diff --git a/.gitignore b/.gitignore
index bf23a33..6888734 100644
--- a/.gitignore
+++ b/.gitignore
@@ -167,3 +167,4 @@ cython_debug/
#.idea/
.env
+.DS_Store
diff --git a/Makefile b/Makefile
index b986e95..129b055 100644
--- a/Makefile
+++ b/Makefile
@@ -24,18 +24,14 @@ build: ## Build wheel file using poetry
@echo "🚀 Creating wheel file"
@poetry build
-.PHONY: docs-test
-docs-test: ## Test if documentation can be built without warnings or errors
- @poetry run mkdocs build -s
-
-.PHONY: docs
-docs: ## Build and serve the documentation
- @poetry run mkdocs serve
-
.PHONY: serve
-serve: ## Serve API with uvicorn
+serve: ## Serve API with uvicorn in development mode
@poetry run uvicorn pypi_scout.api.main:app --reload
+.PHONY: frontend
+frontend: ## Serve frontend in development mode
+ @cd frontend; npm run dev
+
.PHONY: help
help:
@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-20s\033[0m %s\n", $$1, $$2}'
diff --git a/frontend/app/components/InfoBox.tsx b/frontend/app/components/InfoBox.tsx
index 88c5cd4..60b9b08 100644
--- a/frontend/app/components/InfoBox.tsx
+++ b/frontend/app/components/InfoBox.tsx
@@ -24,7 +24,7 @@ const InfoBox: React.FC = ({ infoBoxVisible }) => {
packages on PyPI, which includes all packages with at least ~100
downloads per week. The results are then scored based on their
similarity to the query and their number of weekly downloads, and the
- best results are displayed in the table below.
+ best results are displayed in the plot and table above.
);
diff --git a/frontend/app/components/ScatterPlot.tsx b/frontend/app/components/ScatterPlot.tsx
new file mode 100644
index 0000000..2e1e923
--- /dev/null
+++ b/frontend/app/components/ScatterPlot.tsx
@@ -0,0 +1,278 @@
+import React from "react";
+import { Scatter } from "react-chartjs-2";
+import {
+ Chart,
+ Tooltip,
+ Legend,
+ PointElement,
+ LinearScale,
+ Title,
+ LogarithmicScale,
+ CategoryScale,
+} from "chart.js";
+
+Chart.register(
+ Tooltip,
+ Legend,
+ PointElement,
+ LinearScale,
+ Title,
+ LogarithmicScale,
+ CategoryScale,
+);
+
+interface Match {
+ name: string;
+ similarity: number;
+ weekly_downloads: number;
+ summary: string;
+}
+
+interface ScatterPlotProps {
+ results: Match[];
+}
+
+const getColor = (
+ similarity: number,
+ downloads: number,
+ minSim: number,
+ maxSim: number,
+ minLogDownloads: number,
+ maxLogDownloads: number,
+) => {
+ const baseColor = [54, 162, 235]; // Blue
+ const highlightColor = [255, 99, 132]; // Red
+
+ const normalizedSimilarity = (similarity - minSim) / (maxSim - minSim);
+ const normalizedDownloads =
+ (Math.log10(downloads) - minLogDownloads) /
+ (maxLogDownloads - minLogDownloads);
+
+ const weight = Math.min(
+ ((normalizedSimilarity + normalizedDownloads) / 2) * 1.5,
+ 1,
+ );
+
+ const color = baseColor.map((base, index) =>
+ Math.round(base + weight * (highlightColor[index] - base)),
+ );
+
+ return `rgba(${color.join(",")}, 0.8)`;
+};
+
+const getPointSize = (
+ similarity: number,
+ downloads: number,
+ minSim: number,
+ maxSim: number,
+ minLogDownloads: number,
+ maxLogDownloads: number,
+) => {
+ const normalizedSimilarity = (similarity - minSim) / (maxSim - minSim);
+ const normalizedDownloads =
+ (Math.log10(downloads) - minLogDownloads) /
+ (maxLogDownloads - minLogDownloads);
+
+ const minSize = 2;
+ const size = Math.min(
+ (normalizedSimilarity + normalizedDownloads) * 10 + minSize,
+ 25,
+ );
+ return size;
+};
+
+const ScatterPlot: React.FC = ({ results }) => {
+ const similarities = results.map((result) => result.similarity);
