diff --git a/docs/quickstart.md b/docs/quickstart.md
index fa1737c..d3951df 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -77,11 +77,11 @@ The aim of the data generator is not to generate realistic data suitable for use
For this reason the data generator is opiniated by use case and workflow. See [Use Cases](usecases.md) for more information.
!!! note
- We're aware we may not cover everyone's use cases, so if you have strong opinions about this, please [reach out](https://discord.gg/jG4UWCUh)!
+ We're aware we may not cover everyone's use cases, so if you have strong opinions about this, please [reach out](https://discord.gg/4v6XgGBZ)!
On the synthetic data spectrum defined by [this UK ONS methodology working paper](https://www.ons.gov.uk/methodology/methodologicalpublications/generalmethodology/onsworkingpaperseries/onsmethodologyworkingpaperseriesnumber16syntheticdatapilot#:~:text=Synthetic%20data%20at%20ONS&text=Synthetic%20data%20is%20created%20by,that%20provided%20the%20original%20data.%E2%80%9D), HealthChain generates level 1: synthetic structural data.
-
+
You can use the data generator within a client function or on its own. The `.generate()` is dependent on workflow. For CDS use cases, it will return a `CdsFhirData` model with the `prefetch` field populated with a [Bundle](https://www.hl7.org/fhir/bundle.html) of generated structural synthetic FHIR data.
diff --git a/docs/stylesheets/extra.css b/docs/stylesheets/extra.css
index df7daf8..f6b5164 100644
--- a/docs/stylesheets/extra.css
+++ b/docs/stylesheets/extra.css
@@ -69,9 +69,9 @@
margin-bottom: 2rem;
}
- .language-python {
+ /* .language-python {
background: #FFFFFF ! important
- }
+ } */
.language-bash {
background: #FFFFFF ! important
diff --git a/docs/usecases.md b/docs/usecases.md
index 9f2aa40..a5e6ba1 100644
--- a/docs/usecases.md
+++ b/docs/usecases.md
@@ -22,6 +22,41 @@ Current implemented workflows:
| [order-sign](https://cds-hooks.org/hooks/order-sign/)| :material-check: Partial | Future: `MedicationRequest`, `ProcedureRequest`, `ServiceRequest` |
| [order-select](https://cds-hooks.org/hooks/order-select/) | :material-check: Partial | Future: `MedicationRequest`, `ProcedureRequest`, `ServiceRequest` |
+`ClinicalDecisionSupport` functions receive `CdsRequest` and return a list of `Card`.
+
+```python
+class Card(BaseModel):
+ """
+ Cards can provide a combination of information (for reading), suggested actions
+ (to be applied if a user selects them), and links (to launch an app if the user selects them).
+ The CDS Client decides how to display cards, but this specification recommends displaying suggestions
+ using buttons, and links using underlined text.
+
+ https://cds-hooks.org/specification/current/#card-attributes
+ """
+
+ summary: str = Field(..., max_length=140)
+ indicator: IndicatorEnum
+ source: Source
+ uuid: Optional[str] = None
+ detail: Optional[str] = None
+ suggestions: Optional[List[Suggestion]] = None
+ selectionBehavior: Optional[SelectionBehaviorEnum] = None
+ overrideReasons: Optional[List[SimpleCoding]] = None
+ links: Optional[List[Link]] = None
+```
+
+ The `DataGenerator` returns data represented as `CdsFhirData`, which contains a `Bundle` of FHIR resources in the `prefetch` field.
+
+```python
+class CdsFhirData(BaseModel):
+ """
+ Data model for CDS FHIR data, this matches the expected fields in CDSRequests
+ """
+
+ context: Dict = Field(default={})
+ prefetch: Bundle
+```
### Example `CDSRequest`
@@ -74,22 +109,86 @@ Current implemented workflows:
- `Procedure`
- `MedicationRequest`
+### Example Sandbox Usage
+
+A CDS sandbox which uses `gpt-4o` to summarise patient information from synthetically generated FHIR resources received from the `patient-view` CDS hook.
