Commit a91db259 authored by ZeinabRm13's avatar ZeinabRm13

Setup frontend

parent 3f1e8493
from transformers import AutoTokenizer
from PIL import Image
import onnxruntime as ort
import numpy as np
import requests
# Download tokenizer only (very small)
tokenizer = AutoTokenizer.from_pretrained('kppkkp/OneChart', trust_remote_code=True)
# Load pre-converted ONNX model (you'll need to get/make this first)
onnx_session = ort.InferenceSession("onechart_model.onnx")
# Prepare inputs
image = Image.open("/home/zeinabrm/Documents/ChartToText/Project/ChartAnalyzer/multiset_barchart.png")
inputs = tokenizer("analyze this chart", return_tensors="np")
pixel_values = np.array(image.convert("RGB")) # Simple image processing
# Run inference
outputs = onnx_session.run(
None,
{
"input_ids": inputs["input_ids"],
"attention_mask": inputs["attention_mask"],
"pixel_values": np.expand_dims(pixel_values, 0)
}
)
print(tokenizer.decode(outputs[0]))
\ No newline at end of file
# 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?
# React + TypeScript + Vite
This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
Currently, two official plugins are available:
- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Babel](https://babeljs.io/) for Fast Refresh
- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh
## Expanding the ESLint configuration
If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules:
```js
export default tseslint.config([
globalIgnores(['dist']),
{
files: ['**/*.{ts,tsx}'],
extends: [
// Other configs...
// Remove tseslint.configs.recommended and replace with this
...tseslint.configs.recommendedTypeChecked,
// Alternatively, use this for stricter rules
...tseslint.configs.strictTypeChecked,
// Optionally, add this for stylistic rules
...tseslint.configs.stylisticTypeChecked,
// Other configs...
],
languageOptions: {
parserOptions: {
project: ['./tsconfig.node.json', './tsconfig.app.json'],
tsconfigRootDir: import.meta.dirname,
},
// other options...
},
},
])
```
You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules:
```js
// eslint.config.js
import reactX from 'eslint-plugin-react-x'
import reactDom from 'eslint-plugin-react-dom'
export default tseslint.config([
globalIgnores(['dist']),
{
files: ['**/*.{ts,tsx}'],
extends: [
// Other configs...
// Enable lint rules for React
reactX.configs['recommended-typescript'],
// Enable lint rules for React DOM
reactDom.configs.recommended,
],
languageOptions: {
parserOptions: {
project: ['./tsconfig.node.json', './tsconfig.app.json'],
tsconfigRootDir: import.meta.dirname,
},
// other options...
},
},
])
```
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 { globalIgnores } from 'eslint/config'
export default tseslint.config([
globalIgnores(['dist']),
{
files: ['**/*.{ts,tsx}'],
extends: [
js.configs.recommended,
tseslint.configs.recommended,
reactHooks.configs['recommended-latest'],
reactRefresh.configs.vite,
],
languageOptions: {
ecmaVersion: 2020,
globals: globals.browser,
},
},
])
<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Vite + React + TS</title>
</head>
<body>
<div id="root"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
</html>
This source diff could not be displayed because it is too large. You can view the blob instead.