+ const downloads = results.map((result) => result.weekly_downloads);
+ const logDownloads = downloads.map((download) => Math.log10(download));
+
+ const minSim = Math.min(...similarities);
+ const maxSim = Math.max(...similarities);
+ const minLogDownloads = Math.min(...logDownloads);
+ const maxLogDownloads = Math.max(...logDownloads);
+
+ const data = {
+ datasets: [
+ {
+ label: "Packages",
+ data: results.map((result) => ({
+ x: result.similarity,
+ y: result.weekly_downloads,
+ name: result.name,
+ summary: result.summary,
+ link: `https://pypi.org/project/${result.name}/`,
+ })),
+ backgroundColor: results.map((result) =>
+ getColor(
+ result.similarity,
+ result.weekly_downloads,
+ minSim,
+ maxSim,
+ minLogDownloads,
+ maxLogDownloads,
+ ),
+ ),
+ borderColor: results.map((result) =>
+ getColor(
+ result.similarity,
+ result.weekly_downloads,
+ minSim,
+ maxSim,
+ minLogDownloads,
+ maxLogDownloads,
+ ),
+ ),
+ pointRadius: results.map((result) =>
+ getPointSize(
+ result.similarity,
+ result.weekly_downloads,
+ minSim,
+ maxSim,
+ minLogDownloads,
+ maxLogDownloads,
+ ),
+ ),
+ hoverBackgroundColor: results.map((result) =>
+ getColor(
+ result.similarity,
+ result.weekly_downloads,
+ minSim,
+ maxSim,
+ minLogDownloads,
+ maxLogDownloads,
+ ),
+ ),
+ hoverBorderColor: results.map((result) =>
+ getColor(
+ result.similarity,
+ result.weekly_downloads,
+ minSim,
+ maxSim,
+ minLogDownloads,
+ maxLogDownloads,
+ ),
+ ),
+ pointHoverRadius: 15,
+ },
+ ],
+ };
+
+ const options = {
+ responsive: true,
+ maintainAspectRatio: false,
+ plugins: {
+ tooltip: {
+ callbacks: {
+ title: (context: any) => {
+ const dataPoint = context[0].raw;
+ return dataPoint.name;
+ },
+ beforeLabel: (context: any) => {
+ const dataPoint = context.raw;
+ return dataPoint.summary;
+ },
+ label: () => "",
+ afterLabel: (context: any) => {
+ const dataPoint = context.raw;
+ return `\nWeekly downloads: ${dataPoint.y.toLocaleString()}`;
+ },
+ },
+ titleFont: { size: 16, weight: "bold" },
+ bodyFont: { size: 14 },
+ footerFont: { size: 12 },
+ displayColors: false,
+ backgroundColor: "rgba(0, 0, 0, 0.8)",
+ padding: 10,
+ bodySpacing: 4,
+ titleAlign: "left",
+ bodyAlign: "left",
+ footerAlign: "left",
+ },
+ legend: {
+ display: false,
+ },
+ },
+ scales: {
+ x: {
+ title: {
+ display: true,
+ text: "Similarity",
+ color: "#FFFFFF",
+ font: {
+ size: 24,
+ },
+ },
+ ticks: {
+ color: "#FFFFFF",
+ },
+ },
+ y: {
+ title: {
+ display: true,
+ text: "Weekly Downloads",
+ color: "#FFFFFF",
+ font: {
+ size: 24,
+ },
+ },
+ ticks: {
+ callback: function (value: any) {
+ return value.toLocaleString();
+ },
+ color: "#FFFFFF",
+ maxTicksLimit: 5,
+ },
+ type: "logarithmic",
+ },
+ },
+ onClick: (event: any, elements: any) => {
+ if (elements.length > 0) {
+ const elementIndex = elements[0].index;
+ const datasetIndex = elements[0].datasetIndex;
+ const link = data.datasets[datasetIndex].data[elementIndex].link;
+ window.open(link, "_blank");
+ }
+ },
+ onHover: (event: any, elements: any) => {
+ event.native.target.style.cursor = elements[0] ? "pointer" : "default";
+ },
+ elements: {
+ point: {
+ hoverRadius: 15,
+ },
+ },
+ };
+
+ const plugins = [
+ {
+ id: "customLabels",
+ afterDatasetsDraw: (chart: any) => {
+ const ctx = chart.ctx;
+ chart.data.datasets.forEach((dataset: any) => {
+ dataset.data.forEach((dataPoint: any, index: number) => {
+ const { x, y } = chart
+ .getDatasetMeta(0)
+ .data[index].tooltipPosition();
+ ctx.fillStyle = "white";
+ ctx.textAlign = "center";