+
+```python
+import healthchain as hc
+from healthchain.use_cases import ClinicalDecisionSupport
+from healthchain.data_generators import CdsDataGenerator
+from healthchain.models import Card, CdsFhirData, CDSRequest
+
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import PromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+
+from typing import List
+
+@hc.sandbox
+class CdsSandbox(ClinicalDecisionSupport):
+ def __init__(self):
+ self.chain = self._init_llm_chain()
+ self.data_generator = CdsDataGenerator()
+
+ def _init_llm_chain(self):
+ prompt = PromptTemplate.from_template(
+ "Extract conditions from the FHIR resource below and summarize in one sentence using simple language \n'''{text}'''"
+ )
+ model = ChatOpenAI(model="gpt-4o")
+ parser = StrOutputParser()
+
+ chain = prompt | model | parser
+ return chain
+
+ @hc.ehr(workflow="patient-view")
+ def load_data_in_client(self) -> CdsFhirData:
+ data = self.data_generator.generate()
+ return data
+
+ @hc.api
+ def my_service(self, request: CDSRequest) -> List[Card]:
+ result = self.chain.invoke(str(request.prefetch))
+ return Card(
+ summary="Patient summary",
+ indicator="info",
+ source={"label": "openai"},
+ detail=result,
+ )
+```
## Clinical Documentation
The `ClinicalDocumentation` use case implements a real-time Clinical Documentation Improvement (CDI) service. It currently implements the Epic-integrated NoteReader CDI specification, which communicates with a third-party natural language processing (NLP) engine to analyse clinical notes and extract structured data. It helps convert free-text medical documentation into coded information that can be used for billing, quality reporting, and clinical decision support.
-`ClinicalDocumentation` communicates using [CDAs (Clinical Document Architecture)](https://www.hl7.org/implement/standards/product_brief.cfm?product_id=7). CDAs are standardized electronic documents for exchanging clinical information. They provide a common structure for capturing and sharing patient data like medical history, medications, and care plans between different healthcare systems and providers. The communication protocol is over a SOAP-based API.
-
-Note that NoteReader is a vendor-specific component (Epic). This particular note-based workfow is one type of CDI service.
-
-In HealthChain, the workflow is named `sign-note-inpatient`. We plan to implement additional CDI services and workflows for different vendor specifications.
+`ClinicalDocumentation` communicates using [CDAs (Clinical Document Architecture)](https://www.hl7.org/implement/standards/product_brief.cfm?product_id=7). CDAs are standardised electronic documents for exchanging clinical information. 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. CDAs typically uses a SOAP-based communication protocol (unfortunately).
-The `DataGenerator` currently does not support synthetic CDA data - we're working on it! At the moment, you can only load and return a prexisting CDA from your sandbox api function.
+Note that NoteReader is a vendor-specific component (Epic). This particular note-based workflow is one type of CDI service. Different EHR vendors will have different support for third-party CDI services.
| When | Where | What you receive | What you send back |
| :-------- | :-----| :-------------------------- |----------------------------|
| Triggered when a clinician opts in to a CDI functionality and signs or pends a note after writing it. | Specific modules in EHR where clinical documentation takes place, such as NoteReader in Epic. | A CDA document which contains continuity of care data and free-text data, e.g. a patient's problem list and the progress note that the clinician has entered in the EHR. | A CDA document which contains additional structured data extracted and returned by your CDI service. |
+In HealthChain, the workflow is named `sign-note-inpatient` or `sign-note-outpatient`. We support parsing of problems, medications, and allergies sections, though some of the data fields may be limited. We plan to implement additional CDI services and workflows for different vendor specifications.
+
+A `ClinicalDocumentation` function receives and returns `CcdData`:
+
+```python
+class CcdData(BaseModel):
+ """
+ Data model for CCD (Continuity of Care Document) that can be converted to CDA.
