diff --git a/meme-rater/log.jsonl b/meme-rater/log.jsonl
new file mode 100644
index 0000000..728e02b
--- /dev/null
+++ b/meme-rater/log.jsonl
@@ -0,0 +1,7041 @@
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+ "windows_aarch64_msvc 0.52.0",
+ "windows_i686_gnu 0.52.0",
+ "windows_i686_msvc 0.52.0",
+ "windows_x86_64_gnu 0.52.0",
+ "windows_x86_64_gnullvm 0.52.0",
+ "windows_x86_64_msvc 0.52.0",
+]
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+ "memchr",
+]
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+dependencies = [
+ "cfg-if",
+ "windows-sys 0.48.0",
+]
+
+[[package]]
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+checksum = "74d4d3961e53fa4c9a25a8637fc2bfaf2595b3d3ae34875568a5cf64787716be"
+dependencies = [
+ "zerocopy-derive",
+]
+
+[[package]]
+name = "zerocopy-derive"
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+checksum = "9ce1b18ccd8e73a9321186f97e46f9f04b778851177567b1975109d26a08d2a6"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.48",
+]
+
+[[package]]
+name = "zune-inflate"
+version = "0.2.54"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "73ab332fe2f6680068f3582b16a24f90ad7096d5d39b974d1c0aff0125116f02"
+dependencies = [
+ "simd-adler32",
+]
diff --git a/misc/Cargo.toml b/misc/Cargo.toml
new file mode 100644
index 0000000..ff984da
--- /dev/null
+++ b/misc/Cargo.toml
@@ -0,0 +1,29 @@
+[package]
+name = "meme-search-engine"
+version = "0.1.0"
+edition = "2021"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[dependencies]
+axum = { version = "0.5", features = ["multipart"] }
+tokio = { version = "1.0", features = ["full"] }
+anyhow = "1"
+tracing = "0.1"
+tracing-subscriber = { version="0.3", features = ["env-filter"] }
+tower-http = { version = "0.2.0", features = ["fs", "trace", "add-extension"] }
+rusty_ulid = "1"
+serde = { version = "1.0", features = ["derive"] }
+chrono = { version = "0.4", features = ["serde"] }
+rmp-serde = "1"
+futures-util = "0.3"
+regex = "1.5"
+lazy_static = "1"
+config = { version = "0.13", default-features = false, features = ["toml"] }
+faiss = { version = "0.12", features = [] }
+reqwest = "0.11"
+walkdir = "2"
+rusqlite = { version = "0.30.0", features = ["bundled"] }
+futures = "0.3"
+image = { version = "0.24", features = ["avif", "webp", "default"] }
+rayon = "1.8"
\ No newline at end of file
diff --git a/misc/clip_accursed.py b/misc/clip_accursed.py
new file mode 100644
index 0000000..9fdb907
--- /dev/null
+++ b/misc/clip_accursed.py
@@ -0,0 +1,189 @@
+import os
+import time
+import threading
+from aiohttp import web
+import aiohttp
+import asyncio
+import traceback
+import umsgpack
+import collections
+import queue
+from PIL import Image
+from prometheus_client import Counter, Histogram, REGISTRY, generate_latest
+import io
+import json
+import sys
+import torch
+from transformers import SiglipTokenizer, SiglipImageProcessor, T5TokenizerFast, SiglipTextConfig, SiglipVisionConfig
+import numpy
+
+with open(sys.argv[1], "r") as config_file:
+    CONFIG = json.load(config_file)
+
+# blatantly copypasted from colab
+# https://colab.research.google.com/github/google-research/big_vision/blob/main/big_vision/configs/proj/image_text/SigLIP_demo.ipynb
+VARIANT, RES = CONFIG["model"]
+CKPT, TXTVARIANT, EMBDIM, SEQLEN, VOCAB = {
+    ("So400m/14", 384): ("webli_en_so400m_384_58765454-fp16.safetensors", "So400m", 1152, 64, 32_000),
+}[VARIANT, RES]
+
+model_cfg = ml_collections.ConfigDict()
+model_cfg.image_model = "vit"  # TODO(lbeyer): remove later, default
+model_cfg.text_model = "proj.image_text.text_transformer"  # TODO(lbeyer): remove later, default
+model_cfg.image = dict(variant=VARIANT, pool_type="map")
+model_cfg.text = dict(variant=TXTVARIANT, vocab_size=VOCAB)
+model_cfg.out_dim = (None, EMBDIM)  # (image_out_dim, text_out_dim)
+model_cfg.bias_init = -10.0
+model_cfg.temperature_init = 10.0
+
+model = model_mod.Model(**model_cfg)
+
+init_params = None  # sanity checks are a low-interest-rate phenomenon
