feat: add hyko_toolkit including APIs

hyko_toolkit/apis/__init__.py

@@ -0,0 +1,9 @@
+from hyko_sdk.definitions import ToolkitAPI
+
+from .openai.text_completion.metadata import func as text_completion
+
+all = {text_completion.name: text_completion}
+
+
+def api_handler(name: str) -> ToolkitAPI:
+    return all[name]

hyko_toolkit/apis/openai/text_completion/metadata.py

@@ -0,0 +1,102 @@
+from enum import Enum
+
+import httpx
+from hyko_sdk.definitions import ToolkitAPI
+from hyko_sdk.models import CoreModel, Method
+from pydantic import Field
+
+from hyko_toolkit.exceptions import APICallError
+
+func = ToolkitAPI(
+    name="text_completion",
+    task="openai",
+    description="Use openai api for text completion.",
+)
+
+
+class Model(str, Enum):
+    gpt_4 = "gpt-4"
+    chatgpt = "gpt-3.5-turbo"
+
+
+@func.set_input
+class Inputs(CoreModel):
+    system_prompt: str = Field(
+        default="You are a helpful assistant", description="generated text."
+    )
+    prompt: str = Field(..., description="Input prompt.")
+
+
+@func.set_param
+class Params(CoreModel):
+    api_key: str = Field(default="", description="API key")
+    model: Model = Field(
+        default=Model.chatgpt,
+        description="Openai model to use.",
+    )
+    max_tokens: int = Field(
+        default=1024,
+        description="The maximum number of tokens that can be generated in the chat completion.",
+    )
+    temperature: int = Field(
+        default=1,
+        description="What sampling temperature to use, between 0 and 2, defaults to 1.",
+    )
+
+
+@func.set_output
+class Outputs(CoreModel):
+    result: str = Field(..., description="generated text.")
+
+
+class Message(CoreModel):
+    role: str
+    content: str
+
+
+class Choice(CoreModel):
+    index: int
+    message: Message
+    finish_reason: str
+
+
+class Usage(CoreModel):
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+
+
+class Response(CoreModel):
+    created: int
+    model: str
+    choices: list[Choice]
+    usage: Usage
+
+
+@func.on_call
+async def call(inputs: Inputs, params: Params):
+    async with httpx.AsyncClient() as client:
+        res = await client.request(
+            method=Method.post,
+            url="https://api.openai.com/v1/chat/completions",
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {params.api_key}",
+            },
+            json={
+                "model": params.model,
+                "max_tokens": params.max_tokens,
+                "temperature": params.temperature,
+                "messages": [
+                    {"role": "system", "content": inputs.system_prompt},
+                    {"role": "user", "content": inputs.prompt},
+                ],
+            },
+            timeout=60 * 5,
+        )
+    if res.is_success:
+        response = Response(**res.json())
+    else:
+        raise APICallError(status=res.status_code, detail=res.text)
+
+    return Outputs(result=response.choices[0].message.content)

hyko_toolkit/exceptions.py

@@ -0,0 +1,7 @@
+from dataclasses import dataclass
+
+
+@dataclass
+class APICallError(BaseException):
+    status: int
+    detail: str = "An api call error happened"

hyko_toolkit/functions/converters/image_converter/main.py

@@ -1,8 +1,7 @@
 import cv2
 import numpy as np
-from metadata import Inputs, Outputs, Params, func
-
 from hyko_sdk.io import Image
+from metadata import Inputs, Outputs, Params, func
 
 
 @func.on_execute

hyko_toolkit/functions/converters/image_converter/metadata.py

@@ -1,10 +1,9 @@
 from enum import Enum
 
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import Image
 from hyko_sdk.models import CoreModel, Ext
+from pydantic import Field
 
 
 class SupportedTypes(Enum):

hyko_toolkit/functions/converters/markdown_to_pdf/main.py

@@ -4,14 +4,13 @@
 import markdown
 import pygments
 from fpdf import FPDF
-from metadata import Inputs, Outputs, Params, func
+from hyko_sdk.io import PDF
+from hyko_sdk.models import CoreModel, Ext
+from metadata import Inputs, Outputs, func
 from pygments.formatters import HtmlFormatter
 from pygments.lexers import get_lexer_by_name
 from pygments.util import ClassNotFound
 
-from hyko_sdk.io import PDF
-from hyko_sdk.models import Ext
-
 
 def format_code_block(code: str, language: str):
     """
@@ -128,6 +127,6 @@ def convert_markdown_to_pdf(markdown_string: str):
 
 
 @func.on_execute
-async def main(inputs: Inputs, params: Params) -> Outputs:
+async def main(inputs: Inputs, params: CoreModel) -> Outputs:
     buff = convert_markdown_to_pdf(inputs.markdown_string)
     return Outputs(pdf=PDF(val=buff, obj_ext=Ext.PDF))

hyko_toolkit/functions/converters/markdown_to_pdf/metadata.py

@@ -1,8 +1,7 @@
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import PDF
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 func = ToolkitFunction(
     name="markdown_to_pdf",
@@ -16,11 +15,6 @@ class Inputs(CoreModel):
     markdown_string: str = Field(..., description="The Markdown content to convert.")
 