+ ctx.fillText(dataPoint.name, x, y - 10);
+ });
+ });
+ },
+ },
+ ];
+
+ return (
+
+
+ Click a package to go to PyPI
+
+
+
+
+
+
+ );
+};
+
+export default ScatterPlot;
diff --git a/frontend/app/components/ToggleSwitch.tsx b/frontend/app/components/ToggleSwitch.tsx
new file mode 100644
index 0000000..3bec932
--- /dev/null
+++ b/frontend/app/components/ToggleSwitch.tsx
@@ -0,0 +1,42 @@
+import React from "react";
+
+interface ToggleSwitchProps {
+ option1: string;
+ option2: string;
+ selectedOption: string;
+ onToggle: (option: string) => void;
+}
+
+const ToggleSwitch: React.FC = ({
+ option1,
+ option2,
+ selectedOption,
+ onToggle,
+}) => {
+ return (
+
+ onToggle(option1)}
+ >
+ {option1}
+
+ onToggle(option2)}
+ >
+ {option2}
+
+
+ );
+};
+
+export default ToggleSwitch;
diff --git a/frontend/app/page.tsx b/frontend/app/page.tsx
index 1a21814..4132ae6 100644
--- a/frontend/app/page.tsx
+++ b/frontend/app/page.tsx
@@ -1,9 +1,11 @@
"use client";
-import { useState } from "react";
+import { useState, useEffect, useRef } from "react";
import { handleSearch, sortResults } from "./utils/search";
import SearchResultsTable from "./components/SearchResultsTable";
import InfoBox from "./components/InfoBox";
+import ScatterPlot from "./components/ScatterPlot";
+import ToggleSwitch from "./components/ToggleSwitch";
import { ClipLoader } from "react-spinners";
import Header from "./components/Header";
@@ -22,6 +24,22 @@ export default function Home() {
const [loading, setLoading] = useState(false);
const [error, setError] = useState("");
const [infoBoxVisible, setInfoBoxVisible] = useState(false);
+ const [view, setView] = useState("Plot");
+
+ const resultsRef = useRef(null);
+
+ // If user is on small screen, we probably
+ useEffect(() => {
+ if (window.innerWidth < 768) {
+ setView("Table");
+ }
+ }, []);
+
+ useEffect(() => {
+ if (results.length > 0) {
+ resultsRef.current?.scrollIntoView({ behavior: "smooth" });
+ }
+ }, [results]);
const handleSort = (field: string) => {
const direction =
@@ -31,17 +49,21 @@ export default function Home() {
setResults(sortResults(results, field, direction));
};
+ const handleSearchAction = () => {
+ handleSearch(
+ text,
+ sortField,
+ sortDirection,
+ setResults,
+ setLoading,
+ setError,
+ );
+ };
+
const handleKeyDown = (e: React.KeyboardEvent) => {
if (e.key === "Enter" && !e.shiftKey) {
e.preventDefault();
- handleSearch(
- text,
- sortField,
- sortDirection,
- setResults,
- setLoading,
- setError,
- );
+ handleSearchAction();
}
};
@@ -74,16 +96,7 @@ export default function Home() {
>
- handleSearch(
- text,
- sortField,
- sortDirection,
- setResults,
- setLoading,
- setError,
- )
- }
+ onClick={handleSearchAction}
>
Search
@@ -93,6 +106,41 @@ export default function Home() {
{error && {error}
}
+ {results.length > 0 && (
+
+
+
+ )}
+
+
+ {" "}
+ {/* Reference to this div */}
+ {results.length > 0 && view === "Plot" && (
+
+ )}
+ {results.length > 0 && view === "Table" && (
+
+ )}
+
+
-
- {results.length > 0 && (
-
- )}
);
diff --git a/frontend/app/utils/search.ts b/frontend/app/utils/search.ts
index 88bfb28..c497acc 100644
--- a/frontend/app/utils/search.ts
+++ b/frontend/app/utils/search.ts
@@ -30,6 +30,7 @@ export const handleSearch = async (
`${apiUrl}/search`,
{
query: query,
+ top_k: 40,
},
{
headers: {
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
index 8e8f3ef..26eb8c1 100644
--- a/frontend/package-lock.json
+++ b/frontend/package-lock.json
@@ -9,8 +9,10 @@
"version": "0.1.0",
"dependencies": {
"axios": "^1.7.2",
