diff --git a/.github/workflows/extension_ci.yml b/.github/workflows/extension_ci.yml
index 3a24fda..18588b3 100644
--- a/.github/workflows/extension_ci.yml
+++ b/.github/workflows/extension_ci.yml
@@ -3,7 +3,7 @@ name: PG Vectorize Extension
 defaults:
   run:
     shell: bash
-    working-directory: ./
+    working-directory: ./extension
 
 on:
   pull_request:
@@ -73,7 +73,7 @@ jobs:
           cache-directories: /home/runner/.pgrx
       - uses: ./.github/actions/pgx-init
         with:
-          working-directory: ./
+          working-directory: ./extension
       - name: Cargo format
         run: cargo fmt --all --check
       - name: Clippy
@@ -103,7 +103,7 @@ jobs:
           cache-directories: /home/runner/.pgrx
       - uses: ./.github/actions/pgx-init
         with:
-          working-directory: ./
+          working-directory: ./extension
       - name: Restore cached binaries
         uses: actions/cache@v2
         with:
@@ -160,10 +160,10 @@ jobs:
          sudo mv stoml /usr/local/bin/
          cargo install pg-trunk
       - name: trunk build
-        working-directory: ./
+        working-directory: ./extension
         run: ~/.cargo/bin/trunk build --pg-version ${{ matrix.pg-version }}
       - name: trunk publish
-        working-directory: ./
+        working-directory: ./extension
         env:
           TRUNK_API_TOKEN: ${{ secrets.TRUNK_AUTH_TOKEN }}
         run: ~/.cargo/bin/trunk publish
diff --git a/.github/workflows/extension_upgrade.yml b/.github/workflows/extension_upgrade.yml
index b5a2ff4..5f420b8 100644
--- a/.github/workflows/extension_upgrade.yml
+++ b/.github/workflows/extension_upgrade.yml
@@ -3,7 +3,7 @@ name: Extension Upgrade
 defaults:
   run:
     shell: bash
-    working-directory: ./
+    working-directory: ./extension
 
 on:
   pull_request:
@@ -46,17 +46,17 @@ jobs:
         run: echo "CI_BRANCH=$(git name-rev --name-only HEAD)" >> $GITHUB_OUTPUT
       - uses: ./.github/actions/pgx-init
         with:
-          working-directory: ./
+          working-directory: ./extension
       - name: Install sys dependencies
         run: |
           sudo apt-get update && sudo apt-get install -y postgresql-server-dev-14
           make setup
-      - name: Test previous version (main))
-        run: |
-          git fetch --tags
-          git checkout main
-          echo "\q" | make run
-          cargo test -- --ignored --test-threads=1
+      # - name: Test previous version (main))
+      #   run: |
+      #     git fetch --tags
+      #     git checkout main
+      #     echo "\q" | make run
+      #     cargo test -- --ignored --test-threads=1
       - name: Test branch's version
         env:
           CI_BRANCH: ${{ steps.current-version.outputs.CI_BRANCH }}
diff --git a/.github/workflows/pgxn-release.yml b/.github/workflows/pgxn-release.yml
index fc41114..5af8fe6 100644
--- a/.github/workflows/pgxn-release.yml
+++ b/.github/workflows/pgxn-release.yml
@@ -12,9 +12,11 @@ jobs:
     - name: Check out the repo
       uses: actions/checkout@v4
     - name: Bundle the Release
+      working-directory: ./extension
       env: { GIT_BUNDLE_OPTS: --add-file META.json }
       run: make META.json && pgxn-bundle
     - name: Release on PGXN
+      working-directory: ./extension
       env:
         PGXN_USERNAME: ${{ secrets.PGXN_USERNAME }}
         PGXN_PASSWORD: ${{ secrets.PGXN_PASSWORD }}
diff --git a/Cargo.lock b/Cargo.lock
deleted file mode 100644
index a5c590b..0000000
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diff --git a/core/.gitignore b/core/.gitignore
new file mode 100644
index 0000000..9f97022
--- /dev/null
+++ b/core/.gitignore
@@ -0,0 +1 @@
+target/
\ No newline at end of file
diff --git a/core/Cargo.toml b/core/Cargo.toml
new file mode 100644
index 0000000..aed21cf
--- /dev/null
+++ b/core/Cargo.toml
@@ -0,0 +1,34 @@
+[package]
+name = "vectorize-core"
+version = "0.1.0"
+edition = "2021"
+publish = false
+
+[lib]
+crate-type = ["lib"]
+
+[[bin]]
+name = "vectorize-worker"
+path = "src/bin/worker.rs"
+
+
+[dependencies]
+anyhow = "1.0.81"
+chrono = {version = "0.4.26", features = ["serde"] }
+env_logger = "0.11.3"
+lazy_static = "1.4.0"
+log = "0.4.21"
+pgmq = "0.26.1"
+regex = "1.9.2"
+reqwest = {version = "0.11.18", features = ["json"] }
+serde = { version = "1.0.173", features = ["derive"] }
+serde_json = "1.0.103"
+sqlx = { version = "0.7.3", features = [
+    "runtime-tokio-native-tls",
+    "postgres",
+    "chrono",
+    "json"
+] }
+thiserror = "1.0.44"
+tiktoken-rs = "0.5.7"
+tokio = {version = "1.29.1", features = ["rt-multi-thread"] }
diff --git a/core/Makefile b/core/Makefile
new file mode 100644
index 0000000..2db9272
--- /dev/null
+++ b/core/Makefile
@@ -0,0 +1,10 @@
+SQLX_OFFLINE:=true
+DATABASE_URL:=postgres://${USER}:${USER}@localhost:28815/postgres
+RUST_LOG:=debug
+
+
+sqlx-cache:
+	cargo sqlx prepare
+
+run-worker:
+	cargo run --bin vectorize-worker
\ No newline at end of file
diff --git a/core/src/bin/worker.rs b/core/src/bin/worker.rs
new file mode 100644
index 0000000..89fa55b
--- /dev/null
+++ b/core/src/bin/worker.rs
@@ -0,0 +1,41 @@
+use log::{error, info};
+
+use vectorize_core::worker::base::{poll_job, Config};
+
+#[tokio::main]
+async fn main() {
+    env_logger::init();
+    info!("starting pg-vectorize remote-worker");
+
+    let conn = sqlx::postgres::PgPoolOptions::new()
+        .max_connections(5)
+        .connect("postgres://postgres:password@localhost:28815/postgres")
+        .await
+        .unwrap();
+    let queue = pgmq::PGMQueueExt::new_with_pool(conn.clone())
+        .await
+        .unwrap();
+
+    let cfg = Config::from_env();
+
+    loop {
+        match poll_job(&conn, &queue, &cfg).await {
+            Ok(Some(_)) => {
+                // continue processing
+            }
+            Ok(None) => {
+                // no messages, small wait
+                info!(
+                    "No messages in queue, waiting for {} seconds",
+                    cfg.poll_interval
+                );
+                tokio::time::sleep(tokio::time::Duration::from_secs(cfg.poll_interval)).await;
+            }
+            Err(e) => {
+                // error, long wait
+                error!("Error processing job: {:?}", e);
+                tokio::time::sleep(tokio::time::Duration::from_secs(cfg.poll_interval)).await;
+            }
+        }
+    }
+}
diff --git a/core/src/lib.rs b/core/src/lib.rs
new file mode 100644
index 0000000..b808094
--- /dev/null
+++ b/core/src/lib.rs
@@ -0,0 +1,3 @@
+pub mod transformers;
+pub mod types;
+pub mod worker;
diff --git a/src/transformers/generic.rs b/core/src/transformers/generic.rs
similarity index 83%
rename from src/transformers/generic.rs
rename to core/src/transformers/generic.rs
index 3175b7c..159d940 100644
--- a/src/transformers/generic.rs
+++ b/core/src/transformers/generic.rs
@@ -1,24 +1,22 @@
 use anyhow::{Context, Result};
 use lazy_static::lazy_static;
 use regex::Regex;
+use std::collections::HashSet;
+use std::env;
 
 use crate::{
-    executor::VectorizeMeta,
-    guc,
     transformers::types::{EmbeddingPayload, EmbeddingRequest, Inputs},
     types,
 };
 
-use super::openai::trim_inputs;
+use crate::transformers::openai::trim_inputs;
 
 lazy_static! {
     static ref REGEX: Regex = Regex::new(r"\$\{([^}]+)\}").expect("Invalid regex");
 }
-use std::collections::HashSet;
-use std::env;
 
 // finds all placeholders in a string
-fn find_placeholders(var: &str) -> Option<Vec<String>> {
+pub fn find_placeholders(var: &str) -> Option<Vec<String>> {
     let placeholders: HashSet<String> = REGEX
         .captures_iter(var)
         .filter_map(|cap| cap.get(1))
@@ -41,22 +39,10 @@ pub fn interpolate(base_str: &str, env_vars: Vec<String>) -> Result<String> {
     Ok(interpolated_str)
 }
 
-pub fn get_generic_svc_url() -> Result<String> {
-    if let Some(url) = guc::get_guc(guc::VectorizeGuc::EmbeddingServiceUrl) {
-        if let Some(phs) = find_placeholders(&url) {
-            let interpolated = interpolate(&url, phs)?;
-            Ok(interpolated)
-        } else {
-            Ok(url)
-        }
-    } else {
-        Err(anyhow::anyhow!("vectorize.embedding_service_url not set"))
-    }
-}
-
 pub fn prepare_generic_embedding_request(
-    job_meta: VectorizeMeta,
+    job_meta: types::VectorizeMeta,
     inputs: &[Inputs],
+    url: String,
 ) -> Result<EmbeddingRequest> {
     let text_inputs = trim_inputs(inputs);
     let payload = EmbeddingPayload {
@@ -66,10 +52,8 @@ pub fn prepare_generic_embedding_request(
 
     let job_params: types::JobParams = serde_json::from_value(job_meta.params)?;
 
