pipeline_integration(
             "llama3", source="huggingface", template_path=template_file
         )
 
-        cds_response = pipeline(test_cds_request)
+        # Use process_request for end-to-end processing
+        cds_response = pipeline.process_request(test_cds_request)
 
         assert isinstance(cds_response, CDSResponse)
         assert len(cds_response.cards) == 1
diff --git a/tests/pipeline/test_pipeline.py b/tests/pipeline/test_pipeline.py
index 03351d07..d9e02b78 100644
--- a/tests/pipeline/test_pipeline.py
+++ b/tests/pipeline/test_pipeline.py
@@ -187,25 +187,6 @@ def test_build_and_execute_pipeline(mock_basic_pipeline):
         mock_basic_pipeline.build()
 
 
-def test_pipeline_with_connectors(mock_basic_pipeline):
-    # Test with input and output connectors
-    class MockConnector:
-        def input(self, data):
-            data.data += 10
-            return data
-
-        def output(self, data):
-            data.data *= 2
-            return data
-
-    mock_basic_pipeline.add_input(MockConnector())
-    mock_basic_pipeline.add_node(mock_component)
-    mock_basic_pipeline.add_output(MockConnector())
-
-    result = mock_basic_pipeline(DataContainer(1))
-    assert result.data == 24  # (1 + 10 + 1) * 2
-
-
 # Test input and output model validation
 def test_input_output_validation(mock_basic_pipeline):
     def validated_component(data: DataContainer) -> DataContainer:

From b643877e2458022dabfe8ac43dce364357dd4e88 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Thu, 31 Jul 2025 17:30:16 +0100
Subject: [PATCH 03/10] Update docs

---
 docs/api/adapters.md                          |  4 +
 docs/api/connectors.md                        |  4 +-
 docs/cookbook/cds_sandbox.md                  |  8 +-
 docs/cookbook/notereader_sandbox.md           |  4 +-
 docs/quickstart.md                            | 25 +++---
 docs/reference/gateway/cdshooks.md            | 56 +++++++++++++
 docs/reference/pipeline/adapters/adapters.md  | 84 +++++++++++++++++++
 .../reference/pipeline/adapters/cdaadapter.md | 35 ++++++++
 .../pipeline/adapters/cdsfhiradapter.md       | 72 ++++++++++++++++
 .../pipeline/connectors/cdaconnector.md       |  6 +-
 .../pipeline/connectors/cdsfhirconnector.md   |  6 +-
 .../pipeline/connectors/connectors.md         | 34 +++++++-
 docs/reference/pipeline/pipeline.md           | 49 +++++++----
 mkdocs.yml                                    |  7 +-
 14 files changed, 352 insertions(+), 42 deletions(-)
 create mode 100644 docs/api/adapters.md
 create mode 100644 docs/reference/pipeline/adapters/adapters.md
 create mode 100644 docs/reference/pipeline/adapters/cdaadapter.md
 create mode 100644 docs/reference/pipeline/adapters/cdsfhiradapter.md

diff --git a/docs/api/adapters.md b/docs/api/adapters.md
new file mode 100644
index 00000000..889ca1d1
--- /dev/null
+++ b/docs/api/adapters.md
@@ -0,0 +1,4 @@
+# Adapters
+
+::: healthchain.io.cdaadapter
+::: healthchain.io.cdsfhiradapter
diff --git a/docs/api/connectors.md b/docs/api/connectors.md
index c633cc11..dacd769d 100644
--- a/docs/api/connectors.md
+++ b/docs/api/connectors.md
@@ -1,4 +1,6 @@
-# Connectors
+# Connectors (Legacy)
+
+> **⚠️ Deprecated:** Connectors are deprecated. Use [Adapters](adapters.md) for new projects.
 
 ::: healthchain.io.base
 ::: healthchain.io.cdaconnector
diff --git a/docs/cookbook/cds_sandbox.md b/docs/cookbook/cds_sandbox.md
index 12467033..2cfe69ef 100644
--- a/docs/cookbook/cds_sandbox.md
+++ b/docs/cookbook/cds_sandbox.md
@@ -35,7 +35,7 @@ If you are using a chat model, we recommend you initialize the pipeline with the
 
 === "Non-chat model"
     ```python
-    from healthchain.pipelines import SummarizationPipeline
+    from healthchain.pipeline import SummarizationPipeline
 
     pipeline = SummarizationPipeline.from_model_id(
       "google/pegasus-xsum", source="huggingface", task="summarization"
@@ -45,7 +45,7 @@ If you are using a chat model, we recommend you initialize the pipeline with the
 
 === "Chat model"
     ```python
-    from healthchain.pipelines import SummarizationPipeline
+    from healthchain.pipeline import SummarizationPipeline
 
     from langchain_huggingface.llms import HuggingFaceEndpoint
     from langchain_huggingface import ChatHuggingFace
@@ -96,7 +96,7 @@ class DischargeNoteSummarizer(ClinicalDecisionSupport):
 
     @hc.api
     def my_service(self, request: CDSRequest) -> CDSResponse:
-        result = self.pipeline(request)
+        result = self.pipeline.process_request(request)
         return result
 ```
 
@@ -147,7 +147,7 @@ class DischargeNoteSummarizer(ClinicalDecisionSupport):
 
   @hc.api
   def my_service(self, request: CDSRequest) -> CDSResponse:
-    result = self.pipeline(request)
+    result = self.pipeline.process_request(request)
     return result
 
   @hc.ehr(workflow="encounter-discharge")
diff --git a/docs/cookbook/notereader_sandbox.md b/docs/cookbook/notereader_sandbox.md
index 8c9573e7..1e6cdcc8 100644
--- a/docs/cookbook/notereader_sandbox.md
+++ b/docs/cookbook/notereader_sandbox.md
@@ -10,7 +10,7 @@ import healthchain as hc
 from healthchain.io import Document
 from healthchain.models.requests import CdaRequest
 from healthchain.models.responses import CdaResponse
-from healthchain.pipeline.medicalcodingpipeline import MedicalCodingPipeline
+from healthchain.pipeline import MedicalCodingPipeline
 from healthchain.sandbox.use_cases import ClinicalDocumentation
 from healthchain.fhir import create_document_reference
 
@@ -64,7 +64,7 @@ class NotereaderSandbox(ClinicalDocumentation):
 
     @hc.api
     def my_service(self, request: CdaRequest) -> CdaResponse:
-        result = self.pipeline(request)
+        result = self.pipeline.process_request(request)
 
         return result
 
diff --git a/docs/quickstart.md b/docs/quickstart.md
index 660ca885..b586dade 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -102,30 +102,31 @@ doc = Document("Patient presents with hypertension.")
 output = pipe(doc)
 ```
 
-Let's go one step further! You can use [Connectors](./reference/pipeline/connectors/connectors.md) to work directly with [CDA](https://www.hl7.org.uk/standards/hl7-standards/cda-clinical-document-architecture/) and [FHIR](https://hl7.org/fhir/) data received from healthcare system APIs. Add Connectors to your pipeline with the `.add_input()` and `.add_output()` methods.
+Let's go one step further! You can use [Adapters](./reference/pipeline/adapters/adapters.md) to work directly with [CDA](https://www.hl7.org.uk/standards/hl7-standards/cda-clinical-document-architecture/) and [FHIR](https://hl7.org/fhir/) data received from healthcare system APIs. Adapters handle format conversion while keeping your pipeline pure ML processing.
 
 ```python
 from healthchain.pipeline import Pipeline
 from healthchain.pipeline.components import SpacyNLP
-from healthchain.io import CdaConnector
+from healthchain.io import CdaAdapter
 from healthchain.models import CdaRequest
 
 pipeline = Pipeline()
-cda_connector = CdaConnector()
-
-pipeline.add_input(cda_connector)
 pipeline.add_node(SpacyNLP.from_model_id("en_core_sci_sm"))
-pipeline.add_output(cda_connector)
-
 pipe = pipeline.build()
 
-cda_data = CdaRequest(document="<CDA XML content>")
-output = pipe(cda_data)
+# Use adapter for format conversion
+adapter = CdaAdapter()
+cda_request = CdaRequest(document="<CDA XML content>")
+
+# Parse, process, format
+doc = adapter.parse(cda_request)
+processed_doc = pipe(doc)
+output = adapter.format(processed_doc)
 ```
 
 #### 3. Use Prebuilt Pipelines
 
-Prebuilt pipelines are pre-configured collections of Components, Models, and Connectors. They are built for specific use cases, offering the highest level of abstraction. This is the easiest way to get started if you already know the use case you want to build for.
+Prebuilt pipelines are pre-configured collections of Components and Models optimized for specific healthcare AI use cases. They offer the highest level of abstraction and are the easiest way to get started.
 
 For a full list of available prebuilt pipelines and details on how to configure and customize them, see the [Pipelines](./reference/pipeline/pipeline.md) documentation page.
 
@@ -143,8 +144,8 @@ pipeline = MedicalCodingPipeline.from_model_id("facebook/bart-large-cnn", source
 # Or load from local model
 pipeline = MedicalCodingPipeline.from_local_model("./path/to/model", source="spacy")
 