+ "chart.js": "^4.4.3",
"next": "14.2.4",
"react": "^18",
+ "react-chartjs-2": "^5.2.0",
"react-dom": "^18",
"react-icons": "^5.2.1",
"react-spinners": "^0.13.8"
@@ -233,6 +235,11 @@
"@jridgewell/sourcemap-codec": "^1.4.14"
}
},
+ "node_modules/@kurkle/color": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@kurkle/color/-/color-0.3.2.tgz",
+ "integrity": "sha512-fuscdXJ9G1qb7W8VdHi+IwRqij3lBkosAm4ydQtEmbY58OzHXqQhvlxqEkoz0yssNVn38bcpRWgA9PP+OGoisw=="
+ },
"node_modules/@next/env": {
"version": "14.2.4",
"resolved": "https://registry.npmjs.org/@next/env/-/env-14.2.4.tgz",
@@ -1069,6 +1076,17 @@
"url": "https://github.com/chalk/chalk?sponsor=1"
}
},
+ "node_modules/chart.js": {
+ "version": "4.4.3",
+ "resolved": "https://registry.npmjs.org/chart.js/-/chart.js-4.4.3.tgz",
+ "integrity": "sha512-qK1gkGSRYcJzqrrzdR6a+I0vQ4/R+SoODXyAjscQ/4mzuNzySaMCd+hyVxitSY1+L2fjPD1Gbn+ibNqRmwQeLw==",
+ "dependencies": {
+ "@kurkle/color": "^0.3.0"
+ },
+ "engines": {
+ "pnpm": ">=8"
+ }
+ },
"node_modules/chokidar": {
"version": "3.6.0",
"resolved": "https://registry.npmjs.org/chokidar/-/chokidar-3.6.0.tgz",
@@ -3805,6 +3823,15 @@
"node": ">=0.10.0"
}
},
+ "node_modules/react-chartjs-2": {
+ "version": "5.2.0",
+ "resolved": "https://registry.npmjs.org/react-chartjs-2/-/react-chartjs-2-5.2.0.tgz",
+ "integrity": "sha512-98iN5aguJyVSxp5U3CblRLH67J8gkfyGNbiK3c+l1QI/G4irHMPQw44aEPmjVag+YKTyQ260NcF82GTQ3bdscA==",
+ "peerDependencies": {
+ "chart.js": "^4.1.1",
+ "react": "^16.8.0 || ^17.0.0 || ^18.0.0"
+ }
+ },
"node_modules/react-dom": {
"version": "18.3.1",
"resolved": "https://registry.npmjs.org/react-dom/-/react-dom-18.3.1.tgz",
diff --git a/frontend/package.json b/frontend/package.json
index 0e5834f..9287417 100644
--- a/frontend/package.json
+++ b/frontend/package.json
@@ -10,8 +10,10 @@
},
"dependencies": {
"axios": "^1.7.2",
+ "chart.js": "^4.4.3",
"next": "14.2.4",
"react": "^18",
+ "react-chartjs-2": "^5.2.0",
"react-dom": "^18",
"react-icons": "^5.2.1",
"react-spinners": "^0.13.8"
diff --git a/package-lock.json b/package-lock.json
new file mode 100644
index 0000000..13a2b7b
--- /dev/null
+++ b/package-lock.json
@@ -0,0 +1,68 @@
+{
+ "name": "pypi-llm",
+ "lockfileVersion": 3,
+ "requires": true,
+ "packages": {
+ "": {
+ "dependencies": {
+ "chart.js": "^4.4.3",
+ "react-chartjs-2": "^5.2.0"
+ }
+ },
+ "node_modules/@kurkle/color": {
+ "version": "0.3.2",
+ "resolved": "https://registry.npmjs.org/@kurkle/color/-/color-0.3.2.tgz",
+ "integrity": "sha512-fuscdXJ9G1qb7W8VdHi+IwRqij3lBkosAm4ydQtEmbY58OzHXqQhvlxqEkoz0yssNVn38bcpRWgA9PP+OGoisw=="
+ },
+ "node_modules/chart.js": {
+ "version": "4.4.3",
+ "resolved": "https://registry.npmjs.org/chart.js/-/chart.js-4.4.3.tgz",
+ "integrity": "sha512-qK1gkGSRYcJzqrrzdR6a+I0vQ4/R+SoODXyAjscQ/4mzuNzySaMCd+hyVxitSY1+L2fjPD1Gbn+ibNqRmwQeLw==",
+ "dependencies": {
+ "@kurkle/color": "^0.3.0"
+ },
+ "engines": {
+ "pnpm": ">=8"
+ }
+ },
+ "node_modules/js-tokens": {
+ "version": "4.0.0",
+ "resolved": "https://registry.npmjs.org/js-tokens/-/js-tokens-4.0.0.tgz",
+ "integrity": "sha512-RdJUflcE3cUzKiMqQgsCu06FPu9UdIJO0beYbPhHN4k6apgJtifcoCtT9bcxOpYBtpD2kCM6Sbzg4CausW/PKQ==",
+ "peer": true
+ },
+ "node_modules/loose-envify": {
+ "version": "1.4.0",
+ "resolved": "https://registry.npmjs.org/loose-envify/-/loose-envify-1.4.0.tgz",
+ "integrity": "sha512-lyuxPGr/Wfhrlem2CL/UcnUc1zcqKAImBDzukY7Y5F/yQiNdko6+fRLevlw1HgMySw7f611UIY408EtxRSoK3Q==",
+ "peer": true,
+ "dependencies": {
+ "js-tokens": "^3.0.0 || ^4.0.0"
+ },
+ "bin": {
+ "loose-envify": "cli.js"
