diff --git a/.env-example b/.env-example
new file mode 100644
index 0000000..82b581a
--- /dev/null
+++ b/.env-example
@@ -0,0 +1,17 @@
+DATABASE_URL=
+SECRET_KEY=
+
+AWS_ACCESS_KEY_ID=
+AWS_ENDPOINT_URL_S3=
+AWS_REGION=
+AWS_SECRET_ACCESS_KEY=
+BUCKET_NAME=
+
+CORS_ORIGINS=
+FORWARDED_ALLOW_IPS=
+
+GOOGLE_API_KEY=
+TOGETHER_API_KEY=
+HYPERBOLIC_API_KEY=
+
+AUTH_TOKEN=
\ No newline at end of file
diff --git a/README.md b/README.md
index 2c50d74..bfd28cf 100644
--- a/README.md
+++ b/README.md
@@ -1,3 +1,123 @@
+# VisuLinx API
+
+A robust FastAPI-based backend service for managing organizations, projects, and file processing with secure authentication.
+
+## 🚀 Features
+
+- **User Management**: Secure user authentication and authorization
+- **Organization Management**: Create and manage organizations with multiple users
+- **Project Management**: Organize work into projects within organizations
+- **File Processing**: Handle file uploads with S3 integration
+- **Preferences System**: Flexible system-wide preferences management
+- **RESTful API**: Modern, fast, and well-documented API endpoints
+- **CORS Support**: Configured for cross-origin resource sharing
+
+## 🏗 Project Structure
+
+```
+app/
+├── api.py # FastAPI application configuration
+├── database.py # Database connection and settings
+├── models.py # SQLAlchemy ORM models
+├── routers/ # API route handlers
+├── schemas.py # Pydantic models for request/response
+├── security.py # Authentication and authorization
+├── services/ # Business logic services
+└── settings.py # Application settings
+```
+
+## 🔧 Technical Stack
+
+- **Framework**: FastAPI
+- **Database**: SQLAlchemy ORM
+- **Authentication**: JWT-based authentication
+- **Storage**: AWS S3 integration
+- **Data Validation**: Pydantic
+- **API Documentation**: Automatic OpenAPI/Swagger docs
+
+## 💻 Key Components
+
+### Models
+- **User**: Manages user accounts and authentication
+- **Organization**: Handles multi-user organizations
+- **Project**: Organizes work within organizations
+- **File**: Manages file uploads and processing
+- **Preference**: Stores system-wide preferences
+
+### API Endpoints
+- `/users`: User management endpoints
+- `/auth`: Authentication endpoints
+- `/organizations`: Organization management
+- `/projects`: Project-related operations
+- `/preferences`: System preferences management
+
+### 🤖 AI Services
+
+The project integrates with multiple AI providers for advanced image analysis and object detection:
+
+#### Supported AI Providers
+- **Together AI**: Uses the Qwen2-VL-72B-Instruct model for high-quality visual analysis
+- **Hyperbolic AI**: Implements the same Qwen model through a different API endpoint
+- **Google Gemini**: Utilizes Gemini 1.5 Pro for advanced image processing
+
+#### Features
+- **Object Detection**: Extract bounding boxes for objects in images
+- **Image Processing**: Automatic image resizing and compression for optimal AI processing
+- **Multi-Provider Support**: Fallback options across different AI services
+- **Standardized Interface**: Consistent API across all providers through the `AiService` abstract base class
+
+#### Configuration
+The AI services require the following environment variables:
+```
+GOOGLE_API_KEY= # For Gemini AI
+TOGETHER_API_KEY= # For Together AI
+HYPERBOLIC_API_KEY= # For Hyperbolic AI
+```
+
+## 🔒 Security Features
+
+- Secure password hashing
+- JWT token-based authentication
+- Role-based access control
+- CORS middleware configuration
+
+## 🚀 Getting Started