-    let svc_host = get_generic_svc_url().context("failed to get embedding service url from GUC")?;
-
     Ok(EmbeddingRequest {
-        url: svc_host,
+        url,
         payload,
         api_key: job_params.api_key,
     })
diff --git a/core/src/transformers/http_handler.rs b/core/src/transformers/http_handler.rs
new file mode 100644
index 0000000..48a8d00
--- /dev/null
+++ b/core/src/transformers/http_handler.rs
@@ -0,0 +1,57 @@
+use anyhow::Result;
+
+use crate::transformers::types::{
+    EmbeddingPayload, EmbeddingRequest, EmbeddingResponse, Inputs, PairedEmbeddings,
+};
+pub async fn handle_response<T: for<'de> serde::Deserialize<'de>>(
+    resp: reqwest::Response,
+    method: &'static str,
+) -> Result<T> {
+    if !resp.status().is_success() {
+        let errmsg = format!(
+            "Failed to call method '{}', received response with status code:{} and body: {}",
+            method,
+            resp.status(),
+            resp.text().await?
+        );
+        return Err(anyhow::anyhow!(errmsg));
+    }
+    let value = resp.json::<T>().await?;
+    Ok(value)
+}
+
+// handle an OpenAI compatible embedding transform request
+pub async fn openai_embedding_request(
+    request: EmbeddingRequest,
+    timeout: i32,
+) -> Result<Vec<Vec<f64>>> {
+    let client = reqwest::Client::new();
+    let mut req = client
+        .post(request.url)
+        .timeout(std::time::Duration::from_secs(timeout as u64))
+        .json::<EmbeddingPayload>(&request.payload)
+        .header("Content-Type", "application/json");
+    if let Some(key) = request.api_key {
+        req = req.header("Authorization", format!("Bearer {}", key));
+    }
+    let resp = req.send().await?;
+    let embedding_resp = handle_response::<EmbeddingResponse>(resp, "embeddings").await?;
+    let embeddings = embedding_resp
+        .data
+        .iter()
+        .map(|d| d.embedding.clone())
+        .collect();
+    Ok(embeddings)
+}
+
+// merges the vec of inputs with the embedding responses
+pub fn merge_input_output(inputs: Vec<Inputs>, values: Vec<Vec<f64>>) -> Vec<PairedEmbeddings> {
+    inputs
+        .into_iter()
+        .zip(values)
+        .map(|(input, value)| PairedEmbeddings {
+            primary_key: input.record_id,
+            embeddings: value,
+        })
+        .collect()
+}
diff --git a/core/src/transformers/mod.rs b/core/src/transformers/mod.rs
new file mode 100644
index 0000000..b80720a
--- /dev/null
+++ b/core/src/transformers/mod.rs
@@ -0,0 +1,4 @@
+pub mod generic;
+pub mod http_handler;
+pub mod openai;
+pub mod types;
diff --git a/src/transformers/openai.rs b/core/src/transformers/openai.rs
similarity index 70%
rename from src/transformers/openai.rs
rename to core/src/transformers/openai.rs
index 83b59a3..4a41c30 100644
--- a/src/transformers/openai.rs
+++ b/core/src/transformers/openai.rs
@@ -1,16 +1,7 @@
-use pgrx::prelude::*;
-
 use anyhow::Result;
 
-use crate::{
-    executor::VectorizeMeta,
-    guc::{EMBEDDING_REQ_TIMEOUT_SEC, OPENAI_KEY},
-    transformers::{
-        http_handler::handle_response,
-        types::{EmbeddingPayload, EmbeddingRequest, Inputs},
-    },
-    types::JobParams,
-};
+use crate::transformers::types::{EmbeddingPayload, EmbeddingRequest, Inputs};
+use crate::types::{JobParams, VectorizeMeta};
 
 // max token length is 8192
 // however, depending on content of text, token count can be higher than
@@ -21,6 +12,7 @@ pub const OPENAI_EMBEDDING_MODEL: &str = "text-embedding-ada-002";
 pub fn prepare_openai_request(
     vect_meta: VectorizeMeta,
     inputs: &[Inputs],
+    api_key: Option<String>,
 ) -> Result<EmbeddingRequest> {
     let text_inputs = trim_inputs(inputs);
     let job_params: JobParams = serde_json::from_value(vect_meta.params.clone())?;
@@ -31,16 +23,12 @@ pub fn prepare_openai_request(
 
     let apikey = match job_params.api_key {
         Some(k) => k,
-        None => {
-            let key = match OPENAI_KEY.get() {
-                Some(k) => k.to_str()?.to_owned(),
-                None => {
-                    warning!("pg-vectorize: Error getting API key from GUC");
-                    return Err(anyhow::anyhow!("failed to get API key"));
-                }
-            };
-            key
-        }
+        None => match api_key {
+            Some(k) => k.to_owned(),
+            None => {
+                return Err(anyhow::anyhow!("failed to get API key"));
+            }
+        },
     };
     Ok(EmbeddingRequest {
         url: OPENAI_EMBEDDING_URL.to_owned(),
@@ -70,30 +58,6 @@ pub fn trim_inputs(inputs: &[Inputs]) -> Vec<String> {
         .collect()
 }
 
-pub fn validate_api_key(key: &str) -> Result<()> {
-    let client = reqwest::Client::new();
-    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
-    let runtime = tokio::runtime::Builder::new_current_thread()
-        .enable_io()
-        .enable_time()
-        .build()
-        .unwrap_or_else(|e| error!("failed to initialize tokio runtime: {}", e));
-    runtime.block_on(async {
-        let resp = client
-            .get("https://api.openai.com/v1/models")
-            .header("Content-Type", "application/json")
-            .header("Authorization", format!("Bearer {}", key))
-            .timeout(std::time::Duration::from_secs(timeout as u64))
-            .send()
-            .await
-            .unwrap_or_else(|e| error!("failed to make Open AI key validation call: {}", e));
-        let _ = handle_response::<serde_json::Value>(resp, "models")
-            .await
-            .unwrap_or_else(|e| error!("failed validate API key: {}", e));
-    });
-    Ok(())
-}
-
 #[cfg(test)]
 mod tests {
     use super::*;
diff --git a/src/transformers/types.rs b/core/src/transformers/types.rs
similarity index 95%
rename from src/transformers/types.rs
rename to core/src/transformers/types.rs
index 41513c1..d53b182 100644
--- a/src/transformers/types.rs
+++ b/core/src/transformers/types.rs
@@ -33,6 +33,7 @@ pub struct Inputs {
     pub token_estimate: i32, // estimated token count
 }
 
+#[derive(Clone, Debug, Deserialize, Serialize)]
 pub struct PairedEmbeddings {
     pub primary_key: String,
     pub embeddings: Vec<f64>,
diff --git a/src/types.rs b/core/src/types.rs
similarity index 73%
rename from src/types.rs
rename to core/src/types.rs
index 3cbf666..84e99dd 100644
--- a/src/types.rs
+++ b/core/src/types.rs
@@ -1,5 +1,6 @@
-use pgrx::prelude::*;
+use chrono::serde::ts_seconds_option::deserialize as from_tsopt;
 use serde::{Deserialize, Serialize};
+use sqlx::types::chrono::Utc;
 use sqlx::FromRow;
 use std::fmt::{Display, Formatter};
 use std::str::FromStr;
@@ -7,7 +8,7 @@ use std::str::FromStr;
 pub const VECTORIZE_SCHEMA: &str = "vectorize";
 
 #[allow(non_camel_case_types)]
-#[derive(Clone, Debug, Serialize, Deserialize, PostgresEnum)]
+#[derive(Clone, Debug, Serialize, Deserialize)]
 pub enum SimilarityAlg {
     pgv_cosine_similarity,
 }
@@ -40,7 +41,7 @@ impl From<String> for SimilarityAlg {
     }
 }
 
-#[derive(Clone, Debug, Serialize, Deserialize, PostgresEnum)]
+#[derive(Clone, Debug, Serialize, Deserialize)]
 pub enum JobType {
     Columns,
     // row,
@@ -76,7 +77,7 @@ impl Display for JobType {
 }
 
