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shreyask commited on 25 days ago

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dd0233f

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1 Parent(s): eb89325

Deploy qmd-web

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Files changed (14) hide show

.gitignore +0 -26
deploy.sh +0 -49
eslint.config.js +0 -23
{public/eval-docs → eval-docs}/history-of-coffee.md +0 -0
index.html +1 -1
package-lock.json +0 -0
package.json +0 -33
public/eval-docs/api-design-principles.md +0 -73
public/eval-docs/distributed-systems-overview.md +0 -92
public/eval-docs/machine-learning-primer.md +0 -125
tsconfig.app.json +0 -28
tsconfig.json +0 -7
tsconfig.node.json +0 -26
vite.config.ts +0 -15

.gitignore DELETED Viewed

@@ -1,26 +0,0 @@
-# Logs
-logs
-*.log
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-pnpm-debug.log*
-lerna-debug.log*
-node_modules
-dist
-dist-ssr
-*.local
-# Editor directories and files
-.vscode/*
-!.vscode/extensions.json
-.idea
-.DS_Store
-*.suo
-*.ntvs*
-*.njsproj
-*.sln
-*.sw?
-assets/
-dist/

deploy.sh DELETED Viewed

@@ -1,49 +0,0 @@
-#!/bin/bash
-# Deploy qmd-web to HuggingFace Space
-# Uploads dist/ + eval-docs/ + src/ via HF API (no git LFS needed)
-set -e
-SPACE_ID="shreyask/qmd-web"
-echo "Building..."
-npm run build
-echo "Deploying to $SPACE_ID..."
-python3 -c "
-from huggingface_hub import HfApi
-import shutil, os
-from pathlib import Path
-SPACE_ID = '$SPACE_ID'
-PROJECT = '$(pwd)'
-STAGE = '/tmp/qmd-web-deploy'
-if os.path.exists(STAGE):
-    shutil.rmtree(STAGE)
-os.makedirs(STAGE)
-# dist/ contents -> root (includes index.html, assets/, eval-docs/ from public/)
-for item in Path(f'{PROJECT}/dist').iterdir():
-    dest = Path(STAGE) / item.name
-    if item.is_dir():
-        shutil.copytree(item, dest)
-    else:
-        shutil.copy2(item, dest)
-# src/ for reference
-shutil.copytree(f'{PROJECT}/src', f'{STAGE}/src')
-# README with HF Space metadata
-shutil.copy2(f'{PROJECT}/README.md', f'{STAGE}/README.md')
-api = HfApi()
-api.upload_folder(
-    folder_path=STAGE,
-    repo_id=SPACE_ID,
-    repo_type='space',
-    delete_patterns=['*'],
-    commit_message='Deploy qmd-web',
-)
-print(f'Deployed! https://huggingface.co/spaces/{SPACE_ID}')
-"

eslint.config.js DELETED Viewed

@@ -1,23 +0,0 @@
-import js from '@eslint/js'
-import globals from 'globals'
-import reactHooks from 'eslint-plugin-react-hooks'
-import reactRefresh from 'eslint-plugin-react-refresh'
-import tseslint from 'typescript-eslint'
-import { defineConfig, globalIgnores } from 'eslint/config'
-export default defineConfig([
-  globalIgnores(['dist']),
-  {
-    files: ['**/*.{ts,tsx}'],
-    extends: [
-      js.configs.recommended,
-      tseslint.configs.recommended,
-      reactHooks.configs.flat.recommended,
-      reactRefresh.configs.vite,
-    ],
-    languageOptions: {
-      ecmaVersion: 2020,
-      globals: globals.browser,
-    },
-  },
-])

{public/eval-docs → eval-docs}/history-of-coffee.md RENAMED Viewed

File without changes

index.html CHANGED Viewed

@@ -81,9 +81,9 @@
         }
       })();
     </script>
   </head>
   <body>
     <div id="root"></div>
-    <script type="module" src="/src/main.tsx"></script>
   </body>
 </html>