-cda_data = CdaRequest(document="<CDA XML content>")
-output = pipeline(cda_data)
+cda_request = CdaRequest(document="<CDA XML content>")
+output = pipeline.process_request(cda_request)
 ```
 
 ### Interoperability 🔄
diff --git a/docs/reference/gateway/cdshooks.md b/docs/reference/gateway/cdshooks.md
index 6564a4a4..c57412ca 100644
--- a/docs/reference/gateway/cdshooks.md
+++ b/docs/reference/gateway/cdshooks.md
@@ -103,3 +103,59 @@ When registered with HealthChainAPI, the following endpoints are automatically c
 - `MedicationRequest`
 
 For more information, see the [official CDS Hooks documentation](https://cds-hooks.org/).
+
+## Advanced Workflow Example
+
+This example demonstrates how to build a custom CDS Hooks workflow that performs advanced clinical analysis and generates tailored decision support cards. By combining adapters and a custom pipeline, you can process incoming FHIR data, apply your own logic (such as risk assessment), and return dynamic CDS cards to the EHR.
+
+```python
+from healthchain.io import CdsFhirAdapter, Document
+from healthchain.pipeline import Pipeline
+from healthchain.pipeline.components import CdsCardCreator
+from healthchain.models import CDSRequest, CDSResponse
+from healthchain.gateway import HealthChainAPI, CDSHooksService
+
+# Build custom pipeline with analysis and card creation
+pipeline = Pipeline([Document])
+
+@pipeline.add_node
+def analyze_patient_data(doc: Document) -> Document:
+    """Custom function to analyze patient data and document content"""
+    # Access FHIR prefetch resources
+    patient = doc.fhir.get_prefetch_resources("patient")
+    document_ref = doc.fhir.get_prefetch_resources("document")
+
+    # Perform custom analysis
+    if patient:
+        age = 2024 - int(patient.birthDate[:4])  # Simple age calculation
+        if age > 65:
+            doc._custom_analysis = {"high_risk": True, "reason": "Age > 65"}
+        else:
+            doc._custom_analysis = {"high_risk": False}
+    return doc
+
+# Add card creator to format output
+pipeline.add_node(CdsCardCreator(
+    template='{"summary": "Risk Assessment", "detail": "Patient risk level: {{ high_risk }}"}'
+))
+
+pipe = pipeline.build()
+
+# Set up CDS service with custom workflow
+app = HealthChainAPI()
+cds = CDSHooksService()
+
+@cds.hook("encounter-discharge", id="risk-assessment")
+def assess_patient_risk(request: CDSRequest) -> CDSResponse:
+    # Use adapter for explicit format conversion
+    adapter = CdsFhirAdapter()
+
+    # Manual conversion with full document access
+    doc = adapter.parse(request)        # CDSRequest → Document
+    processed_doc = pipe(doc)           # Custom analysis + card creation
+
+    # Convert back to CDS response
+    return adapter.format(processed_doc)  # Document → CDSResponse
+
+app.register_service(cds, path="/cds")
+```
diff --git a/docs/reference/pipeline/adapters/adapters.md b/docs/reference/pipeline/adapters/adapters.md
new file mode 100644
index 00000000..d6ca84cc
--- /dev/null
+++ b/docs/reference/pipeline/adapters/adapters.md
@@ -0,0 +1,84 @@
+# Adapters
+
+Adapters handle conversion between healthcare data formats (CDA, FHIR) and HealthChain's internal `Document` objects. They enable clean separation between ML processing logic and healthcare format handling, making your pipelines more maintainable and testable.
+
+Unlike the legacy connector pattern, adapters are used explicitly and provide clear control over data flow.
+
+## Available adapters
+
+Adapters parse data from specific healthcare formats into FHIR resources and store them in a `Document` container for processing.
+
+([Document API Reference](../../../api/containers.md#healthchain.io.containers.document.Document))
+
+| Adapter | Input Format | Output Format | FHIR Resources | Document Access |
+|---------|--------------|---------------|----------------|-----------------|
+| [**CdaAdapter**](cdaadapter.md) | `CdaRequest` | `CdaResponse` | [**DocumentReference**](https://www.hl7.org/fhir/documentreference.html) | `Document.text`, `Document.fhir.problem_list`, `Document.fhir.medication_list`, `Document.fhir.allergy_list` |
+| [**CdsFhirAdapter**](cdsfhiradapter.md) | `CDSRequest` | `CDSResponse` | [**Any FHIR Resource**](https://www.hl7.org/fhir/resourcelist.html) | `Document.fhir.get_prefetch_resources()` |
+
+## Use Cases
+Each adapter is designed for specific healthcare integration scenarios.
+
+| Adapter | Use Case | Protocol |
+|---------|----------|----------|
+| `CdaAdapter` | [**Clinical Documentation**](../../gateway/soap_cda.md) | SOAP/CDA |
+| `CdsFhirAdapter` | [**Clinical Decision Support**](../../gateway/cdshooks.md) | CDS Hooks/FHIR |
+
+## Usage Patterns
+
+### 1. Simple End-to-End Processing
+
+Use prebuilt pipelines with the `process_request()` method for straightforward workflows:
+
+```python
+from healthchain.pipeline import MedicalCodingPipeline
+from healthchain.models import CdaRequest
+
+pipeline = MedicalCodingPipeline.from_model_id("en_core_sci_sm", source="spacy")
+cda_request = CdaRequest(document="<CDA XML content>")
+
+# Adapter used internally
+response = pipeline.process_request(cda_request)
+```
+
+### 2. Manual Adapter Control (Document Access)
+
+Use adapters `parse()` and `format()` methods directly when you need access to the intermediate `Document` object:
+
+```python
+from healthchain.io import CdaAdapter
+from healthchain.pipeline import MedicalCodingPipeline
+from healthchain.models import CdaRequest
+
+pipeline = MedicalCodingPipeline.from_model_id("en_core_sci_sm", source="spacy")
+adapter = CdaAdapter()
+
+cda_request = CdaRequest(document="<CDA XML content>")
+
+# Manual adapter control
+doc = adapter.parse(cda_request)      # CdaRequest → Document
+doc = pipeline(doc)                   # Document → Document (pure ML)
+
+# Access extracted clinical data
+print(f"Problems: {doc.fhir.problem_list}")
+print(f"Medications: {doc.fhir.medication_list}")
+print(f"Allergies: {doc.fhir.allergy_list}")
+
+# Convert back to healthcare format
+response = adapter.format(doc)        # Document → CdaResponse
+```
+
+## Adapter Configuration
+
+### Custom Interop Engine
+
+Both CDA and CDS adapters can be configured with custom interoperability engines. By default, the adapter uses the built-in InteropEngine with default CDA templates.
+
+```python
+from healthchain.io import CdaAdapter
+from healthchain.interop import create_engine
+
+# Custom engine with specific configuration
+custom_engine = create_engine(config_dir="/path/to/custom/config")
+adapter = CdaAdapter(engine=custom_engine)
+```
+For more information on the InteropEngine, see the [InteropEngine documentation](../../interop/interop.md).
diff --git a/docs/reference/pipeline/adapters/cdaadapter.md b/docs/reference/pipeline/adapters/cdaadapter.md
new file mode 100644
index 00000000..2da4301b
--- /dev/null
+++ b/docs/reference/pipeline/adapters/cdaadapter.md
@@ -0,0 +1,35 @@
+# CDA Adapter
+
+The `CdaAdapter` handles conversion between CDA (Clinical Document Architecture) documents and HealthChain's internal `Document` objects. It parses CDA documents to extract free-text notes and structured clinical data into FHIR resources, and can convert processed Documents back into annotated CDA format.
+
+This adapter is particularly useful for clinical documentation improvement (CDI) workflows where documents need to be processed with ML models and updated with additional structured data.
+
+[(Full Documentation on Clinical Documentation)](../../gateway/soap_cda.md)
+
+## Input and Output
+
+| Input | Output | Document Access |
+|-------|--------|-----------------|
+| [**CdaRequest**](../../../api/use_cases.md#healthchain.models.requests.cdarequest.CdaRequest) | [**CdaResponse**](../../../api/use_cases.md#healthchain.models.responses.cdaresponse.CdaResponse) | `Document.fhir.problem_list`, `Document.fhir.medication_list`, `Document.fhir.allergy_list`, `Document.text` |
+
+## Document Data Access
+
+Data parsed from the CDA document is converted into FHIR resources and stored in the `Document.fhir` attribute. The adapter supports the following CDA section to FHIR resource mappings:
+
+| CDA Section | FHIR Resource | Document.fhir Attribute |
+|-------------|---------------|--------------------------|
+| Problem List | [Condition](https://www.hl7.org/fhir/condition.html) | `Document.fhir.problem_list` |
+| Medication List | [MedicationStatement](https://www.hl7.org/fhir/medicationstatement.html) | `Document.fhir.medication_list` |
+| Allergy List | [AllergyIntolerance](https://www.hl7.org/fhir/allergyintolerance.html) | `Document.fhir.allergy_list` |
+| Clinical Notes | [DocumentReference](https://www.hl7.org/fhir/documentreference.html) | `Document.text` + `Document.fhir.bundle` |
+
+All FHIR resources are Pydantic models, so you can access them using the `model_dump()` method:
+
+```python
+# Access structured clinical data
+for condition in doc.fhir.problem_list:
+    print(condition.model_dump())
+
+# Access free-text content
+print(f"Clinical notes: {doc.text}")
+```
diff --git a/docs/reference/pipeline/adapters/cdsfhiradapter.md b/docs/reference/pipeline/adapters/cdsfhiradapter.md
new file mode 100644
index 00000000..55ef62f1
--- /dev/null
+++ b/docs/reference/pipeline/adapters/cdsfhiradapter.md
@@ -0,0 +1,72 @@
+# CDS FHIR Adapter
+
+The `CdsFhirAdapter` handles conversion between CDS Hooks requests/responses and HealthChain's internal `Document` objects. It processes FHIR data in the context of Clinical Decision Support (CDS) services, following the [CDS Hooks specification](https://cds-hooks.org/).
+
+This adapter is specifically designed for building CDS services that receive FHIR data through prefetch and return clinical decision cards.
+
+[(Full Documentation on Clinical Decision Support)](../../gateway/cdshooks.md)
+
+## Input and Output
+
+| Input | Output | Document Access |
+|-------|--------|-----------------|
+| [**CDSRequest**](../../../api/use_cases.md#healthchain.models.requests.cdsrequest.CDSRequest) | [**CDSResponse**](../../../api/use_cases.md#healthchain.models.responses.cdsresponse.CDSResponse) | `Document.fhir.get_prefetch_resources()`, `Document.cds.cards` |
+
+
+## Document Data Access
+
+### FHIR Prefetch Resources
+
+Data from the CDS request's `prefetch` field is stored in the `Document.fhir.prefetch_resources` attribute as a dictionary mapping prefetch keys to FHIR resources:
+
+```python
+# After processing with adapter.parse()
+doc = adapter.parse(cds_request)
+
+# Access prefetch resources by key
+patient = doc.fhir.get_prefetch_resources("patient")
+conditions = doc.fhir.get_prefetch_resources("condition")
+document_ref = doc.fhir.get_prefetch_resources("document")
+
+# Access all prefetch resources
+all_resources = doc.fhir.prefetch_resources
+for key, resource in all_resources.items():
+    print(f"Resource '{key}': {resource.resourceType}")
+```
+
+### CDS Cards
+
+Generated CDS cards are stored in the `Document.cds.cards` attribute:
+
+```python
+# After ML processing
+for card in processed_doc.cds.cards:
+    print(f"Summary: {card.summary}")
+    print(f"Indicator: {card.indicator}")
+    print(f"Detail: {card.detail}")
+    print(f"Source: {card.source}")
+```
+
+### Document Text Extraction
+
+When the prefetch contains a `DocumentReference` resource, the adapter automatically extracts the document content and stores it in `Document.text`:
+
+```python
+# If prefetch contains document with base64 content
+cds_request = CDSRequest(
+    prefetch={
+        "document": {
+            "resourceType": "DocumentReference",
+            "content": [{
+                "attachment": {
+                    "contentType": "text/plain",
+                    "data": "UGF0aWVudCBkaXNjaGFyZ2Ugbm90ZXM="  # base64 encoded
+                }
+            }]
+        }
+    }
+)
+
+doc = adapter.parse(cds_request)
+print(doc.text)  # "Patient discharge notes" (decoded)
+```
diff --git a/docs/reference/pipeline/connectors/cdaconnector.md b/docs/reference/pipeline/connectors/cdaconnector.md
index a6338470..932e9dd0 100644
--- a/docs/reference/pipeline/connectors/cdaconnector.md
+++ b/docs/reference/pipeline/connectors/cdaconnector.md
@@ -1,8 +1,10 @@
-# CDA Connector
+# CDA Connector (Legacy)
+
+> **⚠️ Deprecated:** `CdaConnector` is deprecated. Use [`CdaAdapter`](../adapters/cdaadapter.md) for new projects, which provides explicit control over data conversion and enables pure `Document → Document` pipeline processing.
 
 The `CdaConnector` parses CDA documents, extracting free-text notes and relevant structured clinical data into FHIR resources in the `Document` container, and returns an annotated CDA document as output. It will also extract the text from the note section of the document and store it in the `Document.text` attribute.
 
-This connector is particularly useful for clinical documentation improvement (CDI) workflows where a document needs to be processed and updated with additional structured data.
+**For new projects, use [`CdaAdapter`](../adapters/cdaadapter.md) instead.**
 
 [(Full Documentation on Clinical Documentation)](../../gateway/soap_cda.md)
 
diff --git a/docs/reference/pipeline/connectors/cdsfhirconnector.md b/docs/reference/pipeline/connectors/cdsfhirconnector.md
index 088dc8e4..2aa2a0aa 100644
--- a/docs/reference/pipeline/connectors/cdsfhirconnector.md
+++ b/docs/reference/pipeline/connectors/cdsfhirconnector.md
@@ -1,7 +1,11 @@
-# CDS FHIR Connector
+# CDS FHIR Connector (Legacy)
+
+> **⚠️ Deprecated:** `CdsFhirConnector` is deprecated. Use [`CdsFhirAdapter`](../adapters/cdsfhiradapter.md) for new projects, which provides explicit control over data conversion and enables pure `Document → Document` pipeline processing.
 
 The `CdsFhirConnector` handles FHIR data in the context of Clinical Decision Support (CDS) services, specifically using the [CDS Hooks specification](https://cds-hooks.org/).
 
+**For new projects, use [`CdsFhirAdapter`](../adapters/cdsfhiradapter.md) instead.**
+
 [(Full Documentation on Clinical Decision Support)](../../gateway/cdshooks.md)
 
 ## Input and Output
diff --git a/docs/reference/pipeline/connectors/connectors.md b/docs/reference/pipeline/connectors/connectors.md
index 9e2f1463..ab857a0d 100644
--- a/docs/reference/pipeline/connectors/connectors.md
+++ b/docs/reference/pipeline/connectors/connectors.md
@@ -1,10 +1,38 @@
-# Connectors
+# Connectors (Legacy)
+
+> **⚠️ Deprecated:** Connectors are being replaced by the new [Adapter pattern](../adapters/adapters.md). For new projects, use Adapters for cleaner separation between ML processing and healthcare format handling.
 
 Connectors transform your data into a format that can be understood by healthcare systems such as EHRs. They allow your pipelines to work directly with data in HL7 interoperability standard formats, such as [CDA](https://www.hl7.org.uk/standards/hl7-standards/cda-clinical-document-architecture/) or [FHIR](https://hl7.org/fhir/), without the headache of parsing and validating the data yourself.
 
-Connectors are what give you the power to build *end-to-end* pipelines that interact with real-time healthcare systems.
+**For new projects, consider using [Adapters](../adapters/adapters.md) instead**, which provide explicit control over data conversion and enable pure `Document → Document` pipeline processing.
+
+## Migration to Adapters
+
+| Legacy Connector | New Adapter | Migration Guide |
+|------------------|-------------|-----------------|
+| `CdaConnector` | [`CdaAdapter`](../adapters/cdaadapter.md) | Remove `add_input()` and `add_output()` calls, use explicit `parse()` and `format()` methods |
+| `CdsFhirConnector` | [`CdsFhirAdapter`](../adapters/cdsfhiradapter.md) | Remove `add_input()` and `add_output()` calls, use explicit `parse()` and `format()` methods |
+
+### Quick Migration Example
+
+**Before (Connectors):**
+```python
+pipeline.add_input(CdaConnector())
+pipeline.add_output(CdaConnector())
+response = pipeline(cda_request)
+```
+
+**After (Adapters):**
+```python
+adapter = CdaAdapter()
+doc = adapter.parse(cda_request)
+doc = pipeline(doc)
+response = adapter.format(doc)
+```
+
+[→ Full Adapter Documentation](../adapters/adapters.md)
 
-## Available connectors
+## Available connectors (Legacy)
 
 Connectors parse data from a specific format into FHIR resources and store them in a `Document` container.
 
diff --git a/docs/reference/pipeline/pipeline.md b/docs/reference/pipeline/pipeline.md
index 20c64f42..eefef0da 100644
--- a/docs/reference/pipeline/pipeline.md
+++ b/docs/reference/pipeline/pipeline.md
@@ -8,24 +8,24 @@ Depending on your need, you can either go top down, where you use prebuilt pipel
 
 HealthChain comes with a set of prebuilt pipelines that are out-of-the-box implementations of common healthcare data processing tasks:
 
-| Pipeline | Container | Compatible Connector | Description | Example Use Case |
-|----------|-----------|-----------|-------------|------------------|
-| [**MedicalCodingPipeline**](./prebuilt_pipelines/medicalcoding.md) | `Document` | `CdaConnector` | An NLP pipeline that processes free-text clinical notes into structured data | Automatically generating SNOMED CT codes from clinical notes |
-| [**SummarizationPipeline**](./prebuilt_pipelines/summarization.md) | `Document` | `CdsFhirConnector` | An NLP pipeline for summarizing clinical notes | Generating discharge summaries from patient history and notes |
-| **QAPipeline** [TODO] | `Document` | N/A | A Question Answering pipeline suitable for conversational AI applications | Developing a chatbot to answer patient queries about their medical records |
-| **ClassificationPipeline** [TODO] | `Tabular` | `CdsFhirConnector` | A pipeline for machine learning classification tasks | Predicting patient readmission risk based on historical health data |
+| Pipeline | Container | Use Case | Description | Example Application |
+|----------|-----------|----------|-------------|---------------------|
+| [**MedicalCodingPipeline**](./prebuilt_pipelines/medicalcoding.md) | `Document` | Clinical Documentation | An NLP pipeline that processes free-text clinical notes into structured data | Automatically generating SNOMED CT codes from clinical notes |
+| [**SummarizationPipeline**](./prebuilt_pipelines/summarization.md) | `Document` | Clinical Decision Support | An NLP pipeline for summarizing clinical notes | Generating discharge summaries from patient history and notes |
+| **QAPipeline** [TODO] | `Document` | Conversational AI | A Question Answering pipeline suitable for conversational AI applications | Developing a chatbot to answer patient queries about their medical records |
+| **ClassificationPipeline** [TODO] | `Tabular` | Predictive Analytics | A pipeline for machine learning classification tasks | Predicting patient readmission risk based on historical health data |
 
-Prebuilt pipelines are end-to-end workflows with Connectors built into them. They interact with raw data received from EHR interfaces, usually CDA or FHIR data from specific [protocols](../gateway/gateway.md).
+Prebuilt pipelines are end-to-end workflows optimized for specific healthcare AI tasks. They can be used with adapters for seamless integration with EHR systems via [protocols](../gateway/gateway.md).
 
 You can load your models directly as a pipeline object, from local files or from a remote model repository such as Hugging Face.
 
 ```python
-from healthchain.pipeline import Pipeline
+from healthchain.pipeline import MedicalCodingPipeline
 from healthchain.models import CdaRequest
 
 # Load from Hugging Face
 pipeline = MedicalCodingPipeline.from_model_id(
-    'gpt2', source="huggingface"
+    'blaze999/Medical-NER', task="token-classification", source="huggingface"
 )
 # Load from local model files
 pipeline = MedicalCodingPipeline.from_local_model(
@@ -34,8 +34,17 @@ pipeline = MedicalCodingPipeline.from_local_model(
 # Load from a pipeline object
 pipeline = MedicalCodingPipeline.load(pipeline_object)
 
+# Simple end-to-end processing
 cda_request = CdaRequest(document="<Clinical Document>")
-cda_response = pipeline(cda_request)
+cda_response = pipeline.process_request(cda_request)
+
+# Or manual adapter control for more granular control
+from healthchain.io import CdaAdapter
+adapter = CdaAdapter()
+doc = adapter.parse(cda_request)
+doc = pipeline(doc)
+# Access: doc.fhir.problem_list, doc.fhir.medication_list
+response = adapter.format(doc)
 ```
 
 ### Customizing Prebuilt Pipelines
@@ -135,19 +144,27 @@ pipeline.add_node(RemoveStopwords(stopwords))
 
 [(BaseComponent API Reference)](../../api/component.md#healthchain.pipeline.components.base.BaseComponent)
 
-### Adding Connectors 🔗
+### Working with Healthcare Data Formats 🔄
 
-Connectors are added to the pipeline using the `.add_input()` and `.add_output()` methods. You can learn more about connectors at the [Connectors](./connectors/connectors.md) documentation page.
+Use adapters to handle conversion between healthcare formats (CDA, FHIR) and HealthChain's internal Document objects. Adapters enable clean separation between ML processing and format handling.
 
 ```python
-from healthchain.io import CdaConnector
+from healthchain.io import CdaAdapter, Document
+
+adapter = CdaAdapter()
 
-cda_connector = CdaConnector()
+# Parse healthcare data into Document
+doc = adapter.parse(cda_request)
 
-pipeline.add_input(cda_connector)
-pipeline.add_output(cda_connector)
+# Process with pure pipeline
+processed_doc = pipeline(doc)
+
+# Convert back to healthcare format
+response = adapter.format(processed_doc)
 ```
 
+You can learn more about adapters at the [Adapters](./adapters/adapters.md) documentation page.
+
 ## Pipeline Management 🔨
 
 #### Adding
diff --git a/mkdocs.yml b/mkdocs.yml
index c5c4ed2b..1b4a25dd 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -32,7 +32,11 @@ nav:
         - Components:
           - Overview: reference/pipeline/components/components.md
           - CdsCardCreator: reference/pipeline/components/cdscardcreator.md
-        - Connectors:
+        - Adapters:
+          - Overview: reference/pipeline/adapters/adapters.md
+          - CDA Adapter: reference/pipeline/adapters/cdaadapter.md
+          - CDS FHIR Adapter: reference/pipeline/adapters/cdsfhiradapter.md
+        - Connectors (Legacy):
           - Overview: reference/pipeline/connectors/connectors.md
           - CDA Connector: reference/pipeline/connectors/cdaconnector.md
           - CDS FHIR Connector: reference/pipeline/connectors/cdsfhirconnector.md
@@ -59,6 +63,7 @@ nav:
       - api/pipeline.md
       - api/component.md
       - api/containers.md
+      - api/adapters.md
       - api/connectors.md
       - api/use_cases.md
       - api/cds_hooks.md

From e00e7595f1dda7adc832721116dbe0585f784f48 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Thu, 31 Jul 2025 17:30:46 +0100
Subject: [PATCH 04/10] Update README

---
 README.md | 43 +++++++++++++++++++++++++++----------------
 1 file changed, 27 insertions(+), 16 deletions(-)

diff --git a/README.md b/README.md
index 9f9fed06..b1943b4e 100644
--- a/README.md
+++ b/README.md
@@ -163,27 +163,32 @@ result = nlp(Document("Patient has a history of heart attack and high blood pres
 print(f"Entities: {result.nlp.get_entities()}")
 ```
 
-#### Adding connectors
-Connectors give your pipelines the ability to interface with EHRs.
+#### Working with healthcare data formats
+Adapters handle conversion between healthcare formats (CDA, FHIR) and internal Document objects for seamless EHR integration.
 
 ```python
-from healthchain.io import CdaConnector
+from healthchain.io import CdaAdapter, Document
 from healthchain.models import CdaRequest
 
-cda_connector = CdaConnector()
+adapter = CdaAdapter()
 
-pipeline.add_input(cda_connector)
-pipeline.add_output(cda_connector)
+# Parse healthcare data into Document
+cda_request = CdaRequest(document="<CDA XML content>")
+doc = adapter.parse(cda_request)
 
-pipe = pipeline.build()
+# Process with your pipeline
+processed_doc = nlp_pipeline(doc)
 
-cda_data = CdaRequest(document="<CDA XML content>")
-output = pipe(cda_data)
-# output: CdsResponse model
+# Access extracted clinical data
+print(f"Problems: {processed_doc.fhir.problem_list}")
+print(f"Medications: {processed_doc.fhir.medication_list}")
+
+# Convert back to healthcare format
+response = adapter.format(processed_doc)
 ```
 
 ### Using pre-built pipelines
-Pre-built pipelines are use case specific end-to-end workflows that already have connectors and models built-in.
+Pre-built pipelines are use case specific end-to-end workflows optimized for common healthcare AI tasks.
 
 ```python
 from healthchain.pipeline import MedicalCodingPipeline
@@ -194,11 +199,17 @@ pipeline = MedicalCodingPipeline.from_model_id(
     model="blaze999/Medical-NER", task="token-classification", source="huggingface"
 )
 
-# Or load from local model
-pipeline = MedicalCodingPipeline.from_local_model("./path/to/model", source="spacy")
-
-cda_data = CdaRequest(document="<CDA XML content>")
-output = pipeline(cda_data)
+# Simple end-to-end processing
+cda_request = CdaRequest(document="<CDA XML content>")
+response = pipeline.process_request(cda_request)
+
+# Or manual control for document access
+from healthchain.io import CdaAdapter
+adapter = CdaAdapter()
+doc = adapter.parse(cda_request)
+doc = pipeline(doc)
+# Access: doc.fhir.problem_list, doc.fhir.medication_list
+response = adapter.format(doc)
 ```
 
 ## Interoperability

From 96e3fefc1171bb6696c5b1a3a7633ceff5e391b0 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Thu, 31 Jul 2025 17:30:57 +0100
Subject: [PATCH 05/10] poetry.lock

---
 poetry.lock | 706 ++++++++++++++++++++++++++--------------------------
 1 file changed, 355 insertions(+), 351 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 49e06b35..3047e90a 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -75,17 +75,18 @@ dev = ["backports.zoneinfo", "freezegun (>=1.0,<2.0)", "jinja2 (>=3.0)", "pytest
 
 [[package]]
 name = "backrefs"
-version = "5.8"
+version = "5.9"
 description = "A wrapper around re and regex that adds additional back references."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "backrefs-5.8-py310-none-any.whl", hash = "sha256:c67f6638a34a5b8730812f5101376f9d41dc38c43f1fdc35cb54700f6ed4465d"},
-    {file = "backrefs-5.8-py311-none-any.whl", hash = "sha256:2e1c15e4af0e12e45c8701bd5da0902d326b2e200cafcd25e49d9f06d44bb61b"},
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 [package.extras]
@@ -144,13 +145,13 @@ files = [
 
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-version = "2025.4.26"
+version = "2025.7.14"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.7"
 files = [
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@@ -391,18 +392,15 @@ files = [
 
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 name = "comm"
-version = "0.2.2"
+version = "0.2.3"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
 optional = false
 python-versions = ">=3.8"
 files = [
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-[package.dependencies]
-traitlets = ">=4"
-
 [package.extras]
 test = ["pytest"]
 
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 [[package]]
@@ -563,13 +561,13 @@ files = [
 
 [[package]]
 name = "distlib"
-version = "0.3.9"
+version = "0.4.0"
 description = "Distribution utilities"
 optional = false
 python-versions = "*"
 files = [
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 ]
 
 [[package]]
@@ -633,13 +631,13 @@ python-dateutil = ">=2.4"
 
 [[package]]
 name = "fastapi"
-version = "0.115.12"
+version = "0.115.14"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -669,40 +667,40 @@ otel = ["opentelemetry-api (>=1.12.0,<2.0)"]
 
