feat: frontend integration

This commit is contained in:
Timothy J. Baek 2024-04-14 18:31:40 -04:00
parent 2952e61167
commit 9cdb5bf9fe
3 changed files with 134 additions and 33 deletions

View File

@ -138,20 +138,22 @@ async def get_status():
}
@app.get("/embedding/model")
async def get_embedding_model(user=Depends(get_admin_user)):
@app.get("/embedding")
async def get_embedding_config(user=Depends(get_admin_user)):
return {
"status": True,
"embedding_engine": app.state.RAG_EMBEDDING_ENGINE,
"embedding_model": app.state.RAG_EMBEDDING_MODEL,
}
class EmbeddingModelUpdateForm(BaseModel):
embedding_engine: str
embedding_model: str
@app.post("/embedding/model/update")
async def update_embedding_model(
@app.post("/embedding/update")
async def update_embedding_config(
form_data: EmbeddingModelUpdateForm, user=Depends(get_admin_user)
):
@ -160,18 +162,26 @@ async def update_embedding_model(
)
try:
sentence_transformer_ef = (
embedding_functions.SentenceTransformerEmbeddingFunction(
model_name=get_embedding_model_path(form_data.embedding_model, True),
device=DEVICE_TYPE,
)
)
app.state.RAG_EMBEDDING_ENGINE = form_data.embedding_engine
app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model
app.state.sentence_transformer_ef = sentence_transformer_ef
if app.state.RAG_EMBEDDING_ENGINE == "ollama":
app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model
app.state.sentence_transformer_ef = None
else:
sentence_transformer_ef = (
embedding_functions.SentenceTransformerEmbeddingFunction(
model_name=get_embedding_model_path(
form_data.embedding_model, True
),
device=DEVICE_TYPE,
)
)
app.state.RAG_EMBEDDING_MODEL = form_data.embedding_model
app.state.sentence_transformer_ef = sentence_transformer_ef
return {
"status": True,
"embedding_engine": app.state.RAG_EMBEDDING_ENGINE,
"embedding_model": app.state.RAG_EMBEDDING_MODEL,
}

View File

@ -346,10 +346,10 @@ export const resetVectorDB = async (token: string) => {
return res;
};
export const getEmbeddingModel = async (token: string) => {
export const getEmbeddingConfig = async (token: string) => {
let error = null;
const res = await fetch(`${RAG_API_BASE_URL}/embedding/model`, {
const res = await fetch(`${RAG_API_BASE_URL}/embedding`, {
method: 'GET',
headers: {
'Content-Type': 'application/json',
@ -374,13 +374,14 @@ export const getEmbeddingModel = async (token: string) => {
};
type EmbeddingModelUpdateForm = {
embedding_engine: string;
embedding_model: string;
};
export const updateEmbeddingModel = async (token: string, payload: EmbeddingModelUpdateForm) => {
export const updateEmbeddingConfig = async (token: string, payload: EmbeddingModelUpdateForm) => {
let error = null;
const res = await fetch(`${RAG_API_BASE_URL}/embedding/model/update`, {
const res = await fetch(`${RAG_API_BASE_URL}/embedding/update`, {
method: 'POST',
headers: {
'Content-Type': 'application/json',