+
+### Prerequisites
+
+- Python >= 3.13
+- uv (Python package installer)
+
+### Installation
+
+1. Clone the repository
+2. Install dependencies using uv:
+ ```bash
+ uv sync
+ ```
+3. Configure environment variables
+4. Run the application:
+ ```bash
+ uv run fastapi dev
+ ```
+
+## 📝 API Documentation
+
+Once the server is running, access the API documentation at:
+- Swagger UI: `http://localhost:8000/docs`
+
+## 🤝 Contributing
+
+1. Fork the repository
+2. Create a feature branch
+3. Commit your changes
+4. Push to the branch
+5. Create a Pull Request
+
+## 📄 License
+
+MIT License
+
## Autogenerate migration
```sh
@@ -8,4 +128,3 @@ uv run alembic revision --autogenerate -m "add ... table"
```sh
python -c "import secrets; print(secrets.token_urlsafe(32))"
-```
diff --git a/app/routers/projects.py b/app/routers/projects.py
index 16c2336..68a03d7 100644
--- a/app/routers/projects.py
+++ b/app/routers/projects.py
@@ -1,4 +1,5 @@
import asyncio
+import json
import logging
from datetime import datetime
from http import HTTPStatus
@@ -14,26 +15,28 @@
Response,
UploadFile,
)
-from sqlalchemy import select
+from sqlalchemy import func, select
from sqlalchemy.orm import Session
from app.database import get_session
-from app.models import File, Organization, Project, User
-from app.schemas import FileSchema, ProjectList, ProjectPublic, ProjectSchema
+from app.models import File, Organization, Preference, Project, User
+from app.schemas import (
+ FileSchema,
+ ProjectList,
+ ProjectPublic,
+ ProjectPublicList,
+ ProjectSchema,
+)
from app.security import get_current_user
-from app.services.document_service import process
+from app.services import ai_service, document_service
from app.services.upload_service import (
delete_file_from_s3,
get_download_url,
upload_file_to_s3,
)
-from app.settings import Settings
logger = logging.getLogger(__name__)
-settings = Settings.model_validate({})
-
-
router = APIRouter(
prefix='/organizations/{organization_id}/projects', tags=['projects']
)
@@ -97,7 +100,25 @@ def list_organization_projects(
Project.deleted_at.is_(None),
)
).all()
- return {'projects': projects}
+
+ project_list = []
+ for project in projects:
+ file_count = session.scalar(
+ select(func.count()).where(File.project_id == project.id)
+ )
+ if project.organization_id:
+ project_list.append(
+ ProjectPublicList(
+ id=project.id,
+ name=project.name,
+ description=project.description,
+ organization_id=project.organization_id,
+ created_at=project.created_at,
+ file_count=file_count or 0,
+ )
+ )
+
+ return {'projects': project_list}
@router.post('/', response_model=ProjectPublic, status_code=HTTPStatus.CREATED)
@@ -236,7 +257,7 @@ async def upload( # noqa: PLR0913, PLR0917
for result, download_url in zip(results, download_urls):
if result and result.id and result.mime_type == 'application/pdf':
background_tasks.add_task(
- process,
+ document_service.extract_text,
download_url,
result.id,
session,
@@ -341,3 +362,85 @@ async def download_file(
download_url = await get_download_url(file.path, file.original_filename)
return {'download_url': download_url}
+
+
+@router.get(
+ '/{project_id}/files/{file_id}/extract_bounding_boxes',
+ response_model=ai_service.DetectedObjectListSchema,
+)
+async def extract_bounding_boxes(
+ organization_id: UUID,
+ project_id: UUID,
+ file_id: UUID,
+ user: CurrentUser,
+ session: DbSession,
+):
+ _ = get_project(session, user, organization_id, project_id)
+
+ preferences = {
+ pref.key: pref.value
+ for pref in session.scalars(