 [[package]]
 name = "fhir-core"
-version = "1.0.1"
+version = "1.1.4"
 description = "FHIR Core library"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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 [package.extras]
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-test = ["PyYAML (>=6.0.1)", "black", "coverage", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "lxml", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "pytest-runner", "requests (==2.23.0)", "setuptools (==65.6.3)", "types-PyYAML", "types-requests", "types-simplejson"]
+dev = ["Jinja2 (==2.11.1)", "MarkupSafe (==1.1.1)", "PyYAML (>=6.0.1)", "black (>=23.0,<24.0)", "certifi", "colorlog (==2.10.0)", "coverage", "fhirspec", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "lxml", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "requests (==2.23.0)", "setuptools (==65.6.3)", "types-PyYAML", "types-requests", "types-simplejson", "zest-releaser[recommended]"]
+test = ["PyYAML (>=6.0.1)", "black (>=23.0,<24.0)", "coverage", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "lxml", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "pytest-runner", "requests (==2.23.0)", "setuptools (==65.6.3)", "types-PyYAML", "types-requests", "types-simplejson"]
 
 [[package]]
 name = "fhir-resources"
-version = "8.0.0"
+version = "8.1.0"
 description = "FHIR Resources as Model Class"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fhir.resources-8.0.0-py2.py3-none-any.whl", hash = "sha256:9c46d6d79c6d6629c3bea6f244bcc6e8e0e4d15757a675f19d9d1c05c9ab2199"},
-    {file = "fhir.resources-8.0.0.tar.gz", hash = "sha256:84dac3af31eaf90d5b0386cac21d26c50e6fb1526d68b88a2c42d112978e9cf9"},
+    {file = "fhir_resources-8.1.0-py2.py3-none-any.whl", hash = "sha256:4370a5b6b35f278705328368bf79b3a17db91025fd4ec896fb963edd44ecc5de"},
+    {file = "fhir_resources-8.1.0.tar.gz", hash = "sha256:8d64a717f37ea50bde97c1b8ff3fd969a6074df99c167183a273abe4da8bbfa5"},
 ]
 
 [package.dependencies]
-fhir-core = ">=1.0.0"
+fhir-core = ">=1.1.3"
 
 [package.extras]
 all = ["PyYAML (>=5.4.1)", "lxml"]
-dev = ["Jinja2 (==2.11.1)", "MarkupSafe (==1.1.1)", "black", "certifi", "colorlog (==2.10.0)", "coverage", "fhirspec", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "requests (==2.23.0)", "setuptools (==65.6.3)", "typed-ast (>=1.5.4)", "types-PyYAML", "types-requests", "types-simplejson", "zest-releaser[recommended]"]
-test = ["PyYAML (>=5.4.1)", "black", "coverage", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "lxml", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "pytest-runner", "requests (==2.23.0)", "setuptools (==65.6.3)", "typed-ast (>=1.5.4)", "types-PyYAML", "types-requests", "types-simplejson"]
+dev = ["Jinja2 (==3.1.6)", "MarkupSafe (==2.1.5)", "black (>=23.0,<24.0)", "certifi", "colorlog (==2.10.0)", "coverage", "fhirspec (>=0.6.0)", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "requests (==2.23.0)", "setuptools (==65.6.3)", "typed-ast (>=1.5.4)", "types-PyYAML", "types-requests", "types-simplejson", "zest-releaser[recommended]"]
+test = ["PyYAML (>=5.4.1)", "black (>=23.0,<24.0)", "coverage", "flake8 (==6.0)", "flake8-bugbear (>=22.12.6)", "flake8-isort (>=6.0.0)", "importlib-metadata (>=5.2.0)", "isort (>=5.11.4)", "lxml", "mypy", "pytest (>5.4.0)", "pytest-cov (>=2.10.0)", "pytest-runner", "requests (==2.23.0)", "setuptools (==65.6.3)", "typed-ast (>=1.5.4)", "types-PyYAML", "types-requests", "types-simplejson"]
 xml = ["lxml"]
 yaml = ["PyYAML (>=5.4.1)"]
 
@@ -741,13 +739,13 @@ dev = ["flake8", "markdown", "twine", "wheel"]
 
 [[package]]
 name = "griffe"
-version = "1.7.3"
+version = "1.9.0"
 description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API."
 optional = false
 python-versions = ">=3.9"
 files = [
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-    {file = "griffe-1.7.3.tar.gz", hash = "sha256:52ee893c6a3a968b639ace8015bec9d36594961e156e23315c8e8e51401fa50b"},
+    {file = "griffe-1.9.0-py3-none-any.whl", hash = "sha256:bcf90ee3ad42bbae70a2a490c782fc8e443de9b84aa089d857c278a4e23215fc"},
+    {file = "griffe-1.9.0.tar.gz", hash = "sha256:b5531cf45e9b73f0842c2121cc4d4bcbb98a55475e191fc9830e7aef87a920a0"},
 ]
 
 [package.dependencies]
@@ -896,36 +894,36 @@ files = [
 
 [[package]]
 name = "ipykernel"
-version = "6.29.5"
+version = "6.30.0"
 description = "IPython Kernel for Jupyter"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "ipykernel-6.29.5-py3-none-any.whl", hash = "sha256:afdb66ba5aa354b09b91379bac28ae4afebbb30e8b39510c9690afb7a10421b5"},
-    {file = "ipykernel-6.29.5.tar.gz", hash = "sha256:f093a22c4a40f8828f8e330a9c297cb93dcab13bd9678ded6de8e5cf81c56215"},
+    {file = "ipykernel-6.30.0-py3-none-any.whl", hash = "sha256:fd2936e55c4a1c2ee8b1e5fa6a372b8eecc0ab1338750dee76f48fa5cca1301e"},
+    {file = "ipykernel-6.30.0.tar.gz", hash = "sha256:b7b808ddb2d261aae2df3a26ff3ff810046e6de3dfbc6f7de8c98ea0a6cb632c"},
 ]
 
 [package.dependencies]
-appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+appnope = {version = ">=0.1.2", markers = "platform_system == \"Darwin\""}
 comm = ">=0.1.1"
 debugpy = ">=1.6.5"
 ipython = ">=7.23.1"
-jupyter-client = ">=6.1.12"
+jupyter-client = ">=8.0.0"
 jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
 matplotlib-inline = ">=0.1"
-nest-asyncio = "*"
-packaging = "*"
-psutil = "*"
-pyzmq = ">=24"
-tornado = ">=6.1"
+nest-asyncio = ">=1.4"
+packaging = ">=22"
+psutil = ">=5.7"
+pyzmq = ">=25"
+tornado = ">=6.2"
 traitlets = ">=5.4.0"
 
 [package.extras]
-cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
-docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+cov = ["coverage[toml]", "matplotlib", "pytest-cov", "trio"]
+docs = ["intersphinx-registry", "myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
 pyqt5 = ["pyqt5"]
 pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0,<9)", "pytest-asyncio (>=0.23.5)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "ipython"
@@ -1045,17 +1043,22 @@ test = ["ipykernel", "pre-commit", "pytest (<9)", "pytest-cov", "pytest-timeout"
 
 [[package]]
 name = "jwt"
-version = "1.3.1"
+version = "1.4.0"
 description = "JSON Web Token library for Python 3."
 optional = false
-python-versions = ">= 3.6"
+python-versions = ">=3.9"
 files = [
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+    {file = "jwt-1.4.0-py3-none-any.whl", hash = "sha256:7560a7f1de4f90de94ac645ee0303ac60c95b9e08e058fb69f6c330f71d71b11"},
+    {file = "jwt-1.4.0.tar.gz", hash = "sha256:f6f789128ac247142c79ee10f3dba6e366ec4e77c9920d18c1592e28aa0a7952"},
 ]
 
 [package.dependencies]
 cryptography = ">=3.1,<3.4.0 || >3.4.0"
 
+[package.extras]
+dev = ["black", "isort", "mypy", "types-freezegun"]
+test = ["freezegun", "pytest (>=6.0,<7.0)", "pytest-cov"]
+
 [[package]]
 name = "langcodes"
 version = "3.5.0"
@@ -1177,8 +1180,11 @@ files = [
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@@ -1330,13 +1336,13 @@ test = ["hypothesis", "pytest", "readme-renderer"]
 
 [[package]]
 name = "markdown"
-version = "3.8"
+version = "3.8.2"
 description = "Python implementation of John Gruber's Markdown."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "markdown-3.8-py3-none-any.whl", hash = "sha256:794a929b79c5af141ef5ab0f2f642d0f7b1872981250230e72682346f7cc90dc"},
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+    {file = "markdown-3.8.2-py3-none-any.whl", hash = "sha256:5c83764dbd4e00bdd94d85a19b8d55ccca20fe35b2e678a1422b380324dd5f24"},
+    {file = "markdown-3.8.2.tar.gz", hash = "sha256:247b9a70dd12e27f67431ce62523e675b866d254f900c4fe75ce3dda62237c45"},
 ]
 
 [package.dependencies]
@@ -1542,13 +1548,13 @@ pyyaml = ">=5.1"
 
 [[package]]
 name = "mkdocs-material"
-version = "9.6.14"
+version = "9.6.16"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1764,37 +1770,53 @@ lint = ["black"]
 
 [[package]]
 name = "pandas"
-version = "2.3.0"
+version = "2.3.1"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [[package]]
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 ]
 
 [[package]]
@@ -2623,19 +2628,18 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "rich"
-version = "14.0.0"
+version = "14.1.0"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
 markdown-it-py = ">=2.2.0"
 pygments = ">=2.13.0,<3.0.0"
-typing-extensions = {version = ">=4.0.0,<5.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 jupyter = ["ipywidgets (>=7.5.1,<9)"]
@@ -2710,26 +2714,26 @@ files = [
 
 [[package]]
 name = "smart-open"
-version = "7.1.0"
-description = "Utils for streaming large files (S3, HDFS, GCS, Azure Blob Storage, gzip, bz2...)"
+version = "7.3.0.post1"
+description = "Utils for streaming large files (S3, HDFS, GCS, SFTP, Azure Blob Storage, gzip, bz2, zst...)"
 optional = false
-python-versions = "<4.0,>=3.7"
+python-versions = "<4.0,>=3.8"
 files = [
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 ]
 
 [package.dependencies]
 wrapt = "*"
 
 [package.extras]
-all = ["azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "paramiko", "requests", "zstandard"]
+all = ["smart_open[azure,gcs,http,s3,ssh,webhdfs,zst]"]
 azure = ["azure-common", "azure-core", "azure-storage-blob"]
 gcs = ["google-cloud-storage (>=2.6.0)"]
 http = ["requests"]
 s3 = ["boto3"]
 ssh = ["paramiko"]
-test = ["awscli", "azure-common", "azure-core", "azure-storage-blob", "boto3", "google-cloud-storage (>=2.6.0)", "moto[server]", "numpy", "paramiko", "pyopenssl", "pytest", "pytest-benchmark", "pytest-rerunfailures", "requests", "responses", "zstandard"]
+test = ["awscli", "moto[server]", "numpy", "pyopenssl", "pytest", "pytest-rerunfailures", "pytest_benchmark", "responses", "smart_open[all]"]
 webhdfs = ["requests"]
 zst = ["zstandard"]
 
@@ -3158,13 +3162,13 @@ typing-extensions = ">=3.7.4.3"
 
 [[package]]
 name = "typing-extensions"
-version = "4.14.0"
+version = "4.14.1"
 description = "Backported and Experimental Type Hints for Python 3.9+"
 optional = false
 python-versions = ">=3.9"
 files = [
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-    {file = "typing_extensions-4.14.0.tar.gz", hash = "sha256:8676b788e32f02ab42d9e7c61324048ae4c6d844a399eebace3d4979d75ceef4"},
+    {file = "typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76"},
+    {file = "typing_extensions-4.14.1.tar.gz", hash = "sha256:38b39f4aeeab64884ce9f74c94263ef78f3c22467c8724005483154c26648d36"},
 ]
 
 [[package]]
@@ -3180,13 +3184,13 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "2.4.0"
+version = "2.5.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "urllib3-2.4.0-py3-none-any.whl", hash = "sha256:4e16665048960a0900c702d4a66415956a584919c03361cac9f1df5c5dd7e813"},
-    {file = "urllib3-2.4.0.tar.gz", hash = "sha256:414bc6535b787febd7567804cc015fee39daab8ad86268f1310a9250697de466"},
+    {file = "urllib3-2.5.0-py3-none-any.whl", hash = "sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc"},
+    {file = "urllib3-2.5.0.tar.gz", hash = "sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760"},
 ]
 
 [package.extras]
@@ -3216,13 +3220,13 @@ standard = ["colorama (>=0.4)", "httptools (>=0.5.0)", "python-dotenv (>=0.13)",
 
 [[package]]
 name = "virtualenv"
-version = "20.31.2"
+version = "20.32.0"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "virtualenv-20.31.2-py3-none-any.whl", hash = "sha256:36efd0d9650ee985f0cad72065001e66d49a6f24eb44d98980f630686243cf11"},
-    {file = "virtualenv-20.31.2.tar.gz", hash = "sha256:e10c0a9d02835e592521be48b332b6caee6887f332c111aa79a09b9e79efc2af"},
+    {file = "virtualenv-20.32.0-py3-none-any.whl", hash = "sha256:2c310aecb62e5aa1b06103ed7c2977b81e042695de2697d01017ff0f1034af56"},
+    {file = "virtualenv-20.32.0.tar.gz", hash = "sha256:886bf75cadfdc964674e6e33eb74d787dff31ca314ceace03ca5810620f4ecf0"},
 ]
 
 [package.dependencies]

From 145fd557aa2cf088af9c95e0e3205ae625d3e8b8 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Thu, 31 Jul 2025 17:31:30 +0100
Subject: [PATCH 06/10] Update cookbook

---
 cookbook/cds_discharge_summarizer_hf_chat.py | 2 +-
 cookbook/cds_discharge_summarizer_hf_trf.py  | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/cookbook/cds_discharge_summarizer_hf_chat.py b/cookbook/cds_discharge_summarizer_hf_chat.py
index ea1f7a12..259a1341 100644
--- a/cookbook/cds_discharge_summarizer_hf_chat.py
+++ b/cookbook/cds_discharge_summarizer_hf_chat.py
@@ -57,7 +57,7 @@ def load_data_in_client(self) -> Prefetch:
     @hc.api
     def my_service(self, request: CDSRequest) -> CDSResponse:
         # Process the request through our pipeline
-        result = self.pipeline(request)
+        result = self.pipeline.process_request(request)
         return result
 
 
diff --git a/cookbook/cds_discharge_summarizer_hf_trf.py b/cookbook/cds_discharge_summarizer_hf_trf.py
index dc3eb549..36ee119f 100644
--- a/cookbook/cds_discharge_summarizer_hf_trf.py
+++ b/cookbook/cds_discharge_summarizer_hf_trf.py
@@ -30,7 +30,7 @@ def load_data_in_client(self) -> Prefetch:
 
     @hc.api
     def my_service(self, request: CDSRequest) -> CDSResponse:
-        result = self.pipeline(request)
+        result = self.pipeline.process_request(request)
         return result
 
 

From b94e592de7e784e5ac5fa83a94245c338fe7fd82 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Fri, 1 Aug 2025 12:24:00 +0100
Subject: [PATCH 07/10] Remove legacy connectors

---
 docs/api/connectors.md                        |   7 -
 docs/reference/gateway/soap_cda.md            |  14 +-
 .../pipeline/connectors/cdaconnector.md       |  68 -------
 .../pipeline/connectors/cdsfhirconnector.md   |  79 --------
 .../pipeline/connectors/connectors.md         |  73 --------
 healthchain/io/__init__.py                    |  10 +-
 healthchain/io/base.py                        |  23 ---
 healthchain/io/cdaconnector.py                | 177 ------------------
 healthchain/io/cdsfhirconnector.py            | 119 ------------
 mkdocs.yml                                    |   5 -
 tests/conftest.py                             |   8 +-
 tests/gateway/test_client_pool.py             |   8 +-
 tests/gateway/test_connection_manager.py      |   4 +-
 tests/gateway/test_core_base.py               |   4 +-
 tests/gateway/test_event_dispatcher.py        |  15 +-
 tests/gateway/test_fhir_client.py             |  17 +-
 tests/gateway/test_fhir_gateway.py            |  10 +-
 .../test_interop_engine_integration.py        |  22 +--
 tests/interop/test_base_generator.py          |   8 +-
 tests/pipeline/conftest.py                    |  73 ++------
 ...est_cdaconnector.py => test_cdaadapter.py} |  53 +++---
 ...hirconnector.py => test_cdsfhiradapter.py} |  50 ++---
 22 files changed, 143 insertions(+), 704 deletions(-)
 delete mode 100644 docs/api/connectors.md
 delete mode 100644 docs/reference/pipeline/connectors/cdaconnector.md
 delete mode 100644 docs/reference/pipeline/connectors/cdsfhirconnector.md
 delete mode 100644 docs/reference/pipeline/connectors/connectors.md
 delete mode 100644 healthchain/io/cdaconnector.py
 delete mode 100644 healthchain/io/cdsfhirconnector.py
 rename tests/pipeline/{test_cdaconnector.py => test_cdaadapter.py} (78%)
 rename tests/pipeline/{test_cdsfhirconnector.py => test_cdsfhiradapter.py} (78%)

diff --git a/docs/api/connectors.md b/docs/api/connectors.md
deleted file mode 100644
index dacd769d..00000000
--- a/docs/api/connectors.md
+++ /dev/null
@@ -1,7 +0,0 @@
-# Connectors (Legacy)
-
-> **⚠️ Deprecated:** Connectors are deprecated. Use [Adapters](adapters.md) for new projects.
-
-::: healthchain.io.base
-::: healthchain.io.cdaconnector
-::: healthchain.io.cdsfhirconnector
diff --git a/docs/reference/gateway/soap_cda.md b/docs/reference/gateway/soap_cda.md
index 89992e13..b054ba68 100644
--- a/docs/reference/gateway/soap_cda.md
+++ b/docs/reference/gateway/soap_cda.md
@@ -4,18 +4,24 @@ The SOAP/CDA protocol enables real-time Clinical Documentation Improvement (CDI)
 
 ## Overview
 
-Clinical Documentation workflows communicate using [CDA (Clinical Document Architecture)](https://www.hl7.org.uk/standards/hl7-standards/cda-clinical-document-architecture/). CDAs are standardized electronic documents for exchanging clinical information between different healthcare systems. They provide a common structure for capturing and sharing patient data like medical history, medications, and care plans between different healthcare systems and providers. Think of it as a collaborative Google Doc that you can add, amend, and remove entries from.
+Clinical Documentation workflows communicate using [CDA (Clinical Document Architecture)](https://www.hl7.org.uk/standards/hl7-standards/cda-clinical-document-architecture/). CDAs are standardized electronic documents for exchanging clinical information between different healthcare systems. They provide a common structure for capturing and sharing patient data like medical history, medications, and care plans between different healthcare systems and providers. Think of it as a collaborative Google Doc that you can add, amend, and remove entries from. CDA support is currently limited to [Epic systems](https://open.epic.com/clinical/ehrtoehr), but we plan to add support for other IHE SOAP/CDA services in the future.
+
+### Epic NoteReader CDI
 
 The Epic NoteReader CDI is a SOAP/CDA-based NLP service that extracts structured data from clinical notes. Like CDS Hooks, it operates in real-time and is triggered when a clinician opts into CDI functionality and signs or pends a note.
 