 #[allow(non_camel_case_types)]
-#[derive(Clone, Debug, Default, Serialize, Deserialize, PostgresEnum, PartialEq, Eq)]
+#[derive(Clone, Debug, Default, Serialize, Deserialize, PartialEq, Eq)]
 pub enum TableMethod {
     // append a new column to the existing table
     append,
@@ -103,3 +104,25 @@ pub struct JobParams {
 fn default_schedule() -> String {
     "realtime".to_string()
 }
+
+// schema for all messages that hit pgmq
+#[derive(Clone, Deserialize, Debug, Serialize)]
+pub struct JobMessage {
+    pub job_name: String,
+    pub job_meta: VectorizeMeta,
+    pub inputs: Vec<crate::transformers::types::Inputs>,
+}
+
+// schema for every job
+// also schema for the vectorize.vectorize_meta table
+#[derive(Clone, Debug, Deserialize, FromRow, Serialize)]
+pub struct VectorizeMeta {
+    pub job_id: i64,
+    pub name: String,
+    pub job_type: JobType,
+    pub transformer: String,
+    pub search_alg: SimilarityAlg,
+    pub params: serde_json::Value,
+    #[serde(deserialize_with = "from_tsopt")]
+    pub last_completion: Option<chrono::DateTime<Utc>>,
+}
diff --git a/core/src/worker/base.rs b/core/src/worker/base.rs
new file mode 100644
index 0000000..d1ccee7
--- /dev/null
+++ b/core/src/worker/base.rs
@@ -0,0 +1,132 @@
+use crate::transformers::{generic, http_handler, openai};
+use crate::types::{JobMessage, JobParams};
+use crate::worker::ops;
+use anyhow::Result;
+use log::{error, info};
+use pgmq::{Message, PGMQueueExt};
+use sqlx::{Pool, Postgres};
+use std::env;
+
+pub async fn poll_job(
+    conn: &Pool<Postgres>,
+    queue: &PGMQueueExt,
+    config: &Config,
+) -> Result<Option<()>> {
+    let msg: Message<JobMessage> = match queue.read::<JobMessage>(&config.queue_name, 1_i32).await {
+        Ok(Some(msg)) => msg,
+        Ok(None) => {
+            return Ok(None);
+        }
+        Err(e) => {
+            return Err(anyhow::anyhow!("failed reading message: {}", e));
+        }
+    };
+
+    let read_ct: i32 = msg.read_ct;
+    let msg_id: i64 = msg.msg_id;
+    if read_ct <= config.max_retries {
+        execute_job(conn, msg, config).await?;
+    } else {
+        error!(
+            "message exceeds max retry of {}, archiving msg_id: {}",
+            config.max_retries, msg_id
+        );
+    }
+
+    queue.archive(&config.queue_name, msg_id).await?;
+
+    Ok(Some(()))
+}
+
+pub struct Config {
+    pub database_url: String,
+    pub queue_name: String,
+    pub embedding_svc_url: String,
+    pub openai_api_key: Option<String>,
+    pub embedding_request_timeout: i32,
+    pub poll_interval: u64,
+    pub poll_interval_error: u64,
+    pub max_retries: i32,
+}
+
+impl Config {
+    pub fn from_env() -> Config {
+        Config {
+            database_url: from_env_default(
+                "DATABASE_URL",
+                "postgres://postgres:postgres@localhost:5432/postgres",
+            ),
+            queue_name: from_env_default("VECTORIZE_QUEUE", "vectorize_jobs"),
+            embedding_svc_url: from_env_default(
+                "EMBEDDING_SVC_URL",
+                "http://localhost:3000/v1/embeddings",
+            ),
+            openai_api_key: env::var("OPENAI_API_KEY").ok(),
+            embedding_request_timeout: from_env_default("EMBEDDING_REQUEST_TIMEOUT", "6")
+                .parse()
+                .unwrap(),
+            // time to wait between polling for job when there are no messages in queue
+            poll_interval: from_env_default("POLL_INTERVAL", "2").parse().unwrap(),
+            // time to wait between polling for job when there has been an error in processing
+            poll_interval_error: from_env_default("POLL_INTERVAL_ERROR", "10")
+                .parse()
+                .unwrap(),
+            max_retries: from_env_default("MAX_RETRIES", "2").parse().unwrap(),
+        }
+    }
+}
+
+/// source a variable from environment - use default if not exists
+fn from_env_default(key: &str, default: &str) -> String {
+    env::var(key).unwrap_or_else(|_| default.to_owned())
+}
+
+/// processes a single job from the queue
+async fn execute_job(
+    dbclient: &Pool<Postgres>,
+    msg: Message<JobMessage>,
+    cfg: &Config,
+) -> Result<()> {
+    let job_meta = msg.message.job_meta;
+    let job_params: JobParams = serde_json::from_value(job_meta.params.clone())?;
+
+    let embedding_request = match job_meta.transformer.as_ref() {
+        "text-embedding-ada-002" => openai::prepare_openai_request(
+            job_meta.clone(),
+            &msg.message.inputs,
+            cfg.openai_api_key.clone(),
+        )?,
+        _ => generic::prepare_generic_embedding_request(
+            job_meta.clone(),
+            &msg.message.inputs,
+            cfg.embedding_svc_url.clone(),
+        )?,
+    };
+    info!(
+        "pg-vectorize: embeddings request length: {}",
+        embedding_request.payload.input.len()
+    );
+    let embeddings =
+        http_handler::openai_embedding_request(embedding_request, cfg.embedding_request_timeout)
+            .await?;
+    let paired_embeddings = http_handler::merge_input_output(msg.message.inputs, embeddings);
+    match job_params.clone().table_method {
+        crate::types::TableMethod::append => {
+            ops::update_embeddings(
+                dbclient,
+                &job_params.schema,
+                &job_params.table,
+                &job_meta.clone().name,
+                &job_params.primary_key,
+                &job_params.pkey_type,
+                paired_embeddings,
+            )
+            .await?;
+        }
+        crate::types::TableMethod::join => {
+            ops::upsert_embedding_table(dbclient, &job_meta.name, &job_params, paired_embeddings)
+                .await?
+        }
+    }
+    Ok(())
+}
diff --git a/core/src/worker/mod.rs b/core/src/worker/mod.rs
new file mode 100644
index 0000000..17dc461
--- /dev/null
+++ b/core/src/worker/mod.rs
@@ -0,0 +1,2 @@
+pub mod base;
+pub mod ops;
diff --git a/core/src/worker/ops.rs b/core/src/worker/ops.rs
new file mode 100644
index 0000000..e848304
--- /dev/null
+++ b/core/src/worker/ops.rs
@@ -0,0 +1,184 @@
+use crate::transformers::types::PairedEmbeddings;
+use crate::types;
+use anyhow::Result;
+use serde_json::to_string;
+use sqlx::{Pool, Postgres};
+use std::fmt::Write;
+
+pub async fn upsert_embedding_table(
+    conn: &Pool<Postgres>,
+    project: &str,
+    job_params: &types::JobParams,
+    embeddings: Vec<PairedEmbeddings>,
+) -> Result<()> {
+    let (query, bindings) = build_upsert_query(project, job_params, embeddings);
+    let mut q = sqlx::query(&query);
+    for (record_id, embeddings) in bindings {
+        q = q.bind(record_id).bind(embeddings);
+    }
+    match q.execute(conn).await {
+        Ok(_) => Ok(()),
+        Err(e) => Err(anyhow::anyhow!("failed to execute query: {}", e)),
+    }
+}
+
+// returns query and bindings
+// only compatible with pg-vector data types
+fn build_upsert_query(
+    project: &str,
+    job_params: &types::JobParams,
+    embeddings: Vec<PairedEmbeddings>,
+) -> (String, Vec<(String, String)>) {
+    let join_key = &job_params.primary_key;
+    let schema = match &job_params.table_method {
+        types::TableMethod::append => job_params.schema.clone(),
+        types::TableMethod::join => "vectorize".to_string(),
+    };
+    let mut query = format!(
+        "
+        INSERT INTO {schema}._embeddings_{project} ({join_key}, embeddings) VALUES",
+        schema = schema,
+        join_key = join_key,
+    );
+    let mut bindings: Vec<(String, String)> = Vec::new();
+
+    for (index, pair) in embeddings.into_iter().enumerate() {
+        if index > 0 {
+            query.push(',');
+        }
+        query.push_str(&format!(
+            " (${}::{}, ${}::vector)",
+            2 * index + 1,
+            job_params.pkey_type,
+            2 * index + 2
+        ));
+
+        let embedding =
+            serde_json::to_string(&pair.embeddings).expect("failed to serialize embedding");
+        bindings.push((pair.primary_key, embedding));
+    }
+    let upsert = format!(
+        " ON CONFLICT ({join_key})
+        DO UPDATE SET embeddings = EXCLUDED.embeddings, updated_at = NOW();",
+        join_key = join_key
+    );
+    query.push_str(&upsert);
+    (query, bindings)
+}
+
+pub async fn update_embeddings(
+    pool: &Pool<Postgres>,
+    schema: &str,
+    table: &str,
+    project: &str,
+    pkey: &str,
+    pkey_type: &str,
+    embeddings: Vec<PairedEmbeddings>,
+) -> anyhow::Result<()> {
+    if embeddings.len() > 10 {
+        bulk_update_embeddings(pool, schema, table, project, pkey, pkey_type, embeddings).await
+    } else {
+        update_append_table(pool, embeddings, schema, table, project, pkey, pkey_type).await
+    }
+}
+
+// creates a temporary table, inserts all new values into the temporary table, and then performs an update by join
+async fn bulk_update_embeddings(
+    pool: &Pool<Postgres>,
+    schema: &str,
+    table: &str,
+    project: &str,
+    pkey: &str,
+    pkey_type: &str,
+    embeddings: Vec<PairedEmbeddings>,
+) -> anyhow::Result<()> {
+    let mut tx = pool.begin().await?;
+
+    let tmp_table = format!("temp_embeddings_{project}");
+
+    let temp_table_query = format!(
+        "CREATE TEMP TABLE IF NOT EXISTS {tmp_table} (
+            pkey {pkey_type} PRIMARY KEY,
+            embeddings vector
+        ) ON COMMIT DROP;", // note, dropping on commit
+    );
+
+    sqlx::query(&temp_table_query).execute(&mut *tx).await?;
+
+    // insert all new values into the temporary table
+    let mut insert_query = format!("INSERT INTO {tmp_table} (pkey, embeddings) VALUES ");
+    let mut params: Vec<(String, String)> = Vec::new();
+
+    for embed in &embeddings {
+        let embedding_json = to_string(&embed.embeddings).expect("failed to serialize embedding");
+        params.push((embed.primary_key.to_string(), embedding_json));
+    }
+
+    // Constructing query values part and collecting bind parameters
+    for (i, (_pkey, _embedding)) in params.iter().enumerate() {
+        if i > 0 {
+            insert_query.push_str(", ");
+        }
+        write!(
+            &mut insert_query,
+            "(${}::{}, ${}::vector)",
+            i * 2 + 1,
+            pkey_type,
+            i * 2 + 2
+        )
+        .expect("Failed to write to query string");
+    }
+
+    let mut insert_statement = sqlx::query(&insert_query);
+
+    for (pkey, embedding) in params {
+        insert_statement = insert_statement.bind(pkey).bind(embedding);
+    }
+    // insert to the temp table
+    insert_statement.execute(&mut *tx).await?;
+
+    let update_query = format!(
+        "UPDATE {schema}.{table} SET
+            {project}_embeddings = temp.embeddings,
+            {project}_updated_at = (NOW())
+        FROM {tmp_table} temp
+        WHERE {schema}.{table}.{pkey}::{pkey_type} = temp.pkey::{pkey_type};"
+    );
+
+    sqlx::query(&update_query).execute(&mut *tx).await?;
+    tx.commit().await?;
+
+    Ok(())
+}
+
+async fn update_append_table(
+    pool: &Pool<Postgres>,
+    embeddings: Vec<PairedEmbeddings>,
+    schema: &str,
+    table: &str,
+    project: &str,
+    pkey: &str,
+    pkey_type: &str,
+) -> anyhow::Result<()> {
+    for embed in embeddings {
+        // Serialize the Vec<f64> to a JSON string
+        let embedding = to_string(&embed.embeddings).expect("failed to serialize embedding");
+
+        let update_query = format!(
+            "
+            UPDATE {schema}.{table}
+            SET 
+                {project}_embeddings = $1::vector,
+                {project}_updated_at = (NOW())
+            WHERE {pkey} = $2::{pkey_type}
+        "
+        );
+        // Prepare and execute the update statement for this pair within the transaction
+        sqlx::query(&update_query)
+            .bind(embedding)
+            .bind(embed.primary_key)
+            .execute(pool)
+            .await?;
+    }
+    Ok(())
+}
diff --git a/extension/.gitignore b/extension/.gitignore
new file mode 100644
index 0000000..9f97022
--- /dev/null
+++ b/extension/.gitignore
@@ -0,0 +1 @@
+target/
\ No newline at end of file
diff --git a/.sqlx/query-406fb387c8a2d04c3a5362ae2da0154ff0295f078171f59b904e97fdd2933989.json b/extension/.sqlx/query-406fb387c8a2d04c3a5362ae2da0154ff0295f078171f59b904e97fdd2933989.json
similarity index 100%
rename from .sqlx/query-406fb387c8a2d04c3a5362ae2da0154ff0295f078171f59b904e97fdd2933989.json
rename to extension/.sqlx/query-406fb387c8a2d04c3a5362ae2da0154ff0295f078171f59b904e97fdd2933989.json
diff --git a/Cargo.toml b/extension/Cargo.toml
similarity index 92%
rename from Cargo.toml
rename to extension/Cargo.toml
index 4470d98..a224588 100644
--- a/Cargo.toml
+++ b/extension/Cargo.toml
@@ -17,6 +17,7 @@ pg_test = []
 [dependencies]
 anyhow = "1.0.72"
 chrono = {version = "0.4.26", features = ["serde"] }
+env_logger = "0.11.3"
 handlebars = "5.1.0"
 lazy_static = "1.4.0"
 log = "0.4.19"
@@ -38,6 +39,7 @@ thiserror = "1.0.44"
 tiktoken-rs = "0.5.7"
 tokio = {version = "1.29.1", features = ["rt-multi-thread"] }
 url = "2.4.0"
+vectorize_core = { path = "../core", package = "vectorize-core" }
 
