51 lines
1.9 KiB
Markdown
51 lines
1.9 KiB
Markdown
## AI Reasoning Agent
|
|
|
|
The AI Reasoning Agent leverages advanced AI models to provide insightful reasoning and decision-making capabilities. This agent is designed to assist users in various analytical tasks by processing information and generating structured outputs.
|
|
|
|
### Features
|
|
- **Advanced Reasoning**: Utilizes the Ollama model to perform complex reasoning tasks
|
|
- **Interactive Playground**: Provides a user-friendly interface for interacting with the reasoning agent
|
|
- **Markdown Support**: Outputs results in markdown format for easy readability and sharing
|
|
- **Customizable Agent**: Easily configurable to suit different reasoning scenarios
|
|
|
|
### How to Get Started
|
|
1. **Clone the repository**:
|
|
```bash
|
|
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
|
|
cd ai_agent_tutorials/ai_reasoning_agent
|
|
```
|
|
|
|
2. **Install the required packages**:
|
|
#### For Local AI Reasoning Agent
|
|
```bash
|
|
pip install -r requirements.txt
|
|
```
|
|
|
|
3. **Run the application**:
|
|
```bash
|
|
python local_ai_reasoning_agent.py
|
|
```
|
|
|
|
### Using the Agent
|
|
1. **Access the Playground**:
|
|
- Open the provided URL to access the interactive playground
|
|
- The playground allows you to input queries and receive structured reasoning outputs
|
|
|
|
2. **Input Queries**:
|
|
- Enter your queries in the provided input field
|
|
- The agent processes the input and provides detailed reasoning and analysis
|
|
|
|
3. **View Results**:
|
|
- Results are displayed in markdown format
|
|
- Easily copy and share the outputs for further use
|
|
|
|
### Features in Detail
|
|
- **Reasoning Capabilities**:
|
|
- Handles a wide range of analytical tasks
|
|
- Provides clear and structured outputs
|
|
- Supports markdown for easy sharing and readability
|
|
|
|
- **Interactive Interface**:
|
|
- User-friendly playground for seamless interaction
|
|
- Real-time processing and output generation
|
|
- Configurable settings to tailor the agent's behavior
|