+model_params = model_mod.load(init_params, f"{CKPT}", model_cfg) # assume path
+
+pp_img = pp_builder.get_preprocess_fn(f"resize({RES})|value_range(-1, 1)")
+TOKENIZERS = {
+    32_000: "c4_en",
+    250_000: "mc4",
+}
+pp_txt = pp_builder.get_preprocess_fn(f'tokenize(max_len={SEQLEN}, model="{TOKENIZERS[VOCAB]}", eos="sticky", pad_value=1, inkey="text")')
+print("Model loaded")
+
+BS = CONFIG["max_batch_size"]
+MODELNAME = CONFIG["model_name"]
+
+InferenceParameters = collections.namedtuple("InferenceParameters", ["text", "images", "callback"])
+
+items_ctr = Counter("modelserver_total_items", "Items run through model server", ["model", "modality"])
+inference_time_hist = Histogram("modelserver_inftime", "Time running inference", ["model", "batch_size"])
+batch_count_ctr = Counter("modelserver_batchcount", "Inference batches run", ["model"])
+
+@jax.jit
+def run_text_model(text_batch):
+    _, features, out = model.apply({"params": model_params}, None, text_batch)
+    return features
+
+@jax.jit
+def run_image_model(image_batch):
+    features, _, out = model.apply({"params": model_params}, image_batch, None)
+    return features
+
+def round_down_to_power_of_two(x):
+    return 1<<(x.bit_length()-1)
+
+def minimize_jits(fn, batch):
+    out = numpy.zeros((batch.shape[0], EMBDIM), dtype="float16")
+    i = 0
+    while True:
+        batch_dim = batch.shape[0]
+        s = round_down_to_power_of_two(batch_dim)
+        fst = batch[:s,...]
+        out[i:(i + s), ...] = fn(fst)
+        i += s
+        batch = batch[s:, ...]
+        if batch.shape[0] == 0: break
+    return out
+
+def do_inference(params: InferenceParameters):
+    try:
+        text, images, callback = params
+        if text is not None:
+            items_ctr.labels(MODELNAME, "text").inc(text.shape[0])
+            with inference_time_hist.labels(MODELNAME + "-text", text.shape[0]).time():
+                features = run_text_model(text)
+        elif images is not None:
+            items_ctr.labels(MODELNAME, "image").inc(images.shape[0])
+            with inference_time_hist.labels(MODELNAME + "-image", images.shape[0]).time():
+                features = run_image_model(images)
+        batch_count_ctr.labels(MODELNAME).inc()
+        callback(True, numpy.asarray(features))
+    except Exception as e:
+        traceback.print_exc()
+        callback(False, str(e))
+
+iq = queue.Queue(100)
+def infer_thread():
+    while True:
+        do_inference(iq.get())
+
+pq = queue.Queue(100)
+def preprocessing_thread():
+    while True:
+        text, images, callback = pq.get()
+        try:
+            if text:
+                assert len(text) <= BS, f"max batch size is {BS}"
+                # I feel like this ought to be batchable but I can't see how to do that
+                text = numpy.array([pp_txt({"text": text})["labels"] for text in text])
+            elif images:
+                assert len(images) <= BS, f"max batch size is {BS}"
+                images = numpy.array([pp_img({"image": numpy.array(Image.open(io.BytesIO(image)).convert("RGB"))})["image"] for image in images])
+            else:
+                assert False, "images or text required"
+            iq.put(InferenceParameters(text, images, callback))
+        except Exception as e:
+            traceback.print_exc()
+            callback(False, str(e))
+
+app = web.Application(client_max_size=2**26)
+routes = web.RouteTableDef()
+
+@routes.post("/")
+async def run_inference(request):
+    loop = asyncio.get_event_loop()
+    data = umsgpack.loads(await request.read())
+    event = asyncio.Event()
+    results = None
+    def callback(*argv):
+        nonlocal results
+        results = argv
+        loop.call_soon_threadsafe(lambda: event.set())
+    pq.put_nowait(InferenceParameters(data.get("text"), data.get("images"), callback))
+    await event.wait()
+    body_data = results[1]
+    if results[0]:
+        status = 200
