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Dan v2 updates (#1491)
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‎pgml-cms/docs/product/cloud-database/serverless.md

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@@ -19,39 +19,14 @@ Once logged in, select "New Database" from the left menu and choose the Serverle
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### Serverless Pricing
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Storage is charged per GB/mo, and all requests by CPU or GPU millisecond of compute required to perform them.
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#### Vector & Relational Database
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| NAME | PRICING |
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| :--- | ---: |
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| Tables & Index Storage | $0.20 GB per month |
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| Retrieval, Filtering, Ranking & other Queries | $7.50 per hour |
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| Embeddings | Included w/ Queries |
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| LLMs | Included w/ Queries |
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| Fine Tuning | Included w/ Queries |
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| Machine Learning | Included w/ Queries |
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<turbo-frame id="serverless-pricing-turboframe" src="/dashboard/serverless_pricing/turboframe?style=marketing">
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Loading our current pricing model...
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</turbo-frame>
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### Serverless Models
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Serverless AI engines come with predefined models and a flexible pricing structure
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#### Embedding Models
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| NAME | PARAMETERS (M) | MAX INPUT TOKENS | DIMENSIONS | STRENGTHS |
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| --- | --- | --- | --- | --- |
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| intfloat/e5-large-v2 | 33.4 | 512 | 384 | High quality, low latency |
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| mixedbread-ai/mxbai-embed-large-v1 | 334 | 512 | 1024 | High quality, higher latency |
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| Alibaba-NLP/gte-base-en-v1.5 | 137 | 8192 | 768 | Supports up to 8k input tokens, low latency |
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| Alibaba-NLP/gte-large-en-v1.5 | 434 | 8192 | 1024 | Supports up to 8k input tokens, higher latency |
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#### Instruct Models
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| NAME | TOTAL PARAMETERS (M) | ACTIVE PARAMETERS (M) | CONTEXT SIZE | STRENGTHS |
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| --- | --- | --- | --- | --- |
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| meta-llama/Meta-Llama-3-70B-Instruct | 70,000 | 70,000 | 8,000 | High quality |
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| meta-llama/Meta-Llama-3-8B-Instruct | 8,000 | 8,000 | 8,000 | High quality, low latency |
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| microsoft/Phi-3-mini-128k-instruct | 3,820 | 3,820 | 128,000 | Lowest latency |
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| mistralai/Mixtral-8x7B-Instruct-v0.1 | 56,000 | 12,900 | 32,768 | MOE high quality |
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| mistralai/Mistral-7B-Instruct-v0.2 | 7,000 | 7,000 | 32,768 | High quality, low latency |
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#### Summarization Models
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| NAME | PARAMETERS (M) | CONTEXT SIZE | STRENGTHS |
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| --- | --- | --- | --- |
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| google/pegasus-xsum | 568 | 512 | Efficient summarization |
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<turbo-frame id="serverless-models-turboframe" src="/dashboard/serverless_models/turboframe?style=marketing">
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Loading our current serverless models offered...
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</turbo-frame>

‎pgml-dashboard/Cargo.lock

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‎pgml-dashboard/src/components/tables/mod.rs

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// src/components/tables/large
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pub mod large;
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// src/components/tables/serverless_models
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pub mod serverless_models;
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pub use serverless_models::ServerlessModels;
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// src/components/tables/serverless_pricing
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pub mod serverless_pricing;
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pub use serverless_pricing::ServerlessPricing;
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// src/components/tables/small
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pub mod small;

‎pgml-dashboard/src/components/tables/serverless_models/mod.rs

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use crate::components::tables::small::row::Row;
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use pgml_components::component;
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use pgml_components::Component;
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use sailfish::TemplateOnce;
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#[derive(TemplateOnce, Default)]
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#[template(path = "tables/serverless_models/template.html")]
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pub struct ServerlessModels {
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style_type: String,
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embedding_models: [Component; 4],
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instruct_models: [Component; 5],
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summarization_models: [Component; 1],
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}
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impl ServerlessModels {
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pub fn new() -> ServerlessModels {
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ServerlessModels {
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style_type: "product".to_string(),
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embedding_models: [
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Component::from(Row::new(&[
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"intfloat/e5-small-v2".into(),
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"33.4".into(),
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"512".into(),
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"384".into(),
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"Good quality, low latency".into(),
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])),
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Component::from(Row::new(&[
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"mixedbread-ai/mxbai-embed-large-v1".into(),
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"335".into(),
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"512".into(),
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"1024".into(),
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"High quality, higher latency".into(),
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])),
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Component::from(Row::new(&[
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"Alibaba-NLP/gte-base-en-v1.5".into(),
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"137".into(),
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"8192".into(),
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"768".into(),
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"Supports up to 8,000 input tokens".into(),
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])),
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Component::from(Row::new(&[
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"Alibaba-NLP/gte-large-en-v1.5".into(),
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"434".into(),
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"8192".into(),
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"1024".into(),
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"Highest quality, 8,000 input tokens".into(),
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])),
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],
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instruct_models: [
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Component::from(Row::new(&[
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"meta-llama/Meta-Llama-3-70B-Instruct".into(),
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"70,000".into(),
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"70,000".into(),
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"8,000".into(),
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"Highest quality".into(),
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])),
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Component::from(Row::new(&[
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"meta-llama/Meta-Llama-3-8B-Instruct".into(),
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"8,000".into(),
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"8,000".into(),
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"8,000".into(),
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"High quality, low latency".into(),
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])),
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Component::from(Row::new(&[
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"microsoft/Phi-3-mini-128k-instruct".into(),
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"3,820".into(),
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"3,820".into(),
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"128,000".into(),
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"Lowest latency".into(),
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])),
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Component::from(Row::new(&[
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"mistralai/Mixtral-8x7B-Instruct-v0.1".into(),
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"56,000".into(),
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"12,900".into(),
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"32,768".into(),
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"MOE high quality".into(),
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])),
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Component::from(Row::new(&[
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"mistralai/Mistral-7B-Instruct-v0.2".into(),
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"7,000".into(),
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"7,000".into(),
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"32,768".into(),
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"High quality, low latency".into(),
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])),
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],
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summarization_models: [Component::from(Row::new(&[
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"google/pegasus-xsum".into(),
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"568".into(),
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"512".into(),
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"8,000".into(),
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]))],
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}
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}
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pub fn set_style_type(mut self, style_type: &str) -> Self {
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self.style_type = style_type.to_string();
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self
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}
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}
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#[derive(TemplateOnce, Default)]
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#[template(path = "tables/serverless_models/turbotemplate.html")]
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pub struct ServerlessModelsTurbo {
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comp: Component,
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}
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impl ServerlessModelsTurbo {
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pub fn new(comp: Component) -> ServerlessModelsTurbo {
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ServerlessModelsTurbo { comp }
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}
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}
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component!(ServerlessModels);
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component!(ServerlessModelsTurbo);

‎pgml-dashboard/src/components/tables/serverless_models/serverless_models.scss

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div[data-controller="tables-serverless-models"] {
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table.table.table-sm thead th, table.table-sm thead th {
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vertical-align: top;
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padding-top: 8px;
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padding-bottom: 8px;
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}
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}

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