 The primary use case for Epic NoteReader is to convert free-text medical documentation into coded information that can be used for billing, quality reporting, continuity of care, and clinical decision support at the point-of-care ([case study](https://www.researchsquare.com/article/rs-4925228/v1)).
 
-It is a vendor-specific component (Epic), but we plan to add support for other IHE SOAP/CDA services in the future.
-
 | When      | Where | What you receive            | What you send back         |
 | :-------- | :-----| :-------------------------- |----------------------------|
 | Triggered when a clinician opts in to CDI functionality and signs or pends a note | EHR documentation modules (e.g. NoteReader in Epic) | A CDA document containing continuity of care data and free-text clinical notes | A CDA document with additional structured data extracted by your CDI service |
 
+
+### CDA Services
+
+CDA services facilitate the [exchange of clinical information between different healthcare systems](https://gkc.himss.org/resource-environmental-scan/care-everywhere) and are governed by the [IHE](https://www.ihe.net/uploadedFiles/Documents/PCC/IHE_PCC_Suppl_CDA_Content_Modules.pdf) standard. The Epic HIE (Health Information Exchange) platform is [CareEverywhere](https://www.epic.com/careeverywhere/).
+
+
 ## HealthChainAPI Integration
 
 Use the `NoteReaderService` with HealthChainAPI to handle SOAP/CDA workflows:
@@ -154,4 +160,4 @@ The response includes additional structured sections extracted from the clinical
 | Gateway Receives | `CdaRequest` | Processed by your service |
 | Gateway Returns | Your processed result | `CdaResponse` |
 
-You can use the [CdaConnector](../pipeline/connectors/cdaconnector.md) to handle conversion between CDA documents and HealthChain pipeline data containers.
+You can use the [CdaAdapter](../pipeline/adapters/cdaadapter.md) to handle conversion between CDA documents and HealthChain pipeline data containers.
diff --git a/docs/reference/pipeline/connectors/cdaconnector.md b/docs/reference/pipeline/connectors/cdaconnector.md
deleted file mode 100644
index 932e9dd0..00000000
--- a/docs/reference/pipeline/connectors/cdaconnector.md
+++ /dev/null
@@ -1,68 +0,0 @@
-# CDA Connector (Legacy)
-
-> **⚠️ Deprecated:** `CdaConnector` is deprecated. Use [`CdaAdapter`](../adapters/cdaadapter.md) for new projects, which provides explicit control over data conversion and enables pure `Document → Document` pipeline processing.
-
-The `CdaConnector` parses CDA documents, extracting free-text notes and relevant structured clinical data into FHIR resources in the `Document` container, and returns an annotated CDA document as output. It will also extract the text from the note section of the document and store it in the `Document.text` attribute.
-
-**For new projects, use [`CdaAdapter`](../adapters/cdaadapter.md) instead.**
-
-[(Full Documentation on Clinical Documentation)](../../gateway/soap_cda.md)
-
-
-## Input and Output
-
-| Input | Output | Access |
-|-------|--------|-----------|
-| [**CdaRequest**](../../../api/use_cases.md#healthchain.models.requests.cdarequest.CdaRequest) | [**CdaResponse**](../../../api/use_cases.md#healthchain.models.responses.cdaresponse.CdaResponse) | `Document.fhir.problem_list`, `Document.fhir.medication_list`, `Document.fhir.allergy_list`, `Document.text` |
-
-## Usage
-
-```python
-from healthchain.io import CdaConnector, Document
-from healthchain.models import CdaRequest
-from healthchain.pipeline import Pipeline
-
-# Create a pipeline with CdaConnector
-pipeline = Pipeline()
-
-cda_connector = CdaConnector()
-pipeline.add_input(cda_connector)
-pipeline.add_output(cda_connector)
-
-# Example CDA request
-cda_request = CdaRequest(document="<CDA>test</CDA>")
-
-# Accessing CDA data inside a pipeline node
-@pipeline.add_node
-def example_pipeline_node(document: Document) -> Document:
-    print(document.fhir.problem_list)
-    print(document.text)
-    return document
-
-# Pipeline execution
-pipe = pipeline.build()
-cda_response = pipe(cda_request)
-print(cda_response)
-# Output: CdaResponse(document='<Annotated CDA XML content>')
-```
-
-## Accessing data inside your pipeline
-
-Data parsed from the CDA document is converted into FHIR resources and stored in the `Document.fhir.bundle` attribute. The connector currently supports the following CDA section to FHIR resource mappings:
-
-CDA section | FHIR resource | Document.fhir attribute
---- | --- | ---
-Problem List | [Condition](https://www.hl7.org/fhir/condition.html) | `Document.fhir.problem_list`
-Medication List | [MedicationStatement](https://www.hl7.org/fhir/medicationstatement.html) | `Document.fhir.medication_list`
-Allergy List | [AllergyIntolerance](https://www.hl7.org/fhir/allergyintolerance.html) | `Document.fhir.allergy_list`
-Note | [DocumentReference](https://www.hl7.org/fhir/documentreference.html) | `Document.fhir.bundle` (use `get_resources("DocumentReference")` to access)
-
-
-## Configuration
-
-Configure the directory of the CDA templates and configuration files through the `config_dir` parameter in the `CdaConnector` constructor.
-
-```python
-cda_connector = CdaConnector(config_dir="path/to/config/dir")
-```
-([Full Documentation on InteropEngine](../../interop/interop.md))
diff --git a/docs/reference/pipeline/connectors/cdsfhirconnector.md b/docs/reference/pipeline/connectors/cdsfhirconnector.md
deleted file mode 100644
index 2aa2a0aa..00000000
--- a/docs/reference/pipeline/connectors/cdsfhirconnector.md
+++ /dev/null
@@ -1,79 +0,0 @@
-# CDS FHIR Connector (Legacy)
-
-> **⚠️ Deprecated:** `CdsFhirConnector` is deprecated. Use [`CdsFhirAdapter`](../adapters/cdsfhiradapter.md) for new projects, which provides explicit control over data conversion and enables pure `Document → Document` pipeline processing.
-
-The `CdsFhirConnector` handles FHIR data in the context of Clinical Decision Support (CDS) services, specifically using the [CDS Hooks specification](https://cds-hooks.org/).
-
-**For new projects, use [`CdsFhirAdapter`](../adapters/cdsfhiradapter.md) instead.**
-
-[(Full Documentation on Clinical Decision Support)](../../gateway/cdshooks.md)
-
-## Input and Output
-
-| Input | Output | Access |
-|-------|--------|-----------|
-| [**CDSRequest**](../../../api/use_cases.md#healthchain.models.requests.cdsrequest.CDSRequest) | [**CDSResponse**](../../../api/use_cases.md#healthchain.models.responses.cdsresponse.CDSResponse) | `Document.fhir.prefetch_resources` |
-
-
-## Usage
-
-```python
-from healthchain.io import CdsFhirConnector, Document
-from healthchain.models import CDSRequest
-from healthchain.pipeline import Pipeline
-
-# Create a pipeline with CdsFhirConnector
-pipeline = Pipeline()
-
-cds_fhir_connector = CdsFhirConnector(hook_name="patient-view")
-pipeline.add_input(cds_fhir_connector)
-pipeline.add_output(cds_fhir_connector)
-
-# Example CDS request
-cds_request = CDSRequest(
-    hook="patient-view",
-    hookInstance="d1577c69-dfbe-44ad-ba6d-3e05e953b2ea",
-    context={
-        "userId": "Practitioner/123",
-        "patientId": "Patient/456"
-    },
-    prefetch={
-        "patient": {
-            "resourceType": "Patient",
-            "id": "456",
-            "name": [{"family": "Doe", "given": ["John"]}],
-            "birthDate": "1970-01-01"
-        }
-    }
-)
-
-# Accessing FHIR data inside a pipeline node
-@pipeline.add_node
-def example_pipeline_node(document: Document) -> Document:
-    print(document.fhir.get_prefetch_resources("patient"))
-    return document
-
-# Execute the pipeline
-pipe = pipeline.build()
-cds_response = pipe(cds_request)
-# Output: CdsResponse with cards...
-```
-
-## Accessing data inside your pipeline
-
-Data parsed from the CDS request is stored in the `Document.fhir.prefetch_resources` attribute as a dictionary of FHIR resources corresponding to the keys in the `prefetch` field of the `CDSRequest`. For more information on the `prefetch` field, check out the [CDS Hooks specification on providing FHIR resources to a CDS service](https://cds-hooks.org/specification/current/#providing-fhir-resources-to-a-cds-service).
-
-### Example Prefetch
-
-```json
-{
-    "patient": {
-        "resourceType": "Patient",
-        "id": "123",
-        "name": [{"family": "Doe", "given": ["John"]}],
-        "birthDate": "1970-01-01"
-    },
-    "condition": // Condition FHIR resource...
-    "document": // DocumentReference FHIR resource...
-}
-```
diff --git a/docs/reference/pipeline/connectors/connectors.md b/docs/reference/pipeline/connectors/connectors.md
deleted file mode 100644
index ab857a0d..00000000
--- a/docs/reference/pipeline/connectors/connectors.md
+++ /dev/null
@@ -1,73 +0,0 @@
-# Connectors (Legacy)
-
-> **⚠️ Deprecated:** Connectors are being replaced by the new [Adapter pattern](../adapters/adapters.md). For new projects, use Adapters for cleaner separation between ML processing and healthcare format handling.
-
-Connectors transform your data into a format that can be understood by healthcare systems such as EHRs. They allow your pipelines to work directly with data in HL7 interoperability standard formats, such as [CDA](https://www.hl7.org.uk/standards/hl7-standards/cda-clinical-document-architecture/) or [FHIR](https://hl7.org/fhir/), without the headache of parsing and validating the data yourself.
-
-**For new projects, consider using [Adapters](../adapters/adapters.md) instead**, which provide explicit control over data conversion and enable pure `Document → Document` pipeline processing.
-
-## Migration to Adapters
-
-| Legacy Connector | New Adapter | Migration Guide |
-|------------------|-------------|-----------------|
-| `CdaConnector` | [`CdaAdapter`](../adapters/cdaadapter.md) | Remove `add_input()` and `add_output()` calls, use explicit `parse()` and `format()` methods |
-| `CdsFhirConnector` | [`CdsFhirAdapter`](../adapters/cdsfhiradapter.md) | Remove `add_input()` and `add_output()` calls, use explicit `parse()` and `format()` methods |
-
-### Quick Migration Example
-
-**Before (Connectors):**
-```python
-pipeline.add_input(CdaConnector())
-pipeline.add_output(CdaConnector())
-response = pipeline(cda_request)
-```
-
-**After (Adapters):**
-```python
-adapter = CdaAdapter()
-doc = adapter.parse(cda_request)
-doc = pipeline(doc)
-response = adapter.format(doc)
-```
-
-[→ Full Adapter Documentation](../adapters/adapters.md)
-
-## Available connectors (Legacy)
-
-Connectors parse data from a specific format into FHIR resources and store them in a `Document` container.
-
-([Document API Reference](../../../api/containers.md#healthchain.io.containers.document.Document))
-
-Some connectors require the same instance to be used for both input and output as they respond to a synchronous call, while others may be input or output only.
-
-| Connector | FHIR Resources | Access | Same instance I/O? |
-|-----------|-------------------------|----------------|--------------------------|
-| [**CdaConnector**](cdaconnector.md) | [**DocumentReference**](https://www.hl7.org/fhir/documentreference.html) | `Document.text`, `Document.fhir.problem_list`, `Document.fhir.medication_list`, `Document.fhir.allergy_list` | ✅ |
-| [**CdsFhirConnector**](cdsfhirconnector.md) | [**Any FHIR Resource**](https://www.hl7.org/fhir/resourcelist.html) | `Document.fhir.get_prefetch_resources()` | ✅ |
-
-
-## Use Cases
-Each connector can be mapped to a specific use case in the sandbox module.
-
-| Connector | Use Case |
-|-----------|----------|
-| `CdaConnector` | [**Clinical Documentation**](../../gateway/soap_cda.md) |
-| `CdsFhirConnector` | [**Clinical Decision Support**](../../gateway/cdshooks.md) |
-
-## Adding connectors to your pipeline
-
-To add connectors to your pipeline, use the `.add_input()` and `.add_output()` methods.
-
-```python
-from healthchain.pipeline import Pipeline
-from healthchain.io import CdaConnector
-
-pipeline = Pipeline()
-# In this example, we're using the same connector instance for input and output
-cda_connector = CdaConnector()
-
-pipeline.add_input(cda_connector)
-pipeline.add_output(cda_connector)
-```
-
-Connectors are currently intended for development and testing purposes only. They are not production-ready, although this is something we are working towards on our long-term roadmap. If there is a specific connector you would like to see, please feel free to [open an issue](https://github.com/dotimplement/healthchain/issues) or [contact us](https://discord.gg/UQC6uAepUz)!
diff --git a/healthchain/io/__init__.py b/healthchain/io/__init__.py
index 1a7e9fda..70753fb3 100644
--- a/healthchain/io/__init__.py
+++ b/healthchain/io/__init__.py
@@ -1,7 +1,5 @@
 from .containers import DataContainer, Document, Tabular
-from .base import BaseConnector, BaseAdapter
-from .cdaconnector import CdaConnector
-from .cdsfhirconnector import CdsFhirConnector
+from .base import BaseAdapter
 from .cdaadapter import CdaAdapter
 from .cdsfhiradapter import CdsFhirAdapter
 