+        body_data = [x.astype("float16").tobytes() for x in body_data]
+    else:
+        status = 500
+        print(results[1])
+    return web.Response(body=umsgpack.dumps(body_data), status=status, content_type="application/msgpack")
+
+@routes.get("/config")
+async def config(request):
+    return web.Response(body=umsgpack.dumps({
+        "model": CONFIG["model"],
+        "batch": BS,
+        "image_size": (RES, RES),
+        "embedding_size": EMBDIM
+    }), status=200, content_type="application/msgpack")
+
+@routes.get("/")
+async def health(request):
+    return web.Response(status=204)
+
+@routes.get("/metrics")
+async def metrics(request):
+    return web.Response(body=generate_latest(REGISTRY))
+
+app.router.add_routes(routes)
+
+async def run_webserver():
+    runner = web.AppRunner(app)
+    await runner.setup()
+    site = web.TCPSite(runner, "", CONFIG["port"])
+    print("Ready")
+    await site.start()
+
+try:
+    th = threading.Thread(target=infer_thread)
+    th.start()
+    th = threading.Thread(target=preprocessing_thread)
+    th.start()
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    loop.run_until_complete(run_webserver())
+    loop.run_forever()
+except KeyboardInterrupt:
+    import sys
+    sys.exit(0)
\ No newline at end of file
diff --git a/misc/config.toml b/misc/config.toml
new file mode 100644
index 0000000..7ac2829
--- /dev/null
+++ b/misc/config.toml
@@ -0,0 +1,4 @@
+log_level = "debug"
+listen_address = "[::1]:1710"
+db_path = "./mse.sqlite3"
+images_path = "/data/public"
\ No newline at end of file
diff --git a/misc/eval.html b/misc/eval.html
new file mode 100644
index 0000000..5eb90ca
--- /dev/null
+++ b/misc/eval.html
@@ -0,0 +1,13 @@
+<!DOCTYPE html>
+<div>
+<div><img src="images/9e/t3_1c629c3.jpg" width="30%"><br><input type=checkbox data-score="1.2792096138000488"></div><div><img src="images/16/t3_1b80tkn.png" width="30%"><br><input type=checkbox data-score="1.1153279542922974"></div><div><img src="images/a2/t3_1bsqrmg.jpg" width="30%"><br><input type=checkbox data-score="0.9720794558525085"></div><div><img src="images/e7/t3_1c1yrql.jpg" width="30%"><br><input type=checkbox data-score="-0.5180545449256897"></div><div><img src="images/0f/t3_1b80fhz.png" width="30%"><br><input type=checkbox data-score="1.4547114372253418"></div><div><img src="images/76/t3_1bis1mq.jpg" width="30%"><br><input type=checkbox data-score="1.3289614915847778"></div><div><img src="images/1a/t3_1bqbba4.jpg" width="30%"><br><input type=checkbox data-score="1.8748269081115723"></div><div><img src="images/fa/t3_1c79pcf.jpg" width="30%"><br><input type=checkbox data-score="0.05465051531791687"></div><div><img src="images/e0/t3_1b9rnxe.jpg" width="30%"><br><input 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diff --git a/misc/log-1713711190.1288905.jsonl b/misc/log-1713711190.1288905.jsonl
new file mode 100644
index 0000000..fb8e7fb
--- /dev/null
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diff --git a/misc/log-1713711267.4419498.jsonl b/misc/log-1713711267.4419498.jsonl
new file mode 100644
index 0000000..f9276ef
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+{"loss": 0.47830042243003845, "step": 2137, "time": 1713711297.134634}
+{"loss": 0.5306532979011536, "step": 2138, "time": 1713711297.143615}
+{"loss": 0.5806128978729248, "step": 2139, "time": 1713711297.1525788}
diff --git a/misc/mse_accursed.py b/misc/mse_accursed.py
new file mode 100644
index 0000000..ed6a407
--- /dev/null
+++ b/misc/mse_accursed.py
@@ -0,0 +1,212 @@
+from aiohttp import web
+import aiohttp
+import asyncio
+import traceback
+import umsgpack
+from PIL import Image
+import base64
+import aiosqlite
+import faiss
+import numpy
+import os
+import aiohttp_cors
+import json
+import io
+import sys
+from concurrent.futures import ProcessPoolExecutor
+
+with open(sys.argv[1], "r") as config_file:
+    CONFIG = json.load(config_file)
+
+app = web.Application(client_max_size=32*1024**2)