         }
       })();
     </script>
+    <script type="module" crossorigin src="./assets/index-CkVH_59C.js"></script>
   </head>
   <body>
     <div id="root"></div>
   </body>
 </html>

package-lock.json DELETED Viewed

The diff for this file is too large to render. See raw diff

package.json DELETED Viewed

@@ -1,33 +0,0 @@
-{
-  "name": "qmd-web",
-  "private": true,
-  "version": "0.0.0",
-  "type": "module",
-  "scripts": {
-    "dev": "vite",
-    "build": "tsc -b && vite build",
-    "lint": "eslint .",
-    "preview": "vite preview"
-  },
-  "dependencies": {
-    "@huggingface/transformers": "^4.0.0-next.7",
-    "react": "^19.2.0",
-    "react-dom": "^19.2.0"
-  },
-  "devDependencies": {
-    "@eslint/js": "^9.39.1",
-    "@types/node": "^24.10.1",
-    "@types/react": "^19.2.7",
-    "@types/react-dom": "^19.2.3",
-    "@vitejs/plugin-react": "^5.1.1",
-    "@webgpu/types": "^0.1.69",
-    "eslint": "^9.39.1",
-    "eslint-plugin-react-hooks": "^7.0.1",
-    "eslint-plugin-react-refresh": "^0.4.24",
-    "globals": "^16.5.0",
-    "typescript": "~5.9.3",
-    "typescript-eslint": "^8.48.0",
-    "vite": "^7.3.1",
-    "vitest": "^4.0.18"
-  }
-}

public/eval-docs/api-design-principles.md DELETED Viewed

@@ -1,73 +0,0 @@
-# API Design Principles
-## Introduction
-Good API design is crucial for developer experience. This document outlines the core principles we follow when designing REST APIs.
-## Principle 1: Use Nouns, Not Verbs
-URLs should represent resources, not actions. Use HTTP methods to indicate the action.
-**Good:**
-- GET /users/123
-- POST /orders
-- DELETE /products/456
-**Bad:**
-- GET /getUser?id=123
-- POST /createOrder
-- GET /deleteProduct/456
-## Principle 2: Use Plural Nouns
-Always use plural nouns for consistency.
-- /users (not /user)
-- /orders (not /order)
-- /products (not /product)
-## Principle 3: Hierarchical Relationships
-Express relationships through URL hierarchy.
-- GET /users/123/orders - Get all orders for user 123
-- GET /users/123/orders/456 - Get specific order 456 for user 123
-## Principle 4: Filtering and Pagination
-Use query parameters for filtering, sorting, and pagination.
-- GET /products?category=electronics&sort=price&page=2&limit=20
-## Principle 5: Versioning
-Always version your APIs. We prefer URL versioning.
-- /v1/users
-- /v2/users
-## Principle 6: Error Handling
-Return consistent error responses with appropriate HTTP status codes.
-```json
-{
-  "error": {
-    "code": "VALIDATION_ERROR",
-    "message": "Email format is invalid",
-    "field": "email"
-  }
-}
-```
-## Principle 7: Rate Limiting
-Implement rate limiting and communicate limits via headers:
-- X-RateLimit-Limit: 1000
-- X-RateLimit-Remaining: 999
-- X-RateLimit-Reset: 1640000000
-## Conclusion
-Following these principles leads to APIs that are intuitive, consistent, and easy to maintain. Remember: the best API is one that developers can use without reading documentation.