+ select(Preference).where(
+ Preference.key.in_(['system_prompt', 'assistant_prompt'])
+ )
+ ).all()
+ }
+
+ image_file = session.scalar(
+ select(File).where(
+ File.id == file_id,
+ File.project_id == project_id,
+ )
+ )
+ if not image_file:
+ raise HTTPException(
+ status_code=HTTPStatus.NOT_FOUND,
+ detail='File not found.',
+ )
+
+ if not image_file.mime_type.startswith('image'):
+ raise HTTPException(
+ status_code=HTTPStatus.BAD_REQUEST,
+ detail='File is not an image.',
+ )
+
+ download_url = await get_download_url(
+ image_file.path, image_file.original_filename
+ )
+
+ documents = session.scalars(
+ select(File).where(
+ File.project_id == project_id,
+ File.mime_type == 'application/pdf',
+ File.processed_at.isnot(None),
+ )
+ ).all()
+
+ if not documents:
+ raise HTTPException(
+ status_code=HTTPStatus.BAD_REQUEST,
+ detail='No PDF documents found in project.',
+ )
+
+ document_contents = {
+ document.original_filename: document.contents
+ for document in documents
+ if document.contents is not None
+ }
+
+ ai = ai_service.GeminiAiService()
+
+ bounding_boxes = ai.extract_bounding_boxes(
+ image_url=download_url,
+ document_contents=document_contents,
+ system_prompt=preferences['system_prompt'],
+ assistant_prompt=preferences['assistant_prompt'],
+ )
+
+ # image_file.contents = str(bounding_boxes)
+ image_file.contents = json.dumps(bounding_boxes)
+ image_file.processed_at = datetime.now()
+ session.commit()
+ session.refresh(image_file)
+
+ return bounding_boxes
diff --git a/app/schemas.py b/app/schemas.py
index 821cbeb..b13af41 100644
--- a/app/schemas.py
+++ b/app/schemas.py
@@ -24,6 +24,7 @@ class FilePublic(BaseModel):
size: int
mime_type: str
original_filename: str
+ contents: str | None
created_at: datetime
updated_at: datetime
processed_at: datetime | None
@@ -49,8 +50,18 @@ class ProjectPublic(BaseModel):
model_config = ConfigDict(from_attributes=True)
+class ProjectPublicList(BaseModel):
+ id: UUID
+ name: str
+ description: str
+ organization_id: UUID
+ created_at: datetime
+ file_count: int
+ model_config = ConfigDict(from_attributes=True)
+
+
class ProjectList(BaseModel):
- projects: list[ProjectPublic]
+ projects: list[ProjectPublicList]
class OrganizationBasic(BaseModel):
diff --git a/app/services/ai_service.py b/app/services/ai_service.py
new file mode 100644
index 0000000..87ab857
--- /dev/null
+++ b/app/services/ai_service.py
@@ -0,0 +1,331 @@
+import base64
+import json
+import os
+from abc import ABC, abstractmethod
+from io import BytesIO
+
+import google.generativeai as genai
+import openai
+import requests
+from dotenv import load_dotenv
+from openai.types.chat import ChatCompletion
+from together import Together
+from together.types import ChatCompletionResponse
+from typing_extensions import TypedDict
+
+# Ensure environment variables are loaded at the very beginning
+load_dotenv(override=True)
+
+
+class DetectedObjectSchema(TypedDict):
+ name: str
+ bounding_boxes: list[int]
+
+
+class DetectedObjectListSchema(TypedDict):
+ objects: list[DetectedObjectSchema]
+
+
+class AiService(ABC):
+ @abstractmethod
+ def extract_bounding_boxes(
+ self,
+ image_url: str,
+ document_contents: dict[str, str],
+ system_prompt: str,
+ assistant_prompt: str,
+ ) -> DetectedObjectListSchema:
+ pass
+
+ @staticmethod
+ def resize_and_compress_image(
+ image_path: str,
+ max_width: int = 1000,
+ quality: int = 95,
+ ) -> BytesIO:
+ from PIL import Image # noqa: PLC0415
+
+ """Resize and compress the input image."""