+routes = web.RouteTableDef()
+
+async def clip_server(query, unpack_buffer=True):
+    async with aiohttp.ClientSession() as sess:
+        async with sess.post(CONFIG["clip_server"], data=umsgpack.dumps(query)) as res:
+            response = umsgpack.loads(await res.read())
+            if res.status == 200:
+                if unpack_buffer:
+                    response = [ numpy.frombuffer(x, dtype="float16") for x in response ]
+                return response
+            else:
+                raise Exception(response if res.headers.get("content-type") == "application/msgpack" else (await res.text()))
+
+@routes.post("/")
+async def run_query(request):
+    data = await request.json()
+    embeddings = []
+    if images := data.get("images", []):
+        embeddings.extend(await clip_server({ "images": [ base64.b64decode(x) for x, w in images ] }))
+    if text := data.get("text", []):
+        embeddings.extend(await clip_server({ "text": [ x for x, w in text ] }))
+    weights = [ w for x, w in images ] + [ w for x, w in text ]
+    embeddings = [ e * w for e, w in zip(embeddings, weights) ]
+    if not embeddings:
+        return web.json_response([])
+    return web.json_response(app["index"].search(sum(embeddings)))
+
+@routes.get("/")
+async def health_check(request):
+    return web.Response(text="OK")
+
+@routes.post("/reload_index")
+async def reload_index_route(request):
+    await request.app["index"].reload()
+    return web.json_response(True)
+
+def load_image(path, image_size):
+    im = Image.open(path)
+    im.draft("RGB", image_size)
+    buf = io.BytesIO()
+    im.resize(image_size).convert("RGB").save(buf, format="BMP")
+    return buf.getvalue(), path
+
+class Index:
+    def __init__(self, inference_server_config):
+        self.faiss_index = faiss.IndexFlatIP(inference_server_config["embedding_size"])
+        self.associated_filenames = []
+        self.inference_server_config = inference_server_config
+        self.lock = asyncio.Lock()
+
+    def search(self, query):
+        distances, indices = self.faiss_index.search(numpy.array([query]), 4000)
+        distances = distances[0]
+        indices = indices[0]
+        try:
+            indices = indices[:numpy.where(indices==-1)[0][0]]
+        except IndexError: pass
+        return [ { "score": float(distance), "file": self.associated_filenames[index] } for index, distance in zip(indices, distances) ]
+
+    async def reload(self):
+        async with self.lock:
+            with ProcessPoolExecutor(max_workers=12) as executor:
+                print("Indexing")
+                conn = await aiosqlite.connect(CONFIG["db_path"], parent_loop=asyncio.get_running_loop())
+                conn.row_factory = aiosqlite.Row
+                await conn.executescript("""
+        CREATE TABLE IF NOT EXISTS files (
+            filename TEXT PRIMARY KEY,
+            modtime REAL NOT NULL,
+            embedding_vector BLOB NOT NULL
+        );
+                """)
+                try:
+                    async with asyncio.TaskGroup() as tg:
+                        batch_sem = asyncio.Semaphore(32)
+
+                        modified = set()
+
+                        async def do_batch(batch):
+                            try:
+                                query = { "images": [ arg[2] for arg in batch ] }
+                                embeddings = await clip_server(query, False)
+                                await conn.executemany("INSERT OR REPLACE INTO files VALUES (?, ?, ?)", [
+                                    (filename, modtime, embedding) for (filename, modtime, _), embedding in zip(batch, embeddings)
+                                ])
+                                await conn.commit()
+                                for filename, _, _ in batch:
+                                    modified.add(filename)
+                                sys.stdout.write(".")