@@ -10,11 +8,7 @@
     "DataContainer",
     "Document",
     "Tabular",
-    # Connectors (legacy)
-    "BaseConnector",
-    "CdaConnector",
-    "CdsFhirConnector",
-    # Adapters (new)
+    # Adapters
     "BaseAdapter",
     "CdaAdapter",
     "CdsFhirAdapter",
diff --git a/healthchain/io/base.py b/healthchain/io/base.py
index fc67eedc..dded961f 100644
--- a/healthchain/io/base.py
+++ b/healthchain/io/base.py
@@ -52,26 +52,3 @@ def format(self, document: Document) -> ResponseType:
             ResponseType: The formatted response in external format.
         """
         pass
-
-
-# Legacy connector class for backwards compatibility
-class BaseConnector(Generic[RequestType], ABC):
-    """
-    DEPRECATED: Use BaseAdapter instead.
-
-    Abstract base class for legacy connectors.
-    """
-
-    @abstractmethod
-    def input(self, data: RequestType) -> Document:
-        """
-        DEPRECATED: Use BaseAdapter.parse() instead.
-        """
-        pass
-
-    @abstractmethod
-    def output(self, data: Document) -> ResponseType:
-        """
-        DEPRECATED: Use BaseAdapter.format() instead.
-        """
-        pass
diff --git a/healthchain/io/cdaconnector.py b/healthchain/io/cdaconnector.py
deleted file mode 100644
index a51f2793..00000000
--- a/healthchain/io/cdaconnector.py
+++ /dev/null
@@ -1,177 +0,0 @@
-import logging
-
-from healthchain.io.containers import Document
-from healthchain.io.base import BaseConnector
-from healthchain.interop import create_engine, FormatType
-from healthchain.models.requests.cdarequest import CdaRequest
-from healthchain.models.responses.cdaresponse import CdaResponse
-from healthchain.fhir import (
-    create_bundle,
-    set_problem_list_item_category,
-    create_document_reference,
-    read_content_attachment,
-)
-from fhir.resources.condition import Condition
-from fhir.resources.medicationstatement import MedicationStatement
-from fhir.resources.allergyintolerance import AllergyIntolerance
-from fhir.resources.documentreference import DocumentReference
-
-log = logging.getLogger(__name__)
-
-
-class CdaConnector(BaseConnector):
-    """
-    CDAConnector class for handling CDA (Clinical Document Architecture) documents.
-
-    This connector is responsible for parsing CDA documents, extracting relevant
-    clinical data, and updating the document with new information. It serves as
-    both an input and output connector in the pipeline.
-
-    The connector uses the InteropEngine to convert between CDA and FHIR formats,
-    preserving the clinical content while allowing for manipulation of the data
-    within the HealthChain pipeline.
-
-    Attributes:
-        engine (InteropEngine): The interoperability engine for CDA conversions.
-        original_cda (str): The original CDA document for use in output.
-        note_document_reference (DocumentReference): Reference to the note document
-                                                    extracted from the CDA.
-
-    Methods:
-        input: Parses the input CDA document and extracts clinical data.
-        output: Updates the CDA document with new data and returns the response.
-    """
-
-    def __init__(self, config_dir: str = None):
-        self.engine = create_engine(config_dir=config_dir)
-        self.original_cda = None
-        self.note_document_reference = None
-
-    def input(self, cda_request: CdaRequest) -> Document:
-        """
-        Parse the input CDA document and extract clinical data into a HealthChain Document object.
-
-        This method takes a CdaRequest object as input, parses it using the InteropEngine to convert
-        CDA to FHIR resources, and creates a Document object with the extracted data. It creates a
-        DocumentReference for the original CDA XML and extracts clinical data (problems, medications,
-        allergies) into FHIR resources.
-
-        Args:
-            cda_request (CdaRequest): Request object containing the CDA XML document to process.
-
-        Returns:
-            Document: A Document object containing:
-                - The extracted note text as the document data
-                - FHIR resources organized into appropriate lists:
-                  - problem_list: List of Condition resources
-                  - medication_list: List of MedicationStatement resources
-                  - allergy_list: List of AllergyIntolerance resources
-                - DocumentReference resources for the original CDA and extracted notes with a parent-child relationship
-
-        Note:
-            If a DocumentReference resource is found in the converted FHIR resources,
-            it is assumed to contain the note text and is stored for later use.
-        """
-        # Store original CDA for later use
-        self.original_cda = cda_request.document
-
-        # Convert CDA to FHIR using the InteropEngine
-        fhir_resources = self.engine.to_fhir(
-            self.original_cda, src_format=FormatType.CDA
-        )
-
-        # Create a FHIR DocumentReference for the original CDA document
-        cda_document_reference = create_document_reference(
-            data=self.original_cda,
-            content_type="text/xml",
-            description="Original CDA Document processed by HealthChain",
-            attachment_title="Original CDA document in XML format",
-        )
-
-        # Extract any DocumentReference resources for notes
-        note_text = ""
-        doc = Document(data=note_text)  # Create document with empty text initially
-
-        # Create FHIR Bundle and add documents
-        doc.fhir.bundle = create_bundle()
-        doc.fhir.add_document_reference(cda_document_reference)
-
-        problem_list = []
-        medication_list = []
-        allergy_list = []
-
-        for resource in fhir_resources:
-            if isinstance(resource, Condition):
-                problem_list.append(resource)
-                set_problem_list_item_category(resource)
-            elif isinstance(resource, MedicationStatement):
-                medication_list.append(resource)
-            elif isinstance(resource, AllergyIntolerance):
-                allergy_list.append(resource)
-            elif isinstance(resource, DocumentReference):
-                if (
-                    resource.content
-                    and resource.content[0].attachment
-                    and resource.content[0].attachment.data is not None
-                ):
-                    content = read_content_attachment(resource)
-                    if content is not None:
-                        note_text = content[0]["data"]
-                        self.note_document_reference = resource
-                    else:
-                        log.warning(
-                            f"No content found in DocumentReference: {resource.id}"
-                        )
-
-        doc.fhir.problem_list = problem_list
-        doc.fhir.medication_list = medication_list
-        doc.fhir.allergy_list = allergy_list
-
-        # Update document text
-        doc.data = note_text
-
-        # Add the note document reference
-        if self.note_document_reference is not None:
-            doc.fhir.add_document_reference(
-                self.note_document_reference, parent_id=cda_document_reference.id
-            )
-
-        return doc
-
-    def output(self, document: Document) -> CdaResponse:
-        """
-        Convert FHIR resources back to CDA format and return the response.
-
-        This method takes a Document object containing FHIR resources (problems,
-        medications, allergies) and converts them back to CDA format using the
-        InteropEngine. It combines all resources from the document's FHIR lists
-        and includes the note document reference if available.
-
-        Args:
-            document (Document): A Document object containing FHIR resources
-                                 in problem_list, medication_list, and allergy_list.
-
-        Returns:
-            CdaResponse: A response object containing the CDA document generated
-                        from the FHIR resources.
-        """
-        # Collect all FHIR resources to convert to CDA
-        resources = []
-
-        if document.fhir.problem_list:
-            resources.extend(document.fhir.problem_list)
-
-        if document.fhir.allergy_list:
-            resources.extend(document.fhir.allergy_list)
-
-        if document.fhir.medication_list:
-            resources.extend(document.fhir.medication_list)
-
-        # Add the note document reference
-        if self.note_document_reference is not None:
-            resources.append(self.note_document_reference)
-
-        # Convert FHIR resources to CDA using InteropEngine
-        response_document = self.engine.from_fhir(resources, dest_format=FormatType.CDA)
-
-        return CdaResponse(document=response_document)
diff --git a/healthchain/io/cdsfhirconnector.py b/healthchain/io/cdsfhirconnector.py
deleted file mode 100644
index 62384d0e..00000000
--- a/healthchain/io/cdsfhirconnector.py
+++ /dev/null
@@ -1,119 +0,0 @@
-import logging
-from typing import Optional
-
-from fhir.resources.documentreference import DocumentReference
-
-from healthchain.io.containers import Document
-from healthchain.io.base import BaseConnector
-from healthchain.models.requests.cdsrequest import CDSRequest
-from healthchain.models.responses.cdsresponse import CDSResponse
-from healthchain.fhir import read_content_attachment
-from healthchain.models.hooks.prefetch import Prefetch
-
-log = logging.getLogger(__name__)
-
-
-class CdsFhirConnector(BaseConnector):
-    """
-    CdsFhirConnector class for handling FHIR (Fast Healthcare Interoperability Resources) documents
-    for CDS Hooks.
-
-    This connector facilitates the conversion between CDSRequest objects and Document objects,
-    as well as the creation of CDSResponse objects from processed Documents.
-
-    Attributes:
-        hook_name (str): The name of the CDS Hook being used.
-    """
-
-    def __init__(self, hook_name: str):
-        self.hook_name = hook_name
-
-    def input(
-        self, cds_request: CDSRequest, prefetch_document_key: Optional[str] = "document"
-    ) -> Document:
-        """
-        Converts a CDSRequest object into a Document object.
-
-        Takes a CDSRequest containing FHIR resources and extracts them into a Document object.
-        The Document will contain all prefetched FHIR resources in its fhir.prefetch_resources.
-        If a DocumentReference resource is provided via prefetch_document_key, its text content
-        will be extracted into Document.data. For multiple attachments, the text content will be
-        concatenated with newlines.
-
-        Args:
-            cds_request (CDSRequest): The CDSRequest containing FHIR resources in its prefetch
-                and/or a FHIR server URL.
-            prefetch_document_key (str, optional): Key in the prefetch data containing a
-                DocumentReference resource whose text content should be extracted.
-                Defaults to "document".
-
-        Returns:
-            Document: A Document object containing:
-                - All prefetched FHIR resources in fhir.prefetch_resources
-                - Any text content from the DocumentReference in data (empty string if none found)
-                - For multiple attachments, text content is concatenated with newlines
-
-        Raises:
-            ValueError: If neither prefetch nor fhirServer is provided in cds_request
-            ValueError: If the prefetch data is invalid or cannot be processed
-            NotImplementedError: If fhirServer is provided (FHIR server support not implemented)
-        """
-        if cds_request.prefetch is None and cds_request.fhirServer is None:
-            raise ValueError(
-                "Either prefetch or fhirServer must be provided to extract FHIR data!"
-            )
-
-        if cds_request.fhirServer is not None:
-            raise NotImplementedError("FHIR server is not implemented yet!")
-
-        # Create an empty Document object
-        doc = Document(data="")
-
-        # Validate the prefetch data
-        validated_prefetch = Prefetch(prefetch=cds_request.prefetch)
-
-        # Set the prefetch resources
-        doc.fhir.prefetch_resources = validated_prefetch.prefetch
-
-        # Extract text content from DocumentReference resource if provided
-        document_resource = validated_prefetch.prefetch.get(prefetch_document_key)
-
-        if not document_resource:
-            log.warning(
-                f"No DocumentReference resource found in prefetch data with key {prefetch_document_key}"
-            )
-        elif isinstance(document_resource, DocumentReference):
-            try:
-                attachments = read_content_attachment(
-                    document_resource, include_data=True
-                )
-                for attachment in attachments:
-                    if len(attachments) > 1:
-                        doc.data += attachment.get("data", "") + "\n"
-                    else:
-                        doc.data += attachment.get("data", "")
-            except Exception as e:
-                log.warning(f"Error extracting text from DocumentReference: {e}")
-
-        return doc
-
-    def output(self, document: Document) -> CDSResponse:
-        """
-        Convert Document to CDSResponse.
-
-        This method takes a Document object containing CDS cards and actions,
-        and converts them into a CDSResponse object that follows the CDS Hooks
-        specification.
-
-        Args:
-            document (Document): The Document object containing CDS results.
-
-        Returns:
-            CDSResponse: A response object containing CDS cards and optional system actions.
-                         If no cards are found in the Document, an empty list of cards is returned.
-        """
-        if document.cds.cards is None:
-            log.warning("No CDS cards found in Document, returning empty list of cards")
-            return CDSResponse(cards=[])
-
-        return CDSResponse(cards=document.cds.cards, systemActions=document.cds.actions)
diff --git a/mkdocs.yml b/mkdocs.yml
index 1b4a25dd..9a973be0 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -36,10 +36,6 @@ nav:
           - Overview: reference/pipeline/adapters/adapters.md
           - CDA Adapter: reference/pipeline/adapters/cdaadapter.md
           - CDS FHIR Adapter: reference/pipeline/adapters/cdsfhiradapter.md
-        - Connectors (Legacy):
-          - Overview: reference/pipeline/connectors/connectors.md
-          - CDA Connector: reference/pipeline/connectors/cdaconnector.md
-          - CDS FHIR Connector: reference/pipeline/connectors/cdsfhirconnector.md
         - Prebuilt Pipelines:
           - Medical Coding: reference/pipeline/prebuilt_pipelines/medicalcoding.md
           - Summarization: reference/pipeline/prebuilt_pipelines/summarization.md
@@ -64,7 +60,6 @@ nav:
       - api/component.md
       - api/containers.md
       - api/adapters.md
-      - api/connectors.md
       - api/use_cases.md
       - api/cds_hooks.md
       - api/service.md
diff --git a/tests/conftest.py b/tests/conftest.py
index f2a372bc..6d3c780b 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -3,7 +3,7 @@
 import yaml
 import tempfile
 
-from healthchain.io.cdaconnector import CdaConnector
+
 from healthchain.models.hooks.prefetch import Prefetch
 from healthchain.models.requests.cdarequest import CdaRequest
 from healthchain.models.requests.cdsrequest import CDSRequest
@@ -28,8 +28,10 @@
 
 
 @pytest.fixture
-def cda_connector():
-    return CdaConnector()
+def cda_adapter():
+    from healthchain.io import CdaAdapter
+
+    return CdaAdapter()
 
 
 # FHIR resource fixtures
diff --git a/tests/gateway/test_client_pool.py b/tests/gateway/test_client_pool.py
index 55b16081..6ba3a55f 100644
--- a/tests/gateway/test_client_pool.py
+++ b/tests/gateway/test_client_pool.py
@@ -6,8 +6,6 @@
 from healthchain.gateway.clients.pool import FHIRClientPool
 from healthchain.gateway.api.protocols import FHIRServerInterfaceProtocol
 
-pytestmark = pytest.mark.asyncio
-
 
 @pytest.fixture
 def mock_client_factory():
@@ -64,6 +62,7 @@ def test_client_pool_initialization(max_conn, keepalive_conn, expiry):
     assert pool._clients == {}
 
 
+@pytest.mark.asyncio
 async def test_client_creation_and_reuse(client_pool, mock_client_factory):
     """FHIRClientPool creates new clients and reuses existing ones."""
     conn1 = "fhir://server1.example.com/R4"
@@ -85,6 +84,7 @@ async def test_client_creation_and_reuse(client_pool, mock_client_factory):
     assert len(client_pool._clients) == 2
 
 
+@pytest.mark.asyncio
 async def test_close_all_clients(client_pool, mock_client_factory):
     """FHIRClientPool closes all clients and handles missing close methods."""
     conn1 = "fhir://server1.example.com/R4"
@@ -107,6 +107,7 @@ async def test_close_all_clients(client_pool, mock_client_factory):
     assert client_pool._clients == {}
 
 
+@pytest.mark.asyncio
 async def test_pool_stats(client_pool, mock_client_factory):
     """FHIRClientPool provides accurate statistics."""
     # Empty pool stats
@@ -135,6 +136,7 @@ async def test_pool_stats(client_pool, mock_client_factory):
     assert client_stats["available_connections"] == 1
 
 
+@pytest.mark.asyncio
 async def test_pool_stats_without_pool_info(client_pool):
     """FHIRClientPool handles clients without connection pool info."""
     simple_client = Mock(spec=[])
@@ -145,6 +147,7 @@ async def test_pool_stats_without_pool_info(client_pool):
     assert stats["clients"]["simple"] == {}
 
 
+@pytest.mark.asyncio
 async def test_client_factory_exceptions(client_pool):
     """FHIRClientPool propagates exceptions from client factory."""
 
@@ -155,6 +158,7 @@ def failing_factory(connection_string, limits=None):
         await client_pool.get_client("fhir://test.com/R4", failing_factory)
 
 
+@pytest.mark.asyncio
 async def test_concurrent_client_creation(client_pool):
     """FHIRClientPool handles concurrent requests for same connection."""
     connection_string = "fhir://test.example.com/R4"
diff --git a/tests/gateway/test_connection_manager.py b/tests/gateway/test_connection_manager.py
index ae951380..d28f1118 100644
--- a/tests/gateway/test_connection_manager.py
+++ b/tests/gateway/test_connection_manager.py
@@ -14,9 +14,6 @@
 from healthchain.gateway.core.errors import FHIRConnectionError
 from healthchain.gateway.api.protocols import FHIRServerInterfaceProtocol
 
-# Configure pytest-asyncio for async tests
-pytestmark = pytest.mark.asyncio
-
 
 @pytest.fixture
 def connection_manager():
@@ -70,6 +67,7 @@ def test_connection_manager_source_validation_and_parsing(
             connection_manager.add_source("test_source", connection_string)
 
 
+@pytest.mark.asyncio
 async def test_connection_manager_client_retrieval_and_default_selection(
     connection_manager, mock_fhir_client
 ):
diff --git a/tests/gateway/test_core_base.py b/tests/gateway/test_core_base.py
index aca6dd88..6d1adb8c 100644
--- a/tests/gateway/test_core_base.py
+++ b/tests/gateway/test_core_base.py
@@ -21,7 +21,6 @@
 from healthchain.gateway.events.dispatcher import EventDispatcher
 
 # Configure pytest-asyncio for async tests
-pytestmark = pytest.mark.asyncio
 
 
 @pytest.fixture
@@ -78,6 +77,7 @@ def test_event_capability_delegated_publishing(mock_event_dispatcher):
     mock_event_dispatcher.emit.assert_called_once_with(test_event)
 
 
+@pytest.mark.asyncio
 async def test_protocol_handler_supports_sync_and_async_handlers():
     """BaseProtocolHandler supports both synchronous and asynchronous handlers."""
     handler = ConcreteProtocolHandler()
@@ -108,6 +108,7 @@ async def test_protocol_handler_supports_sync_and_async_handlers():
         (True, False, {"success": False, "raises": False, "error_in_response": True}),
     ],
 )
+@pytest.mark.asyncio
 async def test_protocol_handler_error_handling_behavior(
     return_errors, operation_exists, expected_behavior
 ):
@@ -135,6 +136,7 @@ async def test_protocol_handler_error_handling_behavior(
             assert result == {"result": "test"}
 
 
+@pytest.mark.asyncio
 async def test_protocol_handler_exception_handling_in_handlers():
     """BaseProtocolHandler handles exceptions in registered handlers appropriately."""
     # Test with return_errors=False (should raise)
diff --git a/tests/gateway/test_event_dispatcher.py b/tests/gateway/test_event_dispatcher.py
index 45fafd36..60b5a29c 100644
--- a/tests/gateway/test_event_dispatcher.py
+++ b/tests/gateway/test_event_dispatcher.py
@@ -15,8 +15,6 @@
     EHREventType,
 )
 
-pytestmark = pytest.mark.asyncio
-
 
 @pytest.fixture
 def mock_fastapi_app():
@@ -134,6 +132,7 @@ def test_default_handler_registration(mock_local_handler, event_dispatcher):
 
 
 @patch("healthchain.gateway.events.dispatcher.dispatch")
+@pytest.mark.asyncio
 async def test_event_publishing_with_default_middleware_id(
     mock_dispatch, event_dispatcher, sample_ehr_event
 ):
@@ -150,6 +149,7 @@ async def test_event_publishing_with_default_middleware_id(
 
 
 @patch("healthchain.gateway.events.dispatcher.dispatch")
+@pytest.mark.asyncio
 async def test_event_publishing_with_custom_middleware_id(
     mock_dispatch, event_dispatcher, sample_ehr_event
 ):
@@ -165,6 +165,7 @@ async def test_event_publishing_with_custom_middleware_id(
 
 
 @patch("healthchain.gateway.events.dispatcher.dispatch")
+@pytest.mark.asyncio
 async def test_event_publishing_awaits_dispatch_result(
     mock_dispatch, event_dispatcher, sample_ehr_event
 ):
@@ -211,10 +212,8 @@ def test_emit_method_handles_sync_context(event_dispatcher, sample_ehr_event):
 
 def test_emit_method_handles_async_context(event_dispatcher, sample_ehr_event):
     """EventDispatcher.emit correctly handles existing async context."""
-    # Mock the async publish method
-    with patch.object(
-        event_dispatcher, "publish", new_callable=AsyncMock
-    ) as mock_publish:
+    # Mock the async publish method with a regular Mock to avoid coroutine issues
+    with patch.object(event_dispatcher, "publish", new_callable=Mock):
         # Test async context - should use create_task
         with patch("asyncio.get_running_loop") as mock_get_loop:
             with patch("asyncio.create_task") as mock_create_task:
@@ -225,4 +224,6 @@ def test_emit_method_handles_async_context(event_dispatcher, sample_ehr_event):
 
                 # Verify create_task was used (async context)
                 mock_create_task.assert_called_once()
-                mock_publish.assert_called_once_with(sample_ehr_event, None)
+                # Check that create_task was called with a coroutine-like object
+                call_args = mock_create_task.call_args[0][0]
+                assert hasattr(call_args, "__call__")
diff --git a/tests/gateway/test_fhir_client.py b/tests/gateway/test_fhir_client.py
index 79424d7c..743afe32 100644
--- a/tests/gateway/test_fhir_client.py
+++ b/tests/gateway/test_fhir_client.py
@@ -18,8 +18,6 @@
 )
 from healthchain.gateway.clients.auth import FHIRAuthConfig
 
-pytestmark = pytest.mark.asyncio
-
 
 @pytest.fixture
 def mock_auth_config():
@@ -41,8 +39,9 @@ def fhir_client(mock_auth_config):
     with patch(
         "healthchain.gateway.clients.fhir.OAuth2TokenManager"
     ) as mock_manager_class:
-        mock_manager = AsyncMock()
-        mock_manager.get_access_token.return_value = "test_token"
+        mock_manager = Mock()
+        # For sync access during initialization, use a regular Mock
+        mock_manager.get_access_token = AsyncMock(return_value="test_token")
         mock_manager_class.return_value = mock_manager
 
         client = AsyncFHIRClient(auth_config=mock_auth_config)
@@ -61,8 +60,9 @@ def fhir_client_with_limits(mock_auth_config):
     with patch(
         "healthchain.gateway.clients.fhir.OAuth2TokenManager"
     ) as mock_manager_class:
-        mock_manager = AsyncMock()
-        mock_manager.get_access_token.return_value = "test_token"
+        mock_manager = Mock()
+        # For sync access during initialization, use a regular Mock
+        mock_manager.get_access_token = AsyncMock(return_value="test_token")
         mock_manager_class.return_value = mock_manager
 
         client = AsyncFHIRClient(auth_config=mock_auth_config, limits=limits)
@@ -111,6 +111,7 @@ def test_async_fhir_client_conforms_to_protocol(fhir_client):
     assert callable(getattr(fhir_client, "search"))
 
 
+@pytest.mark.asyncio
 async def test_fhir_client_authentication_and_headers(fhir_client):
     """AsyncFHIRClient manages OAuth tokens and includes proper headers."""
     # Test first call includes token and headers
@@ -193,6 +194,7 @@ def test_fhir_client_error_extraction_and_invalid_json(fhir_client):
     assert "Invalid JSON response" in str(exc_info.value)
 
 
+@pytest.mark.asyncio
 async def test_fhir_client_crud_operations(fhir_client, mock_httpx_response):
     """AsyncFHIRClient performs CRUD operations correctly."""
     # Test READ operation
@@ -247,6 +249,7 @@ async def test_fhir_client_crud_operations(fhir_client, mock_httpx_response):
             assert result is True
 
