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FunctionEditor.svelte 12.1 KB
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<script>
	import { getContext, createEventDispatcher, onMount } from 'svelte';
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	import { goto } from '$app/navigation';
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	const dispatch = createEventDispatcher();
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	const i18n = getContext('i18n');

	import CodeEditor from '$lib/components/common/CodeEditor.svelte';
	import ConfirmDialog from '$lib/components/common/ConfirmDialog.svelte';

	let formElement = null;
	let loading = false;
	let showConfirm = false;

	export let edit = false;
	export let clone = false;

	export let id = '';
	export let name = '';
	export let meta = {
		description: ''
	};
	export let content = '';

	$: if (name && !edit && !clone) {
		id = name.replace(/\s+/g, '_').toLowerCase();
	}

	let codeEditor;
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	let boilerplate = `from pydantic import BaseModel
from typing import Optional
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class Filter:
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    class Valves(BaseModel):
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        max_turns: int = 4
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        pass

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    def __init__(self):
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        # Indicates custom file handling logic. This flag helps disengage default routines in favor of custom
        # implementations, informing the WebUI to defer file-related operations to designated methods within this class.
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        # Alternatively, you can remove the files directly from the body in from the inlet hook
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        self.file_handler = True

        # Initialize 'valves' with specific configurations. Using 'Valves' instance helps encapsulate settings,
        # which ensures settings are managed cohesively and not confused with operational flags like 'file_handler'.
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        self.valves = self.Valves(**{"max_turns": 2})
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        pass

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    def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
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        # Modify the request body or validate it before processing by the chat completion API.
        # This function is the pre-processor for the API where various checks on the input can be performed.
        # It can also modify the request before sending it to the API.
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        print(f"inlet:{__name__}")
        print(f"inlet:body:{body}")
        print(f"inlet:user:{user}")
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        if user.get("role", "admin") in ["user", "admin"]:
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            messages = body.get("messages", [])
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            if len(messages) > self.valves.max_turns:
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                raise Exception(
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                    f"Conversation turn limit exceeded. Max turns: {self.valves.max_turns}"
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                )
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        return body
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    def outlet(self, body: dict, user: Optional[dict] = None) -> dict:
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        # Modify or analyze the response body after processing by the API.
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        # This function is the post-processor for the API, which can be used to modify the response
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        # or perform additional checks and analytics.
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        print(f"outlet:{__name__}")
        print(f"outlet:body:{body}")
        print(f"outlet:user:{user}")
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        messages = [
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            {
                **message,
                "content": f"{message['content']} - @@Modified from Filter Outlet",
            }
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            for message in body.get("messages", [])
        ]

        return {"messages": messages}
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`;

	const _boilerplate = `from pydantic import BaseModel
from typing import Optional, Union, Generator, Iterator
from utils.misc import get_last_user_message

import os
import requests


# Filter Class: This class is designed to serve as a pre-processor and post-processor
# for request and response modifications. It checks and transforms requests and responses
# to ensure they meet specific criteria before further processing or returning to the user.
class Filter:
    class Valves(BaseModel):
        max_turns: int = 4
        pass

    def __init__(self):
        # Indicates custom file handling logic. This flag helps disengage default routines in favor of custom
        # implementations, informing the WebUI to defer file-related operations to designated methods within this class.
        # Alternatively, you can remove the files directly from the body in from the inlet hook
        self.file_handler = True

        # Initialize 'valves' with specific configurations. Using 'Valves' instance helps encapsulate settings,
        # which ensures settings are managed cohesively and not confused with operational flags like 'file_handler'.
        self.valves = self.Valves(**{"max_turns": 2})
        pass

    def inlet(self, body: dict, user: Optional[dict] = None) -> dict:
        # Modify the request body or validate it before processing by the chat completion API.
        # This function is the pre-processor for the API where various checks on the input can be performed.
        # It can also modify the request before sending it to the API.
        print(f"inlet:{__name__}")
        print(f"inlet:body:{body}")
        print(f"inlet:user:{user}")

        if user.get("role", "admin") in ["user", "admin"]:
            messages = body.get("messages", [])
            if len(messages) > self.valves.max_turns:
                raise Exception(
                    f"Conversation turn limit exceeded. Max turns: {self.valves.max_turns}"
                )

        return body

    def outlet(self, body: dict, user: Optional[dict] = None) -> dict:
        # Modify or analyze the response body after processing by the API.
        # This function is the post-processor for the API, which can be used to modify the response
        # or perform additional checks and analytics.
        print(f"outlet:{__name__}")
        print(f"outlet:body:{body}")
        print(f"outlet:user:{user}")

        messages = [
            {
                **message,
                "content": f"{message['content']} - @@Modified from Filter Outlet",
            }
            for message in body.get("messages", [])
        ]

        return {"messages": messages}



# Pipe Class: This class functions as a customizable pipeline.
# It can be adapted to work with any external or internal models,
# making it versatile for various use cases outside of just OpenAI models.
class Pipe:
    class Valves(BaseModel):
        OPENAI_API_BASE_URL: str = "https://api.openai.com/v1"
        OPENAI_API_KEY: str = "your-key"
        pass

    def __init__(self):
        self.type = "manifold"
        self.valves = self.Valves()
        self.pipes = self.get_openai_models()
        pass

    def get_openai_models(self):
        if self.valves.OPENAI_API_KEY:
            try:
                headers = {}
                headers["Authorization"] = f"Bearer {self.valves.OPENAI_API_KEY}"
                headers["Content-Type"] = "application/json"

                r = requests.get(
                    f"{self.valves.OPENAI_API_BASE_URL}/models", headers=headers
                )

                models = r.json()
                return [
                    {
                        "id": model["id"],
                        "name": model["name"] if "name" in model else model["id"],
                    }
                    for model in models["data"]
                    if "gpt" in model["id"]
                ]

