capinvest-platform-api 1.0.9
CapInvest Platform API: Launch script and widgets builder for the CapInvest Platform API and Workspace Backend Connector.
Requires Python: <3.14,>=3.9

# CapInvest Platform API Launcher

This package is responsible for launching and configuring an CapInvest Platform environment, or FastAPI instance, to use as an CapInvest Workspace .

## Installation

To install as a standalone, use a Python environment between versions 3.9 and 3.12, inclusively.

```sh
pip install capinvest-platform-api
```

## Usage

See the [keyword arguments](#keyword-arguments) section for parameters and descriptions.

### Launch CapInvest Platform

To start the CapInvest Platform API, open a terminal, activate the environment where it is installed, and then enter:

```
capinvest-api
```

This will launch a Fast API instance, via `uvicorn`, at `http://127.0.0.1:6900`

Uvicorn can be configured by adding keyword arguments, see the section [below](#keyword-arguments)

### Launch Custom App

To run your application as an CapInvest Workspace custom backend, add the path to the Python file with the FastAPI instance to the launch command.

```sh
capinvest-api --app /Users/some_user/path/to/main.py
```

#### Arbitrary Instance Name

Define the FastAPI instance as an arbitrary name with the `--name` argument.

```sh
capinvest-api --app some_file.py --name my_app
```

#### Factory Flag

If the FastAPI instance is served via a factory function, set the `--factory` flag.

```sh
capinvest-api --app some_file.py:main --factory
```

## Keyword Arguments

The behavior of the script can be configured with the use of arguments and keyword arguments.

Launcher specific arguments:

    --app                           Absolute path to the Python file with the target FastAPI instance. Default is the installed CapInvest Platform API.
    --name                          Name of the FastAPI instance in the app file. Default is 'app'.
    --factory                       Flag to indicate if the app name is a factory function. Default is 'false'.
    --editable                      Flag to make widgets.json an editable file that can be modified during runtime. Default is 'false'.
    --build                         If the file already exists, changes prompt action to overwrite/append/ignore. Only valid when --editable true.
    --no-build                      Do not build the widgets.json file. Use this flag to load an existing widgets.json file without checking for updates.
    --login                         Login to the CapInvest Platform.
    --exclude                       JSON encoded list of API paths to exclude from widgets.json. Disable entire routes with '*' - e.g. '["/api/v1/*"]'.
    --no-filter                     Do not filter out widgets in widget_settings.json file.
    --widgets-json                  Absolute/relative path to use as the widgets.json file. Default is ~/envs/{env}/assets/widgets.json, when --editable is 'true'.
    --apps-json                     Absolute/relative path to use as the apps.json file. Default is ~/CapInvestUserData/workspace_apps.json.
    --agents-json                   Absolute/relative path to use as the agents.json file. Including this will add the /agents endpoint to the API.


All other arguments will be passed to uvicorn. Here are the most common ones:

    --host TEXT                     Host IP address or hostname.
                                      [default: 127.0.0.1]
    --port INTEGER                  Port number.
                                      [default: 6900]
    --ssl_keyfile TEXT              SSL key file.
    --ssl_certfile TEXT             SSL certificate file.
    --ssl_keyfile_password TEXT     SSL keyfile password.
    --ssl_version INTEGER           SSL version to use.
                                      (see stdlib ssl module's)
                                      [default: 17]
    --ssl_cert_reqs INTEGER         Whether client certificate is required.
                                      (see stdlib ssl module's)
                                      [default: 0]
    --ssl_ca_certs TEXT             CA certificates file.
    --ssl_ciphers TEXT              Ciphers to use.
                                      (see stdlib ssl module's)
                                      [default: TLSv1]

Run `uvicorn --help` to get the full list of arguments.

**Note** Replace, '-', with, '_' in the command line arguments of `uvicorn` (as per `uvicorn.run`)

### API Over HTTPS

To run the API over the HTTPS protocol, you must first create a self-signed certificate and the associated key. After activating the environment, you can generate the files by entering this to the command line:

```sh
openssl req -x509 -days 3650 -out localhost.crt -keyout localhost.key   -newkey rsa:4096 -nodes -sha256   -subj '/CN=localhost' -extensions EXT -config <( \
   printf "[dn]\nCN=localhost\n[req]\ndistinguished_name = dn\n[EXT]\nsubjectAltName=DNS:localhost\nkeyUsage=digitalSignature\nextendedKeyUsage=serverAuth")
```

Two files will be created, in the current working directory, that are passed as keyword arguments to the `capinvest-api` entry point.

```sh
capinvest-api --ssl_keyfile localhost.key --ssl_certfile localhost.crt
```

**Note** Adjust the command to include the full path to the file if the current working directory is not where they are located.