 [dev-dependencies]
 pgrx-tests = "0.11.3"
diff --git a/META.json.in b/extension/META.json.in
similarity index 100%
rename from META.json.in
rename to extension/META.json.in
diff --git a/Makefile b/extension/Makefile
similarity index 99%
rename from Makefile
rename to extension/Makefile
index a91d8bc..4c39714 100644
--- a/Makefile
+++ b/extension/Makefile
@@ -6,6 +6,7 @@ PG_VERSION:=15
 PGRX_PG_CONFIG =$(shell cargo pgrx info pg-config pg${PG_VERSION})
 UPGRADE_FROM_VER:=0.9.0
 BRANCH:=$(git rev-parse --abbrev-ref HEAD)
+RUST_LOG:=debug
 
 .PHONY: install-pg_cron install-pg_vector install-pgmq run setup test-integration test-unit test-version test-branch test-upgrade cat-logs docs
 
diff --git a/Trunk.toml b/extension/Trunk.toml
similarity index 100%
rename from Trunk.toml
rename to extension/Trunk.toml
diff --git a/sql/example.sql b/extension/sql/example.sql
similarity index 100%
rename from sql/example.sql
rename to extension/sql/example.sql
diff --git a/sql/meta.sql b/extension/sql/meta.sql
similarity index 100%
rename from sql/meta.sql
rename to extension/sql/meta.sql
diff --git a/sql/vectorize--0.10.0--0.10.1.sql b/extension/sql/vectorize--0.10.0--0.10.1.sql
similarity index 100%
rename from sql/vectorize--0.10.0--0.10.1.sql
rename to extension/sql/vectorize--0.10.0--0.10.1.sql
diff --git a/sql/vectorize--0.10.1--0.11.0.sql b/extension/sql/vectorize--0.10.1--0.11.0.sql
similarity index 100%
rename from sql/vectorize--0.10.1--0.11.0.sql
rename to extension/sql/vectorize--0.10.1--0.11.0.sql
diff --git a/sql/vectorize--0.11.0--0.11.1.sql b/extension/sql/vectorize--0.11.0--0.11.1.sql
similarity index 100%
rename from sql/vectorize--0.11.0--0.11.1.sql
rename to extension/sql/vectorize--0.11.0--0.11.1.sql
diff --git a/sql/vectorize--0.11.1--0.12.0.sql b/extension/sql/vectorize--0.11.1--0.12.0.sql
similarity index 100%
rename from sql/vectorize--0.11.1--0.12.0.sql
rename to extension/sql/vectorize--0.11.1--0.12.0.sql
diff --git a/sql/vectorize--0.12.0--0.12.1.sql b/extension/sql/vectorize--0.12.0--0.12.1.sql
similarity index 100%
rename from sql/vectorize--0.12.0--0.12.1.sql
rename to extension/sql/vectorize--0.12.0--0.12.1.sql
diff --git a/sql/vectorize--0.2.0--0.3.0.sql b/extension/sql/vectorize--0.2.0--0.3.0.sql
similarity index 100%
rename from sql/vectorize--0.2.0--0.3.0.sql
rename to extension/sql/vectorize--0.2.0--0.3.0.sql
diff --git a/sql/vectorize--0.3.0--0.4.0.sql b/extension/sql/vectorize--0.3.0--0.4.0.sql
similarity index 100%
rename from sql/vectorize--0.3.0--0.4.0.sql
rename to extension/sql/vectorize--0.3.0--0.4.0.sql
diff --git a/sql/vectorize--0.4.0--0.5.0.sql b/extension/sql/vectorize--0.4.0--0.5.0.sql
similarity index 100%
rename from sql/vectorize--0.4.0--0.5.0.sql
rename to extension/sql/vectorize--0.4.0--0.5.0.sql
diff --git a/sql/vectorize--0.5.0--0.6.0.sql b/extension/sql/vectorize--0.5.0--0.6.0.sql
similarity index 100%
rename from sql/vectorize--0.5.0--0.6.0.sql
rename to extension/sql/vectorize--0.5.0--0.6.0.sql
diff --git a/sql/vectorize--0.6.0--0.6.1.sql b/extension/sql/vectorize--0.6.0--0.6.1.sql
similarity index 100%
rename from sql/vectorize--0.6.0--0.6.1.sql
rename to extension/sql/vectorize--0.6.0--0.6.1.sql
diff --git a/sql/vectorize--0.7.0--0.8.0.sql b/extension/sql/vectorize--0.7.0--0.8.0.sql
similarity index 100%
rename from sql/vectorize--0.7.0--0.8.0.sql
rename to extension/sql/vectorize--0.7.0--0.8.0.sql
diff --git a/sql/vectorize--0.8.0--0.8.1.sql b/extension/sql/vectorize--0.8.0--0.8.1.sql
similarity index 100%
rename from sql/vectorize--0.8.0--0.8.1.sql
rename to extension/sql/vectorize--0.8.0--0.8.1.sql
diff --git a/sql/vectorize--0.8.1--0.9.0.sql b/extension/sql/vectorize--0.8.1--0.9.0.sql
similarity index 100%
rename from sql/vectorize--0.8.1--0.9.0.sql
rename to extension/sql/vectorize--0.8.1--0.9.0.sql
diff --git a/sql/vectorize--0.9.0--0.10.0.sql b/extension/sql/vectorize--0.9.0--0.10.0.sql
similarity index 100%
rename from sql/vectorize--0.9.0--0.10.0.sql
rename to extension/sql/vectorize--0.9.0--0.10.0.sql
diff --git a/src/api.rs b/extension/src/api.rs
similarity index 96%
rename from src/api.rs
rename to extension/src/api.rs
index f205896..fa21ed2 100644
--- a/src/api.rs
+++ b/extension/src/api.rs
@@ -1,8 +1,8 @@
-use crate::chat::call_chat;
+use crate::chat::ops::call_chat;
 use crate::search::{self, init_table};
 use crate::transformers::transform;
-use crate::types;
 