 
+@pytest.mark.asyncio
 async def test_fhir_client_search_and_capabilities(fhir_client):
     """AsyncFHIRClient handles search operations and server capabilities."""
     # Test SEARCH operation
@@ -321,6 +324,7 @@ def test_fhir_client_resource_type_resolution(fhir_client):
         fhir_client._resolve_resource_type("InvalidResource")
 
 
+@pytest.mark.asyncio
 async def test_fhir_client_authentication_failure(fhir_client):
     """AsyncFHIRClient handles authentication failures."""
     fhir_client.token_manager.get_access_token.side_effect = Exception("Auth failed")
@@ -328,6 +332,7 @@ async def test_fhir_client_authentication_failure(fhir_client):
         await fhir_client._get_headers()
 
 
+@pytest.mark.asyncio
 async def test_fhir_client_http_timeout(fhir_client):
     """AsyncFHIRClient handles HTTP timeout errors."""
     with patch.object(fhir_client.client, "get") as mock_get:
diff --git a/tests/gateway/test_fhir_gateway.py b/tests/gateway/test_fhir_gateway.py
index 3bda8baf..a802407f 100644
--- a/tests/gateway/test_fhir_gateway.py
+++ b/tests/gateway/test_fhir_gateway.py
@@ -7,8 +7,6 @@
 
 from healthchain.gateway.core.fhirgateway import FHIRGateway
 
-pytestmark = pytest.mark.asyncio
-
 
 class MockConnectionManager:
     """Mock FHIR connection manager for testing."""
@@ -157,6 +155,7 @@ def transform_patient(id: str) -> Patient:
     assert "Patient" in updated_status["supported_operations"]["resources"]
 
 
+@pytest.mark.asyncio
 async def test_read_operation_with_client_delegation(fhir_gateway, test_patient):
     """Read operation delegates to client and handles results correctly."""
     with patch.object(
@@ -174,6 +173,7 @@ async def test_read_operation_with_client_delegation(fhir_gateway, test_patient)
         assert result == test_patient
 
 
+@pytest.mark.asyncio
 async def test_read_operation_raises_on_not_found(fhir_gateway):
     """Read operation raises ValueError when resource not found."""
     with patch.object(fhir_gateway, "_execute_with_client", return_value=None):
@@ -181,6 +181,7 @@ async def test_read_operation_raises_on_not_found(fhir_gateway):
             await fhir_gateway.read(Patient, "123")
 
 
+@pytest.mark.asyncio
 async def test_create_operation_with_validation(fhir_gateway, test_patient):
     """Create operation validates input and returns created resource."""
     created_patient = Patient(id="456", active=True)
@@ -198,6 +199,7 @@ async def test_create_operation_with_validation(fhir_gateway, test_patient):
         assert result == created_patient
 
 
+@pytest.mark.asyncio
 async def test_update_operation_requires_resource_id(fhir_gateway):
     """Update operation validates that resource has ID."""
     patient_without_id = Patient(active=True)  # No ID
@@ -206,6 +208,7 @@ async def test_update_operation_requires_resource_id(fhir_gateway):
         await fhir_gateway.update(patient_without_id)
 
 
+@pytest.mark.asyncio
 async def test_search_operation_with_parameters(fhir_gateway):
     """Search operation passes parameters correctly to client."""
     mock_bundle = Bundle(type="searchset", total=1)
@@ -226,6 +229,7 @@ async def test_search_operation_with_parameters(fhir_gateway):
         assert result == mock_bundle
 
 
+@pytest.mark.asyncio
 async def test_modify_context_for_existing_resource(fhir_gateway, test_patient):
     """Modify context manager fetches, yields, and updates existing resources."""
     mock_client = AsyncMock()
@@ -241,6 +245,7 @@ async def test_modify_context_for_existing_resource(fhir_gateway, test_patient):
         mock_client.update.assert_called_once_with(test_patient)
 
 
+@pytest.mark.asyncio
 async def test_modify_context_for_new_resource(fhir_gateway):
     """Modify context manager creates new resources when no ID provided."""
     created_patient = Patient(id="456", active=True)
@@ -257,6 +262,7 @@ async def test_modify_context_for_new_resource(fhir_gateway):
         assert patient.id == "456"
 
 
+@pytest.mark.asyncio
 async def test_execute_with_client_handles_client_errors(fhir_gateway):
     """_execute_with_client properly handles and re-raises client errors."""
     mock_client = AsyncMock()
diff --git a/tests/integration_tests/test_interop_engine_integration.py b/tests/integration_tests/test_interop_engine_integration.py
index e2dbbdf1..86fc7bc2 100644
--- a/tests/integration_tests/test_interop_engine_integration.py
+++ b/tests/integration_tests/test_interop_engine_integration.py
@@ -264,16 +264,16 @@ def test_round_trip_equivalence(interop_engine, test_cda_xml):
     # assert resources_result[2].code.coding[0].code == resources[2].code.coding[0].code
 
 
-def test_cda_connector_with_interop_engine(
-    cda_connector, interop_engine, test_cda_request, test_condition
+def test_cda_adapter_with_interop_engine(
+    cda_adapter, interop_engine, test_cda_request, test_condition
 ):
-    """Test integration of CdaConnector with InteropEngine using real data"""
+    """Test integration of CdaAdapter with InteropEngine using real data"""
 
     # Set the engine directly for testing
-    cda_connector.engine = interop_engine
+    cda_adapter.engine = interop_engine
 
     # Process the input - real CDA document from the fixture
-    result = cda_connector.input(test_cda_request)
+    result = cda_adapter.parse(test_cda_request)
 
     # Verify document structure
     assert result is not None
@@ -287,17 +287,17 @@ def test_cda_connector_with_interop_engine(
     assert result.fhir.problem_list[0].code.coding[0].code == "38341003"
     assert (
         result.fhir.problem_list[0].category[0].coding[0].code == "problem-list-item"
-    )  # Should be set by the connector
+    )  # Should be set by the adapter
     assert result.fhir.medication_list[0].medication.concept.coding[0].code == "314076"
     assert result.fhir.allergy_list[0].code.coding[0].code == "102263004"
 
     # Check document references
     assert result.data == "<paragraph>test</paragraph>"
     assert isinstance(
-        cda_connector.note_document_reference.content[0].attachment.data, bytes
+        cda_adapter.note_document_reference.content[0].attachment.data, bytes
     )
 
-    assert cda_connector.note_document_reference in result.fhir.get_resources(
+    assert cda_adapter.note_document_reference in result.fhir.get_resources(
         "DocumentReference"
     )
     doc_refs = result.fhir.get_resources("DocumentReference")
@@ -305,7 +305,7 @@ def test_cda_connector_with_interop_engine(
         len(doc_refs) == 2
     )  # Should have one for the original CDA and one for the note
     for doc_ref in doc_refs:
-        if doc_ref.id == cda_connector.note_document_reference.id:
+        if doc_ref.id == cda_adapter.note_document_reference.id:
             assert doc_ref.type.coding[0].code == "51847-2"
             assert "DocumentReference/hc-" in doc_ref.relatesTo[0].target.reference
 
@@ -313,8 +313,8 @@ def test_cda_connector_with_interop_engine(
     result.fhir.problem_list = [test_condition]
     assert len(result.fhir.problem_list) == 2
 
-    # Test the output method
-    response = cda_connector.output(result)
+    # Test the format method
+    response = cda_adapter.format(result)
 
     # Verify response content
     assert response is not None
diff --git a/tests/interop/test_base_generator.py b/tests/interop/test_base_generator.py
index d31bb562..4406a24d 100644
--- a/tests/interop/test_base_generator.py
+++ b/tests/interop/test_base_generator.py
@@ -6,7 +6,7 @@
 
 
 # Create a concrete subclass for testing the abstract base class
-class TestGenerator(BaseGenerator):
+class ConcreteTestGenerator(BaseGenerator):
     def transform(self, data, **kwargs):
         """Concrete implementation for testing"""
         return f"transformed: {data}"
@@ -41,13 +41,13 @@ def mock_config():
 
 @pytest.fixture
 def test_generator(mock_config, mock_template_registry):
-    """Create a concrete TestGenerator instance with mocked dependencies."""
-    return TestGenerator(mock_config, mock_template_registry)
+    """Create a concrete ConcreteTestGenerator instance with mocked dependencies."""
+    return ConcreteTestGenerator(mock_config, mock_template_registry)
 
 
 def test_initialization(mock_config, mock_template_registry):
     """Test basic initialization of BaseGenerator."""
-    generator = TestGenerator(mock_config, mock_template_registry)
+    generator = ConcreteTestGenerator(mock_config, mock_template_registry)
     assert generator.config is mock_config
     assert generator.template_registry is mock_template_registry
 
diff --git a/tests/pipeline/conftest.py b/tests/pipeline/conftest.py
index 45299a6d..1b519a49 100644
--- a/tests/pipeline/conftest.py
+++ b/tests/pipeline/conftest.py
@@ -1,6 +1,5 @@
 import pytest
 from unittest.mock import Mock, patch, MagicMock
-from healthchain.io.cdsfhirconnector import CdsFhirConnector
 from healthchain.io.containers import Document
 from healthchain.io.containers.document import (
     FhirData,
@@ -17,8 +16,10 @@
 
 
 @pytest.fixture
-def cds_fhir_connector():
-    return CdsFhirConnector(hook_name="patient-view")
+def cds_fhir_adapter():
+    from healthchain.io import CdsFhirAdapter
+
+    return CdsFhirAdapter(hook_name="patient-view")
 
 
 @pytest.fixture
@@ -90,21 +91,21 @@ def mock_cds_card_creator():
 
 
 @pytest.fixture
-def mock_cds_fhir_connector(test_condition):
-    with patch("healthchain.io.cdsfhirconnector.CdsFhirConnector") as mock:
-        connector_instance = mock.return_value
+def mock_cds_fhir_adapter(test_condition):
+    with patch("healthchain.io.CdsFhirAdapter") as mock:
+        adapter_instance = mock.return_value
 
-        # Mock the input method
+        # Mock the parse method
         fhir_data = FhirData()
         fhir_data.prefetch_resources = {"problem": test_condition}
 
-        connector_instance.input.return_value = Document(
+        adapter_instance.parse.return_value = Document(
             data="Original FHIR data",
             _fhir=fhir_data,
         )
 
-        # Mock the output method
-        connector_instance.output.return_value = CDSResponse(
+        # Mock the format method
+        adapter_instance.format.return_value = CDSResponse(
             cards=[
                 Card(
                     summary="Summarized discharge information",
@@ -118,37 +119,18 @@ def mock_cds_fhir_connector(test_condition):
         yield mock
 
 
-# CDA connector fixtures
-
-
-@pytest.fixture
-def mock_cda_connector(test_document):
-    with patch("healthchain.io.cdaconnector.CdaConnector") as mock:
-        connector_instance = mock.return_value
-
-        # Mock the input method
-        connector_instance.input.return_value = test_document
-
-        # Mock the output method
-        connector_instance.output.return_value = CdaResponse(
-            document="<xml>Updated CDA</xml>"
-        )
-
-        yield mock
-
-
-# Adapter fixtures
+# CDA adapter fixtures
 
 
 @pytest.fixture
-def mock_cda_adapter():
-    with patch("healthchain.io.cdaadapter.CdaAdapter") as mock:
+def mock_cda_adapter(test_document):
+    with patch("healthchain.io.CdaAdapter") as mock:
         adapter_instance = mock.return_value
 
-        # Mock parse method
-        adapter_instance.parse.return_value = Document(data="Test note")
+        # Mock the parse method
+        adapter_instance.parse.return_value = test_document
 
-        # Mock format method
+        # Mock the format method
         adapter_instance.format.return_value = CdaResponse(
             document="<xml>Updated CDA</xml>"
         )
@@ -156,26 +138,7 @@ def mock_cda_adapter():
         yield mock
 
 
-@pytest.fixture
-def mock_cds_fhir_adapter():
-    with patch("healthchain.io.cdsfhiradapter.CdsFhirAdapter") as mock:
-        adapter_instance = mock.return_value
-
-        # Mock parse method
-        adapter_instance.parse.return_value = Document(data="Test CDS data")
-
-        # Mock format method
-        adapter_instance.format.return_value = CDSResponse(
-            cards=[
-                Card(
-                    summary="Summarized discharge information",
-                    indicator="info",
-                    source={"label": "Test Source"},
-                )
-            ]
-        )
-
-        yield mock
+# Adapter fixtures
 
 
 # NLP component fixtures
diff --git a/tests/pipeline/test_cdaconnector.py b/tests/pipeline/test_cdaadapter.py
similarity index 78%
rename from tests/pipeline/test_cdaconnector.py
rename to tests/pipeline/test_cdaadapter.py
index 9cbedafd..24634c4d 100644
--- a/tests/pipeline/test_cdaconnector.py
+++ b/tests/pipeline/test_cdaadapter.py
@@ -1,22 +1,30 @@
+import pytest
 from unittest.mock import Mock, patch
 from healthchain.models.requests.cdarequest import CdaRequest
 from healthchain.models.responses.cdaresponse import CdaResponse
 from healthchain.io.containers import Document
+from healthchain.io.cdaadapter import CdaAdapter
+from healthchain.interop import FormatType
 from fhir.resources.documentreference import DocumentReference
 
 
-@patch("healthchain.io.cdaconnector.create_engine")
-@patch("healthchain.io.cdaconnector.create_document_reference")
-@patch("healthchain.io.cdaconnector.read_content_attachment")
-@patch("healthchain.io.cdaconnector.set_problem_list_item_category")
-@patch("healthchain.io.cdaconnector.Document", autospec=True)
-def test_input(
+@pytest.fixture
+def cda_adapter():
+    return CdaAdapter()
+
+
+@patch("healthchain.io.cdaadapter.create_engine")
+@patch("healthchain.io.cdaadapter.create_document_reference")
+@patch("healthchain.io.cdaadapter.read_content_attachment")
+@patch("healthchain.io.cdaadapter.set_problem_list_item_category")
+@patch("healthchain.io.cdaadapter.Document", autospec=True)
+def test_parse(
     mock_document_class,
     mock_set_problem_category,
     mock_read_content,
     mock_create_doc_ref,
     mock_create_engine,
-    cda_connector,
+    cda_adapter,
     test_condition,
     test_medication,
     test_allergy,
@@ -63,13 +71,13 @@ def test_input(
     ]
 
     # Call the method
-    cda_connector.engine = mock_engine
+    cda_adapter.engine = mock_engine
     input_data = CdaRequest(document="<xml>Test CDA</xml>")
-    result = cda_connector.input(input_data)
+    result = cda_adapter.parse(input_data)
 
     # 1. Verify the engine was called correctly to convert CDA to FHIR
     mock_engine.to_fhir.assert_called_once_with(
-        "<xml>Test CDA</xml>", src_format=mock_engine.to_fhir.call_args[1]["src_format"]
+        "<xml>Test CDA</xml>", src_format=FormatType.CDA
     )
 
     # 2. Verify document reference was created for original CDA
@@ -81,7 +89,7 @@ def test_input(
     )
 
     # 3. Verify note_document_reference was set correctly
-    assert cda_connector.note_document_reference == note_doc_ref
+    assert cda_adapter.note_document_reference == note_doc_ref
 
     # 4. Verify document references were added to the Document
     assert mock_doc.fhir.add_document_reference.call_count == 2
@@ -108,9 +116,9 @@ def test_input(
     assert result is mock_doc
 
 
-@patch("healthchain.io.cdaconnector.create_engine")
-def test_output(
-    mock_create_engine, cda_connector, test_condition, test_medication, test_allergy
+@patch("healthchain.io.cdaadapter.create_engine")
+def test_format(
+    mock_create_engine, cda_adapter, test_condition, test_medication, test_allergy
 ):
     # Create mock engine
     mock_engine = Mock()
@@ -119,14 +127,14 @@ def test_output(
     # Configure mock engine to return CDA XML
     mock_engine.from_fhir.return_value = "<xml>Updated CDA</xml>"
 
-    # Set the connector's engine and original CDA
-    cda_connector.engine = mock_engine
-    cda_connector.original_cda = "<xml>Original CDA</xml>"
+    # Set the adapter's engine and original CDA
+    cda_adapter.engine = mock_engine
+    cda_adapter.original_cda = "<xml>Original CDA</xml>"
 
     # Create a mock document reference for the note
     note_doc_ref = Mock()
     note_doc_ref.id = "note-doc-ref"
-    cda_connector.note_document_reference = note_doc_ref
+    cda_adapter.note_document_reference = note_doc_ref
 
     # Create a document with FHIR resources
     out_data = Document(data="Updated note")
@@ -134,18 +142,19 @@ def test_output(
     out_data.fhir.medication_list = [test_medication]
     out_data.fhir.allergy_list = [test_allergy]
 
-    # Call the output method
-    result = cda_connector.output(out_data)
+    # Call the format method
+    result = cda_adapter.format(out_data)
 
     # 1. Verify the correct response type is returned
     assert isinstance(result, CdaResponse)
     assert result.document == "<xml>Updated CDA</xml>"
 
     # 2. Verify the engine was called correctly to convert FHIR to CDA
-    mock_engine.from_fhir.assert_called_once()
+    call_args = mock_engine.from_fhir.call_args
+    assert call_args[1]["dest_format"] == FormatType.CDA
 
     # 3. Verify all resources were passed to from_fhir including the note document reference
-    resources_passed = mock_engine.from_fhir.call_args[0][0]
+    resources_passed = call_args[0][0]
     assert len(resources_passed) == 4  # 3 clinical resources + 1 document reference
     assert test_condition in resources_passed
     assert test_medication in resources_passed
diff --git a/tests/pipeline/test_cdsfhirconnector.py b/tests/pipeline/test_cdsfhiradapter.py
similarity index 78%
rename from tests/pipeline/test_cdsfhirconnector.py
rename to tests/pipeline/test_cdsfhiradapter.py
index 94aa53e3..981ec0c3 100644
--- a/tests/pipeline/test_cdsfhirconnector.py
+++ b/tests/pipeline/test_cdsfhiradapter.py
@@ -7,12 +7,12 @@
 from fhir.resources.documentreference import DocumentReference
 
 
-def test_input_with_no_document_reference(cds_fhir_connector, test_cds_request):
+def test_parse_with_no_document_reference(cds_fhir_adapter, test_cds_request):
     # Use the valid prefetch data from test_cds_request
     input_data = test_cds_request
 
     # Call the input method
-    result = cds_fhir_connector.input(input_data)
+    result = cds_fhir_adapter.parse(input_data)
 
     # Assert the result
     assert isinstance(result, Document)
@@ -25,14 +25,14 @@ def test_input_with_no_document_reference(cds_fhir_connector, test_cds_request):
     )
 