+ with Image.open(image_path) as img:
+ image = img
+
+ # Convert to RGB if necessary
+ if image.mode != 'RGB':
+ image = image.convert('RGB')
+
+ # Calculate new dimensions
+ width, height = image.size
+ if width > max_width:
+ height = int((height * max_width) / width)
+ width = max_width
+
+ # Resize image
+ image = image.resize((width, height), Image.Resampling.LANCZOS)
+
+ # Save compressed image to BytesIO
+ buffer = BytesIO()
+ image.save(buffer, format='JPEG', quality=quality)
+ buffer.seek(0)
+
+ return buffer
+
+
+class TogetherAiService(AiService):
+ def __init__(self) -> None:
+ self.together_api_key = os.getenv('TOGETHER_API_KEY')
+ self.model = 'Qwen/Qwen2-VL-72B-Instruct'
+ self.client = Together(api_key=self.together_api_key)
+
+ if not self.together_api_key:
+ raise ValueError('Please set TOGETHER_API_KEY in the .env file')
+
+ def extract_bounding_boxes(
+ self,
+ image_url: str,
+ document_contents: dict[str, str],
+ system_prompt: str,
+ assistant_prompt: str,
+ ) -> DetectedObjectListSchema:
+ image_path = 'image.jpg'
+ with open(image_path, 'wb') as f:
+ response = requests.get(image_url)
+ f.write(response.content)
+
+ image_buffer = self.resize_and_compress_image(image_path)
+ image_data = base64.b64encode(image_buffer.getvalue()).decode('utf-8')
+
+ modified_system_prompt = (
+ """You are a helpful assistant to detect objects in images. When
+ asked to detect elements you return bounding boxes in the form of
+ [xmin, ymin, xmax, ymax] with the values being scaled to match the
+ 1024x1024 size. """
+ # + system_prompt
+ + """Always respond in JSON format with an object with a key
+ 'objects' that contains a list of objects where each object has the
+ following keys: 'bounding_boxes' and 'name'. Here's an example of
+ what the object must look like:
+ {
+ "objects": [
+ {
+ "bounding_boxes": [435, 595, 704, 710],
+ "name": "electric car"
+ },
+ {
+ "bounding_boxes": [300, 450, 665, 610],
+ "name": "house"
+ }
+ ]
+ }
+ """
+ )
+
+ prompt = assistant_prompt
+
+ # Add the document contents to the prompt
+ for key, value in document_contents.items():
+ prompt += (
+ '\n\n'
+ f'{key}'
+ f'{value}'
+ ''
+ )
+
+ response = self.client.chat.completions.create(
+ model=self.model,
+ messages=[
+ {
+ 'role': 'system',
+ 'content': modified_system_prompt,
+ },
+ {
+ 'role': 'user',
+ 'content': [
+ {'type': 'text', 'text': prompt},
+ {
+ 'type': 'image_url',
+ 'image_url': {
+ 'url': f'data:image/jpeg;base64,{image_data}',
+ },
+ },
+ ],
+ },
+ ],
+ )
+
+ if (
+ type(response) is not ChatCompletionResponse
+ or response.choices is None
+ or len(response.choices) <= 0
+ or response.choices[0].message is None
+ or type(response.choices[0].message.content) is not str
+ ):
+ raise ValueError('Invalid response from Together API')
+
+ info = response.choices[0].message.content
+ print(info)
+
+ # Remove markdown code block delimiters if present
+ info = info.replace('```json', '').replace('```', '').strip()
+ return json.loads(info)
+
+
+class HyperbolicAiService(AiService):
+ def __init__(self) -> None:
+ self.hyperbolic_api_key = os.getenv('HYPERBOLIC_API_KEY')
+ self.model = 'Qwen/Qwen2-VL-72B-Instruct'
+ self.client = openai.OpenAI(
+ api_key=self.hyperbolic_api_key,
+ base_url='https://api.hyperbolic.xyz/v1',
+ )
+ if not self.hyperbolic_api_key:
+ raise ValueError('Please set HYPERBOLIC_API_KEY in the .env file')
+
+ def extract_bounding_boxes(
+ self,
+ image_url: str,
+ document_contents: dict[str, str],
+ system_prompt: str,
+ assistant_prompt: str,
+ ) -> DetectedObjectListSchema:
+ image_path = 'image.jpg'
+ with open(image_path, 'wb') as f:
+ img_response = requests.get(image_url)
+ f.write(img_response.content)
+
+ image_buffer = self.resize_and_compress_image(image_path)
+ image_data = base64.b64encode(image_buffer.getvalue()).decode('utf-8')
+
+ modified_system_prompt = """You are a helpful assistant that precisely
+ detects objects in images. When asked to detect objects, you return
+ bounding boxes in the form of [xmin, ymin, xmax, ymax] with the
+ values being scaled to match the 1024x1024 size.
