> ## Documentation Index
> Fetch the complete documentation index at: https://docs.camel-ai.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Prompting Cookbook

You can also check this cookbook in colab [here](https://colab.research.google.com/drive/1VcjPuy2UEYm0xLdriT7OMGt6I2yX9z32?usp=sharing).

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This notebook demonstrates how to set up and leverage CAMEL's ability to use **Prompt** module.

In this notebook, you'll explore:

* **CAMEL**: A powerful multi-agent framework that enables Retrieval-Augmented Generation and multi-agent role-playing scenarios, allowing for sophisticated AI-driven tasks.

* **Prompt**: Interface to communicate with models with various templates, create custom prompts, and leverage different prompt dictionaries for tasks ranging from role-playing to code generation, evaluation, and more. By mastering the Prompt module, you can significantly enhance your AI agents' capabilities and tailor them to specific tasks.

## 📦 Installation

Ensure you have CAMEL AI installed in your Python environment:

```python theme={"system"}
!pip install "camel-ai==0.2.16"
```

## 🔑 Setting Up API Keys

You'll need to set up your API keys for OpenAI.

```python theme={"system"}
import os
from getpass import getpass

# Prompt for the API key securely
openai_api_key = getpass('Enter your API key: ')
os.environ["OPENAI_API_KEY"] = openai_api_key
```

Alternatively, if running on Colab, you could save your API keys and tokens as **Colab Secrets**,

and use them across notebooks.

To do so, **comment out** the above **manual** API key prompt code block(s),

and **uncomment** the following codeblock.

⚠️ Don't forget granting access to the API key you would be using to the current notebook.

```python theme={"system"}
# import os
# from google.colab import userdata

# os.environ["OPENAI_API_KEY"] = userdata.get("OPENAI_API_KEY")
```

## Getting Started with Prompt Templates

CAMEL offers a wide range of pre-defined prompt templates that you can use to quickly create specialized AI agents. Let's start with a basic example using the TaskSpecifyAgent with the AI\_SOCIETY task type.

```python theme={"system"}
from camel.agents import TaskSpecifyAgent
from camel.configs import ChatGPTConfig
from camel.models import ModelFactory
from camel.types import ModelPlatformType, ModelType, TaskType

# Set up the model
model = ModelFactory.create(
    model_platform=ModelPlatformType.OPENAI,
    model_type=ModelType.GPT_4O_MINI,
)

# Create a task specify agent
task_specify_agent = TaskSpecifyAgent(
    model=model, task_type=TaskType.AI_SOCIETY
)

# Run the agent with a task prompt
specified_task_prompt = task_specify_agent.run(
    task_prompt="Improving stage presence and performance skills",
    meta_dict=dict(
        assistant_role="Musician", user_role="Student", word_limit=100
    ),
)

print(f"Specified task prompt:\n{specified_task_prompt}\n")
```

## Creating Custom Prompts

CAMEL also allows you to create your own custom prompts. Here's an example of how to create and use a custom prompt template:

```python theme={"system"}
from camel.agents import TaskSpecifyAgent
from camel.configs import ChatGPTConfig
from camel.models import ModelFactory
from camel.prompts import TextPrompt
from camel.types import ModelPlatformType, ModelType

# Set up the model
model = ModelFactory.create(
    model_platform=ModelPlatformType.OPENAI,
    model_type=ModelType.GPT_4O_MINI,
)

# Create a custom prompt template
my_prompt_template = TextPrompt(
    'Here is a task: I\'m a {occupation} and I want to {task}. Help me to make this task more specific.'
)

# Create a task specify agent with the custom prompt
task_specify_agent = TaskSpecifyAgent(
    model=model, task_specify_prompt=my_prompt_template
)

# Run the agent with a task prompt
response = task_specify_agent.run(
    task_prompt="get promotion",
    meta_dict=dict(occupation="Software Engineer"),
)

print(response)
```

## Advanced Prompt Usage

CAMEL provides various prompt dictionaries for different purposes. Let's explore some advanced uses of these prompt templates:

### 1. Code Generation with CodePromptTemplateDict

```python theme={"system"}
from camel.prompts import CodePromptTemplateDict

# Generate programming languages
languages_prompt = CodePromptTemplateDict.GENERATE_LANGUAGES.format(num_languages=5)
print(f"Languages prompt:\n{languages_prompt}\n")

# Generate coding tasks
tasks_prompt = CodePromptTemplateDict.GENERATE_TASKS.format(num_tasks=3)
print(f"Tasks prompt:\n{tasks_prompt}\n")

# Create an AI coding assistant prompt
assistant_prompt = CodePromptTemplateDict.ASSISTANT_PROMPT.format(
    assistant_role="Python Expert",
    task_description="Implement a binary search algorithm",
)
print(f"Assistant prompt:\n{assistant_prompt}\n")
```

### 2. Evaluation with EvaluationPromptTemplateDict

```python theme={"system"}
from camel.prompts import EvaluationPromptTemplateDict

# Generate evaluation questions
questions_prompt = EvaluationPromptTemplateDict.GENERATE_QUESTIONS.format(
    num_questions=5,
    field="Machine Learning",
    examples="1. What is the difference between supervised and unsupervised learning?\n2. Explain the concept of overfitting.",
)
print(f"Evaluation questions prompt:\n{questions_prompt}\n")
```

### 3. Object Recognition with ObjectRecognitionPromptTemplateDict

```python theme={"system"}
from camel.prompts import ObjectRecognitionPromptTemplateDict

# Create an object recognition assistant prompt
recognition_prompt = ObjectRecognitionPromptTemplateDict.ASSISTANT_PROMPT
print(f"Object recognition prompt:\n{recognition_prompt}\n")
```

### 4. Translation with TranslationPromptTemplateDict

```python theme={"system"}
from camel.prompts import TranslationPromptTemplateDict

# Create a translation assistant prompt
translation_prompt = TranslationPromptTemplateDict.ASSISTANT_PROMPT.format(target_language="Spanish")
print(f"Translation prompt:\n{translation_prompt}\n")
```

## 🌟 Highlights

This notebook has guided you through setting up and use **Prompt** module. The CAMEL Prompt module provides a powerful and flexible way to guide AI models in producing desired outputs. By using pre-defined prompt templates, creating custom prompts, and leveraging different prompt dictionaries, you can create highly specialized AI agents tailored to your specific needs.

Key tools utilized in this notebook include:

* **CAMEL**: A powerful multi-agent framework that enables Retrieval-Augmented Generation and multi-agent role-playing scenarios, allowing for sophisticated AI-driven tasks.
* **Prompt**: Interface to communicate with models with various templates, create custom prompts, and leverage different prompt dictionaries for tasks ranging from role-playing to code generation, evaluation, and more. By mastering the Prompt module, you can significantly enhance your AI agents' capabilities and tailor them to specific tasks.

That's everything: Got questions about 🐫 CAMEL-AI? Join us on [Discord](https://discord.camel-ai.org)! Whether you want to share feedback, explore the latest in multi-agent systems, get support, or connect with others on exciting projects, we’d love to have you in the community! 🤝

Check out some of our other work:

1. 🐫 Creating Your First CAMEL Agent [free Colab](https://docs.camel-ai.org/cookbooks/create_your_first_agent.html)

2. Graph RAG Cookbook [free Colab](https://colab.research.google.com/drive/1uZKQSuu0qW6ukkuSv9TukLB9bVaS1H0U?usp=sharing)

3. 🧑‍⚖️ Create A Hackathon Judge Committee with Workforce [free Colab](https://colab.research.google.com/drive/18ajYUMfwDx3WyrjHow3EvUMpKQDcrLtr?usp=sharing)

4. 🔥 3 ways to ingest data from websites with Firecrawl & CAMEL [free Colab](https://colab.research.google.com/drive/1lOmM3VmgR1hLwDKdeLGFve_75RFW0R9I?usp=sharing)

5. 🦥 Agentic SFT Data Generation with CAMEL and Mistral Models, Fine-Tuned with Unsloth [free Colab](https://colab.research.google.com/drive/1lYgArBw7ARVPSpdwgKLYnp_NEXiNDOd-?usp=sharingg)

Thanks from everyone at 🐫 CAMEL-AI

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***