+                            finally:
+                                batch_sem.release()
+
+                        async def dispatch_batch(batch):
+                            await batch_sem.acquire()
+                            tg.create_task(do_batch(batch))
+                        
+                        files = {}
+                        for filename, modtime in await conn.execute_fetchall("SELECT filename, modtime FROM files"):
+                            files[filename] = modtime
+                        await conn.commit()
+                        batch = []
+
+                        for dirpath, _, filenames in os.walk(CONFIG["files"]):
+                            paths = []
+                            for file in filenames:
+                                path = os.path.join(dirpath, file)
+                                file = os.path.relpath(path, CONFIG["files"])
+                                st = os.stat(path)
+                                if st.st_mtime != files.get(file):
+                                    paths.append(path)
+                            for task in asyncio.as_completed([ asyncio.get_running_loop().run_in_executor(executor, load_image, path, self.inference_server_config["image_size"]) for path in paths ]):
+                                try:
+                                    b, path = await task
+                                    st = os.stat(path)
+                                    file = os.path.relpath(path, CONFIG["files"])
+                                except Exception as e:
+                                    print(file, "failed", e)
+                                    continue
+                                batch.append((file, st.st_mtime, b))
+                                if len(batch) == self.inference_server_config["batch"]:
+                                    await dispatch_batch(batch)
+                                    batch = []
+                        if batch:
+                            await dispatch_batch(batch)
+
+                    remove_indices = []
+                    for index, filename in enumerate(self.associated_filenames):
+                        if filename not in files or filename in modified:
+                            remove_indices.append(index)
+                            self.associated_filenames[index] = None
+                        if filename not in files:
+                            await conn.execute("DELETE FROM files WHERE filename = ?", (filename,))
+                            await conn.commit()
+                    # TODO concurrency
+                    # TODO understand what that comment meant
+                    if remove_indices:
+                        self.faiss_index.remove_ids(numpy.array(remove_indices))
+                        self.associated_filenames = [ x for x in self.associated_filenames if x is not None ]
+                
+                    filenames_set = set(self.associated_filenames)
+                    new_data = []
+                    new_filenames = []
+                    async with conn.execute("SELECT * FROM files") as csr:
+                        while row := await csr.fetchone():
+                            filename, modtime, embedding_vector = row
+                            if filename not in filenames_set:
+                                new_data.append(numpy.frombuffer(embedding_vector, dtype="float16"))
+                                new_filenames.append(filename)
+                    new_data = numpy.array(new_data)
+                    self.associated_filenames.extend(new_filenames)
+                    self.faiss_index.add(new_data)
+                finally:
+                    await conn.close()
+
+app.router.add_routes(routes)
+