+ Always respond in JSON format with an object with a key
+ 'objects' that contains a list of objects where each object has the
+ following keys: 'bounding_boxes' and 'name'. Here's an example of
+ what the object must look like:
+ {
+ "objects": [
+ {
+ "bounding_boxes": [xmin, ymin, xmax, ymax],
+ "name": "object1"
+ },
+ {
+ "bounding_boxes": [xmin, ymin, xmax, ymax],
+ "name": "object2"
+ }
+ ]
+ }
+ """
+
+ prompt = """Detect all objects in this image and provide
+ bounding boxes for each of them.
+ """
+
+ # Add the document contents to the prompt
+ # for key, value in document_contents.items():
+ # prompt += (
+ # '\n\n'
+ # f'{key}'
+ # f'{value}'
+ # ''
+ # )
+
+ response = self.client.chat.completions.create(
+ model=self.model,
+ messages=[
+ {
+ 'role': 'system',
+ 'content': modified_system_prompt,
+ },
+ {
+ 'role': 'user',
+ 'content': [
+ {'type': 'text', 'text': prompt},
+ {
+ 'type': 'image_url',
+ 'image_url': {
+ 'url': f'data:image/jpeg;base64,{image_data}',
+ },
+ },
+ ],
+ },
+ ],
+ )
+
+ if (
+ type(response) is not ChatCompletion
+ or response.choices is None
+ or len(response.choices) <= 0
+ or response.choices[0].message is None
+ or type(response.choices[0].message.content) is not str
+ ):
+ raise ValueError('Invalid response from Hyperbolic API')
+
+ info = response.choices[0].message.content
+ print(info)
+
+ # Remove markdown code block delimiters if present
+ info = info.replace('```json', '').replace('```', '').strip()
+ return json.loads(info)
+
+
+class GeminiAiService(AiService):
+ def __init__(self) -> None:
+ self.gemini_api_key = os.getenv('GOOGLE_API_KEY')
+ self.model_name = 'gemini-1.5-pro-latest'
+
+ if not self.gemini_api_key:
+ raise ValueError('Please set GOOGLE_API_KEY in the .env file')
+
+ def extract_bounding_boxes(
+ self,
+ image_url: str,
+ document_contents: dict[str, str],
+ system_prompt: str,
+ assistant_prompt: str,
+ ) -> DetectedObjectListSchema:
+ image_path = 'image.jpg'
+ with open(image_path, 'wb') as f:
+ response = requests.get(image_url)
+ f.write(response.content)
+
+ image_buffer = self.resize_and_compress_image(image_path)
+ image_data = base64.b64encode(image_buffer.getvalue()).decode('utf-8')
+
+ # Create the image part for gemini request
+ image_part = {'mime_type': 'image/jpeg', 'data': image_data}
+
+ prompt = assistant_prompt
+
+ # Add the document contents to the prompt
+ for key, value in document_contents.items():
+ prompt += (
+ '\n\n'
+ f'{key}'
+ f'{value}'
+ ''
+ )
+
+ contents = [
+ {'inline_data': image_part},
+ {'text': prompt},
+ ]
+
+ # Initialize the model
+ model = genai.GenerativeModel(
+ model_name=self.model_name,
+ system_instruction=system_prompt,
+ )
+
+ # Generate response
+ response = model.generate_content(
+ contents,
+ generation_config=genai.GenerationConfig(
+ response_mime_type='application/json',
+ response_schema=DetectedObjectListSchema,
+ temperature=0.05,
+ ),
+ )
+
+ # Return decoded json
+ return json.loads(response.text)
diff --git a/app/services/document_service.py b/app/services/document_service.py
index c1fc033..5afc736 100644
--- a/app/services/document_service.py
+++ b/app/services/document_service.py
@@ -11,7 +11,7 @@
load_dotenv()
-async def process(document_url: str, file_id: UUID, session: Session):
+async def extract_text(document_url: str, file_id: UUID, session: Session):
"""
Process the uploaded file by making an HTTP POST request and update the
contents field.