+ }
+ },
+ "node_modules/react": {
+ "version": "18.3.1",
+ "resolved": "https://registry.npmjs.org/react/-/react-18.3.1.tgz",
+ "integrity": "sha512-wS+hAgJShR0KhEvPJArfuPVN1+Hz1t0Y6n5jLrGQbkb4urgPE/0Rve+1kMB1v/oWgHgm4WIcV+i7F2pTVj+2iQ==",
+ "peer": true,
+ "dependencies": {
+ "loose-envify": "^1.1.0"
+ },
+ "engines": {
+ "node": ">=0.10.0"
+ }
+ },
+ "node_modules/react-chartjs-2": {
+ "version": "5.2.0",
+ "resolved": "https://registry.npmjs.org/react-chartjs-2/-/react-chartjs-2-5.2.0.tgz",
+ "integrity": "sha512-98iN5aguJyVSxp5U3CblRLH67J8gkfyGNbiK3c+l1QI/G4irHMPQw44aEPmjVag+YKTyQ260NcF82GTQ3bdscA==",
+ "peerDependencies": {
+ "chart.js": "^4.1.1",
+ "react": "^16.8.0 || ^17.0.0 || ^18.0.0"
+ }
+ }
+ }
+}
diff --git a/package.json b/package.json
new file mode 100644
index 0000000..5dac333
--- /dev/null
+++ b/package.json
@@ -0,0 +1,6 @@
+{
+ "dependencies": {
+ "chart.js": "^4.4.3",
+ "react-chartjs-2": "^5.2.0"
+ }
+}
diff --git a/poetry.lock b/poetry.lock
index 4fc1922..b640108 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -33,144 +33,6 @@ doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphin
test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
trio = ["trio (>=0.23)"]
-[[package]]
-name = "appnope"
-version = "0.1.4"
-description = "Disable App Nap on macOS >= 10.9"
-optional = false
-python-versions = ">=3.6"
-files = [
- {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
- {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
-]
-
-[[package]]
-name = "argon2-cffi"
-version = "23.1.0"
-description = "Argon2 for Python"
-optional = false
-python-versions = ">=3.7"
-files = [
- {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"},
- {file = "argon2_cffi-23.1.0.tar.gz", hash = "sha256:879c3e79a2729ce768ebb7d36d4609e3a78a4ca2ec3a9f12286ca057e3d0db08"},
-]
-
-[package.dependencies]
-argon2-cffi-bindings = "*"
-
-[package.extras]
-dev = ["argon2-cffi[tests,typing]", "tox (>4)"]
-docs = ["furo", "myst-parser", "sphinx", "sphinx-copybutton", "sphinx-notfound-page"]
-tests = ["hypothesis", "pytest"]
-typing = ["mypy"]
-
-[[package]]
-name = "argon2-cffi-bindings"
-version = "21.2.0"
-description = "Low-level CFFI bindings for Argon2"
-optional = false
-python-versions = ">=3.6"
-files = [
- {file = "argon2-cffi-bindings-21.2.0.tar.gz", hash = "sha256:bb89ceffa6c791807d1305ceb77dbfacc5aa499891d2c55661c6459651fc39e3"},
- {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ccb949252cb2ab3a08c02024acb77cfb179492d5701c7cbdbfd776124d4d2367"},
- {file = "argon2_cffi_bindings-21.2.0-cp36-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9524464572e12979364b7d600abf96181d3541da11e23ddf565a32e70bd4dc0d"},
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- {file = "watchdog-4.0.1-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:f27279d060e2ab24c0aa98363ff906d2386aa6c4dc2f1a374655d4e02a6c5e5e"},
- {file = "watchdog-4.0.1-py3-none-manylinux2014_s390x.whl", hash = "sha256:f8affdf3c0f0466e69f5b3917cdd042f89c8c63aebdb9f7c078996f607cdb0f5"},
- {file = "watchdog-4.0.1-py3-none-manylinux2014_x86_64.whl", hash = "sha256:ac7041b385f04c047fcc2951dc001671dee1b7e0615cde772e84b01fbf68ee84"},
- {file = "watchdog-4.0.1-py3-none-win32.whl", hash = "sha256:206afc3d964f9a233e6ad34618ec60b9837d0582b500b63687e34011e15bb429"},
- {file = "watchdog-4.0.1-py3-none-win_amd64.whl", hash = "sha256:7577b3c43e5909623149f76b099ac49a1a01ca4e167d1785c76eb52fa585745a"},
- {file = "watchdog-4.0.1-py3-none-win_ia64.whl", hash = "sha256:d7b9f5f3299e8dd230880b6c55504a1f69cf1e4316275d1b215ebdd8187ec88d"},