+use crate::types;
 use anyhow::Result;
 use pgrx::prelude::*;
 
@@ -31,8 +31,8 @@ fn table(
         Some(serde_json::to_value(args).expect("failed to parse args")),
         Some(update_col),
         transformer,
-        search_alg,
-        table_method,
+        search_alg.into(),
+        table_method.into(),
         schedule,
     )
 }
@@ -85,8 +85,8 @@ fn init_rag(
         None,
         None,
         transformer,
-        search_alg,
-        table_method,
+        search_alg.into(),
+        table_method.into(),
         schedule,
     )
 }
diff --git a/extension/src/chat/mod.rs b/extension/src/chat/mod.rs
new file mode 100644
index 0000000..414c60d
--- /dev/null
+++ b/extension/src/chat/mod.rs
@@ -0,0 +1,2 @@
+pub mod ops;
+pub mod types;
diff --git a/src/chat.rs b/extension/src/chat/ops.rs
similarity index 94%
rename from src/chat.rs
rename to extension/src/chat/ops.rs
index a090e96..f070f33 100644
--- a/src/chat.rs
+++ b/extension/src/chat/ops.rs
@@ -1,7 +1,5 @@
-use crate::executor::VectorizeMeta;
 use crate::guc;
 use crate::search;
-use crate::types;
 use crate::util::get_vectorize_meta_spi;
 
 use anyhow::{anyhow, Result};
@@ -9,31 +7,10 @@ use handlebars::Handlebars;
 use openai_api_rs::v1::api::Client;
 use openai_api_rs::v1::chat_completion::{self, ChatCompletionRequest};
 use pgrx::prelude::*;
-use serde::Serialize;
-use tiktoken_rs::{get_bpe_from_model, model::get_context_size, CoreBPE};
-
-struct PromptTemplate {
-    pub sys_prompt: String,
-    pub user_prompt: String,
-}
-
-struct RenderedPrompt {
-    pub sys_rendered: String,
-    pub user_rendered: String,
-}
 
-#[derive(Clone, Debug, Serialize)]
-pub struct ContextualSearch {
-    pub record_id: String,
-    pub content: String,
-    pub token_ct: i32,
-}
-
-#[derive(Debug, Serialize)]
-pub struct ChatResponse {
-    pub context: Vec<ContextualSearch>,
-    pub chat_response: String,
-}
+use crate::chat::types::{ChatResponse, ContextualSearch, PromptTemplate, RenderedPrompt};
+use tiktoken_rs::{get_bpe_from_model, model::get_context_size, CoreBPE};
+use vectorize_core::types::{JobParams, VectorizeMeta};
 
 pub fn call_chat(
     agent_name: &str,
@@ -51,7 +28,7 @@ pub fn call_chat(
         error!("failed to get project metadata");
     };
 
-    let job_params = serde_json::from_value::<types::JobParams>(project_meta.params.clone())
+    let job_params = serde_json::from_value::<JobParams>(project_meta.params.clone())
         .unwrap_or_else(|e| error!("failed to deserialize job params: {}", e));
 
     // for various token count estimations
diff --git a/extension/src/chat/types.rs b/extension/src/chat/types.rs
new file mode 100644
index 0000000..81b3d00
--- /dev/null
+++ b/extension/src/chat/types.rs
@@ -0,0 +1,24 @@
+use serde::Serialize;
+
+pub struct PromptTemplate {
+    pub sys_prompt: String,
+    pub user_prompt: String,
+}
+
+pub struct RenderedPrompt {
+    pub sys_rendered: String,
+    pub user_rendered: String,
+}
+
+#[derive(Clone, Debug, Serialize)]
+pub struct ContextualSearch {
+    pub record_id: String,
+    pub content: String,
+    pub token_ct: i32,
+}
+
+#[derive(Debug, Serialize)]
+pub struct ChatResponse {
+    pub context: Vec<ContextualSearch>,
+    pub chat_response: String,
+}
diff --git a/src/errors.rs b/extension/src/errors.rs
similarity index 100%
rename from src/errors.rs
rename to extension/src/errors.rs
diff --git a/src/executor.rs b/extension/src/executor.rs
similarity index 87%
rename from src/executor.rs
rename to extension/src/executor.rs
index e6ff80b..5bbc561 100644
--- a/src/executor.rs
+++ b/extension/src/executor.rs
@@ -4,31 +4,15 @@ use crate::errors::DatabaseError;
 use crate::guc::BATCH_SIZE;
 use crate::init::VECTORIZE_QUEUE;
 use crate::query::check_input;
-use crate::transformers::types::Inputs;
-use crate::types;
 use crate::util::get_pg_conn;
-use chrono::serde::ts_seconds_option::deserialize as from_tsopt;
 use chrono::TimeZone;
-use serde::{Deserialize, Serialize};
 use sqlx::error::Error;
 use sqlx::postgres::PgRow;
 use sqlx::types::chrono::Utc;
-use sqlx::{FromRow, Pool, Postgres, Row};
+use sqlx::{Pool, Postgres, Row};
 use tiktoken_rs::cl100k_base;
-
-// schema for every job
-// also schema for the vectorize.vectorize_meta table
-#[derive(Clone, Debug, Deserialize, FromRow, Serialize)]
-pub struct VectorizeMeta {
-    pub job_id: i64,
-    pub name: String,
-    pub job_type: types::JobType,
-    pub transformer: String,
-    pub search_alg: types::SimilarityAlg,
-    pub params: serde_json::Value,
-    #[serde(deserialize_with = "from_tsopt")]
-    pub last_completion: Option<chrono::DateTime<Utc>>,
-}
+use vectorize_core::transformers::types::Inputs;
+use vectorize_core::types::{JobMessage, JobParams, TableMethod, VectorizeMeta};
 
 // creates batches based on total token count
 // batch_size is the max token count per batch
@@ -55,14 +39,6 @@ pub fn create_batches(data: Vec<Inputs>, batch_size: i32) -> Vec<Vec<Inputs>> {
     groups
 }
 
-// schema for all messages that hit pgmq
-#[derive(Clone, Deserialize, Debug, Serialize)]
-pub struct JobMessage {
-    pub job_name: String,
-    pub job_meta: VectorizeMeta,
-    pub inputs: Vec<Inputs>,
-}
-
 // called by pg_cron on schedule
 // identifiers new inputs and enqueues them
 #[pg_extern]
@@ -87,7 +63,7 @@ fn job_execute(job_name: String) {
         let meta = get_vectorize_meta(&job_name, &conn)
             .await
             .unwrap_or_else(|e| error!("failed to get job metadata: {}", e));
-        let job_params = serde_json::from_value::<types::JobParams>(meta.params.clone())
+        let job_params = serde_json::from_value::<JobParams>(meta.params.clone())
             .unwrap_or_else(|e| error!("failed to deserialize job params: {}", e));
         let _last_completion = match meta.last_completion {
             Some(t) => t,
@@ -146,7 +122,7 @@ pub async fn get_vectorize_meta(
     Ok(row)
 }
 
-pub fn new_rows_query_join(job_name: &str, job_params: &types::JobParams) -> String {
+pub fn new_rows_query_join(job_name: &str, job_params: &JobParams) -> String {
     let cols = &job_params
         .columns
         .iter()
@@ -189,7 +165,7 @@ pub fn new_rows_query_join(job_name: &str, job_params: &types::JobParams) -> Str
     }
 }
 
-pub fn new_rows_query(job_name: &str, job_params: &types::JobParams) -> String {
+pub fn new_rows_query(job_name: &str, job_params: &JobParams) -> String {
     let cols = collapse_to_csv(&job_params.columns);
 
     // query source and return any new rows that need transformation
@@ -231,11 +207,11 @@ pub fn new_rows_query(job_name: &str, job_params: &types::JobParams) -> String {
 pub async fn get_new_updates(
     pool: &Pool<Postgres>,
     job_name: &str,
-    job_params: types::JobParams,
+    job_params: JobParams,
 ) -> Result<Option<Vec<Inputs>>, DatabaseError> {
     let query = match job_params.table_method {
-        types::TableMethod::append => new_rows_query(job_name, &job_params),
-        types::TableMethod::join => new_rows_query_join(job_name, &job_params),
+        TableMethod::append => new_rows_query(job_name, &job_params),
+        TableMethod::join => new_rows_query_join(job_name, &job_params),
     };
     let rows: Result<Vec<PgRow>, Error> = sqlx::query(&query).fetch_all(pool).await;
     match rows {
diff --git a/src/guc.rs b/extension/src/guc.rs
similarity index 100%
rename from src/guc.rs
rename to extension/src/guc.rs
diff --git a/src/init.rs b/extension/src/init.rs
similarity index 95%
rename from src/init.rs
rename to extension/src/init.rs
index 9e223fc..26a1579 100644
--- a/src/init.rs
+++ b/extension/src/init.rs
@@ -1,11 +1,13 @@
 use crate::{
     query::check_input,
-    transformers::{http_handler::sync_get_model_info, types::TransformerMetadata},
-    types::{self, TableMethod},
+    transformers::http_handler::sync_get_model_info,
+    types::{self},
 };
 use pgrx::prelude::*;
 
 use anyhow::{Context, Result};
+use vectorize_core::transformers::types::TransformerMetadata;
+use vectorize_core::types::{JobParams, TableMethod};
 
 pub static VECTORIZE_QUEUE: &str = "vectorize_jobs";
 