The certificate - `localhost.crt` - will need to be added to system's trust store. The process for this will depend on the operating system and the user account privilege.

A quick solution is to visit the server's URL, show the details of the warning, and choose to continue anyways.

Contact the system administrator if you are using a work device and require additional permissions to complete the configuration.

![This Connection Is Not Private](https://in.norton.com/content/dam/blogs/images/norton/am/this_connection_not_is_private.png)


## Example Application

Examples below will assume this code block is at the start of the file.

```python
from fastapi import FastAPI

app = FastAPI()
```

### Markdown Widget

This script will create a "markdown" widget with the returned text.

```python
@app.get("/hello")
async def hello() -> str:
    """Widget Description Generated By Docstring"""
    return "Hello, from CapInvest!"
```

### Table Widget

Create a table widget by returning data shaped as a list of dictionaries (records)

```python
@app.get("/hello")
async def hello() -> list:
    """Widget Description Generated By Docstring"""
    return [{"Column 1": "Hello", "Column 2": "from CapInvest!"}]
```

### Metric Widget

This widget displays a label, value, and optional delta.

To create a metric widget, import the custom response model below and define it as a return type.

```python
from capinvest_platform_api.response_models import MetricResponseModel

@app.get("/hello_metric")
async def hello_metric() -> MetricResponseModel:
    """Widget description created by docstring."""
    return MetricResponseModel(label="Good Vibes Score", value=100, delta="1%")
```

This type of widget can be created as an array of MetricResponseModels. Adjust the response to be a `list[MetricRespnoseModel]`

### Query Parameters

Function arguments will populate as widget parameters.

```python
from typing import Literal, Optional

@app.get("/hello")
async def hello(param1: Optional[str] = None, param2: Literal["Choice 1", "Choice 2"] = None, param3: bool = False) -> str:
    """Widget Description Generated By Docstring"""
    if not param1 and not param2 and not param3:
        return "Enter a parameter or make a choice!"
    if param3:
        return f"Param3 enabled!"
    if param2:
        return f"You selected: {param2}"
    if param1:
        return f"You entered: {param1}"

    return "Nothing to return!"
```

### Easy Date Picker

Name the parameter "date", or include "_date" in the name, and type it as a string.

Additionally, a parameter type of `datetime.date` will work.

```python
import datetime

@app.get("/hello_date")
async def hello_date(date: str) -> list:
    """Widget description created by docstring."""
    # Workspace returns the date as YYYY-MM-DD
    return [{"Hello": "Row 1!"}, {"Hello": "Row 2!"}]


@app.get("/hello_date_range")
async def hello_date_range(start: datetime.date, end: datetime.date) -> list:
    """Widget description created by docstring."""
    # Workspace returns the date as YYYY-MM-DD
    return [{"Hello": "Row 1!"}, {"Hello": "Row 2!"}]
```

This demonstrates how to define any of the basic widget parameter types, in a no-frills way. If you just need something that works, it's an easy starting point.

```python
@app.get("/hello_params")
async def hello_params(
    required_param: datetime.date,
    param_1: str = "Default",
    param_2: int = 0,
    param_3: float = None,
    param_4: Literal["Choice 1", "Choice 2", "Choice 3"] = "Choice 1",
    param_5: bool = True,
) -> list:
    """Widget description created by docstring."""
    # Handle the "choices" parameter inside the function to convert the displayed label to the desired one.
    choices_dict = {"Choice 1": "do_one", "Choice 2": "do_two", "Choice 3": "do_three"}
    choice = choices_dict.get(param_4, None)

    # Do something with the parameters and return the result of work.
    return [{"Hello": "Row 1!"}, {"Hello": "Row 2!"}]
```

### Annotated Query Params

Adding helpful placeholder text and tooltips to parameters requires annotating them. This will also help code editors and improve the API documentation.