{
"name": "frontend",
"private": true,
"version": "0.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "tsc -b && vite build",
"lint": "eslint .",
"preview": "vite preview"
},
"dependencies": {
"@types/react-router-dom": "^5.3.3",
"axios": "^1.11.0",
"react": "^19.1.0",
"react-dom": "^19.1.0",
"react-router-dom": "^7.7.1"
},
"devDependencies": {
"@eslint/js": "^9.30.1",
"@types/react": "^19.1.8",
"@types/react-dom": "^19.1.6",
"@vitejs/plugin-react": "^4.6.0",
"eslint": "^9.30.1",
"eslint-plugin-react-hooks": "^5.2.0",
"eslint-plugin-react-refresh": "^0.4.20",
"globals": "^16.3.0",
"typescript": "~5.8.3",
"typescript-eslint": "^8.35.1",
"vite": "^7.0.4"
}
}
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>
\ No newline at end of file
#root {
max-width: 1280px;
margin: 0 auto;
padding: 2rem;
text-align: center;
}
.logo {
height: 6em;
padding: 1.5em;
will-change: filter;
transition: filter 300ms;
}
.logo:hover {
filter: drop-shadow(0 0 2em #646cffaa);
}
.logo.react:hover {
filter: drop-shadow(0 0 2em #61dafbaa);
}
@keyframes logo-spin {
from {
transform: rotate(0deg);
}
to {
transform: rotate(360deg);
}
}
@media (prefers-reduced-motion: no-preference) {
a:nth-of-type(2) .logo {
animation: logo-spin infinite 20s linear;
}
}
.card {
padding: 2em;
}
.read-the-docs {
color: #888;
}
import { useState } from 'react'
import reactLogo from './assets/react.svg'
import viteLogo from '/vite.svg'
import './App.css'
function App() {
const [count, setCount] = useState(0)
return (
<>
<div>
<a href="https://vite.dev" target="_blank">
<img src={viteLogo} className="logo" alt="Vite logo" />
</a>
<a href="https://react.dev" target="_blank">
<img src={reactLogo} className="logo react" alt="React logo" />
</a>
</div>
<h1>Vite + React</h1>
<div className="card">
<button onClick={() => setCount((count) => count + 1)}>
count is {count}
</button>
<p>
Edit <code>src/App.tsx</code> and save to test HMR
</p>
</div>
<p className="read-the-docs">
Click on the Vite and React logos to learn more
</p>
</>
)
}
export default App
import axios from 'axios';
const api = axios.create({
baseURL: 'http://localhost:8000',
headers: {
'Content-Type': 'application/json',
},
});
// Auth services
export const authService = {
register: (data: { username: string; password: string; email: string }) =>
api.post('/auth/register', data),
login: (data: { username: string; password: string }) =>
api.post('/auth/login', data),
};
// Chart services
export const chartService = {
askAboutChart: (data: { chartId: string; question: string }) =>
api.post('/charts/ask', data),
analyzeChart: (data: { chartData: any }) =>
api.post('/charts/analyze', data),
};
// General services
export const appService = {
getRoot: () => api.get('/'),
};
\ No newline at end of file
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\ No newline at end of file
:root {
font-family: system-ui, Avenir, Helvetica, Arial, sans-serif;
line-height: 1.5;
font-weight: 400;
color-scheme: light dark;
color: rgba(255, 255, 255, 0.87);
background-color: #242424;
font-synthesis: none;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
}
a {
font-weight: 500;
color: #646cff;
text-decoration: inherit;
}
a:hover {
color: #535bf2;
}
body {
margin: 0;
display: flex;
place-items: center;
min-width: 320px;
min-height: 100vh;
}
h1 {
font-size: 3.2em;
line-height: 1.1;
}
button {
border-radius: 8px;
border: 1px solid transparent;
padding: 0.6em 1.2em;
font-size: 1em;
font-weight: 500;
font-family: inherit;
background-color: #1a1a1a;
cursor: pointer;
transition: border-color 0.25s;
}
button:hover {
border-color: #646cff;
}
button:focus,
button:focus-visible {
outline: 4px auto -webkit-focus-ring-color;
}
@media (prefers-color-scheme: light) {
:root {
color: #213547;
background-color: #ffffff;
}
a:hover {
color: #747bff;
}
button {
background-color: #f9f9f9;
}
}
import { StrictMode } from 'react'
import { createRoot } from 'react-dom/client'
import './index.css'
import App from './App.tsx'
createRoot(document.getElementById('root')!).render(
<StrictMode>
<App />
</StrictMode>,
)
import { useState } from 'react';
import { authService } from '../../services/api';
import { useNavigate } from 'react-router-dom';
export const Login = () => {
const [formData, setFormData] = useState({
username: '',
password: '',
});
const [error, setError] = useState('');
const navigate = useNavigate();
const handleSubmit = async (e: React.FormEvent) => {
e.preventDefault();
try {
const response = await authService.login(formData);
localStorage.setItem('token', response.data.token);
navigate('/charts');
} catch (err) {
setError('Invalid credentials');
}
};
return (
<div>
<h2>Login</h2>
{error && <p style={{ color: 'red' }}>{error}</p>}
<form onSubmit={handleSubmit}>
<input
type="text"
placeholder="Username"
value={formData.username}
onChange={(e) => setFormData({...formData, username: e.target.value})}
/>
<input
type="password"
placeholder="Password"
value={formData.password}
onChange={(e) => setFormData({...formData, password: e.target.value})}
/>
<button type="submit">Login</button>
</form>
</div>
);
};
\ No newline at end of file
/// <reference types="vite/client" />
{
"compilerOptions": {
"tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
"target": "ES2022",
"useDefineForClassFields": true,
"lib": ["ES2022", "DOM", "DOM.Iterable"],
"module": "ESNext",
"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"]
}
{
"files": [],
"references": [
{ "path": "./tsconfig.app.json" },
{ "path": "./tsconfig.node.json" }
]
}
{
"compilerOptions": {
"tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
"target": "ES2023",
"lib": ["ES2023"],
"module": "ESNext",
"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"]
}
import { defineConfig } from 'vite'
import react from '@vitejs/plugin-react'
// https://vite.dev/config/
export default defineConfig({
plugins: [react()],
})
......@@ -7,7 +7,7 @@ class LLMServicePort(ABC):
"""Port/Interface for LLM services"""
@abstractmethod
async def analyze_chart(self, request: LLMRequestDTO) -> LLMResponseDTO:
async def analyze(self, request: LLMRequestDTO) -> LLMResponseDTO:
"""
Analyze a chart image with a given question
......