@@ -64,7 +66,7 @@ pub fn init_job_query() -> String {
 }
 
 /// creates a project view over a source table and the embeddings table
-fn create_project_view(job_name: &str, job_params: &types::JobParams) -> String {
+fn create_project_view(job_name: &str, job_params: &JobParams) -> String {
     format!(
         "CREATE OR REPLACE VIEW vectorize.{job_name} as 
         SELECT t0.*, t1.embeddings, t1.updated_at as embeddings_updated_at
@@ -82,7 +84,7 @@ fn create_project_view(job_name: &str, job_params: &types::JobParams) -> String
 pub fn init_embedding_table_query(
     job_name: &str,
     transformer: &str,
-    job_params: &types::JobParams,
+    job_params: &JobParams,
 ) -> Vec<String> {
     check_input(job_name).expect("invalid job name");
     let schema = &job_params.schema;
diff --git a/src/job.rs b/extension/src/job.rs
similarity index 94%
rename from src/job.rs
rename to extension/src/job.rs
index ca2dc1e..08ff6a4 100644
--- a/src/job.rs
+++ b/extension/src/job.rs
@@ -1,16 +1,16 @@
 use anyhow::Result;
 
-use crate::executor::{
-    create_batches, new_rows_query, new_rows_query_join, JobMessage, VectorizeMeta,
-};
+use crate::executor::{create_batches, new_rows_query, new_rows_query_join};
 use crate::guc::BATCH_SIZE;
 use crate::init::VECTORIZE_QUEUE;
-use crate::transformers::types::Inputs;
-use crate::types::{self, JobParams, JobType};
 use crate::util;
 
 use pgrx::prelude::*;
 use tiktoken_rs::cl100k_base;
+use vectorize_core::transformers::types::Inputs;
+use vectorize_core::types::{
+    JobMessage, JobParams, JobType, SimilarityAlg, TableMethod, VectorizeMeta,
+};
 
 /// called by the trigger function when a table is updated
 /// handles enqueueing the embedding transform jobs
@@ -118,12 +118,12 @@ pub fn initalize_table_job(
     job_params: &JobParams,
     job_type: &JobType,
     transformer: &str,
-    search_alg: types::SimilarityAlg,
+    search_alg: SimilarityAlg,
 ) -> Result<()> {
     // start with initial batch load
     let rows_need_update_query: String = match job_params.table_method {
-        types::TableMethod::append => new_rows_query(job_name, job_params),
-        types::TableMethod::join => new_rows_query_join(job_name, job_params),
+        TableMethod::append => new_rows_query(job_name, job_params),
+        TableMethod::join => new_rows_query_join(job_name, job_params),
     };
     let mut inputs: Vec<Inputs> = Vec::new();
     let bpe = cl100k_base().unwrap();
diff --git a/src/lib.rs b/extension/src/lib.rs
similarity index 97%
rename from src/lib.rs
rename to extension/src/lib.rs
index c92ff14..1e9812a 100644
--- a/src/lib.rs
+++ b/extension/src/lib.rs
@@ -12,11 +12,12 @@ mod search;
 mod transformers;
 mod types;
 mod util;
-mod workers;
+pub mod workers;
 
 pgrx::pg_module_magic!();
 
 extension_sql_file!("../sql/meta.sql");
+
 // example dataset
 extension_sql_file!("../sql/example.sql");
 
diff --git a/src/query.rs b/extension/src/query.rs
similarity index 100%
rename from src/query.rs
rename to extension/src/query.rs
diff --git a/src/search.rs b/extension/src/search.rs
similarity index 99%
rename from src/search.rs
rename to extension/src/search.rs
index f9e1a0b..949d540 100644
--- a/src/search.rs
+++ b/extension/src/search.rs
@@ -1,16 +1,14 @@
-use crate::executor::VectorizeMeta;
 use crate::guc;
 use crate::init;
 use crate::job::{create_event_trigger, create_trigger_handler, initalize_table_job};
 use crate::transformers::http_handler::sync_get_model_info;
 use crate::transformers::openai;
 use crate::transformers::transform;
-use crate::types;
-use crate::types::TableMethod;
 use crate::util;
 
 use anyhow::Result;
 use pgrx::prelude::*;
+use vectorize_core::types::{self, TableMethod, VectorizeMeta};
 
 #[allow(clippy::too_many_arguments)]
 pub fn init_table(
diff --git a/extension/src/transformers/generic.rs b/extension/src/transformers/generic.rs
new file mode 100644
index 0000000..fa6fd02
--- /dev/null
+++ b/extension/src/transformers/generic.rs
@@ -0,0 +1,17 @@
+use anyhow::Result;
+
+use crate::guc;
+use vectorize_core::transformers::generic::{find_placeholders, interpolate};
+
+pub fn get_generic_svc_url() -> Result<String> {
+    if let Some(url) = guc::get_guc(guc::VectorizeGuc::EmbeddingServiceUrl) {
+        if let Some(phs) = find_placeholders(&url) {
+            let interpolated = interpolate(&url, phs)?;
+            Ok(interpolated)
+        } else {
+            Ok(url)
+        }
+    } else {
+        Err(anyhow::anyhow!("vectorize.embedding_service_url not set"))
+    }
+}
diff --git a/extension/src/transformers/http_handler.rs b/extension/src/transformers/http_handler.rs
new file mode 100644
index 0000000..ab3dff5
--- /dev/null
+++ b/extension/src/transformers/http_handler.rs
@@ -0,0 +1,52 @@
+use super::generic::get_generic_svc_url;
+use crate::guc::EMBEDDING_REQ_TIMEOUT_SEC;
+use anyhow::Result;
+
+use pgrx::prelude::*;
+
+use vectorize_core::transformers::http_handler::handle_response;
+use vectorize_core::transformers::types::TransformerMetadata;
+
+#[pg_extern]
+pub fn mod_info(model_name: &str, api_key: default!(Option<String>, "NULL")) -> pgrx::JsonB {
+    let meta = sync_get_model_info(model_name, api_key).unwrap();
+    pgrx::JsonB(serde_json::to_value(meta).unwrap())
+}
+
+pub fn sync_get_model_info(
+    model_name: &str,
+    api_key: Option<String>,
+) -> Result<TransformerMetadata> {
+    let runtime = tokio::runtime::Builder::new_current_thread()
+        .enable_io()
+        .enable_time()
+        .build()
+        .unwrap_or_else(|e| error!("failed to initialize tokio runtime: {}", e));
+    let meta = match runtime.block_on(async { get_model_info(model_name, api_key).await }) {
+        Ok(e) => e,
+        Err(e) => {
+            error!("error getting model info: {}", e);
+        }
+    };
+    Ok(meta)
+}
+
+pub async fn get_model_info(
+    model_name: &str,
+    api_key: Option<String>,
+) -> Result<TransformerMetadata> {
+    let svc_url = get_generic_svc_url()?;
+    let info_url = svc_url.replace("/embeddings", "/info");
+    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
+    let client = reqwest::Client::new();
+    let mut req = client
+        .get(info_url)
+        .query(&[("model_name", model_name)])
+        .timeout(std::time::Duration::from_secs(timeout as u64));
+    if let Some(key) = api_key {
+        req = req.header("Authorization", format!("Bearer {}", key));
+    }
+    let resp = req.send().await?;
+    let meta_response = handle_response::<TransformerMetadata>(resp, "info").await?;
+    Ok(meta_response)
+}
diff --git a/src/transformers/mod.rs b/extension/src/transformers/mod.rs
similarity index 83%
rename from src/transformers/mod.rs
rename to extension/src/transformers/mod.rs
index 8aac466..8912abd 100644
--- a/src/transformers/mod.rs
+++ b/extension/src/transformers/mod.rs
@@ -4,12 +4,13 @@ pub mod openai;
 pub mod tembo;
 pub mod types;
 
-use crate::guc;
+use crate::guc::{self, EMBEDDING_REQ_TIMEOUT_SEC};
 use generic::get_generic_svc_url;
-use http_handler::openai_embedding_request;
-use openai::{OPENAI_EMBEDDING_MODEL, OPENAI_EMBEDDING_URL};
 use pgrx::prelude::*;
-use types::{EmbeddingPayload, EmbeddingRequest};
+
+use vectorize_core::transformers::http_handler::openai_embedding_request;
+use vectorize_core::transformers::openai::{OPENAI_EMBEDDING_MODEL, OPENAI_EMBEDDING_URL};
+use vectorize_core::transformers::types::{EmbeddingPayload, EmbeddingRequest};
 