+ """
+
+ problems: Optional[List[ProblemConcept]] = None
+ allergies: Optional[List[AllergyConcept]] = None
+ medications: Optional[List[MedicationConcept]] = None
+ note: Optional[Union[Dict, str]] = None
+ cda_xml: Optional[str] = None
+```
+For more information check out the [API Reference](api/data_models.md).
+
+The `DataGenerator` currently does not support synthetic CDA data - we're working on it! At the moment, you can only load and return a pre-existing CDA from your sandbox api function.
+
+
### Example `CdaRequest`
```xml
@@ -276,6 +375,70 @@ The `DataGenerator` currently does not support synthetic CDA data - we're workin
### Implemented CDA Sections
- Problems
-- Medications (Coming soon)
-- Allergies (Coming soon)
-- Progress Note
+- Medications (including information on dosage, frequency, duration, route)
+- Allergies (including information on severity, reaction and type of allergen)
+- Progress Note (free-text)
+
+### Example Sandbox Usage
+A sandbox example of NoteReader clinical documentation improvement which extracts problems, medications, and allergies entries from the progress note section of a pre-configured CDA document.
+
+```python
+import healthchain as hc
+from healthchain.use_cases import ClinicalDocumentation
+from healthchain.models import (
+ CcdData,
+ AllergyConcept,
+ Concept,
+ MedicationConcept,
+ ProblemConcept,
+ Quantity,
+)
+
+@hc.sandbox
+class NotereaderSandbox(ClinicalDocumentation):
+ def __init__(self):
+ self.cda_path = "./resources/uclh_cda.xml"
+
+ @hc.ehr(workflow="sign-note-inpatient")
+ def load_data_in_client(self) -> CcdData:
+ with open(self.cda_path, "r") as file:
+ xml_string = file.read()
+
+ return CcdData(cda_xml=xml_string)
+
+ @hc.api
+ def my_service(self, ccd_data: CcdData) -> CcdData:
+
+ # Apply extraction method from ccd_data.note
+
+ new_problem = ProblemConcept(
+ code="38341003",
+ code_system="2.16.840.1.113883.6.96",
+ code_system_name="SNOMED CT",
+ display_name="Hypertension",
+ )
+ new_allergy = AllergyConcept(
+ code="70618",
+ code_system="2.16.840.1.113883.6.96",
+ code_system_name="SNOMED CT",
+ display_name="Allergy to peanuts",
+ )
+ new_medication = MedicationConcept(
+ code="197361",
+ code_system="2.16.840.1.113883.6.88",
+ code_system_name="RxNorm",
+ display_name="Lisinopril 10 MG Oral Tablet",
+ dosage=Quantity(value=10, unit="mg"),
+ route=Concept(
+ code="26643006",
+ code_system="2.16.840.1.113883.6.96",
+ code_system_name="SNOMED CT",
+ display_name="Oral",
+ ),
+ )
+ ccd_data.problems = [new_problem]
+ ccd_data.allergies = [new_allergy]
+ ccd_data.medications = [new_medication]
+
+ return ccd_data
+```
diff --git a/healthchain/cda_parser/cdaannotator.py b/healthchain/cda_parser/cdaannotator.py
index 830de19..1304377 100644
--- a/healthchain/cda_parser/cdaannotator.py
+++ b/healthchain/cda_parser/cdaannotator.py
@@ -57,7 +57,7 @@ def get_time_range_from_cda_value(value: Dict) -> Range:
return range_model
-def get_value_from_entry_relationship(entry_relationship):
+def get_value_from_entry_relationship(entry_relationship: EntryRelationship) -> List:
"""
Retrieves the values from the given entry_relationship.
@@ -79,7 +79,7 @@ def get_value_from_entry_relationship(entry_relationship):
return values
-def check_has_template_id(section, template_id):
+def check_has_template_id(section: Section, template_id: str) -> bool:
"""
Check if the given section has a matching template ID.