......@@ -5,6 +5,7 @@ from src.application.dtos.analysis import AnalysisRequestDTO, AnalysisResponseDT
from src.application.ports.llm_service_port import LLMServicePort # Domain interface
import uuid
class AnalyzeService(AnalysisServicePort):
"""Concrete implementation of the analysis service"""
......
from ollama import Client
from src.application.ports.llm_service_port import LLMServicePort # Your existing interface
from src.application.dtos.LLM import LLMRequestDTO, LLMResponseDTO
import json
class OllamaService(LLMServicePort):
def __init__(self, host: str ):
self.client = Client(host=host)
async def analyze(self, request: LLMRequestDTO) -> LLMResponseDTO:
data = {
"Telecom": "Telecom",
"title": "Barclength = value amount",
"source": "chat.com",
"x_title": "Scale",
"y_title": "None",
"values": {
"Data Set 1": {
"Category B": "3.4",
"Category A": "4.7",
"Category A Telecom": "4.9",
"Category A Telecom Duplicate": "4.2" # Fixed duplicate key
},
"Data Set 2": {
"Category B": "2.6",
"Category A": "5.8",
"Category A Duplicate": "4.5", # Fixed duplicate key
"Category A Duplicate 2": "4.0" # Fixed duplicate key
},
"Data Set 3": {
"Category B": "2.9",
"Category A": "3.8",
"Category A Duplicate": "3.7", # Fixed duplicate key
"Category A Duplicate 2": "3.9" # Fixed duplicate key
}
}
}
# To convert to string:
data_string = json.dumps(data, indent=4)
response = self.client.chat(
model="llava:34b", # or "chartgemma" if available
messages=[{
"role": "user",
"content": f"having this python dictionary : {data_string} ,Analyze this chart (do not mention any python dictionary in your answer) : {request.question}\n"
}]
)
return LLMResponseDTO(
answer=response['message']['content'],
model_used="llava:34b",
processing_time=response.get('total_duration')
)
\ No newline at end of file
......@@ -14,6 +14,8 @@ from src.application.ports.llm_service_port import LLMServicePort
# from infrastructure.services.llm.openai_service import OpenAIService # Concrete LLM impl
# from infrastructure.services.image.pillow_service import PillowImageService # Concrete impl
from src.config import settings
from src.application.services.ollama_service import OllamaService
engine = create_async_engine(settings.DATABASE_URL, echo=True)
AsyncSessionLocal = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
......@@ -23,6 +25,11 @@ async def get_db_session() -> AsyncGenerator[AsyncSession, None]:
yield session
def get_llm_service() -> LLMServicePort:
return OllamaService(host="http://172.25.1.141:11434")
def get_user_repository(session: AsyncSession = Depends(get_db_session)) -> UserRepositoryPort:
return SqlUserRepository(session)
......@@ -50,14 +57,3 @@ def get_analysis_service() -> AnalyzeService:
# image_service = PillowImageService()
return AnalyzeService(llm_service)
def get_llm_service() -> LLMServicePort:
"""Dependency injection factory for LLMService"""
# Choose adapter based on config
# adapter = HuggingFaceAdapter(
# api_key=os.getenv("HF_API_KEY"),
# model_id="ahmed-masry/chartgemma"
# )
return LLMService()
\ No newline at end of file
from paddlex import create_model
model = create_model('PP-Chart2Table')
results = model.predict(
input={"image": "/home/zeinabrm/Documents/ChartToText/Project/ChartAnalyzer/multiset_barchart.png"},
batch_size=1
)
for res in results:
res.print()
res.save_to_json(f"./output/res.json")