- {file = "watchdog-4.0.1.tar.gz", hash = "sha256:eebaacf674fa25511e8867028d281e602ee6500045b57f43b08778082f7f8b44"},
-]
-
-[package.extras]
-watchmedo = ["PyYAML (>=3.10)"]
-
[[package]]
name = "watchfiles"
version = "0.22.0"
@@ -4822,59 +3127,6 @@ files = [
[package.dependencies]
anyio = ">=3.0.0"
-[[package]]
-name = "wcwidth"
-version = "0.2.13"
-description = "Measures the displayed width of unicode strings in a terminal"
-optional = false
-python-versions = "*"
-files = [
- {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
- {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
-]
-
-[[package]]
-name = "webcolors"
-version = "24.6.0"
-description = "A library for working with the color formats defined by HTML and CSS."
-optional = false
-python-versions = ">=3.8"
-files = [
- {file = "webcolors-24.6.0-py3-none-any.whl", hash = "sha256:8cf5bc7e28defd1d48b9e83d5fc30741328305a8195c29a8e668fa45586568a1"},
- {file = "webcolors-24.6.0.tar.gz", hash = "sha256:1d160d1de46b3e81e58d0a280d0c78b467dc80f47294b91b1ad8029d2cedb55b"},
-]
-
-[package.extras]
-docs = ["furo", "sphinx", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-notfound-page", "sphinxext-opengraph"]
-tests = ["coverage[toml]"]
-
-[[package]]
-name = "webencodings"
-version = "0.5.1"
-description = "Character encoding aliases for legacy web content"
-optional = false
-python-versions = "*"
-files = [
- {file = "webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78"},
- {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
-]
-
-[[package]]
-name = "websocket-client"
-version = "1.8.0"
-description = "WebSocket client for Python with low level API options"
-optional = false
-python-versions = ">=3.8"
-files = [
- {file = "websocket_client-1.8.0-py3-none-any.whl", hash = "sha256:17b44cc997f5c498e809b22cdf2d9c7a9e71c02c8cc2b6c56e7c2d1239bfa526"},
- {file = "websocket_client-1.8.0.tar.gz", hash = "sha256:3239df9f44da632f96012472805d40a23281a991027ce11d2f45a6f24ac4c3da"},
-]
-
-[package.extras]
-docs = ["Sphinx (>=6.0)", "myst-parser (>=2.0.0)", "sphinx-rtd-theme (>=1.1.0)"]
-optional = ["python-socks", "wsaccel"]
-test = ["websockets"]
-
[[package]]
name = "websockets"
version = "12.0"
@@ -5053,4 +3305,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools",
[metadata]
lock-version = "2.0"
python-versions = ">=3.9,<4.0"
-content-hash = "de83ca89b79716cfc21e06d916d81963401155a517238f9ff066b31ef349a160"
+content-hash = "32f2cd0f5a83447abbe6aceece708ca2ac68784b17f229e003e2c521b829ec44"
diff --git a/pypi_scout/api/data_loader.py b/pypi_scout/api/data_loader.py
index c4ea031..9eb246a 100644
--- a/pypi_scout/api/data_loader.py
+++ b/pypi_scout/api/data_loader.py
@@ -19,6 +19,7 @@ def load_dataset(self) -> Tuple[pl.DataFrame, pl.DataFrame]:
else:
raise ValueError(f"Unexpected value found for STORAGE_BACKEND: {self.config.STORAGE_BACKEND}") # noqa: TRY003
+ df_embeddings = self._drop_rows_from_embeddings_that_do_not_appear_in_packages(df_embeddings, df_packages)
return df_packages, df_embeddings
def _load_local_dataset(self) -> Tuple[pl.DataFrame, pl.DataFrame]:
@@ -56,10 +57,22 @@ def _load_blob_dataset(self) -> Tuple[pl.DataFrame, pl.DataFrame]:
return df_packages, df_embeddings
- def _log_packages_dataset_info(self, df_packages: pl.DataFrame) -> None:
+ @staticmethod
+ def _log_packages_dataset_info(df_packages: pl.DataFrame) -> None:
logging.info(f"Finished loading the `packages` dataset. Number of rows in dataset: {len(df_packages):,}")
logging.info(df_packages.describe())