 
-@func.set_param
-class Params(CoreModel):
-    pass
-
-
 @func.set_output
 class Outputs(CoreModel):
     pdf: PDF = Field(..., description="PDF File .")

hyko_toolkit/functions/converters/ocr_pdf_to_text/metadata.py

@@ -1,10 +1,9 @@
 from enum import Enum
 
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import PDF
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 
 class SupportedLanguages(str, Enum):

hyko_toolkit/functions/converters/pdf_to_text/main.py

@@ -1,11 +1,12 @@
 from io import BytesIO
 
+from hyko_sdk.models import CoreModel
 from langchain_community.document_loaders import PyPDFLoader
-from metadata import Inputs, Outputs, Params, func
+from metadata import Inputs, Outputs, func
 
 
 @func.on_execute
-async def main(inputs: Inputs, params: Params) -> Outputs:
+async def main(inputs: Inputs, params: CoreModel) -> Outputs:
     """
     Processes a PDF file provided in binary format, extracts text content from it,
     and returns the concatenated text as output.

hyko_toolkit/functions/converters/pdf_to_text/metadata.py

@@ -1,8 +1,7 @@
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import PDF
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 func = ToolkitFunction(
     name="pdf_to_text",
@@ -16,11 +15,6 @@ class Inputs(CoreModel):
     pdf_file: PDF = Field(..., description="User input pdf to be converted to text")
 
 
-@func.set_param
-class Params(CoreModel):
-    pass
-
-
 @func.set_output
 class Outputs(CoreModel):
     text: str = Field(..., description="Extracted text from pdf")

hyko_toolkit/functions/converters/video_converter/main.py

@@ -2,9 +2,8 @@
 import tempfile
 
 import cv2
-from metadata import Inputs, Outputs, Params, func
-
 from hyko_sdk.io import Video
+from metadata import Inputs, Outputs, Params, func
 
 
 def convert_video(buffer, codec):

hyko_toolkit/functions/converters/video_converter/metadata.py

@@ -1,10 +1,9 @@
 from enum import Enum
 
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import Video
 from hyko_sdk.models import CoreModel, Ext
+from pydantic import Field
 
 func = ToolkitFunction(
     name="video_converter",

hyko_toolkit/functions/converters/video_to_audio/main.py

@@ -1,14 +1,13 @@
 import os
 import subprocess
 
-from metadata import Inputs, Outputs, Params, func
-
 from hyko_sdk.io import Audio
-from hyko_sdk.models import Ext
+from hyko_sdk.models import CoreModel, Ext
+from metadata import Inputs, Outputs, func
 
 
 @func.on_execute
-async def main(inputs: Inputs, params: Params) -> Outputs:
+async def main(inputs: Inputs, params: CoreModel) -> Outputs:
     _, ext = os.path.splitext(inputs.video.get_name())
 
     with open(f"/app/video.{ext}", "wb") as f:

hyko_toolkit/functions/converters/video_to_audio/metadata.py

@@ -1,8 +1,7 @@
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import Audio, Video
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 func = ToolkitFunction(
     name="video_to_audio",
@@ -16,11 +15,6 @@ class Inputs(CoreModel):
     video: Video = Field(..., description="User input video to be converted to audio")
 
 
-@func.set_param
-class Params(CoreModel):
-    pass
-
-
 @func.set_output
 class Outputs(CoreModel):
     audio: Audio = Field(..., description="converted audio")

hyko_toolkit/functions/downloaders/youtube_downloader/main.py

@@ -1,5 +1,7 @@
 import io
 
+from hyko_sdk.io import Video
+from hyko_sdk.models import Ext
 from metadata import (
     Inputs,
     Outputs,
@@ -8,9 +10,6 @@
 )
 from pytube import YouTube
 
-from hyko_sdk.io import Video
-from hyko_sdk.models import Ext
-
 
 def download_video(url, resolution):
     """

hyko_toolkit/functions/downloaders/youtube_downloader/metadata.py

@@ -1,10 +1,9 @@
 from enum import Enum
 
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import Video
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 
 class Resolution(str, Enum):

hyko_toolkit/functions/plotting/bivariate_plot/main.py

@@ -4,10 +4,9 @@
 import matplotlib.pyplot as plt
 import pandas as pd
 import seaborn as sns
-from metadata import Inputs, Outputs, Params, func
-
 from hyko_sdk.io import Image
 from hyko_sdk.models import Ext
+from metadata import Inputs, Outputs, Params, func
 
 
 def generate_violin_plot(x: list[float], y: list[float]):

hyko_toolkit/functions/plotting/bivariate_plot/metadata.py

@@ -1,10 +1,9 @@
 from enum import Enum
 
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import Image
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 
 class SupportedPlots(str, Enum):

hyko_toolkit/functions/plotting/univariate_plot/main.py

@@ -2,10 +2,9 @@
 
 import matplotlib.pyplot as plt
 import pandas as pd
-from metadata import Inputs, Outputs, Params, func
-
 from hyko_sdk.io import Image
 from hyko_sdk.models import Ext
+from metadata import Inputs, Outputs, Params, func
 
 
 def generate_pie_chart(y: list[float]):

hyko_toolkit/functions/plotting/univariate_plot/metadata.py

@@ -1,10 +1,9 @@
 from enum import Enum
 
-from pydantic import Field
-
 from hyko_sdk.definitions import ToolkitFunction
 from hyko_sdk.io import Image
 from hyko_sdk.models import CoreModel
+from pydantic import Field
 
 
 class SupportedPlots(str, Enum):

hyko_toolkit/functions/utils/image_utils/brightness_and_contrast/main.py

@@ -1,8 +1,7 @@
 import cv2
 import numpy as np
-from metadata import Inputs, Outputs, Params, func
-
 from hyko_sdk.io import Image
+from metadata import Inputs, Outputs, Params, func
 
 
 @func.on_execute