public/eval-docs/distributed-systems-overview.md DELETED Viewed

@@ -1,92 +0,0 @@
-# Distributed Systems: A Practical Overview
-## What Makes a System "Distributed"?
-A distributed system is a collection of independent computers that appears to users as a single coherent system. The key challenges arise from:
-1. **Partial failure** - Parts of the system can fail independently
-2. **Unreliable networks** - Messages can be lost, delayed, or duplicated
-3. **No global clock** - Different nodes have different views of time
-## The CAP Theorem
-Eric Brewer's CAP theorem states that a distributed system can only provide two of three guarantees:
-- **Consistency**: All nodes see the same data at the same time
-- **Availability**: Every request receives a response
-- **Partition tolerance**: System continues operating despite network partitions
-In practice, network partitions happen, so you're really choosing between CP and AP systems.
-### CP Systems (Consistency + Partition Tolerance)
-- Examples: ZooKeeper, etcd, Consul
-- Sacrifice availability during partitions
-- Good for: coordination, leader election, configuration
-### AP Systems (Availability + Partition Tolerance)
-- Examples: Cassandra, DynamoDB, CouchDB
-- Sacrifice consistency during partitions
-- Good for: high-throughput, always-on services
-## Consensus Algorithms
-When nodes need to agree on something, they use consensus algorithms.
-### Paxos
-- Original consensus algorithm by Leslie Lamport
-- Notoriously difficult to understand and implement
-- Foundation for many other algorithms
-### Raft
-- Designed to be understandable
-- Used in etcd, Consul, CockroachDB
-- Separates leader election from log replication
-### PBFT (Practical Byzantine Fault Tolerance)
-- Handles malicious nodes
-- Used in blockchain systems
-- Higher overhead than crash-fault-tolerant algorithms
-## Replication Strategies
-### Single-Leader Replication
-- One node accepts writes
-- Followers replicate from leader
-- Simple but leader is bottleneck
-### Multi-Leader Replication
-- Multiple nodes accept writes
-- Must handle write conflicts
-- Good for multi-datacenter deployments
-### Leaderless Replication
-- Any node accepts writes
-- Uses quorum reads/writes
-- Examples: Dynamo-style databases
-## Consistency Models
-From strongest to weakest:
-1. **Linearizability** - Operations appear instantaneous
-2. **Sequential consistency** - Operations appear in some sequential order
-3. **Causal consistency** - Causally related operations appear in order
-4. **Eventual consistency** - Given enough time, all replicas converge
-## Partitioning (Sharding)
-Distributing data across nodes:
-### Hash Partitioning
-- Hash key to determine partition
-- Even distribution
-- Range queries are inefficient
-### Range Partitioning
-- Ranges of keys on different nodes
-- Good for range queries
-- Risk of hot spots
-## Conclusion
-Building distributed systems requires understanding these fundamental concepts. Start simple, add complexity only when needed, and always plan for failure.

public/eval-docs/machine-learning-primer.md DELETED Viewed

@@ -1,125 +0,0 @@
-# Machine Learning: A Beginner's Guide
-## What is Machine Learning?
-Machine learning is a subset of artificial intelligence where systems learn patterns from data rather than being explicitly programmed. Instead of writing rules, you provide examples and let the algorithm discover the rules.
-## Types of Machine Learning
-### Supervised Learning
-The algorithm learns from labeled examples.
-**Classification**: Predicting categories
-- Email spam detection
-- Image recognition
-- Medical diagnosis
-**Regression**: Predicting continuous values
-- House price prediction
-- Stock price forecasting
-- Temperature prediction
-Common algorithms:
-- Linear Regression
-- Logistic Regression
-- Decision Trees
-- Random Forests
-- Support Vector Machines (SVM)
-- Neural Networks
-### Unsupervised Learning
-The algorithm finds patterns in unlabeled data.
-**Clustering**: Grouping similar items
-- Customer segmentation
-- Document categorization
-- Anomaly detection
-**Dimensionality Reduction**: Simplifying data
-- Feature extraction
-- Visualization
-- Noise reduction
-Common algorithms:
-- K-Means Clustering
-- Hierarchical Clustering
-- Principal Component Analysis (PCA)
-- t-SNE
-### Reinforcement Learning
-The algorithm learns through trial and error, receiving rewards or penalties.
-Applications:
-- Game playing (AlphaGo, chess)
-- Robotics
-- Autonomous vehicles
-- Resource management
-## The Machine Learning Pipeline
-1. **Data Collection**: Gather relevant data
-2. **Data Cleaning**: Handle missing values, outliers
-3. **Feature Engineering**: Create useful features
-4. **Model Selection**: Choose appropriate algorithm
-5. **Training**: Fit model to training data
-6. **Evaluation**: Test on held-out data
-7. **Deployment**: Put model into production
-8. **Monitoring**: Track performance over time
-## Key Concepts
-### Overfitting vs Underfitting
-**Overfitting**: Model memorizes training data, performs poorly on new data
-- Solution: More data, regularization, simpler model
-**Underfitting**: Model too simple to capture patterns
-- Solution: More features, complex model, less regularization
-### Train/Test Split
-Never evaluate on training data. Common splits:
-- 80% training, 20% testing
-- 70% training, 15% validation, 15% testing
-### Cross-Validation
-K-fold cross-validation provides more robust evaluation:
-1. Split data into K folds
-2. Train on K-1 folds, test on remaining fold
-3. Repeat K times
-4. Average the results
-### Bias-Variance Tradeoff
-- **High Bias**: Oversimplified model (underfitting)
-- **High Variance**: Overcomplicated model (overfitting)
-- Goal: Find the sweet spot
-## Evaluation Metrics
-### Classification
-- Accuracy: Correct predictions / Total predictions
-- Precision: True positives / Predicted positives
-- Recall: True positives / Actual positives
-- F1 Score: Harmonic mean of precision and recall
-- AUC-ROC: Area under receiver operating curve
-### Regression
-- Mean Absolute Error (MAE)
-- Mean Squared Error (MSE)
-- Root Mean Squared Error (RMSE)
-- R-squared (R2)
-## Getting Started
-1. Learn Python and libraries (NumPy, Pandas, Scikit-learn)
-2. Work through classic datasets (Iris, MNIST, Titanic)
-3. Take online courses (Coursera, fast.ai)
-4. Practice on Kaggle competitions
-5. Build projects with real-world data
-Remember: Machine learning is 80% data preparation and 20% modeling. Start with clean data and simple models before going complex.

