Intelli

Latest version: v0.4.2

Safety actively analyzes 688587 Python packages for vulnerabilities to keep your Python projects secure.

Scan your dependencies

0.4.2

New Features 🌟

- Update the agent to support the Llama 3.1 offline model.
- Add offline model capability to the chatbot.
- Unify Keras loader under a dedicated wrapper `KerasWrapper`.

Using the New Features 💻
- [Gemma 2](https://docs.intellinode.ai/docs/python/offline-chatbot/gemma).
- [Llama 3](https://docs.intellinode.ai/docs/python/offline-chatbot/llama)
- [Mistral](https://docs.intellinode.ai/docs/python/offline-chatbot/mistral).

0.2.3

New Features 🌟

- **Support for ANTHROPIC Models**: Our chatbot integration now supports advanced ANTHROPIC models, including those with large context windows.
- **Chatbot Provider Enumeration**: The selection of AI providers has been simplified through the use of enumerators.
- **Minor Bug Fixes**: Adjust the parameter order for the controllers.

Using the New Features 💻

- `ChatProvider` enum simplifies the selecting providers.

python
from intelli.function.chatbot import ChatProvider

check available chatbot providers
for provider in ChatProvider:
print(provider.name)


- Check the [chatbot documentation](https://docs.intellinode.ai/docs/python/chatbot/model-switching) to use claude-3 model.

Contributors
- gutyoh
- Barqawiz

0.2.0

New Features 🌟

- **Add Keras Agents**: Intelli now supports the loading of offline open-source models using `KerasAgent`.
- **Supported Offline Models**: `gemma_2b_en`, `gemma_instruct_2b_en`, `gemma_7b_en`, `gemma_instruct_7b_en`, `mistral_7b_en`, `mistral_instruct_7b_en`.

Using the New Features 💻
To use the new Keras Agent, instantiate the `KerasAgent` class with the appropriate parameters:
python
from intelli.flow.agents.kagent import KerasAgent

Setting up a Gemma agent
gemma_params = {
"model": "gemma_instruct_2b_en",
"max_length": 200
}
gemma_agent = KerasAgent(agent_type="text",
mission="writing assistant",
model_params=gemma_params,
log=True)

Prepare the tasks with the user instructions:
python
from intelli.flow.input.task_input import TextTaskInput
from intelli.flow.tasks.task import Task

Sample task to write blog post
task1 = Task(
TextTaskInput("write blog post about electric cars"), gemma_agent, log=True
)

Create more tasks as needed

Execute tasks using `SequenceFlow`. The example below shows a single task, but you can include additional tasks for text, image, or vision:
python
from intelli.flow.sequence_flow import SequenceFlow

Start SequenceFlow
flow = SequenceFlow([task1], log=True)
final_result = flow.start()


Fore more details check [the docs](https://docs.intellinode.ai/docs/python/flows/kagent).

0.1.5

What's New 🌟

- Add a function to generate a visual image for the flow.
python
flow.generate_graph_img()


- Add remote speech model, allowing to generate synthesised speeches from openai or google models.

- Fix a minor bug in the semantic search functionality.

0.0.8

What's New 🌟

- Add vision controller, to switch between openai and gemini image to text engine.
- Update the flow to support vision controller, allowing to build advanced use cases like explanation of flowchart for a coder agent.
- Add cohere chatbot model.

Contributors
basilmusa Barqawiz

0.0.6

What's New 🌟

Simplified Chatbot Creation
Create chatbots capable of utilizing various AI backends without altering your core codebase. This feature supports OpenAI, Mistral, and Gemini, simplifying the process of integrating intelligent conversational agents into your applications.

Enhanced Document Interaction
Enable your applications to interact with documents through chat.

Streamlined AI Flows
Create and manage flows of tasks executed by different AI models, enhancing automation and efficiency.


To build async flows with multiple paths, refer to the [flow tutorial](https://github.com/intelligentnode/Intelli/wiki/Flows).

Links

Releases

© 2024 Safety CLI Cybersecurity Inc. All Rights Reserved.