 pub fn transform(input: &str, transformer: &str, api_key: Option<String>) -> Vec<Vec<f64>> {
     let runtime = tokio::runtime::Builder::new_current_thread()
@@ -53,7 +54,9 @@ pub fn transform(input: &str, transformer: &str, api_key: Option<String>) -> Vec
             }
         }
     };
-    match runtime.block_on(async { openai_embedding_request(embedding_request).await }) {
+    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
+
+    match runtime.block_on(async { openai_embedding_request(embedding_request, timeout).await }) {
         Ok(e) => e,
         Err(e) => {
             error!("error getting embeddings: {}", e);
diff --git a/extension/src/transformers/openai.rs b/extension/src/transformers/openai.rs
new file mode 100644
index 0000000..026e6f1
--- /dev/null
+++ b/extension/src/transformers/openai.rs
@@ -0,0 +1,29 @@
+use anyhow::Result;
+use pgrx::prelude::*;
+use vectorize_core::transformers::http_handler::handle_response;
+
+use crate::guc::EMBEDDING_REQ_TIMEOUT_SEC;
+
+pub fn validate_api_key(key: &str) -> Result<()> {
+    let client = reqwest::Client::new();
+    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
+    let runtime = tokio::runtime::Builder::new_current_thread()
+        .enable_io()
+        .enable_time()
+        .build()
+        .unwrap_or_else(|e| error!("failed to initialize tokio runtime: {}", e));
+    runtime.block_on(async {
+        let resp = client
+            .get("https://api.openai.com/v1/models")
+            .header("Content-Type", "application/json")
+            .header("Authorization", format!("Bearer {}", key))
+            .timeout(std::time::Duration::from_secs(timeout as u64))
+            .send()
+            .await
+            .unwrap_or_else(|e| error!("failed to make Open AI key validation call: {}", e));
+        let _ = handle_response::<serde_json::Value>(resp, "models")
+            .await
+            .unwrap_or_else(|e| error!("failed validate API key: {}", e));
+    });
+    Ok(())
+}
diff --git a/src/transformers/tembo.rs b/extension/src/transformers/tembo.rs
similarity index 100%
rename from src/transformers/tembo.rs
rename to extension/src/transformers/tembo.rs
diff --git a/extension/src/transformers/types.rs b/extension/src/transformers/types.rs
new file mode 100644
index 0000000..8b13789
--- /dev/null
+++ b/extension/src/transformers/types.rs
@@ -0,0 +1 @@
+
diff --git a/extension/src/types.rs b/extension/src/types.rs
new file mode 100644
index 0000000..30fd14a
--- /dev/null
+++ b/extension/src/types.rs
@@ -0,0 +1,36 @@
+use pgrx::*;
+use vectorize_core::types::{SimilarityAlg as CoreSimilarityAlg, TableMethod as CoreTableMethod};
+
+use serde::{Deserialize, Serialize};
+pub const VECTORIZE_SCHEMA: &str = "vectorize";
+
+#[allow(non_camel_case_types)]
+#[derive(Clone, Debug, Default, Serialize, Deserialize, PostgresEnum, PartialEq, Eq)]
+pub enum TableMethod {
+    append,
+    #[default]
+    join,
+}
+
+impl From<TableMethod> for CoreTableMethod {
+    fn from(my_method: TableMethod) -> Self {
+        match my_method {
+            TableMethod::append => CoreTableMethod::append,
+            TableMethod::join => CoreTableMethod::join,
+        }
+    }
+}
+
+#[allow(non_camel_case_types)]
+#[derive(Clone, Debug, Serialize, Deserialize, PostgresEnum)]
+pub enum SimilarityAlg {
+    pgv_cosine_similarity,
+}
+
+impl From<SimilarityAlg> for CoreSimilarityAlg {
+    fn from(mysim: SimilarityAlg) -> Self {
+        match mysim {
+            SimilarityAlg::pgv_cosine_similarity => CoreSimilarityAlg::pgv_cosine_similarity,
+        }
+    }
+}
diff --git a/src/util.rs b/extension/src/util.rs
similarity index 96%
rename from src/util.rs
rename to extension/src/util.rs
index 7698773..a3c695c 100644
--- a/src/util.rs
+++ b/extension/src/util.rs
@@ -1,4 +1,5 @@
-use crate::executor::VectorizeMeta;
+use anyhow::Result;
+use log::info;
 use pgrx::spi::SpiTupleTable;
 use pgrx::*;
 use sqlx::postgres::{PgConnectOptions, PgPoolOptions};
@@ -6,9 +7,8 @@ use sqlx::{Pool, Postgres};
 use std::env;
 use url::{ParseError, Url};
 
-use anyhow::Result;
-
 use crate::guc;
+use vectorize_core::types;
 
 #[derive(Clone, Debug)]
 pub struct Config {
@@ -62,7 +62,7 @@ pub fn from_env_default(key: &str, default: &str) -> String {
     env::var(key).unwrap_or_else(|_| default.to_owned())
 }
 
-pub fn get_vectorize_meta_spi(job_name: &str) -> Result<Option<VectorizeMeta>> {
+pub fn get_vectorize_meta_spi(job_name: &str) -> Result<Option<types::VectorizeMeta>> {
     let query: &str = "
         SELECT 
             job_id,
@@ -74,7 +74,7 @@ pub fn get_vectorize_meta_spi(job_name: &str) -> Result<Option<VectorizeMeta>> {
         FROM vectorize.job
         WHERE name = $1
     ";
-    let result: Result<Option<VectorizeMeta>> = Spi::connect(|client| {
+    let result: Result<Option<types::VectorizeMeta>> = Spi::connect(|client| {
         let tup_table: SpiTupleTable = client.select(
             query,
             Some(1),
@@ -89,7 +89,7 @@ pub fn get_vectorize_meta_spi(job_name: &str) -> Result<Option<VectorizeMeta>> {
         let search_alg: String = result_row.get_by_name("search_alg").unwrap().unwrap();
         let params: pgrx::JsonB = result_row.get_by_name("params").unwrap().unwrap();
 
-        Ok(Some(VectorizeMeta {
+        Ok(Some(types::VectorizeMeta {
             job_id,
             name,
             job_type: job_type.into(),
diff --git a/extension/src/workers/mod.rs b/extension/src/workers/mod.rs
new file mode 100644
index 0000000..2e55f07
--- /dev/null
+++ b/extension/src/workers/mod.rs
@@ -0,0 +1,128 @@
+pub mod pg_bgw;
+
+use crate::guc::{EMBEDDING_REQ_TIMEOUT_SEC, OPENAI_KEY};
+use crate::transformers::generic::get_generic_svc_url;
+
+use vectorize_core::transformers::types::PairedEmbeddings;
+use vectorize_core::transformers::{generic, http_handler, openai};
+use vectorize_core::types;
+use vectorize_core::worker::ops;
+
+use anyhow::{Context, Result};
+use pgmq::{Message, PGMQueueExt};
+use pgrx::*;
+use sqlx::{Pool, Postgres};
+
+pub async fn run_worker(
+    queue: PGMQueueExt,
+    conn: &Pool<Postgres>,
+    queue_name: &str,
+) -> Result<Option<()>> {
+    let msg: Message<types::JobMessage> =
+        match queue.read::<types::JobMessage>(queue_name, 180_i32).await {
+            Ok(Some(msg)) => msg,
+            Ok(None) => {
+                info!("pg-vectorize: No messages in queue");
+                return Ok(None);
+            }
+            Err(e) => {
+                warning!("pg-vectorize: Error reading message: {e}");
+                return Err(anyhow::anyhow!("failed to read message"));
+            }
+        };
+
+    let msg_id: i64 = msg.msg_id;
+    let read_ct: i32 = msg.read_ct;
+    info!(
+        "pg-vectorize: received message for job: {:?}",
+        msg.message.job_name
+    );
+    let job_success = execute_job(conn.clone(), msg).await;
+    let delete_it = match job_success {
+        Ok(_) => {
+            info!("pg-vectorize: job success");
+            true
+        }
+        Err(e) => {
+            warning!("pg-vectorize: job failed: {:?}", e);
+            read_ct > 2
+        }
+    };
+
+    // delete message from queue
+    if delete_it {
+        match queue.archive(queue_name, msg_id).await {
+            Ok(_) => {
+                info!("pg-vectorize: deleted message: {}", msg_id);
+            }
+            Err(e) => {
+                warning!("pg-vectorize: Error deleting message: {}", e);
+            }
+        }
+    }
+    // return Some(), indicating that worker consumed some message
+    // any possibly more messages on queue
+    Ok(Some(()))
+}
+
+async fn execute_job(dbclient: Pool<Postgres>, msg: Message<types::JobMessage>) -> Result<()> {
+    let job_meta = msg.message.job_meta;
+    let job_params: types::JobParams = serde_json::from_value(job_meta.params.clone())?;
+
+    let embedding_request = match job_meta.transformer.as_ref() {
+        "text-embedding-ada-002" => {
+            info!("pg-vectorize: OpenAI transformer");
+            let apikey = match job_params.api_key.clone() {
+                Some(k) => k,
+                None => {
+                    let key = match OPENAI_KEY.get() {
+                        Some(k) => k.to_str()?.to_owned(),
+                        None => {
+                            warning!("pg-vectorize: Error getting API key from GUC");
+                            return Err(anyhow::anyhow!("failed to get API key"));
+                        }
+                    };
+                    key
+                }
+            };
+            openai::prepare_openai_request(job_meta.clone(), &msg.message.inputs, Some(apikey))
+        }
+        _ => {
+            let svc_host =
+                get_generic_svc_url().context("failed to get embedding service url from GUC")?;
+            generic::prepare_generic_embedding_request(
+                job_meta.clone(),
+                &msg.message.inputs,
+                svc_host,
+            )
+        }
+    }?;
+
+    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
+    let embeddings = http_handler::openai_embedding_request(embedding_request, timeout).await?;
+    // TODO: validate returned embeddings order is same as the input order
+    let paired_embeddings: Vec<PairedEmbeddings> =
+        http_handler::merge_input_output(msg.message.inputs, embeddings);
+
+    log!("pg-vectorize: embeddings size: {}", paired_embeddings.len());
+    // write embeddings to result table
+    match job_params.clone().table_method {
+        types::TableMethod::append => {
+            ops::update_embeddings(
+                &dbclient,
+                &job_params.schema,
+                &job_params.table,
+                &job_meta.clone().name,
+                &job_params.primary_key,
+                &job_params.pkey_type,
+                paired_embeddings,
+            )
+            .await?;
+        }
+        types::TableMethod::join => {
+            ops::upsert_embedding_table(&dbclient, &job_meta.name, &job_params, paired_embeddings)
+                .await?
+        }
+    };
+    Ok(())
+}
diff --git a/src/workers/mod.rs b/extension/src/workers/ops.rs
similarity index 61%
rename from src/workers/mod.rs
rename to extension/src/workers/ops.rs
index 97419a0..37a5d1f 100644
--- a/src/workers/mod.rs
+++ b/extension/src/workers/ops.rs
@@ -1,68 +1,12 @@
-pub mod pg_bgw;
-
-use crate::executor::JobMessage;
-use crate::transformers::{generic, http_handler, openai, types::PairedEmbeddings};
+use crate::transformers::types::PairedEmbeddings;
 use crate::types;
 
 use anyhow::Result;
-use pgmq::{Message, PGMQueueExt};
-use pgrx::*;
 use serde_json::to_string;
 use sqlx::{Pool, Postgres};
 use std::fmt::Write;
 