+cors = aiohttp_cors.setup(app, defaults={
+    "*": aiohttp_cors.ResourceOptions(
+        allow_credentials=False,
+        expose_headers="*",
+        allow_headers="*",
+    )
+})
+for route in list(app.router.routes()):
+    cors.add(route)
+
+async def main():
+    while True:
+        async with aiohttp.ClientSession() as sess:
+            try:
+                async with await sess.get(CONFIG["clip_server"] + "config") as res:
+                    inference_server_config = umsgpack.unpackb(await res.read())
+                    print("Backend config:", inference_server_config)
+                    break
+            except:
+                traceback.print_exc()
+                await asyncio.sleep(1)
+    index = Index(inference_server_config)
+    app["index"] = index
+    await index.reload()
+    print("Ready")
+    runner = web.AppRunner(app)
+    await runner.setup()
+    site = web.TCPSite(runner, "", CONFIG["port"])
+    await site.start()
+
+if __name__ == "__main__":
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    loop.run_until_complete(main())
+    loop.run_forever()
\ No newline at end of file
diff --git a/misc/src/main.rs b/misc/src/main.rs
new file mode 100644
index 0000000..f69f32e
--- /dev/null
+++ b/misc/src/main.rs
@@ -0,0 +1,167 @@
+use serde::{Deserialize, Serialize};
+use tower_http::{services::ServeDir, add_extension::AddExtensionLayer, services::ServeFile};
+use axum::{extract::{Json, Extension, Multipart, Path as AxumPath}, http::{StatusCode, Request}, response::{IntoResponse}, body::Body, routing::{get, post, get_service}, Router};
+use std::sync::Arc;
+use tokio::{sync::RwLock, runtime::Handle, fs::File};
+use anyhow::Result;
+use rusqlite::Connection;
+use std::collections::HashMap;
+use futures::{stream, StreamExt};
+use std::path::Path;
+use image::{io::Reader as ImageReader, imageops};
+use tokio::task::block_in_place;
+use rayon::prelude::*;
+use std::io::Cursor;
+
+mod util;
+
+use util::CONFIG;
+
+#[derive(Serialize, Deserialize)]
+struct InferenceServerConfig {
+    model: String,
+    embedding_size: usize,
+    batch: usize,
+    image_size: usize
+}
+
+struct Index {
+    vectors: faiss::FlatIndex // we need the index to implement Send, which an arbitrary boxed one might not
+}
+
+async fn build_index() -> Result<Index> {
+    let mut conn = block_in_place(|| Connection::open(&CONFIG.db_path))?;
+    block_in_place(|| conn.execute("CREATE TABLE IF NOT EXISTS files (
+        filename TEXT PRIMARY KEY,
+        modtime REAL NOT NULL,
+        embedding_vector BLOB NOT NULL
+    )", ()))?;
+
+    let SIZE = 1024; // TODO
+    let IMAGE_SIZE = 384; // TODO
+    let BS = 32;
+
+    let mut files = HashMap::new();
+    let mut new_files: HashMap<String, (i64, Option<Vec<u8>>)> = HashMap::new();
+    let mut vectors = faiss::index_factory(SIZE, "Flat", faiss::MetricType::InnerProduct)?.into_flat()?;
+
+    block_in_place(|| -> Result<()> {
+        let mut stmt = conn.prepare_cached("SELECT filename, modtime FROM files")?;
+        let mut rows = stmt.query([])?;
+        while let Some(row) = rows.next()? {
+            let filename: String = row.get(0)?;
+            let modtime: i64 = row.get(1)?;
+            files.insert(filename, modtime);
+        }
+
+        for entry in walkdir::WalkDir::new(&CONFIG.images_path).follow_links(true) {
+            let entry = entry?;
+            if entry.file_type().is_file() {
+                let metadata = entry.metadata()?;
+                let modtime = metadata.modified()?.duration_since(std::time::UNIX_EPOCH)?.as_secs() as i64;
+                let filename = entry.path().strip_prefix(&CONFIG.images_path)?.to_string_lossy().to_string();
+                match files.get(&filename) {
