### Installation

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Instructions for installing the AMIE PyTorch package.

```bash
pip install AMIE-pytorch
```

```bash
git clone https://github.com/lucidrains/AMIE-pytorch
cd AMIE-pytorch
pip install -e .
```

--------------------------------

### Install AMIE PyTorch

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Installation commands for the package via pip or source.

```bash
pip install AMIE-pytorch
```

```bash
# Or install from source
git clone https://github.com/lucidrains/AMIE-pytorch
cd AMIE-pytorch
pip install -e .
```

--------------------------------

### Define PROMPT_EVALUATE_QUALITATIVE template

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Defines the prompt template for qualitative dialogue evaluation using few-shot examples.

```python
from AMIE_pytorch.AMIE_pytorch import PROMPT_EVALUATE_QUALITATIVE

# Template for qualitative dialogue evaluation
# Used for generating ratings on new dialogues
prompt = PROMPT_EVALUATE_QUALITATIVE
"""
I have a doctor-patient dialogue which I would like you to evaluate on the following criterion:
<criterion> (e.g., maintaining patient welfare). The dialogue should be rated on a scale of 1-5 with
respect to the criterion where:

5: <definition> e.g., "Treats patient respectfully, and ensures comfort, safety and dignity"
1: <definition> e.g., "Causes patient physical or emotional discomfort AND jeopardises patient safety"

Here are some example dialogues and their ratings:
DIALOGUE: <example dialog>
EVALUATION: <example self-generated explanation>
Rating: <example rating>
...

Now, please rate the following dialogue as instructed below. First, describe which parts of the dialogue
are good with respect to the criterion. Then, describe which parts are bad with respect to the criterion.
Third, summarise the above findings. Lastly, rate the dialogue on a scale of 1-5 with respect to the
criterion, according to this schema:

Good: ...
Bad: ...
Summary: ...
Rating: ...

DIALOGUE: <dialogue>
EVALUATION:
"""
```

--------------------------------

### Initialize Dialogue Components

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Initialization of dialogue management and moderator components.

```python
from AMIE_pytorch.AMIE_pytorch import SimulatedDialogue

# Initialize simulated dialogue (work in progress)
# dialogue = SimulatedDialogue()
```

```python
from AMIE_pytorch.AMIE_pytorch import Moderator

# Initialize moderator (work in progress)
# moderator = Moderator()
```

--------------------------------

### Initialize Evaluation Components

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Initialization of the critic module and evaluation prompt templates.

```python
from AMIE_pytorch.AMIE_pytorch import Critic

# Initialize critic (work in progress)
# critic = Critic()
```

```python
from AMIE_pytorch.AMIE_pytorch import PROMPT_EVALUATE_EXPLANATION

# Template for evaluating dialogue with existing rating
```

--------------------------------

### List framework dependencies

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Lists the required Python packages for the AMIE PyTorch framework.

```python
# Required dependencies (from setup.py)
dependencies = [
    'accelerate',      # For distributed training
    'beartype',        # Runtime type checking
    'einops>=0.7.0',   # Tensor operations
    'einx>=0.1.2',     # Extended einops
    'torch>=2.0',      # PyTorch deep learning framework
    'tqdm'             # Progress bars
]
```

--------------------------------

### Initialize Self-Play Training Components

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Initialization of the outer and inner self-play loops for training.

```python
from AMIE_pytorch.AMIE_pytorch import OuterSelfPlay

# Initialize outer self-play loop (work in progress)
# outer_loop = OuterSelfPlay()
```

```python
from AMIE_pytorch.AMIE_pytorch import InnerSelfPlay

# Initialize inner self-play loop (work in progress)
# inner_loop = InnerSelfPlay()
```

--------------------------------

### Initialize Agent Components

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Initialization of patient, doctor, and clinical vignette generator agents.

```python
from AMIE_pytorch.AMIE_pytorch import PatientAgent

# Initialize patient agent (work in progress)
# patient = PatientAgent()
```

```python
from AMIE_pytorch.AMIE_pytorch import DoctorAgent

# Initialize doctor agent (work in progress)
# doctor = DoctorAgent()
```

```python
from AMIE_pytorch.AMIE_pytorch import ClinicalVignetteGenerator

# Initialize clinical vignette generator (work in progress)
# vignette_gen = ClinicalVignetteGenerator()
```