diff --git a/app/services/upload_service.py b/app/services/upload_service.py
index 22e14fb..7f16242 100644
--- a/app/services/upload_service.py
+++ b/app/services/upload_service.py
@@ -77,7 +77,9 @@ async def delete_file_from_s3(file_path: str) -> None:
)
-async def get_download_url(file_path: str, original_filename: str) -> str:
+async def get_download_url(
+ file_path: str, original_filename: str | None = None
+) -> str:
if not file_path:
raise HTTPException(
status_code=HTTPStatus.BAD_REQUEST,
@@ -85,14 +87,18 @@ async def get_download_url(file_path: str, original_filename: str) -> str:
)
s3: S3Client = boto3.client('s3')
+ params = {
+ 'Bucket': settings.BUCKET_NAME,
+ 'Key': file_path,
+ }
+ if original_filename:
+ params['ResponseContentDisposition'] = (
+ f'attachment; filename="{original_filename}"' # noqa: E501
+ )
try:
url = s3.generate_presigned_url(
'get_object',
- Params={
- 'Bucket': settings.BUCKET_NAME,
- 'Key': file_path,
- 'ResponseContentDisposition': f'attachment; filename="{original_filename}"', # noqa: E501
- },
+ Params=params,
ExpiresIn=60, # URL expires in 60 seconds
)
return url
diff --git a/pyproject.toml b/pyproject.toml
index 63e8ff7..5d161f5 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -20,7 +20,11 @@ dependencies = [
"testcontainers>=4.8.2",
"python-magic>=0.4.27",
"pytest-asyncio>=0.24.0",
- "modal>=0.67.9",
+ "google-generativeai>=0.8.3",
+ "pillow<11.0.0",
+ "types-requests>=2.32.0.20241016",
+ "together>=1.3.14",
+ "openai>=1.61.0",
]
[dependency-groups]
diff --git a/tests/test_projects.py b/tests/test_projects.py
index 50e5d22..8014f3e 100644
--- a/tests/test_projects.py
+++ b/tests/test_projects.py
@@ -245,7 +245,7 @@ def test_upload_file(
with (
patch('app.routers.projects.upload_file_to_s3') as mock_upload,
patch('app.routers.projects.get_download_url'),
- patch('app.routers.projects.process'),
+ patch('app.routers.projects.document_service.extract_text'),
):
mock_upload.return_value = FileSchema(
path='mocked/path/to/test.pdf',
diff --git a/uv.lock b/uv.lock
index da4fd2e..4da861d 100644
--- a/uv.lock
+++ b/uv.lock
@@ -12,7 +12,7 @@ wheels = [
[[package]]
name = "aiohttp"
-version = "3.11.8"
+version = "3.11.11"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "aiohappyeyeballs" },
@@ -23,35 +23,35 @@ dependencies = [
{ name = "propcache" },
{ name = "yarl" },
]
-sdist = { url = "https://files.pythonhosted.org/packages/2c/e5/c7ad0689e8ab74c3ec9bf20e0f667e1278b3738ae19ae3fed21e6a0543ca/aiohttp-3.11.8.tar.gz", hash = "sha256:7bc9d64a2350cbb29a9732334e1a0743cbb6844de1731cbdf5949b235653f3fd", size = 7667904 }
+sdist = { url = "https://files.pythonhosted.org/packages/fe/ed/f26db39d29cd3cb2f5a3374304c713fe5ab5a0e4c8ee25a0c45cc6adf844/aiohttp-3.11.11.tar.gz", hash = "sha256:bb49c7f1e6ebf3821a42d81d494f538107610c3a705987f53068546b0e90303e", size = 7669618 }
wheels = [
- { url = "https://files.pythonhosted.org/packages/56/12/97a55a4fe36a68e6e51749c2edd546b4792bc47039d78b766273d91178af/aiohttp-3.11.8-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a81525430da5ca356fae6e889daeb6f5cc0d5f0cef88e59cdde48e2394ea1365", size = 696879 },
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