+                    Some(old_modtime) if *old_modtime < modtime => new_files.insert(filename, (modtime, None)),
+                    None => new_files.insert(filename, (modtime, None)),
+                    _ => None
+                };
+            }
+        }
+
+        Ok(())
+    })?;
+
+    let (itx, mut irx) = tokio::sync::mpsc::channel(BS * 2);
+
+    let new_files_ = new_files.clone();
+    let image_reader_task = tokio::task::spawn_blocking(move || {
+        new_files_.par_iter().try_for_each(|(filename, _)| -> Result<()> {
+            let mut path = Path::new(&CONFIG.images_path).to_path_buf();
+            path.push(filename);
+            let image = ImageReader::open(path)?.with_guessed_format()?.decode()?;
+            let resized = imageops::resize(&image.into_rgb8(), IMAGE_SIZE, IMAGE_SIZE, imageops::Lanczos3);
+            let mut bytes: Vec<u8> = Vec::new();
+            resized.write_to(&mut Cursor::new(&mut bytes), image::ImageOutputFormat::Png)?;
+            itx.blocking_send((filename.to_string(), bytes))?;
+            Ok(())
+        })
+    });
+
+    let dispatch_batch = |batch| {
+
+    };
+
+    let mut batch = vec![];
+    while let Some((filename, image)) = irx.recv().await {
+        if batch.len() == BS {
+            dispatch_batch(std::mem::replace(&mut batch, vec![]));
+        }
+        batch.push((filename, image));
+    }
+    if batch.len() > 0 {
+        dispatch_batch(std::mem::replace(&mut batch, vec![]));
+    }
+
+    // TODO switch to blocking
+    {
+        let tx = conn.transaction()?;
+        {
+            let mut stmt = tx.prepare_cached("INSERT OR REPLACE INTO files VALUES (?, ?, ?)")?;
+            for (filename, (modtime, embedding)) in new_files {
+                stmt.execute((filename, modtime, embedding.unwrap()))?;
+            }
+        }
+        tx.commit()?;
+    }
+
+    Ok(Index {
+        vectors: vectors
+    })
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    if std::env::var_os("RUST_LOG").is_none() {
+        std::env::set_var("RUST_LOG", format!("meme-search-engine={}", CONFIG.log_level))
+    }
+
+    let notify = tokio::sync::Notify::new();
+
+    tokio::spawn(async move {
+        loop {
+            notify.notified().await;
+            let index = build_index().await.unwrap();
+        }
+    });
+
+    tracing_subscriber::fmt::init();
+
+    //let db = Arc::new(RwLock::new(DB::init().await?));
+
+    let app = Router::new()
+        .route("/", get(health))
+        .route("/", post(run_query));
+        //.layer(AddExtensionLayer::new(db));
+
+    let addr = CONFIG.listen_address.parse().unwrap();
+    tracing::info!("listening on {}", addr);
+    axum::Server::bind(&addr)
+        .serve(app.into_make_service())
+        .await?;
+    Ok(())
+}
+
+async fn health() -> String {
+    format!("OK")
+}
+
+#[derive(Debug, Serialize, Deserialize)]
+struct RawQuery {
+    text: Vec<String>,
+    images: Vec<String> // base64 (sorry)
+}
+
+async fn run_query(query: Json<RawQuery>) -> Json<Vec<(String, f32)>> {
+    tracing::info!("{:?}", query);
+    Json(vec![])
+}
\ No newline at end of file
diff --git a/misc/src/util.rs b/misc/src/util.rs
new file mode 100644
index 0000000..67f38d0
--- /dev/null
+++ b/misc/src/util.rs
@@ -0,0 +1,23 @@
+use anyhow::{Result, Context};
+use serde::{Serialize, Deserialize};
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct Config {
+    pub log_level: String,
+    pub listen_address: String,
+    pub images_path: String,
+    pub db_path: String,
+    pub backend_url: String
+}
+
+fn load_config() -> Result<Config> {
+    use config::{Config, File};
+    let s = Config::builder()
+        .add_source(File::with_name("./config"))
+        .build().context("loading config")?;
+    Ok(s.try_deserialize().context("parsing config")?)