Additional settings, compatible with `widgets.json`, are defined in the `json_schema_extra` dictionary, under a key, `x-widget_config`

```python
from typing import Annotated
from fastapi import Query
```

The pattern for annotating a query parameter is:

```python
my_param: Annotated[str, Query(title="My Title", description="My custom hovertext with detailed information")] = None
```

```python
@app.get("/hello_annotated_params")
async def hello_annotated_params(
    required_param: Annotated[
        datetime.date, Query(description="The date is required.", title="Required Date")
    ],
    not_required_param: Annotated[
        Literal["Choice 1", "Choice 2", "Choice 3"],
        Query(
            description="Choose from a list of possible choices. The default is, 'Choice 1'",
            title="Selector",
            json_schema_extra={"x-widget_config": {"multiSelect": True}}  # This lets you select multiple items from dropdown choices.
        ),
    ] = "Choice 1",
) -> list:
    """Widget description created by docstring."""

    # Do something with the parameters and return the result of work.
    return [{"Hello": "Row 1!"}, {"Hello": "Row 2!"}]
```

### Annotated Table Fields

The procedure for annotating the output is similar to the query parameters, and involves defining a response model.

A response model is a Data model of Fields. Create one by defining a new class that inherits from "Data", and then define each column as a "Field".

```python
from capinvest_platform_api.response_models import Data
from pydantic import Field
```

Optional values should be defined, as `Optional[{type}]`, with a default value of `None`.

```python
class MyData(Data):
    """This is a custom Data model."""

    # Add fields to the model.
    column_1: datetime.date = Field(
        description="The date column is a mandatory field.",
        title="Some Date",
    )
    column_2: Optional[str] = Field(
        default=None,
        description="This is an optional string column.",
        title="Some String",
    )
    column_3: int = Field(
        default=-1,
        description="This is an integer column.",
        title="Some Integer",
    )
    column_4: float = Field(
        default=10.25,
        description="This is a float column.",
        title="Some Float",
    )
    column_5: float = Field(
        default=10.25,
        description="This is a percent column.",
        title="Some Percent",
        json_schema_extra={"x-widget_config": {"formatterFn": "percent"}},
    )
    column_6: float = Field(
        default=0.1025,
        description="This is a normalized percent value adjusted for presentation.",
        title="Some Normalized Percent",
        json_schema_extra={
            "x-widget_config": {
                "formatterFn": "normalizedPercent",
                "renderFn": "greenRed",
            }
        },
    )


@app.get("/hello_data")
async def hello_data() -> list[MyData]:
    """Widget description created by docstring."""
    # Do something with the parameters and return the result of work.
    return [MyData(column_1=datetime.date.today(), column_2="Hello!")]
```


### PDF Widget

To create a PDF widget, import the custom response model below and define it as a return type.

The model handles conversion of the document, from a bytes object, to a base64 encoded string.


```python
from capinvest_platform_api.response_models import PdfResponseModel

@app.get("/open_pdf")
async def open_pdf(
    url: Annotated[
        str,
        Query(
            description="URL, or local path, to the PDF document.",
            title="URL or Path",
        ),
    ],
    filename: Annotated[
        Optional[str],
        Query(
            description="Filename to associate with the PDF internally.",
            title="Fiilename",
        ),
    ] = "",
    user_agent: Annotated[
        Optional[str],
        Query(description="A specific User-Agent string for the request.", title="User-Agent"),
    ] = None,
) -> PdfResponseModel:
    """Open a PDF document from a URL, or local file path."""
    # pylint: disable=import-outside-toplevel
    from pathlib import Path  # noqa
    from capinvest_core.provider.utils.errors import CapInvestError
    from capinvest_core.provider.utils.helpers import get_requests_session

    if "://" not in url:
        file_path = Path(url)
        if not file_path.is_file():
            raise CapInvestError(f"The file - {url} - does not exist.")
        with open(file_path, "rb") as file:
            pdf = file.read()
    else:
        session = get_requests_session(headers={"User-Agent": user_agent})
        response = session.get(url)
        if response.status_code != 200:
            raise CapInvestError(
                f"Failed to open PDF from URL -> Code: {response.status_code} -> {response.reason}"
            )

        pdf = response.content

    return PdfResponseModel(
        filename = filename,
        content = pdf,
    )
```