@@ -104,7 +104,7 @@ def check_has_template_id(section, template_id):
return False
-def check_for_entry_observation(entry):
+def check_for_entry_observation(entry: Entry) -> bool:
"""
Checks if the given entry contains an observation.
@@ -178,7 +178,7 @@ def __init__(self, cda_data: ClinicalDocument, fallback="LLM") -> None:
self._extract_data()
@classmethod
- def from_dict(cls, data: Dict):
+ def from_dict(cls, data: Dict) -> "CdaAnnotator":
"""
Creates an instance of the class from a dictionary.
@@ -192,7 +192,7 @@ def from_dict(cls, data: Dict):
return cls(cda_data=clinical_document_model)
@classmethod
- def from_xml(cls, data: str):
+ def from_xml(cls, data: str) -> "CdaAnnotator":
"""
Creates an instance of the CDAAnnotator class from an XML string.
diff --git a/healthchain/clients/ehrclient.py b/healthchain/clients/ehrclient.py
index 1701668..bba59b5 100644
--- a/healthchain/clients/ehrclient.py
+++ b/healthchain/clients/ehrclient.py
@@ -103,12 +103,13 @@ def __init__(
):
"""
Initializes the EHRClient with a data generator function and optional workflow and use case.
+ Should be a subclass of BaseUseCase. Example - ClinicalDecisionSupport()
Parameters:
func (Callable[..., Any]): A function to generate data for requests.
workflow ([Workflow]): The workflow context to apply to the data generator.
- use_case ([BaseUseCase]): The strategy object to construct requests based on the generated data.
- Should be a subclass of BaseUseCase. Example - ClinicalDecisionSupport()
+ strategy (BaseStrategy): The strategy object to construct requests based on the generated data.
+
"""
# TODO: Add option to pass in different provider options
self.data_generator_func: Callable[..., Any] = func
diff --git a/healthchain/data_generators/cdsdatagenerator.py b/healthchain/data_generators/cdsdatagenerator.py
index 186912b..07ff218 100644
--- a/healthchain/data_generators/cdsdatagenerator.py
+++ b/healthchain/data_generators/cdsdatagenerator.py
@@ -3,7 +3,7 @@
import logging
from pydantic import BaseModel
-from typing import Callable, Optional
+from typing import Callable, Dict, Optional
from pathlib import Path
from healthchain.base import Workflow
@@ -35,15 +35,39 @@
class CdsDataGenerator:
+ """
+ A class to generate CDS (Clinical Decision Support) data based on specified workflows and constraints.
+
+ Attributes:
+ registry (dict): A registry of data generators.
+ mappings (dict): A mapping of workflows to their respective data generators.
+ data (CdsFhirData): The generated CDS FHIR data.
+ """
+
def __init__(self):
self.registry = generator_registry
self.mappings = workflow_mappings
self.data: CdsFhirData = None
def fetch_generator(self, generator_name: str) -> Callable:
+ """
+ Fetches a data generator function by its name from the registry.
+
+ Parameters:
+ generator_name (str): The name of the data generator to fetch.
+
+ Returns:
+ Callable: The data generator function.
+ """
return self.registry.get(generator_name)
- def set_workflow(self, workflow: str):
+ def set_workflow(self, workflow: str) -> None:
+ """
+ Sets the current workflow to be used for data generation.
+
+ Parameters:
+ workflow (str): The name of the workflow to set.
+ """
self.workflow = workflow
def generate(
@@ -52,6 +76,17 @@ def generate(
free_text_path: Optional[str] = None,
column_name: Optional[str] = None,
) -> BaseModel:
+ """
+ Generates CDS data based on the current workflow, constraints, and optional free text data.
+
+ Parameters:
+ constraints (Optional[list]): A list of constraints to apply to the data generation.
+ free_text_path (Optional[str]): The path to a CSV file containing free text data.
+ column_name (Optional[str]): The column name in the CSV file to use for free text data.
+
+ Returns:
+ BaseModel: The generated CDS FHIR data.
