semvec/pypi-packages huggingface dataset:
modulitiz-mini 2.11.2
Raccolta dei miei moduli - versione mini
Requires Python: >=3.11

# modulitiz-mini

It's a Python library that contains daily use or generic functions.  
The difference between "micro" is that it requires other dependencies.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install:

```bash
pip install -U modulitiz_mini
```
The other required dependencies will be installed automatically.

## Usage

```python
from modulitiz_mini.ModuloRsa import ModuloRsa

moduloRsa=ModuloRsa()
moduloRsa.generateKeys()

# returns cripted string
moduloRsa.encrypt("test")
...
```

## Contributing

If you find any bug you can write me at [sderfo1234@altervista.org](mailto:sderfo1234@altervista.org)

## License

[MIT](https://choosealicense.com/licenses/mit/)
flow-platform-sdk 1.0.0
Python SDK for Uniphore Flow Platform APIs
Requires Python: >=3.10

# Flow Platform SDK

Python SDK for interacting with Uniphore Flow Platform services via async RPC.

## Usage

```python
import asyncio
from flow_platform_sdk import platform_api

async def main():
    # List data connectors
    connectors = await platform_api.list_connectors()

    # Execute SQL query
    result = await platform_api.execute_query(
        connector_id="conn_123",
        sql_query="SELECT * FROM customers LIMIT 10",
        max_rows=10
    )

    # Query knowledge base
    answer = await platform_api.query_knowledge_base(
        knowledge_base_id="kb_123",
        query="What is the revenue?"
    )

asyncio.run(main())
```

## API Reference

### Data Connectors

```python
# List all connectors
await platform_api.list_connectors()

# Get schema
await platform_api.get_schema(connector_id="conn_123")

# Execute query
await platform_api.execute_query(
    connector_id="conn_123",
    sql_query="SELECT * FROM table",
    max_rows=1000
)

# Discover schema
await platform_api.discover_schema(
    connector_id="conn_123",
    include_sample_data=True,
    table_filter="customer*"
)

# Get table info
await platform_api.get_table_info(
    connector_id="conn_123",
    table_name="customers"
)

# Get sample data
await platform_api.get_sample_data(
    connector_id="conn_123",
    table_name="customers",
    limit=5
)
```

### Knowledge Base

```python
# List knowledge bases
await platform_api.list_knowledge_bases()

# Query knowledge base
await platform_api.query_knowledge_base(
    knowledge_base_id="kb_123",
    query="What are the main features?"
)
```

### Agent Evaluation

```python
# Invoke agent with draft skill
result = await platform_api.invoke_agent(
    agent_spec_id="agent_123",
    draft_skill_id="draft_456",
    input_message="What is the weather today?",
    context={"location": "San Francisco"},
    timeout=60
)
```

## Architecture

The SDK uses stdio-based RPC for communication with backend services:

- Requests sent to **stdout**: `REMOTE_SERVICE_CALL:{...}`
- Responses read from **stdin**: `REMOTE_TOOL_RESULT:{...}`

Designed for sandboxed execution environments.

## Configuration

- Default timeout: 120 seconds per request
- Daemon threads for clean exit on timeout

## Development

```bash
# Setup
uv sync

# Format code
uvx ruff format .
uvx ruff check .
```