- def _log_embeddings_dataset_info(self, df_embeddings: pl.DataFrame) -> None:
+ @staticmethod
+ def _log_embeddings_dataset_info(df_embeddings: pl.DataFrame) -> None:
logging.info(f"Finished loading the `embeddings` dataset. Number of rows in dataset: {len(df_embeddings):,}")
logging.info(df_embeddings.describe())
+
+ @staticmethod
+ def _drop_rows_from_embeddings_that_do_not_appear_in_packages(df_embeddings, df_packages):
+ # We only keep the packages in the vector dataset that also occur in the packages dataset.
+ # In theory, this should never drop something. But still good to keep as a fail-safe to prevent issues in the API.
+ logging.info("Dropping packages in the `embeddings` dataset that do not occur in the `packages` dataset...")
+ logging.info(f"Number of rows before dropping: {len(df_embeddings):,}...")
+ df_embeddings = df_embeddings.join(df_packages, on="name", how="semi")
+ logging.info(f"Number of rows after dropping: {len(df_embeddings):,}...")
+ return df_embeddings
diff --git a/pypi_scout/api/main.py b/pypi_scout/api/main.py
index 5e70afb..f54c585 100644
--- a/pypi_scout/api/main.py
+++ b/pypi_scout/api/main.py
@@ -1,10 +1,8 @@
import logging
-import polars as pl
from dotenv import load_dotenv
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel
from sentence_transformers import SentenceTransformer
from slowapi import Limiter, _rate_limit_exceeded_handler
from slowapi.errors import RateLimitExceeded
@@ -12,29 +10,26 @@
from starlette.requests import Request
from pypi_scout.api.data_loader import ApiDataLoader
+from pypi_scout.api.models import QueryModel, SearchResponse
from pypi_scout.config import Config
from pypi_scout.embeddings.simple_vector_database import SimpleVectorDatabase
from pypi_scout.utils.logging import setup_logging
from pypi_scout.utils.score_calculator import calculate_score
-# Setup logging
setup_logging()
logging.info("Initializing backend...")
-# Initialize limiter
limiter = Limiter(key_func=get_remote_address)
app = FastAPI()
app.state.limiter = limiter
app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler)
-# Load environment variables and configuration
load_dotenv()
config = Config()
-# Add CORS middleware
app.add_middleware(
CORSMiddleware,
- allow_origins=["*"], # Temporary wildcard for testing
+ allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
@@ -44,28 +39,9 @@
df_packages, df_embeddings = data_loader.load_dataset()
model = SentenceTransformer(config.EMBEDDINGS_MODEL_NAME)
-
vector_database = SimpleVectorDatabase(embeddings_model=model, df_embeddings=df_embeddings)
-class QueryModel(BaseModel):
- query: str
- top_k: int = config.N_RESULTS_TO_RETURN
-
-
-class Match(BaseModel):
- name: str
- summary: str
- similarity: float
- weekly_downloads: int
-
-
-class SearchResponse(BaseModel):
- matches: list[Match]
- warning: bool = False
- warning_message: str = None
-
-
@app.post("/api/search", response_model=SearchResponse)
@limiter.limit("4/minute")
async def search(query: QueryModel, request: Request):
@@ -75,7 +51,7 @@ async def search(query: QueryModel, request: Request):
The top_k packages with the highest score are returned.
"""
- if query.top_k > 60:
+ if query.top_k > 100:
raise HTTPException(status_code=400, detail="top_k cannot be larger than 100.")
logging.info(f"Searching for similar projects. Query: '{query.query}'")
@@ -85,18 +61,6 @@ async def search(query: QueryModel, request: Request):
f"Fetched the {len(df_matches)} most similar projects. Calculating the weighted scores and filtering..."
