| Name | ingenious JSON |
| Version |
0.1.3
JSON |
| download |
| home_page | None |
| Summary | An enterprise-grade Python library for quickly setting up APIs to interact with AI Agents |
| upload_time | 2025-07-10 05:25:41 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.13 |
| license | MIT |
| keywords |
agent
autogen
azure
fastapi
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Insight Ingenious
An enterprise-grade Python library for quickly setting up APIs to interact with AI Agents, featuring tight integrations with Microsoft Azure services and comprehensive utilities for debugging and customization.
## Quick Start
Get up and running in 5 minutes with Azure OpenAI!
### Prerequisites
- Python 3.13+
- Azure OpenAI API credentials
- [uv package manager](https://docs.astral.sh/uv/)
### 5-Minute Setup
1. **Install and Initialize**:
```bash
# From your project directory
uv add ingenious
uv run ingen init
```
2. **Configure Credentials**:
#### For Linux-based Environments
```bash
# Edit .env with your Azure OpenAI credentials
cp .env.example .env
nano .env # Add AZURE_OPENAI_API_KEY and AZURE_OPENAI_BASE_URL
```
#### For Windows-based Environments
```bash
# Edit .env with your Azure OpenAI credentials
cp .env.example .env
# Assuming you have VSCode installation. If none, open .env file with your favorite editor
# and add AZURE_OPENAI_API_KEY and AZURE_OPENAI_BASE_URL to it.
code .env # Add AZURE_OPENAI_API_KEY and AZURE_OPENAI_BASE_URL
```
3. **Validate Setup** (Recommended):
#### For Linux-based Environments
```bash
export INGENIOUS_PROJECT_PATH=$(pwd)/config.yml
export INGENIOUS_PROFILE_PATH=$(pwd)/profiles.yml
uv run ingen validate # Check configuration before starting
```
#### For Windows-based Environments
```bash
$env:INGENIOUS_PROJECT_PATH = "{your_project_folder}/config.yml"
$env:INGENIOUS_PROFILE_PATH = "{profile_folder_location}/profiles.yml"
uv run ingen validate # Check configuration before starting
```
4. **Start the Server**:
```bash
uv run ingen serve
```
5. **Verify Health**:
```bash
# Check server health
curl http://localhost:80/api/v1/health
```
6. **Test the API**:
```bash
# Test bike insights workflow (the "Hello World" of Ingenious)
curl -X POST http://localhost:80/api/v1/chat \
-H "Content-Type: application/json" \
-d '{
"user_prompt": "{\"stores\": [{\"name\": \"QuickStart Store\", \"location\": \"NSW\", \"bike_sales\": [{\"product_code\": \"QS-001\", \"quantity_sold\": 1, \"sale_date\": \"2023-04-15\", \"year\": 2023, \"month\": \"April\", \"customer_review\": {\"rating\": 5.0, \"comment\": \"Perfect bike for getting started!\"}}], \"bike_stock\": []}], \"revision_id\": \"quickstart-1\", \"identifier\": \"hello-world\"}",
"conversation_flow": "bike-insights"
}'
```
That's it! You should see a comprehensive JSON response with insights from multiple AI agents analyzing the bike sales data.
**Note**: The `bike-insights` workflow is created when you run `ingen init` - it's part of the project template setup, not included in the core library. You can now build on `bike-insights` as a template for your specific use case.
## Workflow Categories
Insight Ingenious provides multiple conversation workflows with different configuration requirements:
### Core Workflows (Available in library)
- `classification-agent` - Route input to specialized agents based on content (Azure OpenAI only)
- `knowledge-base-agent` - Search knowledge bases using local ChromaDB (stable local implementation)
- `sql-manipulation-agent` - Execute SQL queries using local SQLite (stable local implementation)
### Extension Template Workflows (Available via project template)
- `bike-insights` - Comprehensive bike sales analysis showcasing multi-agent coordination (created when you run `ingen init`)
> **Note**: Only local implementations (ChromaDB for knowledge-base-agent, SQLite for sql-manipulation-agent) are currently stable. Azure Search and Azure SQL integrations are experimental and may contain bugs.