View File

@ -7,11 +7,11 @@
scanDocs,
updateQuerySettings,
resetVectorDB,
getEmbeddingModel,
updateEmbeddingModel
getEmbeddingConfig,
updateEmbeddingConfig
} from '$lib/apis/rag';
import { documents } from '$lib/stores';
import { documents, models } from '$lib/stores';
import { onMount, getContext } from 'svelte';
import { toast } from 'svelte-sonner';
@ -27,6 +27,8 @@
let showResetConfirm = false;
let embeddingEngine = '';
let embeddingModel = '';
let chunkSize = 0;
let chunkOverlap = 0;
let pdfExtractImages = true;
@ -36,8 +38,6 @@
k: 4
};
let embeddingModel = '';
const scanHandler = async () => {
scanDirLoading = true;
const res = await scanDocs(localStorage.token);
@ -50,7 +50,16 @@
};
const embeddingModelUpdateHandler = async () => {
if (embeddingModel.split('/').length - 1 > 1) {
if (embeddingModel === '') {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
)
);
return;
}
if (embeddingEngine === '' && embeddingModel.split('/').length - 1 > 1) {
toast.error(
$i18n.t(
'Model filesystem path detected. Model shortname is required for update, cannot continue.'
@ -62,11 +71,17 @@
console.log('Update embedding model attempt:', embeddingModel);
updateEmbeddingModelLoading = true;
const res = await updateEmbeddingModel(localStorage.token, {
const res = await updateEmbeddingConfig(localStorage.token, {
embedding_engine: embeddingEngine,
embedding_model: embeddingModel
}).catch(async (error) => {
toast.error(error);
embeddingModel = (await getEmbeddingModel(localStorage.token)).embedding_model;
const embeddingConfig = await getEmbeddingConfig(localStorage.token);
if (embeddingConfig) {
embeddingEngine = embeddingConfig.embedding_engine;
embeddingModel = embeddingConfig.embedding_model;
}
return null;
});
updateEmbeddingModelLoading = false;
@ -102,7 +117,12 @@
chunkOverlap = res.chunk.chunk_overlap;
}
embeddingModel = (await getEmbeddingModel(localStorage.token)).embedding_model;
const embeddingConfig = await getEmbeddingConfig(localStorage.token);
if (embeddingConfig) {
embeddingEngine = embeddingConfig.embedding_engine;
embeddingModel = embeddingConfig.embedding_model;
}
querySettings = await getQuerySettings(localStorage.token);
});
@ -126,6 +146,9 @@
class="dark:bg-gray-900 w-fit pr-8 rounded px-2 p-1 text-xs bg-transparent outline-none text-right"
bind:value={embeddingEngine}
placeholder="Select an embedding engine"
on:change={() => {
embeddingModel = '';
}}
>
<option value="">{$i18n.t('Default (SentenceTransformer)')}</option>
<option value="ollama">{$i18n.t('Ollama')}</option>
@ -136,10 +159,77 @@
<div class="space-y-2">
<div>
<div class=" mb-2 text-sm font-medium">{$i18n.t('Update Embedding Model')}</div>
{#if embeddingEngine === 'ollama'}
<div>da</div>
<div class="flex w-full">
<div class="flex-1 mr-2">
<select
class="w-full rounded-lg py-2 px-4 text-sm dark:text-gray-300 dark:bg-gray-850 outline-none"
bind:value={embeddingModel}
placeholder={$i18n.t('Select a model')}
required
>
{#if !embeddingModel}
<option value="" disabled selected>{$i18n.t('Select a model')}</option>
{/if}
{#each $models.filter((m) => m.id && !m.external) as model}
<option value={model.name} class="bg-gray-100 dark:bg-gray-700"
>{model.name + ' (' + (model.size / 1024 ** 3).toFixed(1) + ' GB)'}</option
>
{/each}
</select>
</div>
<button
class="px-2.5 bg-gray-100 hover:bg-gray-200 text-gray-800 dark:bg-gray-850 dark:hover:bg-gray-800 dark:text-gray-100 rounded-lg transition"
on:click={() => {
embeddingModelUpdateHandler();
}}
disabled={updateEmbeddingModelLoading}
>
{#if updateEmbeddingModelLoading}
<div class="self-center">
<svg
class=" w-4 h-4"
viewBox="0 0 24 24"
fill="currentColor"
xmlns="http://www.w3.org/2000/svg"
><style>
.spinner_ajPY {
transform-origin: center;
animation: spinner_AtaB 0.75s infinite linear;
}
@keyframes spinner_AtaB {
100% {
transform: rotate(360deg);
}
}
</style><path
d="M12,1A11,11,0,1,0,23,12,11,11,0,0,0,12,1Zm0,19a8,8,0,1,1,8-8A8,8,0,0,1,12,20Z"
opacity=".25"
/><path
d="M10.14,1.16a11,11,0,0,0-9,8.92A1.59,1.59,0,0,0,2.46,12,1.52,1.52,0,0,0,4.11,10.7a8,8,0,0,1,6.66-6.61A1.42,1.42,0,0,0,12,2.69h0A1.57,1.57,0,0,0,10.14,1.16Z"
class="spinner_ajPY"
/></svg
>
</div>
{:else}
<svg
xmlns="http://www.w3.org/2000/svg"
viewBox="0 0 16 16"
fill="currentColor"
class="w-4 h-4"
>
<path
fill-rule="evenodd"
d="M12.416 3.376a.75.75 0 0 1 .208 1.04l-5 7.5a.75.75 0 0 1-1.154.114l-3-3a.75.75 0 0 1 1.06-1.06l2.353 2.353 4.493-6.74a.75.75 0 0 1 1.04-.207Z"
clip-rule="evenodd"
/>
</svg>
{/if}
</button>
</div>
{:else}
<div class=" mb-2 text-sm font-medium">{$i18n.t('Update Embedding Model')}</div>
<div class="flex w-full">
<div class="flex-1 mr-2">
<input
@ -200,14 +290,14 @@
{/if}
</button>
</div>
<div class="mt-2 mb-1 text-xs text-gray-400 dark:text-gray-500">
{$i18n.t(
'Warning: If you update or change your embedding model, you will need to re-import all documents.'
)}
</div>
{/if}
<div class="mt-2 mb-1 text-xs text-gray-400 dark:text-gray-500">
{$i18n.t(
'Warning: If you update or change your embedding model, you will need to re-import all documents.'
)}
</div>
<hr class=" dark:border-gray-700 my-3" />
<div class=" flex w-full justify-between">