+ """
results = []
if self.workflow not in self.mappings.keys():
@@ -76,7 +111,17 @@ def generate(
self.data = output
return output
- def free_text_parser(self, path_to_csv: str, column_name: str) -> dict:
+ def free_text_parser(self, path_to_csv: str, column_name: str) -> Dict:
+ """
+ Parses free text data from a CSV file and converts it into a list of DocumentReference models.
+
+ Parameters:
+ path_to_csv (str): The path to the CSV file containing free text data.
+ column_name (str): The column name in the CSV file to use for free text data.
+
+ Returns:
+ dict: A dictionary of parsed free text data converted into DocumentReference models.
+ """
column_data = []
# Check that path_to_csv is a valid path with pathlib
diff --git a/healthchain/data_generators/encountergenerators.py b/healthchain/data_generators/encountergenerators.py
index c1b3216..1f1b3e4 100644
--- a/healthchain/data_generators/encountergenerators.py
+++ b/healthchain/data_generators/encountergenerators.py
@@ -24,6 +24,14 @@
@register_generator
class PeriodGenerator(BaseGenerator):
+ """
+ A generator class for creating FHIR Period resources.
+
+ Methods:
+ generate() -> Period:
+ Generates a FHIR Period resource with random start and end times.
+ """
+
@staticmethod
def generate():
start = faker.date_time()
@@ -37,8 +45,16 @@ def generate():
@register_generator
class ClassGenerator(BaseGenerator):
+ """
+ A generator class for creating FHIR Class resources.
+
+ Methods:
+ generate() -> CodeableConcept:
+ Generates a FHIR Class resource.
+ """
+
@staticmethod
- def generate():
+ def generate() -> CodeableConcept:
patient_class_mapping = {"IMP": "inpatient", "AMB": "ambulatory"}
patient_class = faker.random_element(elements=("IMP", "AMB"))
return CodeableConcept(
@@ -54,8 +70,16 @@ def generate():
@register_generator
class EncounterTypeGenerator(BaseGenerator):
+ """
+ A generator class for creating FHIR EncounterType resources.
+
+ Methods:
+ generate() -> CodeableConcept:
+ Generates a FHIR EncounterType resource.
+ """
+
@staticmethod
- def generate():
+ def generate() -> CodeableConcept:
encounter_type_mapping = {"11429006": "consultation", "50849002": "emergency"}
encounter_type = faker.random_element(elements=("11429006", "50849002"))
return CodeableConcept(
@@ -71,8 +95,16 @@ def generate():
@register_generator
class EncounterPriorityGenerator(BaseGenerator):
+ """
+ A generator class for creating FHIR EncounterPriority resources.
+
+ Methods:
+ generate() -> CodeableConcept:
+ Generates a FHIR EncounterPriority resource.
+ """
+
@staticmethod
- def generate():
+ def generate() -> CodeableConcept:
encounter_priority_mapping = {"17621005": "normal", "24484000": "critical"}
encounter_priority = faker.random_element(elements=("17621005", "24484000"))
return CodeableConcept(
@@ -88,8 +120,16 @@ def generate():
@register_generator
class EncounterLocationGenerator(BaseGenerator):
+ """
+ A generator class for creating FHIR EncounterLocation resources.
+
+ Methods:
+ generate() -> EncounterLocation:
+ Generates a FHIR EncounterLocation resource.
+ """
+
@staticmethod
- def generate():
+ def generate() -> EncounterLocation:
return EncounterLocation(
location=Reference(reference="Location/123"),
status=faker.random_element(elements=("active", "completed")),
@@ -99,10 +139,18 @@ def generate():
@register_generator
class EncounterGenerator(BaseGenerator):
+ """
+ A generator class for creating FHIR Encounter resources.
+
+ Methods:
+ generate(constraints: Optional[list] = None) -> Encounter:
+ Generates a FHIR Encounter resource with optional constraints.
