semvec/pypi-packages huggingface dataset:
credo_ui 0.0.21
All popular Framework HF integration kit
License: MIT
Requires Python: <4.0,>=3.10

# Credo UI

A Streamlit-based UI for conversational AI with integrated search capabilities.

## Features

- Chat interface with streaming responses
- Multiple search modes:
  - Regular search
  - Deep search
  - Deep research
- Sidebar for additional information and settings
- Session management for chat history
- Built on top of Streamlit and streamlit-shadcn-ui



## Installation

```python
pip install credo-ui
```

## Usage

Run the application:

```
credo_ui
```

## Screenshots


![Search Results](resources/Screenshot%20from%202025-03-03%2007-32-08.png)
*Chat interface with search capabilities*

![Chat Interface](resources/Screenshot%20from%202025-03-03%2007-32-00.png)



## Components

- **Chat Interface**: A clean, responsive UI for interacting with LLMs
- **Search Integration**: Connect to various search backends through the LLMSearch class
- **Customizable Sidebar**: Add additional controls and information
- **Expandable "Thinking" Section**: Shows intermediate processing steps

## Project Structure

```
credo_ui/
├── ui.py             # Main UI components
├── sidebar.py        # Sidebar implementation
├── utils.py          # Helper functions
resources/
├── ui_image1.png     # UI screenshot for chat interface
├── ui_image2.png     # UI screenshot for search results
```

## Example

```python
import streamlit as st
from credo_ui.utils import setup_chat_session
from credo_ui.ui import render_titles
from credo_ui.sidebar import Sidebar

# Initialize
sidebar = Sidebar(st)
chat_manager = setup_chat_session(st)

# Render UI components
render_titles(st)
sidebar.render_sidebar_info()

# ... rest of your application
```

## Configuration

Switch between different search modes using the toggle buttons:
- **DeepSearch**: Enhanced search capabilities
- **Search**: Basic search functionality
- **DeepResearch**: In-depth research capabilities with thinking steps

## License

MIT

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
ids-tk 1.2.1
Incidence Density Sampling CLI Tool
License: MIT
Requires Python: >=3.7

# IDS-RS: Incidence Density Sampling Tool

This Python package provides access to the IDS-RS tool, a Rust implementation for performing incidence density sampling in epidemiological research. The package includes both the binary executable and all necessary mapping and schema files.

## Installation

```bash
pip install ids-tk
```

## Usage

You can use this package from the command line:

```bash
ids --help
```

Or from Python:

```python
import ids_tk

# Run with arguments
ids_tk.run_ids(["--help"])

# Check what mappings and schemas are available
print(ids_tk.list_mappings())
print(ids_tk.list_schemas())

# Get a specific mapping file
hfaudd_mapping = ids_tk.get_mapping_file("hfaudd")
if hfaudd_mapping:
    with open(hfaudd_mapping) as f:
        hfaudd_data = json.load(f)
    print(f"HFAUDD mapping contains {len(hfaudd_data)} entries")
```

## Working with Mappings and Schemas

The package includes all necessary mapping and schema files:

```python
import ids_tk
import json

# List all available mappings
mappings = ids_tk.list_mappings()
print(f"Available mappings: {mappings}")

# Load a specific mapping file
hfaudd_path = ids_tk.get_mapping_file("hfaudd")
with open(hfaudd_path) as f:
    hfaudd_mapping = json.load(f)

# List all available schemas
schemas = ids_tk.list_schemas()
print(f"Available schemas: {schemas}")

# Load a specific schema
bef_schema_path = ids_tk.get_schema_file("bef")
with open(bef_schema_path) as f:
    bef_schema = json.load(f)
```

## Features

- Fast incidence density sampling for large datasets
- Matching on birth date, parent age and other covariates
- Comprehensive reporting and statistics
- Generate synthetic data for testing
- Built-in access to JSON mapping and schema files