# Available models: models=[Model(model='qwen2.5:latest', modified_at=datetime.datetime(2025, 4, 20, 17, 56, 38, 480761, tzinfo=TzInfo(UTC)), digest='845dbda0ea48ed749caafd9e6037047aa19acfcfd82e704d7ca97d631a0b697e', size=4683087332, details=ModelDetails(parent_model='', format='gguf', family='qwen2', families=['qwen2'], parameter_size='7.6B', quantization_level='Q4_K_M'))
# , Model(model='almaghrabima/ALLaM-Thinking:latest', modified_at=datetime.datetime(2025, 3, 20, 19, 42, 49, 644450, tzinfo=TzInfo(UTC)), digest='dd366456e63970b19d414a5fcf6e210d25d3e754eb797aac1e8850885e93f365', size=4263195351, details=ModelDetails(parent_model='', format='gguf', family='llama', families=['llama'], parameter_size='7.0B', quantization_level='Q4_K_M')),
# Model(model='gemma3:27b', modified_at=datetime.datetime(2025, 3, 12, 12, 33, 20, 925514, tzinfo=TzInfo(UTC)), digest='30ddded7fba6d6f9c2f26661e2feba2d7a26a75e20a817538c41c3716d92609d', size=17396936887, details=ModelDetails(parent_model='', format='gguf', family='gemma3', families=['gemma3'], parameter_size='27.4B', quantization_level='Q4_K_M')),
# Model(model='command-r7b-arabic:latest', modified_at=datetime.datetime(2025, 3, 12, 7, 29, 8, 634445, tzinfo=TzInfo(UTC)), digest='4bbe3353e56a7bad7512de135cf875f8cd31b10cd2310c257ce5d4f98a43fe9e', size=5057031326, details=ModelDetails(parent_model='', format='gguf', family='cohere2', families=['cohere2'], parameter_size='8.0B', quantization_level='Q4_K_M')),
# Model(model='llava:34b', modified_at=datetime.datetime(2025, 2, 12, 13, 32, 11, 449775, tzinfo=TzInfo(UTC)), digest='3d2d24f4667475bd28d515495b0dcc03b5a951be261a0babdb82087fc11620ee', size=20166497526, details=ModelDetails(parent_model='', format='gguf', family='llama', families=['llama', 'clip'], parameter_size='34B', quantization_level='Q4_0')),
# Model(model='codestral:latest', modified_at=datetime.datetime(2025, 2, 4, 15, 23, 15, 358294, tzinfo=TzInfo(UTC)), digest='0898a8b286d56d8105587049fec69634fce83c957230fc13f0acfe03b7b11909', size=12569170438, details=ModelDetails(parent_model='', format='gguf', family='llama', families=['llama'], parameter_size='22.2B', quantization_level='Q4_0')),
# Model(model='qwen2.5-coder:32b', modified_at=datetime.datetime(2025, 2, 4, 8, 57, 6, 569891, tzinfo=TzInfo(UTC)), digest='4bd6cbf2d094264457a17aab6bd6acd1ed7a72fb8f8be3cfb193f63c78dd56df', size=19851349856, details=ModelDetails(parent_model='', format='gguf', family='qwen2', families=['qwen2'], parameter_size='32.8B', quantization_level='Q4_K_M')),
# Model(model='mistral-small:latest', modified_at=datetime.datetime(2025, 2, 3, 16, 24, 20, 151181, tzinfo=TzInfo(UTC)), digest='8039dd90c1138d772437a0779a33b7349efd5d9cca71edcd26e4dd463f90439d', size=14333921662, details=ModelDetails(parent_model='', format='gguf', family='llama', families=['llama'], parameter_size='23.6B', quantization_level='Q4_K_M')),
# Model(model='deepseek-r1:14b', modified_at=datetime.datetime(2025, 2, 3, 8, 46, 0, 433369, tzinfo=TzInfo(UTC)), digest='ea35dfe18182f635ee2b214ea30b7520fe1ada68da018f8b395b444b662d4f1a', size=8988112040, details=ModelDetails(parent_model='', format='gguf', family='qwen2', families=['qwen2'], parameter_size='14.8B', quantization_level='Q4_K_M'))]
#
\ No newline at end of file
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