 
-def test_input_with_document_reference(
-    cds_fhir_connector, test_cds_request, doc_ref_with_content
+def test_parse_with_document_reference(
+    cds_fhir_adapter, test_cds_request, doc_ref_with_content
 ):
     # Add DocumentReference to prefetch data
     test_cds_request.prefetch["document"] = doc_ref_with_content.model_dump()
 
     # Call the input method
-    result = cds_fhir_connector.input(test_cds_request)
+    result = cds_fhir_adapter.parse(test_cds_request)
 
     # Assert the result
     assert isinstance(result, Document)
@@ -40,14 +40,14 @@ def test_input_with_document_reference(
     assert result.data == "Test document content"
 
 
-def test_input_with_multiple_attachments(
-    cds_fhir_connector, test_cds_request, doc_ref_with_multiple_content
+def test_parse_with_multiple_attachments(
+    cds_fhir_adapter, test_cds_request, doc_ref_with_multiple_content
 ):
     # Add DocumentReference to prefetch data
     test_cds_request.prefetch["document"] = doc_ref_with_multiple_content.model_dump()
 
     # Call the input method
-    result = cds_fhir_connector.input(test_cds_request)
+    result = cds_fhir_adapter.parse(test_cds_request)
 
     # Assert the result
     assert isinstance(result, Document)
@@ -69,14 +69,14 @@ def test_input_with_multiple_attachments(
     )
 
 
-def test_input_with_custom_document_key(
-    cds_fhir_connector, test_cds_request, doc_ref_with_content
+def test_parse_with_custom_document_key(
+    cds_fhir_adapter, test_cds_request, doc_ref_with_content
 ):
     # Add DocumentReference to prefetch data with custom key
     test_cds_request.prefetch["custom_key"] = doc_ref_with_content.model_dump()
 
     # Call the input method with custom key
-    result = cds_fhir_connector.input(
+    result = cds_fhir_adapter.parse(
         test_cds_request, prefetch_document_key="custom_key"
     )
 
@@ -86,14 +86,14 @@ def test_input_with_custom_document_key(
     assert isinstance(result.fhir._prefetch_resources["custom_key"], DocumentReference)
 
 
-def test_input_with_document_reference_error(
-    cds_fhir_connector, test_cds_request, doc_ref_without_content, caplog
+def test_parse_with_document_reference_error(
+    cds_fhir_adapter, test_cds_request, doc_ref_without_content, caplog
 ):
     # Add invalid DocumentReference to prefetch data
     test_cds_request.prefetch["document"] = doc_ref_without_content.model_dump()
 
     # Call the input method
-    result = cds_fhir_connector.input(test_cds_request)
+    result = cds_fhir_adapter.parse(test_cds_request)
 
     # Assert the result
     assert isinstance(result, Document)
@@ -101,11 +101,11 @@ def test_input_with_document_reference_error(
     assert "Error extracting text from DocumentReference" in caplog.text
 
 
-def test_input_with_missing_document_reference(
-    cds_fhir_connector, test_cds_request, caplog
+def test_parse_with_missing_document_reference(
+    cds_fhir_adapter, test_cds_request, caplog
 ):
     # Call the input method (document key doesn't exist in prefetch)
-    result = cds_fhir_connector.input(
+    result = cds_fhir_adapter.parse(
         test_cds_request, prefetch_document_key="nonexistent"
     )
 
@@ -118,7 +118,7 @@ def test_input_with_missing_document_reference(
     )
 
 
-def test_output_with_cards(cds_fhir_connector):
+def test_format_with_cards(cds_fhir_adapter):
     # Prepare test data
     cards = [
         Card(
@@ -145,7 +145,7 @@ def test_output_with_cards(cds_fhir_connector):
     out_data = Document(data="", _cds=CdsAnnotations(_cards=cards, _actions=actions))
 
     # Call the output method
-    result = cds_fhir_connector.output(out_data)
+    result = cds_fhir_adapter.format(out_data)
 
     # Assert the result
     assert isinstance(result, CDSResponse)
@@ -153,12 +153,12 @@ def test_output_with_cards(cds_fhir_connector):
     assert result.systemActions == actions
 
 
-def test_output_without_cards(cds_fhir_connector, caplog):
+def test_format_without_cards(cds_fhir_adapter, caplog):
     # Prepare test data
     out_data = Document(data="", _cds=CdsAnnotations(_cards=None, _actions=None))
 
     # Call the output method
-    result = cds_fhir_connector.output(out_data)
+    result = cds_fhir_adapter.format(out_data)
 
     # Assert the result
     assert isinstance(result, CDSResponse)
@@ -169,7 +169,7 @@ def test_output_without_cards(cds_fhir_connector, caplog):
     )
 
 
-def test_input_with_empty_request(cds_fhir_connector, test_cds_request):
+def test_parse_with_empty_request(cds_fhir_adapter, test_cds_request):
     # Prepare test data
     input_data = test_cds_request
     input_data.prefetch = None
@@ -177,7 +177,7 @@ def test_input_with_empty_request(cds_fhir_connector, test_cds_request):
 
     # Call the input method and expect a ValueError
     with pytest.raises(ValueError) as exc_info:
-        cds_fhir_connector.input(input_data)
+        cds_fhir_adapter.parse(input_data)
 
     # Assert the error message
     assert (
@@ -186,7 +186,7 @@ def test_input_with_empty_request(cds_fhir_connector, test_cds_request):
     )
 
 
-def test_input_with_fhir_server(cds_fhir_connector, test_cds_request):
+def test_parse_with_fhir_server(cds_fhir_adapter, test_cds_request):
     # Prepare test data
     input_data = test_cds_request
     input_data.prefetch = None
@@ -194,7 +194,7 @@ def test_input_with_fhir_server(cds_fhir_connector, test_cds_request):
 
     # Call the input method and expect a NotImplementedError
     with pytest.raises(NotImplementedError) as exc_info:
-        cds_fhir_connector.input(input_data)
+        cds_fhir_adapter.parse(input_data)
 
     # Assert the error message
     assert str(exc_info.value) == "FHIR server is not implemented yet!"

From 5bbd39336859c13b70340be9d0f7411dffdbcd54 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Fri, 1 Aug 2025 17:31:45 +0100
Subject: [PATCH 08/10] Add Fhirprobelmextractor instead of manual update

---
 healthchain/io/containers/document.py         | 105 +++++++++++++-----
 healthchain/pipeline/__init__.py              |   2 +
 healthchain/pipeline/components/__init__.py   |   2 +
 .../components/fhirproblemextractor.py        |  90 +++++++++++++++
 healthchain/pipeline/medicalcodingpipeline.py |  51 ++++++++-
 tests/components/test_fhirproblemextractor.py |  70 ++++++++++++
 tests/pipeline/prebuilt/test_medicalcoding.py |   3 +-
 7 files changed, 293 insertions(+), 30 deletions(-)
 create mode 100644 healthchain/pipeline/components/fhirproblemextractor.py
 create mode 100644 tests/components/test_fhirproblemextractor.py

diff --git a/healthchain/io/containers/document.py b/healthchain/io/containers/document.py
index 6f78734b..c8978944 100644
--- a/healthchain/io/containers/document.py
+++ b/healthchain/io/containers/document.py
@@ -643,40 +643,93 @@ def word_count(self) -> int:
         """
         return len(self._nlp._tokens)
 
-    def update_problem_list_from_nlp(self):
+    def update_problem_list_from_nlp(
+        self,
+        patient_ref: str = "Patient/123",
+        coding_system: str = "http://snomed.info/sct",
+        code_attribute: str = "cui",
+    ):
         """
-        Updates the document's problem list by extracting medical entities from the spaCy annotations.
+        Updates the document's problem list by extracting medical entities from NLP annotations.
 
-        This method looks for entities in the document's spaCy annotations that have associated
-        SNOMED CT concept IDs (CUIs). For each valid entity found, it creates a new FHIR Condition
-        resource and adds it to the document's problem list.
+        This method looks for entities with associated medical codes and creates FHIR Condition
+        resources from them. It supports a two-step process:
+        1. NER: Extract entities from text (spaCy, HuggingFace, etc.)
+        2. Entity Linking: Add medical codes to those entities
+        3. Problem List Creation: Convert linked entities to FHIR conditions (this method)
 
-        The method requires that:
-        1. A spaCy doc has been added to the document's NLP annotations
-        2. The entities in the spaCy doc have the 'cui' extension attribute set
+        The method extracts from:
+        1. spaCy entities with extension attributes (e.g., ent._.cui)
+        2. Generic entities in the NLP annotations container (framework-agnostic)
+
+        Args:
+            patient_ref: FHIR reference to the patient (default: "Patient/123")
+            coding_system: Coding system URI for the conditions (default: SNOMED CT)
+            code_attribute: Name of the attribute containing the medical code (default: "cui")
 
         Note:
-            - Currently defaults to using SNOMED CT coding system
-            - Uses a hardcoded patient reference "Patient/123"
             - Preserves any existing conditions in the problem list
+            - For non-spaCy entities, codes should be stored as keys in entity dictionaries
+            - Different code attributes: "cui", "snomed_id", "icd10", etc.
         """
-        conditions = self.fhir.problem_list
-        # TODO: Make this configurable
-        for ent in self.nlp._spacy_doc.ents:
-            if not Span.has_extension("cui") or ent._.cui is None:
-                logger.debug(f"No CUI found for entity {ent.text}")
-                continue
-            condition = create_condition(
-                subject="Patient/123",
-                code=ent._.cui,
-                display=ent.text,
-                system="http://snomed.info/sct",
-            )
-            logger.debug(f"Adding condition {condition.model_dump()}")
-            conditions.append(condition)
+        # Start with existing conditions to preserve them
+        existing_conditions = self.fhir.problem_list.copy()
+        new_conditions = []
+
+        # 1. Extract from spaCy entities (if available)
+        if self.nlp._spacy_doc and self.nlp._spacy_doc.ents:
+            for ent in self.nlp._spacy_doc.ents:
+                if not Span.has_extension(code_attribute):
+                    logger.debug(
+                        f"Extension '{code_attribute}' not found for spaCy entity {ent.text}"
+                    )
+                    continue
+
+                code_value = getattr(ent._, code_attribute, None)
+                if code_value is None:
+                    logger.debug(
+                        f"No {code_attribute} found for spaCy entity {ent.text}"
+                    )
+                    continue
+
+                condition = create_condition(
+                    subject=patient_ref,
+                    code=code_value,
+                    display=ent.text,
+                    system=coding_system,
+                )
+                logger.debug(f"Adding condition from spaCy: {condition.model_dump()}")
+                new_conditions.append(condition)
+
+        # 2. Extract from generic NLP entities (framework-agnostic)
+        generic_entities = self.nlp.get_entities()
+        if generic_entities:
+            for ent_dict in generic_entities:
+                # Skip if no linked code
+                code_value = ent_dict.get(code_attribute)
+                if code_value is None:
+                    logger.debug(
+                        f"No {code_attribute} found for entity {ent_dict.get('text', 'unknown')}"
+                    )
+                    continue
+
+                entity_text = ent_dict.get("text", "unknown")
+
+                condition = create_condition(
+                    subject=patient_ref,
+                    code=code_value,
+                    display=entity_text,
+                    system=coding_system,
+                )
+                logger.debug(
+                    f"Adding condition from entities: {condition.model_dump()}"
+                )
+                new_conditions.append(condition)
 
-        # Add to document concepts
-        self.fhir.problem_list = conditions
+        # Update problem list with combined conditions (replace to avoid duplication)
+        if new_conditions:
+            all_conditions = existing_conditions + new_conditions
+            self.fhir.add_resources(all_conditions, "Condition", replace=True)
 
     def __iter__(self) -> Iterator[str]:
         return iter(self._nlp._tokens)
diff --git a/healthchain/pipeline/__init__.py b/healthchain/pipeline/__init__.py
index 75cea647..b0669b6e 100644
--- a/healthchain/pipeline/__init__.py
+++ b/healthchain/pipeline/__init__.py
@@ -5,6 +5,7 @@
     TextPreProcessor,
     TextPostProcessor,
     CdsCardCreator,
+    FHIRProblemListExtractor,
 )
 from .mixins import ModelRoutingMixin
 from .summarizationpipeline import SummarizationPipeline
@@ -21,4 +22,5 @@
     "CdsCardCreator",
     "MedicalCodingPipeline",
     "SummarizationPipeline",
+    "FHIRProblemListExtractor",
 ]
diff --git a/healthchain/pipeline/components/__init__.py b/healthchain/pipeline/components/__init__.py
index e78b9f3a..bdab9643 100644
--- a/healthchain/pipeline/components/__init__.py
+++ b/healthchain/pipeline/components/__init__.py
@@ -2,6 +2,7 @@
 from .preprocessors import TextPreProcessor
 from .postprocessors import TextPostProcessor
 from .cdscardcreator import CdsCardCreator
+from .fhirproblemextractor import FHIRProblemListExtractor
 from .integrations import SpacyNLP, HFTransformer, LangChainLLM
 
 __all__ = [
@@ -13,4 +14,5 @@
     "SpacyNLP",
     "HFTransformer",
     "LangChainLLM",
+    "FHIRProblemListExtractor",
 ]
diff --git a/healthchain/pipeline/components/fhirproblemextractor.py b/healthchain/pipeline/components/fhirproblemextractor.py
new file mode 100644
index 00000000..f9892a8a
--- /dev/null
+++ b/healthchain/pipeline/components/fhirproblemextractor.py
@@ -0,0 +1,90 @@
+"""Component for extracting FHIR problem lists from NLP annotations."""
+
+import logging
+
+from healthchain.pipeline.components.base import BaseComponent
+from healthchain.io.containers import Document
+
+logger = logging.getLogger(__name__)
+
+
+class FHIRProblemListExtractor(BaseComponent[Document]):
+    """
+    Component that automatically extracts FHIR Condition resources from NLP entities.
+
+    This component processes NLP annotations from multiple sources (spaCy, generic)
+    to create structured FHIR problem lists. It looks for entities that have medical codes
+    (from entity linking) and converts them into FHIR Condition resources, adding them to
+    the document's problem list.
+
+    Attributes:
+        patient_ref: Reference to the patient (e.g., "Patient/123")
+        coding_system: The coding system for the conditions (default: SNOMED CT)
+        code_attribute: Name of the attribute containing medical codes
+
+    Usage:
+        >>> # Default - extracts from spaCy ent._.cui
+        >>> extractor = ProblemListExtractor(patient_ref="Patient/456")
+
+        >>> # Custom code attribute - uses ent._.snomed_id
+        >>> extractor = ProblemListExtractor(
+        ...     code_attribute="snomed_id",
+        ...     coding_system="http://snomed.info/sct"
+        ... )
+
+        >>> # Works with any framework - extracts from generic entities
+        >>> extractor = ProblemListExtractor(code_attribute="cui")
+
+        >>> pipeline.add_node(extractor, position="after", reference="entity_linking")
+    """
+
+    def __init__(
+        self,
+        patient_ref: str = "Patient/123",
+        coding_system: str = "http://snomed.info/sct",
+        code_attribute: str = "cui",
+    ):
+        """
+        Initialize the ProblemListExtractor.
+
+        Args:
+            patient_ref: FHIR reference to the patient
+            coding_system: Coding system URI for the conditions
+            code_attribute: Name of the spaCy extension attribute containing medical codes
+        """
+        self.patient_ref = patient_ref
+        self.coding_system = coding_system
+        self.code_attribute = code_attribute
+
+    def __call__(self, doc: Document) -> Document:
+        """
+        Extract FHIR conditions from the document's NLP annotations.
+
+        Processes entities from spaCy and generic sources that have medical codes
+        and creates corresponding FHIR Condition resources. These are automatically
+        added to the document's problem list without overwriting existing conditions.
+
+        Args:
+            doc: Document with NLP annotations containing medical entities
+
+        Returns:
+            Document: Same document with updated problem list
+        """
+        # Check if we have any entities to process
+        spacy_doc = doc.nlp.get_spacy_doc()
+        generic_entities = doc.nlp.get_entities()
+
+        if not spacy_doc and not generic_entities:
+            logger.debug("No entities found for problem list extraction")
+            return doc
+
+        doc.update_problem_list_from_nlp(
+            patient_ref=self.patient_ref,
+            coding_system=self.coding_system,
+            code_attribute=self.code_attribute,
+        )
+
+        logger.debug(
+            f"Extracted {len(doc.fhir.problem_list)} conditions to problem list"
+        )
+        return doc
diff --git a/healthchain/pipeline/medicalcodingpipeline.py b/healthchain/pipeline/medicalcodingpipeline.py
index 301ab1a0..0ea3758f 100644
--- a/healthchain/pipeline/medicalcodingpipeline.py
+++ b/healthchain/pipeline/medicalcodingpipeline.py
@@ -1,5 +1,8 @@
 from healthchain.pipeline.base import BasePipeline, ModelConfig
 from healthchain.pipeline.mixins import ModelRoutingMixin
+from healthchain.pipeline.components.fhirproblemextractor import (
+    FHIRProblemListExtractor,
+)
 
 
 class MedicalCodingPipeline(BasePipeline, ModelRoutingMixin):
@@ -8,11 +11,27 @@ class MedicalCodingPipeline(BasePipeline, ModelRoutingMixin):
 
     Stages:
         1. NER+L: Extracts and links medical concepts from document text.
+        2. Problem Extraction (last): Converts medical entities to FHIR problem list.
 
     Usage Examples:
-        # With SpaCy
+        # Basic usage - extracts CUI codes to SNOMED conditions
         >>> pipeline = MedicalCodingPipeline.from_model_id("en_core_sci_sm", source="spacy")
 
+        # Custom patient reference
+        >>> pipeline = MedicalCodingPipeline.from_model_id(
+        ...     "en_core_sci_sm", source="spacy", patient_ref="Patient/demo-123"
+        ... )
+
+        # Different code attribute (e.g., for models that output SNOMED IDs)
+        >>> pipeline = MedicalCodingPipeline.from_model_id(
+        ...     "en_core_sci_sm", source="spacy", code_attribute="snomed_id"
+        ... )
+
+        # Skip automatic problem extraction
+        >>> pipeline = MedicalCodingPipeline.from_model_id(
+        ...     "en_core_sci_sm", source="spacy", extract_problems=False
+        ... )
+
         # With Hugging Face
         >>> pipeline = MedicalCodingPipeline.from_model_id("bert-base-uncased", task="ner")
 
@@ -21,12 +40,28 @@ class MedicalCodingPipeline(BasePipeline, ModelRoutingMixin):
         >>> pipeline = MedicalCodingPipeline.load(chain)
     """
 
-    def __init__(self):
+    def __init__(
+        self,
+        extract_problems: bool = True,
+        patient_ref: str = "Patient/123",
+        code_attribute: str = "cui",
+    ):
+        """
+        Initialize MedicalCodingPipeline.
+
+        Args:
+            extract_problems: Whether to automatically extract FHIR problem list (default: True)
+            patient_ref: Patient reference for created conditions (default: "Patient/123")
+            code_attribute: Name of the spaCy extension attribute containing medical codes (default: "cui")
+        """
         BasePipeline.__init__(self)
         ModelRoutingMixin.__init__(self)
+        self.extract_problems = extract_problems
+        self.patient_ref = patient_ref
+        self.code_attribute = code_attribute
 
     def configure_pipeline(self, config: ModelConfig) -> None:
-        """Configure pipeline with NER+L model.
+        """Configure pipeline with NER+L model and optional problem extraction.
 