## Project Structure
- `ingenious/`: Core framework code
- `api/`: API endpoints and routes
- `chainlit/`: Web UI components
- `config/`: Configuration management
- `core/`: Core logging and utilities
- `dataprep/`: Data preparation utilities
- `db/`: Database integration
- `document_processing/`: Document analysis and processing
- `errors/`: Error handling and custom exceptions
- `external_services/`: External service integrations
- `files/`: File storage utilities
- `models/`: Data models and schemas
- `services/`: Core services including chat and agent services
- `templates/`: Prompt templates and HTML templates
- `utils/`: Utility functions
- `ingenious_extensions_template/`: Template for custom extensions
- `api/`: Custom API routes
- `models/`: Custom data models
- `sample_data/`: Sample data for testing
- `services/`: Custom agent services
- `templates/`: Custom prompt templates
- `tests/`: Test harness for agent prompts
- `ingenious_prompt_tuner/`: Tool for tuning and testing prompts
## Documentation
For detailed documentation, see the [docs](https://blog.insight-services-apac.dev/ingenious/):
## Contributing
Contributions are welcome! Please see [CONTRIBUTING.md](https://github.com/Insight-Services-APAC/ingenious/blob/main/CONTRIBUTING.md) for guidelines.
## License
This project is licensed under the terms specified in the [LICENSE](https://github.com/Insight-Services-APAC/ingenious/blob/main/LICENSE) file.
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If none, open .env file with your favorite editor\n # and add AZURE_OPENAI_API_KEY and AZURE_OPENAI_BASE_URL to it.\n code .env # Add AZURE_OPENAI_API_KEY and AZURE_OPENAI_BASE_URL\n ```\n\n3. **Validate Setup** (Recommended):\n #### For Linux-based Environments\n ```bash\n export INGENIOUS_PROJECT_PATH=$(pwd)/config.yml\n export INGENIOUS_PROFILE_PATH=$(pwd)/profiles.yml\n uv run ingen validate # Check configuration before starting\n ```\n\n #### For Windows-based Environments\n ```bash\n $env:INGENIOUS_PROJECT_PATH = \"{your_project_folder}/config.yml\"\n $env:INGENIOUS_PROFILE_PATH = \"{profile_folder_location}/profiles.yml\" \n uv run ingen validate # Check configuration before starting\n ```\n\n4. **Start the Server**:\n ```bash\n uv run ingen serve\n ```\n\n5. **Verify Health**:\n ```bash\n # Check server health\n curl http://localhost:80/api/v1/health\n ```\n\n6. **Test the API**:\n ```bash\n # Test bike insights workflow (the \"Hello World\" of Ingenious)\n curl -X POST http://localhost:80/api/v1/chat \\\n -H \"Content-Type: application/json\" \\\n -d '{\n \"user_prompt\": \"{\\\"stores\\\": [{\\\"name\\\": \\\"QuickStart Store\\\", \\\"location\\\": \\\"NSW\\\", \\\"bike_sales\\\": [{\\\"product_code\\\": \\\"QS-001\\\", \\\"quantity_sold\\\": 1, \\\"sale_date\\\": \\\"2023-04-15\\\", \\\"year\\\": 2023, \\\"month\\\": \\\"April\\\", \\\"customer_review\\\": {\\\"rating\\\": 5.0, \\\"comment\\\": \\\"Perfect bike for getting started!\\\"}}], \\\"bike_stock\\\": []}], \\\"revision_id\\\": \\\"quickstart-1\\\", \\\"identifier\\\": \\\"hello-world\\\"}\",\n \"conversation_flow\": \"bike-insights\"\n }'\n ```\n\nThat's it! You should see a comprehensive JSON response with insights from multiple AI agents analyzing the bike sales data.\n\n**Note**: The `bike-insights` workflow is created when you run `ingen init` - it's part of the project template setup, not included in the core library. You can now build on `bike-insights` as a template for your specific use case.\n\n## Workflow Categories\n\nInsight Ingenious provides multiple conversation workflows with different configuration requirements:\n\n### Core Workflows (Available in library)\n- `classification-agent` - Route input to specialized agents based on content (Azure OpenAI only)\n- `knowledge-base-agent` - Search knowledge bases using local ChromaDB (stable local implementation)\n- `sql-manipulation-agent` - Execute SQL queries using local SQLite (stable local implementation)\n\n### Extension Template Workflows (Available via project template)\n- `bike-insights` - Comprehensive bike sales analysis showcasing multi-agent coordination (created when you run `ingen init`)\n\n> **Note**: Only local implementations (ChromaDB for knowledge-base-agent, SQLite for sql-manipulation-agent) are currently stable. 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Please see [CONTRIBUTING.md](https://github.com/Insight-Services-APAC/ingenious/blob/main/CONTRIBUTING.md) for guidelines.\n\n## License\n\nThis project is licensed under the terms specified in the [LICENSE](https://github.com/Insight-Services-APAC/ingenious/blob/main/LICENSE) file.\n",
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