semvec/pypi-packages huggingface dataset:
ovos-solver-openai-persona-plugin 1.2.0
A question solver plugin for ovos
License: MIT
Keywords: ovos plugin utterance fallback query

# <img src='https://raw.githack.com/FortAwesome/Font-Awesome/master/svgs/solid/robot.svg' card_color='#40DBB0' width='50' height='50' style='vertical-align:bottom'/> OpenAI Persona

Give OpenVoiceOS some sass with OpenAI!

Leverages [OpenAI Completions API](https://platform.openai.com/docs/api-reference/completions/create) to create some fun interactions.  Phrases not explicitly handled by other skills will be run by a LLM, so nearly every interaction will have _some_ response.  But be warned, Mycroft might become a bit obnoxious...


## Usage

Spoken answers api with OpenAI or [LocalAI](https://github.com/go-skynet/LocalAI) completions backend, prompt engineering is used to behave like a voice assistant

```python
from ovos_solver_openai_persona import OpenAIPersonaSolver

bot = OpenAIPersonaSolver({"key": "sk-XXX",
                           "persona": "helpful, creative, clever, and very friendly"})
print(bot.get_spoken_answer("describe quantum mechanics in simple terms"))
# Quantum mechanics is a branch of physics that deals with the behavior of particles on a very small scale, such as atoms and subatomic particles. It explores the idea that particles can exist in multiple states at once and that their behavior is not predictable in the traditional sense.
print(bot.spoken_answer("Quem encontrou o caminho maritimo para o Brazil", {"lang": "pt-pt"}))
# Explorador português Pedro Álvares Cabral é creditado com a descoberta do Brasil em 1500

```

This plugin will work with [ovos-persona-server](https://github.com/OpenVoiceOS/ovos-persona-server)

## Configuration

This plugin can be configured to use a LocalAI server instead of OpenAI.

```json
{
    "api_url": <your_local_LocalAI_server_url>,
    "key": <your_OpenAI_key>,
    "enable_memory": true,
    "memory_size": 15,
    "initial_prompt": "You are a helpful assistant."
}
```

When using LocalAI, the `"key"` can be anything, but it has to exist.
memoryfields 0.1.1
A Python client for interacting with SenTech AI's memory fields API.
License: MIT
Requires Python: >=3.7

# Memory Fields

**Memory Fields** is a Python client for interacting with the **SenTech AI Memory API**, enabling users to add, query, and manage memory fields efficiently.

## Installation

You can install the package using `pip`:

```bash
pip install memory-fields
```

## Usage

### Import and Initialize the Client**
```python
from memoryfields import EMFClient

# Replace 'your_api_key' with a valid API key
client = EMFClient(api_key="your_api_key")
```

### Add Memory to a Field**

```python
response = client.add_memory(
    field_id="12345",
    content="This is a test memory.",
    timestamp=1700000000
)
print(response)
```

### Query Memories**
```python
results = client.query_memory(field_id="12345", query="What do I remember?")
print(results)
```

### Query with an Image**
```python
image_results = client.query_image(field_id="12345", image_path="sample.jpg")
print(image_results)
```

## API Methods

| Method | Description |
|--------|-------------|
| `add_memory(field_id, content, timestamp, relevance=1.0, decay_rate=0.01, salience=1.0)` | Adds a memory to a specified field. |
| `query_memory(field_id, query, top_k=50, depth_k=3)` | Searches a field for relevant memories based on a text query. |
| `query_image(field_id, query=None, image_path=None, top_k=50)` | Performs a combined query using text and an optional image. |

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contributing

Contributions are welcome! Please open an issue or submit a pull request.

## Contact

For support or inquiries, reach out via [GitHub Issues](https://github.com/yourusername/memory-fields/issues).
or 
email us at service@sentech.ai