-pub async fn run_worker(
-    queue: PGMQueueExt,
-    conn: &Pool<Postgres>,
-    queue_name: &str,
-) -> Result<Option<()>> {
-    let msg: Message<JobMessage> = match queue.read::<JobMessage>(queue_name, 180_i32).await {
-        Ok(Some(msg)) => msg,
-        Ok(None) => {
-            info!("pg-vectorize: No messages in queue");
-            return Ok(None);
-        }
-        Err(e) => {
-            warning!("pg-vectorize: Error reading message: {e}");
-            return Err(anyhow::anyhow!("failed to read message"));
-        }
-    };
-
-    let msg_id: i64 = msg.msg_id;
-    let read_ct: i32 = msg.read_ct;
-    info!(
-        "pg-vectorize: received message for job: {:?}",
-        msg.message.job_name
-    );
-    let job_success = execute_job(conn.clone(), msg).await;
-    let delete_it = match job_success {
-        Ok(_) => {
-            info!("pg-vectorize: job success");
-            true
-        }
-        Err(e) => {
-            warning!("pg-vectorize: job failed: {:?}", e);
-            read_ct > 2
-        }
-    };
-
-    // delete message from queue
-    if delete_it {
-        match queue.archive(queue_name, msg_id).await {
-            Ok(_) => {
-                info!("pg-vectorize: deleted message: {}", msg_id);
-            }
-            Err(e) => {
-                warning!("pg-vectorize: Error deleting message: {}", e);
-            }
-        }
-    }
-    // return Some(), indicating that worker consumed some message
-    // any possibly more messages on queue
-    Ok(Some(()))
-}
-
-async fn upsert_embedding_table(
+pub async fn upsert_embedding_table(
     conn: &Pool<Postgres>,
     project: &str,
     job_params: &types::JobParams,
@@ -75,10 +19,7 @@ async fn upsert_embedding_table(
     }
     match q.execute(conn).await {
         Ok(_) => Ok(()),
-        Err(e) => {
-            log!("Error: {}", e);
-            Err(anyhow::anyhow!("failed to execute query"))
-        }
+        Err(e) => Err(anyhow::anyhow!("failed to execute query: {}", e)),
     }
 }
 
@@ -126,7 +67,7 @@ fn build_upsert_query(
     (query, bindings)
 }
 
-async fn update_embeddings(
+pub async fn update_embeddings(
     pool: &Pool<Postgres>,
     schema: &str,
     table: &str,
@@ -242,43 +183,3 @@ async fn update_append_table(
     }
     Ok(())
 }
-
-async fn execute_job(dbclient: Pool<Postgres>, msg: Message<JobMessage>) -> Result<()> {
-    let job_meta = msg.message.job_meta;
-    let job_params: types::JobParams = serde_json::from_value(job_meta.params.clone())?;
-
-    let embedding_request = match job_meta.transformer.as_ref() {
-        "text-embedding-ada-002" => {
-            info!("pg-vectorize: OpenAI transformer");
-            openai::prepare_openai_request(job_meta.clone(), &msg.message.inputs)
-        }
-        _ => generic::prepare_generic_embedding_request(job_meta.clone(), &msg.message.inputs),
-    }?;
-
-    let embeddings = http_handler::openai_embedding_request(embedding_request).await?;
-    // TODO: validate returned embeddings order is same as the input order
-    let paired_embeddings: Vec<PairedEmbeddings> =
-        http_handler::merge_input_output(msg.message.inputs, embeddings);
-
-    log!("pg-vectorize: embeddings size: {}", paired_embeddings.len());
-    // write embeddings to result table
-    match job_params.clone().table_method {
-        types::TableMethod::append => {
-            update_embeddings(
-                &dbclient,
-                &job_params.schema,
-                &job_params.table,
-                &job_meta.clone().name,
-                &job_params.primary_key,
-                &job_params.pkey_type,
-                paired_embeddings,
-            )
-            .await?;
-        }
-        types::TableMethod::join => {
-            upsert_embedding_table(&dbclient, &job_meta.name, &job_params, paired_embeddings)
-                .await?
-        }
-    };
-    Ok(())
-}
diff --git a/src/workers/pg_bgw.rs b/extension/src/workers/pg_bgw.rs
similarity index 100%
rename from src/workers/pg_bgw.rs
rename to extension/src/workers/pg_bgw.rs
diff --git a/tests/integration_tests.rs b/extension/tests/integration_tests.rs
similarity index 100%
rename from tests/integration_tests.rs
rename to extension/tests/integration_tests.rs
diff --git a/tests/util.rs b/extension/tests/util.rs
similarity index 100%
rename from tests/util.rs
rename to extension/tests/util.rs
diff --git a/vectorize.control b/extension/vectorize.control
similarity index 100%
rename from vectorize.control
rename to extension/vectorize.control
diff --git a/src/transformers/http_handler.rs b/src/transformers/http_handler.rs
deleted file mode 100644
index 2a90810..0000000
--- a/src/transformers/http_handler.rs
+++ /dev/null
@@ -1,109 +0,0 @@
-use super::generic::get_generic_svc_url;
-use super::types::TransformerMetadata;
-use anyhow::Result;
-
-use crate::guc::EMBEDDING_REQ_TIMEOUT_SEC;
-use crate::transformers::types::{
-    EmbeddingPayload, EmbeddingRequest, EmbeddingResponse, Inputs, PairedEmbeddings,
-};
-use pgrx::prelude::*;
-
-pub async fn handle_response<T: for<'de> serde::Deserialize<'de>>(
-    resp: reqwest::Response,
-    method: &'static str,
-) -> Result<T> {
-    if !resp.status().is_success() {
-        let errmsg = format!(
-            "Failed to call method '{}', received response with status code:{} and body: {}",
-            method,
-            resp.status(),
-            resp.text().await?
-        );
-        warning!("pg-vectorize: error handling response: {}", errmsg);
-        return Err(anyhow::anyhow!(errmsg));
-    }
-    let value = resp.json::<T>().await?;
-    Ok(value)
-}
-
-// handle an OpenAI compatible embedding transform request
-pub async fn openai_embedding_request(request: EmbeddingRequest) -> Result<Vec<Vec<f64>>> {
-    log!(
-        "pg-vectorize: embedding request size: {}",
-        request.payload.input.len()
-    );
-    let client = reqwest::Client::new();
-    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
-    let mut req = client
-        .post(request.url)
-        .timeout(std::time::Duration::from_secs(timeout as u64))
-        .json::<EmbeddingPayload>(&request.payload)
-        .header("Content-Type", "application/json");
-    if let Some(key) = request.api_key {
-        req = req.header("Authorization", format!("Bearer {}", key));
-    }
-    let resp = req.send().await?;
-    let embedding_resp = handle_response::<EmbeddingResponse>(resp, "embeddings").await?;
-    let embeddings = embedding_resp
-        .data
-        .iter()
-        .map(|d| d.embedding.clone())
-        .collect();
-    Ok(embeddings)
-}
-
-// merges the vec of inputs with the embedding responses
-pub fn merge_input_output(inputs: Vec<Inputs>, values: Vec<Vec<f64>>) -> Vec<PairedEmbeddings> {
-    inputs
-        .into_iter()
-        .zip(values)
-        .map(|(input, value)| PairedEmbeddings {
-            primary_key: input.record_id,
-            embeddings: value,
-        })
-        .collect()
-}
-
-#[pg_extern]
-pub fn mod_info(model_name: &str, api_key: default!(Option<String>, "NULL")) -> pgrx::JsonB {
-    let meta = sync_get_model_info(model_name, api_key).unwrap();
-    pgrx::JsonB(serde_json::to_value(meta).unwrap())
-}
-
-pub fn sync_get_model_info(
-    model_name: &str,
-    api_key: Option<String>,
-) -> Result<TransformerMetadata> {
-    let runtime = tokio::runtime::Builder::new_current_thread()
-        .enable_io()
-        .enable_time()
-        .build()
-        .unwrap_or_else(|e| error!("failed to initialize tokio runtime: {}", e));
-    let meta = match runtime.block_on(async { get_model_info(model_name, api_key).await }) {
-        Ok(e) => e,
-        Err(e) => {
-            error!("error getting model info: {}", e);
-        }
-    };
-    Ok(meta)
-}
-
-pub async fn get_model_info(
-    model_name: &str,
-    api_key: Option<String>,
-) -> Result<TransformerMetadata> {
-    let svc_url = get_generic_svc_url()?;
-    let info_url = svc_url.replace("/embeddings", "/info");
-    let timeout = EMBEDDING_REQ_TIMEOUT_SEC.get();
-    let client = reqwest::Client::new();
-    let mut req = client
-        .get(info_url)
-        .query(&[("model_name", model_name)])
-        .timeout(std::time::Duration::from_secs(timeout as u64));
-    if let Some(key) = api_key {
-        req = req.header("Authorization", format!("Bearer {}", key));
-    }
-    let resp = req.send().await?;
-    let meta_response = handle_response::<TransformerMetadata>(resp, "info").await?;
-    Ok(meta_response)
-}