+ """
+
@staticmethod
def generate(
constraints: Optional[list] = None,
- ):
+ ) -> Encounter:
patient_reference = "Patient/123"
return Encounter(
resourceType="Encounter",
diff --git a/healthchain/models/__init__.py b/healthchain/models/__init__.py
index 2efcb4d..58d202c 100644
--- a/healthchain/models/__init__.py
+++ b/healthchain/models/__init__.py
@@ -20,6 +20,9 @@
MedicationConcept,
CdsFhirData,
CcdData,
+ Quantity,
+ Range,
+ TimeInterval,
)
__all__ = [
@@ -44,4 +47,7 @@
"ProblemConcept",
"AllergyConcept",
"MedicationConcept",
+ "Quantity",
+ "Range",
+ "TimeInterval",
]
diff --git a/healthchain/models/data/__init__.py b/healthchain/models/data/__init__.py
index f54941d..d49abf3 100644
--- a/healthchain/models/data/__init__.py
+++ b/healthchain/models/data/__init__.py
@@ -1,4 +1,12 @@
-from .concept import Concept, ProblemConcept, MedicationConcept, AllergyConcept
+from .concept import (
+ Concept,
+ ProblemConcept,
+ MedicationConcept,
+ AllergyConcept,
+ Quantity,
+ Range,
+ TimeInterval,
+)
from .cdsfhirdata import CdsFhirData
from .ccddata import CcdData
@@ -10,4 +18,7 @@
"ProblemConcept",
"MedicationConcept",
"AllergyConcept",
+ "Quantity",
+ "Range",
+ "TimeInterval",
]
diff --git a/healthchain/use_cases/cds.py b/healthchain/use_cases/cds.py
index a0dee81..d372855 100644
--- a/healthchain/use_cases/cds.py
+++ b/healthchain/use_cases/cds.py
@@ -89,8 +89,6 @@ class ClinicalDecisionSupport(BaseUseCase):
Implements EHR backend simulator for Clinical Decision Support (CDS)
Parameters:
- sandbox_id (str): unique ID assigned to an instance
- url (UrlBuilder): Contains url of the service
service_api (APIMethod): the function body to inject into the main service
service_config (Dict): the config kwargs for the uvicorn server passed into service
service (Service): the service runner object
diff --git a/mkdocs.yml b/mkdocs.yml
index 333cb96..cb32041 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -12,21 +12,29 @@ nav:
- Installation: installation.md
- Quickstart: quickstart.md
- Use Cases: usecases.md
- - Licence: license-page.md
+ - Licence: distribution.md
- Cookbook:
- cookbook/index.md
- Docs:
- reference/index.md
- API Reference:
- api/index.md
+ - api/use_cases.md
+ - api/cds_hooks.md
+ - api/service.md
+ - api/clients.md
+ - api/cda_parser.md
+ - api/data_generators.md
+ - api/data_models.md
+
- Community:
- community/index.md
copyright: dotimplement
theme:
name: material
- favicon: assets/healthchain_logo.png
- logo: assets/healthchain_logo.png
+ favicon: assets/images/healthchain_logo.png
+ logo: assets/images/healthchain_logo.png
icon:
repo: fontawesome/brands/github
features:
@@ -83,6 +91,8 @@ plugins:
python:
options:
show_submodules: true
+ heading_level: 2
+ docstring_section_style: spacy
- search
# - section-index
# - social:
diff --git a/poetry.lock b/poetry.lock
index d745ad0..58b002c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -36,95 +36,142 @@ doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphin
test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
trio = ["trio (>=0.23)"]
+[[package]]
+name = "astunparse"
+version = "1.6.3"
+description = "An AST unparser for Python"
+optional = false
+python-versions = "*"
+files = [
+ {file = "astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8"},
+ {file = "astunparse-1.6.3.tar.gz", hash = "sha256:5ad93a8456f0d084c3456d059fd9a92cce667963232cbf763eac3bc5b7940872"},
+]
+
+[package.dependencies]
+six = ">=1.6.1,<2.0"
+wheel = ">=0.23.0,<1.0"
+
[[package]]
name = "attrs"
-version = "23.2.0"