### Custom Plotly Chart

To define a chart widget, update the widget "type" and return the content from the `Figure.to_plotly_json()` method.


```python
@app.get(
    "/hello_chart",
    openapi_extra={"widget_config": {"type": "chart"}},
)
async def hello_chart() -> dict:
    """Widget description created by docstring."""
    from plotly.graph_objs import Bar, Layout, Figure

    fig = Figure(
        data=[Bar(x=["A", "B", "C"], y=[1, 2, 3])],
        layout=Layout(title="Hello Chart!"),
    )

    return fig.to_plotly_json()
```

### Form Submit Widget

When submitted, Workspace makes a POST request to the endpoint.

If the POST function returns a 200 status code, the widget associated with the GET function is refreshed.

The results of the GET function does not have to correspond with the parameters and results of the POST function.

For example, the response to submitting a form can be a Markdown widget with a custom message.

The entry in `widgets.json` will be automatically created if the conditions below are met:

- GET request defines in top-level `widget_config`:
  - `{"form_endpoint": /path_to/form_post_endpoint}`
- POST method takes 1 positional argument, a sub-class of Pydantic BaseModel.
  - Create a model, like annotated table fields, defining all inputs to the form.


#### Example

The code below creates a widget with a form as the input, and an output table of all submitted forms, as processed through the `IntakeForm` model.

```python
import uuid
from datetime import date as dateType
from typing import Literal, Union

# from fastapi import FastAPI
from capinvest_platform_api.response_models import Data
from pydantic import BaseModel, ConfigDict, Field

# app = FastAPI()

AccountTypes = Literal["General Fund", "Separately Managed", "Private Equity", "Family Office"]

class GeneralIntake(BaseModel):
    """Submit a form via POST request."""

    date_created: dateType = Field(
        title="Created On", default_factory=dateType.today
    )
    first_name: str = Field(title="First Name")
    last_name: str = Field(title="Last Name")
    email: str = Field(title="Contact Email")
    dob: dateType = Field(
        title="Date Of Birth",
    )
    account_types: Union[AccountTypes, list[AccountTypes]] = Field(
        title="Type Of Account",
        json_schema_extra={
            "x-widget_config": {"multiSelect": True},
        },
    )
    submit: bool = Field(
        default=True,
        title="Submit",
        json_schema_extra={
            "x-widget_config": {
                "type": "button",
            },
        }
    )


class IntakeForm(Data):
    """Submission Records."""

    model_config = ConfigDict(extra="ignore")

    contacted: bool = Field(
        title="Contacted",
        default=False,
    )
    date_created: dateType = Field(
        title="Created On",
    )
    first_name: str = Field(title="First Name")
    last_name: str = Field(title="Last Name")
    email: str = Field(title="Contact Email")
    dob: dateType = Field(
        title="Date Of Birth",
    )
    account_types: Union[AccountTypes, list[AccountTypes]] = Field(
        title="Account Interest",
    )
    unique_id: uuid.UUID = Field(
        title="Unique ID",
        default_factory=uuid.uuid4,
    )


INTAKE_FORMS: list[IntakeForm] = []


@app.post("/general_intake_submit")
async def general_intake_post(data: GeneralIntake) -> bool:
    global INTAKE_FORMS
    try:
        INTAKE_FORMS.append(IntakeForm(**data.model_dump()))
        return True
    except Exception as e:
        raise e from e


@app.get(
    "/general_intake",
    openapi_extra= {
        "widget_config": {
            "form_endpoint": "/general_intake_submit",
        },
    },
)
async def general_intake() -> list[IntakeForm]:
    return INTAKE_FORMS
```

<img width="1552" alt="Form Input Widget" src="https://github.com/user-attachments/assets/16bb3844-ea43-44c8-ae44-67159b0b70e4" />

### Omni Widget Example

An Omni Widget is a POST request where all parameters are sent to the request body, along with the text input box (keyed as "prompt").

The returned type can be a list of records (table), a Plotly Figure, or formatted Markdwon.
The model will attempt to assign the correct return type dynamically.