tsconfig.app.json DELETED Viewed

@@ -1,28 +0,0 @@
-{
-  "compilerOptions": {
-    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
-    "target": "ES2022",
-    "useDefineForClassFields": true,
-    "lib": ["ES2022", "DOM", "DOM.Iterable"],
-    "module": "ESNext",
-    "types": ["vite/client", "@webgpu/types"],
-    "skipLibCheck": true,
-    /* Bundler mode */
-    "moduleResolution": "bundler",
-    "allowImportingTsExtensions": true,
-    "verbatimModuleSyntax": true,
-    "moduleDetection": "force",
-    "noEmit": true,
-    "jsx": "react-jsx",
-    /* Linting */
-    "strict": true,
-    "noUnusedLocals": true,
-    "noUnusedParameters": true,
-    "erasableSyntaxOnly": true,
-    "noFallthroughCasesInSwitch": true,
-    "noUncheckedSideEffectImports": true
-  },
-  "include": ["src"]
-}

tsconfig.json DELETED Viewed

@@ -1,7 +0,0 @@
-{
-  "files": [],
-  "references": [
-    { "path": "./tsconfig.app.json" },
-    { "path": "./tsconfig.node.json" }
-  ]
-}

tsconfig.node.json DELETED Viewed

@@ -1,26 +0,0 @@
-{
-  "compilerOptions": {
-    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
-    "target": "ES2023",
-    "lib": ["ES2023"],
-    "module": "ESNext",
-    "types": ["node"],
-    "skipLibCheck": true,
-    /* Bundler mode */
-    "moduleResolution": "bundler",
-    "allowImportingTsExtensions": true,
-    "verbatimModuleSyntax": true,
-    "moduleDetection": "force",
-    "noEmit": true,
-    /* Linting */
-    "strict": true,
-    "noUnusedLocals": true,
-    "noUnusedParameters": true,
-    "erasableSyntaxOnly": true,
-    "noFallthroughCasesInSwitch": true,
-    "noUncheckedSideEffectImports": true
-  },
-  "include": ["vite.config.ts"]
-}

vite.config.ts DELETED Viewed

@@ -1,15 +0,0 @@
-import { defineConfig } from 'vite'
-import react from '@vitejs/plugin-react'
-// https://vite.dev/config/
-export default defineConfig({
-  plugins: [react()],
-  base: "./", // relative paths for HF Space static hosting
-  optimizeDeps: {
-    // Don't pre-bundle transformers.js — it dynamically loads ONNX Runtime WASM/WebGPU
-    exclude: ["@huggingface/transformers"],
-  },
-  worker: {
-    format: "es",
-  },
-})