+version = "24.2.0"
description = "Classes Without Boilerplate"
optional = false
python-versions = ">=3.7"
files = [
- {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
- {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
+ {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"},
+ {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"},
]
[package.extras]
-cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[tests]", "pre-commit"]
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description = "Backport of PEP 654 (exception groups)"
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description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
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http2 = ["h2 (>=3,<5)"]
socks = ["socksio (==1.*)"]
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htmlsoup = ["BeautifulSoup4"]
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[package.dependencies]
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[[package]]
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+ {file = "websockets-13.0.1.tar.gz", hash = "sha256:4d6ece65099411cfd9a48d13701d7438d9c34f479046b34c50ff60bb8834e43e"},
+]
+
+[[package]]
+name = "wheel"
+version = "0.44.0"
+description = "A built-package format for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "wheel-0.44.0-py3-none-any.whl", hash = "sha256:2376a90c98cc337d18623527a97c31797bd02bad0033d41547043a1cbfbe448f"},
+ {file = "wheel-0.44.0.tar.gz", hash = "sha256:a29c3f2817e95ab89aa4660681ad547c0e9547f20e75b0562fe7723c9a2a9d49"},
]
+[package.extras]
+test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
+
[[package]]
name = "xmltodict"
version = "0.13.0"
@@ -1845,7 +2200,26 @@ files = [
{file = "xmltodict-0.13.0.tar.gz", hash = "sha256:341595a488e3e01a85a9d8911d8912fd922ede5fecc4dce437eb4b6c8d037e56"},
]
+[[package]]
+name = "zipp"
+version = "3.20.1"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+ {file = "zipp-3.20.1-py3-none-any.whl", hash = "sha256:9960cd8967c8f85a56f920d5d507274e74f9ff813a0ab8889a5b5be2daf44064"},
+ {file = "zipp-3.20.1.tar.gz", hash = "sha256:c22b14cc4763c5a5b04134207736c107db42e9d3ef2d9779d465f5f1bcba572b"},
+]
+
+[package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
+
[metadata]
lock-version = "2.0"
python-versions = ">=3.8,<3.12"
-content-hash = "26d472f3b9912d98009102e7a85e6fe7a0096a0f494fa21b3bb1f400bc4a997a"
+content-hash = "98bd744cc6e5705ee657f9f5cf398ce7cf1894bb88c1d3175ae9cc564f968ae3"
diff --git a/pyproject.toml b/pyproject.toml
index f08ed01..812da12 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,8 +1,8 @@
[tool.poetry]
name = "healthchain"
-version = "0.2.0"
+version = "0.0.0"
description = "Remarkably simple testing and validation of AI/NLP applications in healthcare context."
-authors = ["Adam Kells
", "Jennifer Jiang-Kells "]
+authors = ["Jennifer Jiang-Kells ", "Adam Kells "]
license = "Apache-2.0"
readme = "README.md"
documentation = "https://dotimplement.github.io/HealthChain/"
@@ -41,6 +41,11 @@ pre-commit = "^3.5.0"
pytest-anyio = "^0.0.0"
trio = "^0.25.0"
+[tool.poetry.group.docs.dependencies]
+mkdocs = "^1.6.1"
+mkdocs-material = "^9.5.34"
+mkdocstrings = "^0.26.0"
+mkdocstrings-python = "^1.11.1"
[tool.poetry.scripts]
healthchain = "healthchain.cli:main"
diff --git a/requirements-doc.txt b/requirements-doc.txt
index 5ea0fb4..7f9c42c 100644
--- a/requirements-doc.txt
+++ b/requirements-doc.txt
@@ -1,3 +1,4 @@
mkdocs
mkdocs-material
mkdocstrings
+mkdocstrings-python
+
+ 
+
-# HealthChain
+