Set the response model as `OmniWidgetResponseModel`, then return `{"content": your_content}` from the endpoint.

```python
from typing import Literal, Optional
from capinvest_platform_api.query_models import OmniWidgetInput
from capinvest_platform_api.response_models import OmniWidgetResponseModel
from pydantic import Field

class TestOmniWidgetQueryModel(OmniWidgetInput):
    """Test query model for OmniWidget."""
    param1: str = Field(description="A string parameter for testing")
    param2: int = Field(description="An integer parameter for testing")
    param3: bool = Field(default=False, description="A boolean parameter for testing")
    start_date: str = Field(description="The start date for testing")
    end_date: str = Field(description="The end date for testing")
    parse_as: Optional[Literal["table", "chart", "text"]] = Field(
        default=None,
        description="The format to parse the response as, either 'table', 'chart', or 'text'."
        + " If not defined, the model will try to infer the type based on the content.",
    )

@app.post("/omni_widget", response_model=OmniWidgetResponseModel)
async def create_omni_widget(item: TestOmniWidgetQueryModel):
    """This is a test endpoint for generating an OmniWidget in CapInvest Workspace."""
    # Here you would process the incoming request and return a response
    some_test_data = [
        {"prompt": item.prompt,
        "param1": item.param1,
        "param2": item.param2,
        "param3": item.param3,
        "start_date": item.start_date,
        "end_date": item.end_date,
    }]

    if item.parse_as == "chart":
        some_test_data = {
            "data": [{"type": "bar", "x": ["A", "B", "C"], "y": [1, 2, 3]}],
            "layout": {"template": "plotly_dark", "title": {"text": "Hello Chart!"}}
        }
    elif item.parse_as == "text":
        some_test_data = f"""
### This is a test OmniWidget response

- Prompt: {item.prompt}
- Param1: {item.param1}
- Param2: {item.param2}
- Param3: {item.param3}
- Start Date: {item.start_date}
- End Date: {item.end_date}
"""
    return {"content": some_test_data}
```

![Omni Widget](https://github.com/user-attachments/assets/6a5aa886-9701-4448-b397-ed7bab99cac7)


## Widget Config

Any value from the [`widgets.json`]structure can be passed into the `@app` decorator by including an `openapi_extra` dictionary with the key, `"widget_config"`.

Configurations for `widgets.json` supplied here will override any of the automatically generated content. If the key does not exist, it will be created.

When inserting/updating an entry in a `Params` or `ColumnsDefs` array, the matching identifier is "paramName" and "field", respectively.

```python
@app.get(
    "/hello_data",
    openapi_extra={
        "widget_config": {
            "data": {
                "table": {
                    "columnsDefs": [
                        {
                            "field": "column_1",
                            "headerName": "My Column",
                            "headerTooltip": "This hovertext wins!",
                        }
                    ]
                }
            }
        }
    },
)
async def hello_data() -> list[MyData]:
    """Widget description created by docstring."""
    # Do something with the parameters and return the result of work.
    return [MyData(column_1=datetime.date.today(), column_2="Hello!")]
```

## Location of `widgets.json`

When `--editable` is not flagged, the file remains in memory until the server is stopped. It is regenerated every run.

The file can be served at any time by visiting the URL (host address will vary):

```sh
http://127.0.0.1:6900/widgets.json
```

When launched as `capinvest-api --editable`, a file will be stored to disk. By default, that location is:

```sh
/Path/to/environments/envs/obb/assets/widgets.json
```

The file can be manually edited and served without the build process by passing `--editable --no-build` to the API launch script.

```sh
capinvest-api --editable --no-build
```

If you would like to construct this file manually, create the file and define the path as an argument.

```sh
capinvest-api --widgets-json /Users/some_user/path/to/widgets.json
```


### Location of `workspace_apps.json`

By default, the location is:

> ~/CapInvestUserData/workspace_apps.json

This can be changed by adding the path as an argument.

```sh
capinvest-api --apps-json /Users/some_user/path/to/workspace_apps.json
```

The CapInvest Workspace allows you to export the current dashboard layout - when it is a custom backend - as a template.

To export the layout, right-click on the dashboard and select, "Export apps.json".

A JSON dictionary will be exported. Insert the contents of the export into "~/CapInvestUserData/workspace_apps.json" by pasting between the JSON list markers, [ ].

If there are more than one, add a comma between each dictionary entry.