--------------------------------

### Define PROMPT_EVALUATE_EXPLANATION template

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Defines the prompt template used for training the critic on human-annotated dialogues.

```python
prompt = PROMPT_EVALUATE_EXPLANATION
"""
I have a doctor-patient dialogue and the corresponding rating that quantifies its quality according to
the following criterion: <criterion> (e.g., maintaining patient welfare). The rating of the dialogue is
on a scale of 1 to 5 where:

5: <definition> e.g., "Treats patient respectfully, and ensures comfort, safety and dignity"
1: <definition> e.g., "Causes patient physical or emotional discomfort AND jeopardises patient safety"

First, describe which parts of the dialogue are good with respect to the criterion. Then, describe which parts are bad with respect to the criterion. Lastly, summarise the above to explain the
provided rating, using the following format:

Good: ...
Bad: ...
Summary: ...

DIALOGUE: <dialogue>
Rating: <human rating>
EVALUATION:
"""
```

--------------------------------

### Initialize AMIE Model

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Basic usage of the AMIE class for initializing the model and performing a forward pass.

```python
import torch
from AMIE_pytorch import AMIE

# Initialize the AMIE model
model = AMIE()

# Forward pass with input tensor
x = torch.randn(1, 512)
output = model(x)

print(output.shape)  # torch.Size([1, 512])
```

--------------------------------

### PROMPT_EVALUATE_EXPLANATION

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Description of the PROMPT_EVALUATE_EXPLANATION prompt template for generating dialogue quality ratings.

```python
from AMIE_pytorch.AMIE_pytorch import PROMPT_EVALUATE_EXPLANATION

# Template for evaluating dialogue with existing rating
```

--------------------------------

### OuterSelfPlay Module

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Information about the OuterSelfPlay module for managing the outer loop of self-play training.

```python
from AMIE_pytorch.AMIE_pytorch import OuterSelfPlay

# Initialize outer self-play loop (work in progress)
# outer_loop = OuterSelfPlay()
```

--------------------------------

### InnerSelfPlay Module

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Information about the InnerSelfPlay module for handling the inner loop of self-play training.

```python
from AMIE_pytorch.AMIE_pytorch import InnerSelfPlay

# Initialize inner self-play loop (work in progress)
# inner_loop = InnerSelfPlay()
```

--------------------------------

### Critic Component

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Details on the Critic module for evaluating dialogue quality using self-critique mechanisms.

```python
from AMIE_pytorch.AMIE_pytorch import Critic

# Initialize critic (work in progress)
# critic = Critic()
```

--------------------------------

### SimulatedDialogue Component

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Details on the SimulatedDialogue module for managing agent interactions.

```python
from AMIE_pytorch.AMIE_pytorch import SimulatedDialogue

# Initialize simulated dialogue (work in progress)
# dialogue = SimulatedDialogue()
```

--------------------------------

### PatientAgent Component

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Details on the PatientAgent for simulating patient behavior in diagnostic conversations.

```python
from AMIE_pytorch.AMIE_pytorch import PatientAgent

# Initialize patient agent (work in progress)
# patient = PatientAgent()
```

--------------------------------

### Moderator Component

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Information about the Moderator for overseeing dialogue sessions and managing conversation flow.

```python
from AMIE_pytorch.AMIE_pytorch import Moderator

# Initialize moderator (work in progress)
# moderator = Moderator()
```

--------------------------------

### ClinicalVignetteGenerator Component

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Information about the ClinicalVignetteGenerator for creating patient scenarios.

```python
from AMIE_pytorch.AMIE_pytorch import ClinicalVignetteGenerator

# Initialize clinical vignette generator (work in progress)
# vignette_gen = ClinicalVignetteGenerator()
```

--------------------------------

### DoctorAgent Component

Source: https://context7.com/lucidrains/amie-pytorch/llms.txt

Details on the DoctorAgent representing the AI physician in diagnostic interviews.

```python
from AMIE_pytorch.AMIE_pytorch import DoctorAgent

# Initialize doctor agent (work in progress)
# doctor = DoctorAgent()
```

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