+}
+
+lazy_static::lazy_static! {
+    pub static ref CONFIG: Config = load_config().unwrap();
+}
\ No newline at end of file
diff --git a/misc/top.json b/misc/top.json
new file mode 100644
index 0000000..5d78b30
--- /dev/null
+++ b/misc/top.json
@@ -0,0 +1 @@
+[[["a4/t3_1c5ev98.jpg", "63/t3_1ax0wrg.jpg"], 0.01498831994831562], [["93/t3_1c434a3.jpg", "cc/t3_19a1cew.png"], 0.014810201711952686], [["2f/t3_1c5g9rn.png", "72/t3_1bv8aw3.jpg"], 0.014680219814181328], [["ea/t3_1b9wlme.jpg", "6c/t3_1c3fat4.jpg"], 0.01410622987896204], [["47/t3_1c40zz4.jpg", "cd/t3_1b2yvxa.png"], 0.01398527342826128], [["d0/t3_19f02jw.jpg", "df/t3_1c4bi8t.jpg"], 0.01364255789667368], [["fe/t3_1alutxb.jpg", "9c/t3_1btv9yb.jpg"], 0.013389200903475285], [["3d/t3_1c61zdu.jpg", "8f/t3_1ate90b.jpg"], 0.013078474439680576], [["8b/t3_190rejb.jpg", "5c/t3_1azu3az.jpg"], 0.01302724052220583], [["c1/t3_1bunnad.png", "0e/t3_1bk5kmq.jpg"], 0.01281333900988102], [["a0/t3_1c75db1.jpg", "a5/t3_1c7nml3.png"], 0.012779810465872288], [["97/t3_1ay1hkj.jpg", "4b/t3_1aljzct.jpg"], 0.012725746259093285], [["63/t3_1bn2jfw.jpg", "d4/t3_1ac9t6f.jpg"], 0.01271815225481987], [["3d/t3_19ecy2b.jpg", "20/t3_1950tvh.jpg"], 0.012487626634538174], [["ff/t3_1bcdppd.png", "66/t3_1acg1o0.png"], 0.012418299913406372], [["4b/t3_1bzs635.jpg", "6f/t3_1bk68r4.png"], 0.012354684993624687], [["18/t3_196r9ld.jpg", "24/t3_1c6lnk9.jpg"], 0.012299091555178165], [["0b/t3_1b8261y.jpg", "99/t3_1bjyz0b.jpg"], 0.012270908802747726], [["69/t3_1c32wls.jpg", "b5/t3_1by31fq.jpg"], 0.01227054838091135], [["74/t3_1br4zdo.png", "79/t3_19c3c1a.jpg"], 0.012249837629497051], [["b5/t3_1bb0xgm.png", "b0/t3_1b848ve.png"], 0.012244375422596931], [["47/t3_18xy1cb.jpg", "10/t3_1akgt3s.jpg"], 0.012177427299320698], [["a3/t3_1amibrn.jpg", "b7/t3_1b4aoye.jpg"], 0.012112308293581009], [["6a/t3_1bz8dp2.jpg", "42/t3_1aldct9.jpg"], 0.012097960337996483], [["53/t3_1c3m1y5.jpg", "0f/t3_1bjdcmo.png"], 0.012084811925888062], [["de/t3_1blshzf.png", "63/t3_1bnxut5.jpg"], 0.011981847696006298], [["0c/t3_1btb8bd.jpg", "7b/t3_1bsrjwb.jpg"], 0.01196883711963892], [["1b/t3_1bibmsb.jpg", "14/t3_1blvslc.jpg"], 0.011945528909564018], [["48/t3_1adz5ax.jpg", "19/t3_1c2ul03.jpg"], 0.011935088783502579], [["26/t3_1c5gldf.jpg", 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\ No newline at end of file
diff --git a/misc/train_xgboost.py b/misc/train_xgboost.py
new file mode 100644
index 0000000..a320c57
--- /dev/null
+++ b/misc/train_xgboost.py
@@ -0,0 +1,19 @@
+import numpy
+import xgboost as xgb
+
+import shared
+
+trains, validations = shared.fetch_ratings()
+
+ranker = xgb.XGBRanker(
+    tree_method="hist",
+    lambdarank_num_pair_per_sample=8,
+    objective="rank:ndcg",
+    lambdarank_pair_method="topk",
+    device="cuda"
+)
+flat_samples = [ sample for trainss in trains for sample in trainss ]
+X = numpy.concatenate([ numpy.stack((meme1, meme2)) for meme1, meme2, rating in flat_samples ])
+Y = numpy.concatenate([ numpy.stack((int(rating), int(1 - rating))) for meme1, meme2, rating in flat_samples ])
+qid = numpy.concatenate([ numpy.stack((i, i)) for i in range(len(flat_samples)) ])
+ranker.fit(X, Y, qid=qid, verbose=True)
\ No newline at end of file