)
- warning = False
- warning_message = ""
- matches_missing_in_local_dataset = df_matches.filter(pl.col("weekly_downloads").is_null())["name"].to_list()
- if matches_missing_in_local_dataset:
- warning = True
- warning_message = (
- f"The following entries have 'None' for 'weekly_downloads': {matches_missing_in_local_dataset}. "
- "These entries were found in the vector database but not in the local dataset and have been excluded from the results."
- )
- logging.error(warning_message)
- df_matches = df_matches.filter(~pl.col("name").is_in(matches_missing_in_local_dataset))
-
df_matches = calculate_score(
df_matches, weight_similarity=config.WEIGHT_SIMILARITY, weight_weekly_downloads=config.WEIGHT_WEEKLY_DOWNLOADS
)
@@ -107,4 +71,4 @@ async def search(query: QueryModel, request: Request):
logging.info(f"Returning the {len(df_matches)} best matches.")
df_matches = df_matches.select(["name", "similarity", "summary", "weekly_downloads"])
- return SearchResponse(matches=df_matches.to_dicts(), warning=warning, warning_message=warning_message)
+ return SearchResponse(matches=df_matches.to_dicts())
diff --git a/pypi_scout/api/models.py b/pypi_scout/api/models.py
new file mode 100644
index 0000000..ed54bbb
--- /dev/null
+++ b/pypi_scout/api/models.py
@@ -0,0 +1,19 @@
+from pydantic import BaseModel
+
+
+class QueryModel(BaseModel):
+ query: str
+ top_k: int
+
+
+class Match(BaseModel):
+ name: str
+ summary: str
+ similarity: float
+ weekly_downloads: int
+
+
+class SearchResponse(BaseModel):
+ matches: list[Match]
+ warning: bool = False
+ warning_message: str = None
diff --git a/pypi_scout/config.py b/pypi_scout/config.py
index 57cb849..64bdcf3 100644
--- a/pypi_scout/config.py
+++ b/pypi_scout/config.py
@@ -38,9 +38,6 @@ class Config:
# Google Drive file ID for downloading the raw dataset.
GOOGLE_FILE_ID = "1IDJvCsq1gz0yUSXgff13pMl3nUk7zJzb"
- # Number of top results to return for a query.
- N_RESULTS_TO_RETURN = 40
-
# Fraction of the dataset to include in the vector database. This value determines the portion of top packages
# (sorted by weekly downloads) to include. Increase this value to include a larger portion of the dataset, up to 1.0 (100%).
# For reference, a value of 0.25 corresponds to including all PyPI packages with at least approximately 650 weekly downloads
diff --git a/pyproject.toml b/pyproject.toml
index 7d51b9d..ebe5d94 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -35,12 +35,6 @@ pytest-mock = "^3.14.0"
deptry = "^0.12.0"
pre-commit = "^3.4.0"
tox = "^4.11.1"
-jupyterlab = "^4.2.2"
-
-[tool.poetry.group.docs.dependencies]
-mkdocs = "^1.4.2"
-mkdocs-material = "^9.2.7"
-mkdocstrings = {extras = ["python"], version = "^0.23.0"}
[build-system]
requires = ["poetry-core>=1.0.0"]
diff --git a/tests/test_vdb.py b/tests/embeddings/test_simple_vector_database.py
similarity index 79%
rename from tests/test_vdb.py
rename to tests/embeddings/test_simple_vector_database.py
index ea40271..4d50e00 100644
--- a/tests/test_vdb.py
+++ b/tests/embeddings/test_simple_vector_database.py
@@ -33,9 +33,7 @@ def vector_db(mock_model, df_embeddings):
def test_embeddings_matrix_creation(vector_db):
- expected_matrix = np.array(
- [[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]], dtype=np.float32
- ) # Ensure the expected matrix has dtype float32
+ expected_matrix = np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6], [0.7, 0.8, 0.9]], dtype=np.float32)
np.testing.assert_allclose(vector_db.embeddings_matrix, expected_matrix, rtol=1e-6, atol=1e-8)
@@ -44,13 +42,10 @@ def test_find_similar(vector_db):
query = "Hello"
result = vector_db.find_similar(query, top_k=2)
- # Check that the result has the expected number of rows
assert result.shape[0] == 2
- # Check that the similarity scores are between 0 and 1
assert result["similarity"].min() >= 0
assert result["similarity"].max() <= 1
- # Check that the result contains the expected columns
expected_columns = ["id", "text", "similarity"]
assert set(result.columns) == set(expected_columns)