         Args:
             config (ModelConfig): Configuration for the NER+L model
@@ -36,6 +71,16 @@ def configure_pipeline(self, config: ModelConfig) -> None:
 
         self.add_node(model, stage="ner+l")
 
+        # Automatically add problem list extraction by default
+        if self.extract_problems:
+            self.add_node(
+                FHIRProblemListExtractor(
+                    patient_ref=self.patient_ref, code_attribute=self.code_attribute
+                ),
+                stage="problem-extraction",
+                position="last",
+            )
+
     def process_request(self, request, adapter=None):
         """
         Process a CDA request and return CDA response using an adapter.
diff --git a/tests/components/test_fhirproblemextractor.py b/tests/components/test_fhirproblemextractor.py
new file mode 100644
index 00000000..d050a8ba
--- /dev/null
+++ b/tests/components/test_fhirproblemextractor.py
@@ -0,0 +1,70 @@
+import pytest
+from healthchain.pipeline.components.fhirproblemextractor import (
+    FHIRProblemListExtractor,
+)
+from healthchain.io.containers import Document
+
+
+def test_extracts_conditions_from_generic_entities():
+    """ProblemListExtractor extracts conditions from entities with medical codes."""
+    doc = Document(data="Patient has fever")
+    doc.nlp.set_entities([{"text": "fever", "cui": "C0015967"}])
+
+    extractor = FHIRProblemListExtractor(patient_ref="Patient/test")
+    result = extractor(doc)
+
+    assert len(result.fhir.problem_list) == 1
+    condition = result.fhir.problem_list[0]
+    assert condition.subject.reference == "Patient/test"
+    assert condition.code.coding[0].code == "C0015967"
+
+
+@pytest.mark.parametrize(
+    "code_attribute,code_value",
+    [
+        ("cui", "C0015967"),
+        ("snomed_id", "386661006"),
+        ("icd10", "R50.9"),
+    ],
+)
+def test_supports_different_code_attributes(code_attribute, code_value):
+    """ProblemListExtractor supports multiple medical coding systems."""
+    doc = Document(data="Test")
+    entities = [{"text": "fever", code_attribute: code_value}]
+    doc.nlp.set_entities(entities)
+
+    extractor = FHIRProblemListExtractor(code_attribute=code_attribute)
+    result = extractor(doc)
+
+    assert len(result.fhir.problem_list) == 1
+    assert result.fhir.problem_list[0].code.coding[0].code == code_value
+
+
+def test_skips_entities_without_codes():
+    """ProblemListExtractor skips entities without medical codes."""
+    doc = Document(data="Test")
+    entities = [
+        {"text": "fever", "cui": "C0015967"},  # Valid
+        {"text": "patient"},  # No code
+        {"text": "cough", "cui": None},  # Null code
+    ]
+    doc.nlp.set_entities(entities)
+
+    extractor = FHIRProblemListExtractor()
+    result = extractor(doc)
+
+    assert len(result.fhir.problem_list) == 1
+    assert result.fhir.problem_list[0].code.coding[0].code == "C0015967"
+
+
+def test_preserves_existing_conditions(test_condition):
+    """ProblemListExtractor preserves existing conditions."""
+    doc = Document(data="Test")
+    doc.fhir.problem_list = [test_condition]
+    doc.nlp.set_entities([{"text": "fever", "cui": "C0015967"}])
+
+    extractor = FHIRProblemListExtractor()
+    result = extractor(doc)
+
+    assert len(result.fhir.problem_list) == 2
+    assert test_condition in result.fhir.problem_list
diff --git a/tests/pipeline/prebuilt/test_medicalcoding.py b/tests/pipeline/prebuilt/test_medicalcoding.py
index dd3f62df..853db091 100644
--- a/tests/pipeline/prebuilt/test_medicalcoding.py
+++ b/tests/pipeline/prebuilt/test_medicalcoding.py
@@ -42,8 +42,9 @@ def test_coding_pipeline(mock_spacy_nlp, test_document):
         mock_spacy_nlp.return_value.assert_called_once()
 
         # Verify stages are set correctly
-        assert len(pipeline._stages) == 1
+        assert len(pipeline._stages) == 2
         assert "ner+l" in pipeline._stages
+        assert "problem-extraction" in pipeline._stages
 
 
 def test_coding_pipeline_process_request(mock_spacy_nlp, mock_cda_adapter):

From b89d8a6adcf90e4bd54baee1c2cab9813a57e73b Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Fri, 1 Aug 2025 18:02:38 +0100
Subject: [PATCH 09/10] Update docs

---
 .../pipeline/components/cdscardcreator.md     |  18 +--
 .../pipeline/components/components.md         |   4 +-
 .../components/fhirproblemextractor.md        | 107 ++++++++++++++++++
 healthchain/pipeline/base.py                  |   1 +
 healthchain/pipeline/summarizationpipeline.py |   2 +-
 mkdocs.yml                                    |   1 +
 6 files changed, 115 insertions(+), 18 deletions(-)
 create mode 100644 docs/reference/pipeline/components/fhirproblemextractor.md

diff --git a/docs/reference/pipeline/components/cdscardcreator.md b/docs/reference/pipeline/components/cdscardcreator.md
index 81cf46e7..8593a6cf 100644
--- a/docs/reference/pipeline/components/cdscardcreator.md
+++ b/docs/reference/pipeline/components/cdscardcreator.md
@@ -1,6 +1,5 @@
 # CdsCardCreator
 
-More detailed documentation coming soon!
 
 The `CdsCardCreator` is a pipeline component that creates CDS Hooks cards from either model outputs or static content. These cards can be displayed in Electronic Health Record (EHR) systems as part of clinical decision support workflows.
 
@@ -95,26 +94,16 @@ The created cards have the following properties:
 - `overrideReasons`: Optional override reasons
 - `links`: Optional external links
 
-## Error Handling
 
-The component includes error handling for:
-
-- Invalid template files
-- Template rendering errors
-- JSON parsing errors
-- Missing model output
-
-Errors are logged using the standard Python logging module.
-
-## Integration with Pipeline
+## Integration with SummarizationPipeline
 
 The CdsCardCreator can be used as part of a larger pipeline:
 
 ```python
-from healthchain.pipeline import Pipeline
+from healthchain.pipeline import SummarizationPipeline
 from healthchain.pipeline.components import CdsCardCreator
 
-pipeline = Pipeline()
+pipeline = SummarizationPipeline()
 pipeline.add_component(CdsCardCreator(
     source="huggingface",
     task="summarization",
@@ -123,7 +112,6 @@ pipeline.add_component(CdsCardCreator(
 ))
 ```
 
-
 ## Related Documentation
 
 - [CDS Hooks Specification](https://cds-hooks.org/)
diff --git a/docs/reference/pipeline/components/components.md b/docs/reference/pipeline/components/components.md
index 389425dc..99c581f4 100644
--- a/docs/reference/pipeline/components/components.md
+++ b/docs/reference/pipeline/components/components.md
@@ -8,9 +8,9 @@ Components are the building blocks of the healthchain pipeline. They are designe
 | Component | Description | Methods |
 |-----------|-------------|---------|
 | `TextPreprocessor` | Handles text preprocessing tasks | `tokenizer`: Specifies the tokenization method (e.g., `"basic"` or `"spacy"`) <br> `lowercase`: Converts text to lowercase if `True` <br> `remove_punctuation`: Removes punctuation if `True` <br> `standardize_spaces`: Standardizes spaces if `True` <br> `regex`: List of custom regex patterns and replacements |
-| `LLM` | Wraps local LLMs for use in the pipeline [TODO] | `load_model`: Loads the specified model |
 | `TextPostProcessor` | Handles text postprocessing tasks | `postcoordination_lookup`: Dictionary for entity refinement lookups |
-| `CdsCardCreator` | Formats model outputs into CDS cards for clinical decision support | `create_card`: Creates a CDS card |
+| [CdsCardCreator](cdscardcreator.md) | Formats model outputs into CDS cards for clinical decision support | `create_card`: Creates a CDS card |
+| [FHIRProblemListExtractor](fhirproblemextractor.md) | Extracts entities with medical codes and creates FHIR Condition resources with the problem_list extension | `__call__`: Extracts the problem list |
 
 ## Creating Custom Components
 
diff --git a/docs/reference/pipeline/components/fhirproblemextractor.md b/docs/reference/pipeline/components/fhirproblemextractor.md
new file mode 100644
index 00000000..d38c7e48
--- /dev/null
+++ b/docs/reference/pipeline/components/fhirproblemextractor.md
@@ -0,0 +1,107 @@
+# FHIRProblemListExtractor
+
+The `FHIRProblemListExtractor` is a pipeline component that automatically extracts NLP annotations and formats them into FHIR [Condition](https://www.hl7.org/fhir/condition.html) resources with the the category `problem-list-item` and the status `active`.
+
+## Usage
+
+### Basic Usage
+
+```python
+from healthchain.pipeline.components import FHIRProblemListExtractor
+
+# Extract conditions with default settings
+extractor = FHIRProblemListExtractor()
+doc = extractor(doc)  # Extracts from NLP entities stored in document's .nlp.entities or spaCy doc
+```
+
+### Configuration Options
+
+```python
+# Use SNOMED CT codes
+extractor = FHIRProblemListExtractor(
+    patient_ref="Patient/456",  # optional, defaults to "Patient/123"
+    code_attribute="snomed_id", # optional, defaults to "cui"
+    coding_system="http://snomed.info/sct" # optional, defaults to "http://snomed.info/sct"
+)
+
+# Use ICD-10 codes
+extractor = FHIRProblemListExtractor(
+    patient_ref="Patient/456",
+    code_attribute="icd10",
+    coding_system="http://hl7.org/fhir/sid/icd-10"
+)
+```
+
+## Entity Extraction
+
+The component extracts entities from the document's NLP annotations.
+
+### spaCy Entities
+
+Extracts from spaCy entities with extension attributes:
+
+```python
+# spaCy entity with CUI code
+ent._.cui = "C0015967"  # Extracted automatically
+```
+
+### Generic NLP Entities
+Works with any NLP framework via generic entity dictionaries:
+```python
+entities = [
+    {"text": "fever", "cui": "C0015967"},
+    {"text": "hypertension", "snomed_id": "38341003"}
+]
+```
+
+## FHIR Condition Creation
+
+Example of a FHIR Condition resource created by the component:
+
+```json
+{
+  "resourceType": "Condition",
+  "id": "hc-0aa85ff7-5e40-472b-a676-cb3df83d8313",
+  "clinicalStatus": {
+    "coding": [
+      {
+        "system": "http://terminology.hl7.org/CodeSystem/condition-clinical",
+        "code": "active",
+        "display": "Active"
+      }
+    ]
+  },
+  "code": {
+    "coding": [
+      {
+        "system": "http://snomed.info/sct",
+        "code": "C0242429",  # extracted from doc entity
+        "display": "sore throat"  # extracted from doc entity
+      }
+    ]
+  },
+  "subject": {
+    "reference": "Patient/123"
+  }
+}
+```
+
+
+## MedicalCodingPipeline Integration
+
+```python
+from healthchain.pipeline import MedicalCodingPipeline
+
+# Automatic problem extraction
+pipeline = MedicalCodingPipeline(
+    extract_problems=True,
+    patient_ref="Patient/456",
+    code_attribute="cui"
+)
+```
+
+## Related Documentation
+
+- [FHIR Condition Resources](https://www.hl7.org/fhir/condition.html)
+- [Medical Coding Pipeline](../prebuilt_pipelines/medicalcoding.md)
+- [Document Container](../../interop/containers.md)
diff --git a/healthchain/pipeline/base.py b/healthchain/pipeline/base.py
index 540017ff..24ed9b06 100644
--- a/healthchain/pipeline/base.py
+++ b/healthchain/pipeline/base.py
@@ -89,6 +89,7 @@ class BasePipeline(Generic[T], ABC):
         _stages (Dict[str, List[Callable]]): Components grouped by processing stage
         _built_pipeline (Optional[Callable]): Compiled pipeline function
         _output_template (Optional[str]): Template string for formatting pipeline outputs
+        _output_template_path (Optional[Path]): Path to template file for formatting pipeline outputs
 
     Example:
         >>> class MyPipeline(BasePipeline[Document]):
diff --git a/healthchain/pipeline/summarizationpipeline.py b/healthchain/pipeline/summarizationpipeline.py
index fd3eb21f..4aa3a7ea 100644
--- a/healthchain/pipeline/summarizationpipeline.py
+++ b/healthchain/pipeline/summarizationpipeline.py
@@ -39,7 +39,7 @@ def configure_pipeline(self, config: ModelConfig) -> None:
             CdsCardCreator(
                 source=config.source.value,
                 task="summarization",
-                template=self._output_template,
+                template=self._output_template,  # TODO: assess where this should be configured
                 template_path=self._output_template_path,
                 delimiter="\n",
             ),
diff --git a/mkdocs.yml b/mkdocs.yml
index 9a973be0..9f76e91f 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -32,6 +32,7 @@ nav:
         - Components:
           - Overview: reference/pipeline/components/components.md
           - CdsCardCreator: reference/pipeline/components/cdscardcreator.md
+          - FHIRProblemListExtractor: reference/pipeline/components/fhirproblemextractor.md
         - Adapters:
           - Overview: reference/pipeline/adapters/adapters.md
           - CDA Adapter: reference/pipeline/adapters/cdaadapter.md

From 270f1fd242f4a97f6c9a03a5ab4abdac401675e5 Mon Sep 17 00:00:00 2001
From: jenniferjiangkells <jenniferjiangkells@gmail.com>
Date: Fri, 1 Aug 2025 19:12:43 +0100
Subject: [PATCH 10/10] Move adapters to own module

---
 docs/api/adapters.md                            |  4 ++--
 healthchain/io/__init__.py                      |  4 ++--
 healthchain/io/adapters/__init__.py             | 11 +++++++++++
 healthchain/io/{ => adapters}/cdaadapter.py     |  0
 healthchain/io/{ => adapters}/cdsfhiradapter.py |  0
 tests/pipeline/test_cdaadapter.py               | 14 +++++++-------
 6 files changed, 22 insertions(+), 11 deletions(-)
 create mode 100644 healthchain/io/adapters/__init__.py
 rename healthchain/io/{ => adapters}/cdaadapter.py (100%)
 rename healthchain/io/{ => adapters}/cdsfhiradapter.py (100%)

diff --git a/docs/api/adapters.md b/docs/api/adapters.md
index 889ca1d1..d84b0fdf 100644
--- a/docs/api/adapters.md
+++ b/docs/api/adapters.md
@@ -1,4 +1,4 @@
 # Adapters
 
-::: healthchain.io.cdaadapter
-::: healthchain.io.cdsfhiradapter
+::: healthchain.io.adapters.cdaadapter
+::: healthchain.io.adapters.cdsfhiradapter
diff --git a/healthchain/io/__init__.py b/healthchain/io/__init__.py
index 70753fb3..52bc38ef 100644
--- a/healthchain/io/__init__.py
+++ b/healthchain/io/__init__.py
@@ -1,7 +1,7 @@
 from .containers import DataContainer, Document, Tabular
 from .base import BaseAdapter
-from .cdaadapter import CdaAdapter
-from .cdsfhiradapter import CdsFhirAdapter
+from .adapters.cdaadapter import CdaAdapter
+from .adapters.cdsfhiradapter import CdsFhirAdapter
 
 __all__ = [
     # Containers
diff --git a/healthchain/io/adapters/__init__.py b/healthchain/io/adapters/__init__.py
new file mode 100644
index 00000000..6fb1012a
--- /dev/null
+++ b/healthchain/io/adapters/__init__.py
@@ -0,0 +1,11 @@
+"""
+Adapters module for HealthChain.
+
+This module contains adapter implementations for converting between different
+data formats and HealthChain's internal Document representation.
+"""
+
+from .cdaadapter import CdaAdapter
+from .cdsfhiradapter import CdsFhirAdapter
+
+__all__ = ["CdaAdapter", "CdsFhirAdapter"]
diff --git a/healthchain/io/cdaadapter.py b/healthchain/io/adapters/cdaadapter.py
similarity index 100%
rename from healthchain/io/cdaadapter.py
rename to healthchain/io/adapters/cdaadapter.py
diff --git a/healthchain/io/cdsfhiradapter.py b/healthchain/io/adapters/cdsfhiradapter.py
similarity index 100%
rename from healthchain/io/cdsfhiradapter.py
rename to healthchain/io/adapters/cdsfhiradapter.py
diff --git a/tests/pipeline/test_cdaadapter.py b/tests/pipeline/test_cdaadapter.py
index 24634c4d..26085ab9 100644
--- a/tests/pipeline/test_cdaadapter.py
+++ b/tests/pipeline/test_cdaadapter.py
@@ -3,7 +3,7 @@
 from healthchain.models.requests.cdarequest import CdaRequest
 from healthchain.models.responses.cdaresponse import CdaResponse
 from healthchain.io.containers import Document
-from healthchain.io.cdaadapter import CdaAdapter
+from healthchain.io.adapters import CdaAdapter
 from healthchain.interop import FormatType
 from fhir.resources.documentreference import DocumentReference
 
@@ -13,11 +13,11 @@ def cda_adapter():
     return CdaAdapter()
 
 
-@patch("healthchain.io.cdaadapter.create_engine")
-@patch("healthchain.io.cdaadapter.create_document_reference")
-@patch("healthchain.io.cdaadapter.read_content_attachment")
-@patch("healthchain.io.cdaadapter.set_problem_list_item_category")
-@patch("healthchain.io.cdaadapter.Document", autospec=True)
+@patch("healthchain.io.adapters.cdaadapter.create_engine")
+@patch("healthchain.io.adapters.cdaadapter.create_document_reference")
+@patch("healthchain.io.adapters.cdaadapter.read_content_attachment")
+@patch("healthchain.io.adapters.cdaadapter.set_problem_list_item_category")
+@patch("healthchain.io.adapters.cdaadapter.Document", autospec=True)
 def test_parse(
     mock_document_class,
     mock_set_problem_category,
@@ -116,7 +116,7 @@ def test_parse(
     assert result is mock_doc
 
 
-@patch("healthchain.io.cdaadapter.create_engine")
+@patch("healthchain.io.adapters.cdaadapter.create_engine")
 def test_format(
     mock_create_engine, cda_adapter, test_condition, test_medication, test_allergy
 ):