            except Exception as e:

                print(f"Error: {e}")
                return [
                    {
                        "id": "error",
                        "name": "Could not fetch models from OpenAI, please update the API Key in the valves.",
                    },
                ]
        else:
            return []

    def pipe(self, body: dict) -> Union[str, Generator, Iterator]:
        # This is where you can add your custom pipelines like RAG.
        print(f"pipe:{__name__}")

        if "user" in body:
            print(body["user"])
            del body["user"]

        headers = {}
        headers["Authorization"] = f"Bearer {self.valves.OPENAI_API_KEY}"
        headers["Content-Type"] = "application/json"

        model_id = body["model"][body["model"].find(".") + 1 :]
        payload = {**body, "model": model_id}
        print(payload)

        try:
            r = requests.post(
                url=f"{self.valves.OPENAI_API_BASE_URL}/chat/completions",
                json=payload,
                headers=headers,
                stream=True,
            )

            r.raise_for_status()

            if body["stream"]:
                return r.iter_lines()
            else:
                return r.json()
        except Exception as e:
            return f"Error: {e}"
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`;
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	const saveHandler = async () => {
		loading = true;
		dispatch('save', {
			id,
			name,
			meta,
			content
		});
	};

	const submitHandler = async () => {
		if (codeEditor) {
			const res = await codeEditor.formatPythonCodeHandler();

			if (res) {
				console.log('Code formatted successfully');
				saveHandler();
			}
		}
	};
</script>

<div class=" flex flex-col justify-between w-full overflow-y-auto h-full">
	<div class="mx-auto w-full md:px-0 h-full">
		<form
			bind:this={formElement}
			class=" flex flex-col max-h-[100dvh] h-full"
			on:submit|preventDefault={() => {
				if (edit) {
					submitHandler();
				} else {
					showConfirm = true;
				}
			}}
		>
			<div class="mb-2.5">
				<button
					class="flex space-x-1"
					on:click={() => {
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						goto('/workspace/functions');
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					}}
					type="button"
				>
					<div class=" self-center">
						<svg
							xmlns="http://www.w3.org/2000/svg"
							viewBox="0 0 20 20"
							fill="currentColor"
							class="w-4 h-4"
						>
							<path
								fill-rule="evenodd"
								d="M17 10a.75.75 0 01-.75.75H5.612l4.158 3.96a.75.75 0 11-1.04 1.08l-5.5-5.25a.75.75 0 010-1.08l5.5-5.25a.75.75 0 111.04 1.08L5.612 9.25H16.25A.75.75 0 0117 10z"
								clip-rule="evenodd"
							/>
						</svg>
					</div>
					<div class=" self-center font-medium text-sm">{$i18n.t('Back')}</div>
				</button>
			</div>

			<div class="flex flex-col flex-1 overflow-auto h-0 rounded-lg">
				<div class="w-full mb-2 flex flex-col gap-1.5">
					<div class="flex gap-2 w-full">
						<input
							class="w-full px-3 py-2 text-sm font-medium bg-gray-50 dark:bg-gray-850 dark:text-gray-200 rounded-lg outline-none"
							type="text"
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							placeholder="Function Name (e.g. My Filter)"
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							bind:value={name}
							required
						/>

						<input
							class="w-full px-3 py-2 text-sm font-medium disabled:text-gray-300 dark:disabled:text-gray-700 bg-gray-50 dark:bg-gray-850 dark:text-gray-200 rounded-lg outline-none"
							type="text"
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							placeholder="Function ID (e.g. my_filter)"
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							bind:value={id}
							required
							disabled={edit}
						/>
					</div>
					<input
						class="w-full px-3 py-2 text-sm font-medium bg-gray-50 dark:bg-gray-850 dark:text-gray-200 rounded-lg outline-none"
						type="text"
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						placeholder="Function Description (e.g. A filter to remove profanity from text)"
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						bind:value={meta.description}
						required
					/>
				</div>

				<div class="mb-2 flex-1 overflow-auto h-0 rounded-lg">
					<CodeEditor
						bind:value={content}
						bind:this={codeEditor}
						{boilerplate}
						on:save={() => {
							if (formElement) {
								formElement.requestSubmit();
							}
						}}
					/>
				</div>

				<div class="pb-3 flex justify-between">
					<div class="flex-1 pr-3">
						<div class="text-xs text-gray-500 line-clamp-2">
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							<span class=" font-semibold dark:text-gray-200">Warning:</span> Functions allow
							arbitrary code execution <br />—
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							<span class=" font-medium dark:text-gray-400"
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								>don't install random functions from sources you don't trust.</span
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							>
						</div>
					</div>

					<button
						class="px-3 py-1.5 text-sm font-medium bg-emerald-600 hover:bg-emerald-700 text-gray-50 transition rounded-lg"
						type="submit"
					>
						{$i18n.t('Save')}
					</button>
				</div>
			</div>
		</form>
	</div>
</div>

<ConfirmDialog
	bind:show={showConfirm}
	on:confirm={() => {
		submitHandler();
	}}
>
	<div class="text-sm text-gray-500">
		<div class=" bg-yellow-500/20 text-yellow-700 dark:text-yellow-200 rounded-lg px-4 py-3">
			<div>Please carefully review the following warnings:</div>

			<ul class=" mt-1 list-disc pl-4 text-xs">
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				<li>Functions allow arbitrary code execution.</li>
				<li>Do not install functions from sources you do not fully trust.</li>
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			</ul>
		</div>

		<div class="my-3">
			I acknowledge that I have read and I understand the implications of my action. I am aware of
			the risks associated with executing arbitrary code and I have verified the trustworthiness of
			the source.
		</div>
	</div>
</ConfirmDialog>