> ## 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.
# Prompts
The prompt module in CAMEL guides AI models to produce accurate, relevant, and personalized outputs. It provides a library of templates and dictionaries for diverse tasks — like role description, code generation, evaluation, embeddings, and even object recognition.
You can also craft your own prompts to precisely shape your agent’s behavior.
## Using Prompt Templates
CAMEL provides many ready-to-use prompt templates for quickly spinning up task-specific agents.
```python prompt_template.py theme={"system"}
from camel.agents import TaskSpecifyAgent
from camel.configs import ChatGPTConfig
from camel.models import ModelFactory
from camel.types import ModelPlatformType, ModelType, TaskType
model = ModelFactory.create(
model_platform=ModelPlatformType.OPENAI,
model_type=ModelType.GPT_4O_MINI,
)
task_specify_agent = TaskSpecifyAgent(
model=model, task_type=TaskType.AI_SOCIETY
)
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")
```
```markdown output theme={"system"}
>>>
Musician will help Student enhance stage presence by practicing engaging eye contact, dynamic movement, and expressive gestures during a mock concert, followed by a review session with video playback to identify strengths and areas for improvement.
```
Set `task_type=TaskType.AI_SOCIETY` to use the default society prompt template, or define your own.
## Using Your Own Prompt
Create and pass your own prompt template with full flexibility:
```python custom_prompt.py 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
model = ModelFactory.create(
model_platform=ModelPlatformType.OPENAI,
model_type=ModelType.GPT_4O_MINI,
)
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.'
)
task_specify_agent = TaskSpecifyAgent(
model=model, task_specify_prompt=my_prompt_template
)
response = task_specify_agent.run(
task_prompt="get promotion",
meta_dict=dict(occupation="Software Engineer"),
)
print(response)
```
```markdown output theme={"system"}
>>>
Certainly! To make the task of getting a promotion more specific, you can break it down into actionable steps and set clear, measurable goals. Here’s a more detailed plan:
1. **Set Clear Objectives**
- Identify the Promotion Criteria: Understand what skills, achievements, and experiences are required for the promotion.
- Define Your Desired Position: Specify the role or title you are aiming for.
2. **Skill Development**
- Technical Skills: Identify any technical skills that are necessary for the promotion and create a plan to acquire or improve them.
- Soft Skills: Focus on improving soft skills such as leadership, communication, and teamwork.
```
## Introduction to the `CodePrompt` Class
The `CodePrompt` class represents a code prompt and extends `TextPrompt`. It’s perfect for code generation and execution tasks.
```python code_prompt_import.py theme={"system"}
from camel.prompts import CodePrompt
```
### Creating a `CodePrompt`
```python code_prompt_create.py theme={"system"}
code_prompt = CodePrompt("a = 1 + 1", code_type="python")
```
### Accessing and Modifying the Code and Type
```python code_prompt_access.py theme={"system"}
print(code_prompt) # >>> "a = 1 + 1"
print(code_prompt.code_type) # >>> "python"
code_prompt.set_code_type("python")
print(code_prompt.code_type) # >>> "python"
```
### Executing the Code
```python code_prompt_execute.py theme={"system"}
code_prompt = CodePrompt("a = 1 + 1\nb = a + 1\nprint(a,b)", code_type="python")
output = code_prompt.execute()
# Running code? [Y/n]: y
print(output)
# >>> 2 3
```
## Write Your Prompts with the `TextPrompt` Class
The `TextPrompt` class is a subclass of Python’s `str`, with extra features for managing key words and advanced formatting.
```python text_prompt_intro.py theme={"system"}
from camel.prompts import TextPrompt
prompt = TextPrompt('Please enter your name and age: {name}, {age}')
print(prompt)
# >>> 'Please enter your name and age: {name}, {age}'
```
### The `key_words` Property
```python text_prompt_keywords.py theme={"system"}
from camel.prompts import TextPrompt
prompt = TextPrompt('Please enter your name and age: {name}, {age}')
print(prompt.key_words)
# >>> {'name', 'age'}
```
### The `format` Method (Partial Formatting Supported)
```python text_prompt_format.py theme={"system"}
from camel.prompts import TextPrompt
prompt = TextPrompt('Your name and age are: {name}, {age}')
name, age = 'John', 30
formatted_prompt = prompt.format(name=name, age=age)
print(formatted_prompt)
# >>> "Your name and age are: John, 30"
# Partial formatting
partial_formatted_prompt = prompt.format(name=name)
print(partial_formatted_prompt)
# >>> "Your name and age are: John, {age}"
```
### Manipulating `TextPrompt` Instances
You can concatenate, join, and use string methods with `TextPrompt` just like Python strings:
```python text_prompt_manipulation.py theme={"system"}
from camel.prompts import TextPrompt
prompt1 = TextPrompt('Hello, {name}!')
prompt2 = TextPrompt('Welcome, {name}!')
# Concatenation
prompt3 = prompt1 + ' ' + prompt2
print(prompt3)
# >>> "Hello, {name}! Welcome, {name}!"
print(isinstance(prompt3, TextPrompt)) # >>> True
print(prompt3.key_words) # >>> {'name'}
# Joining
prompt4 = TextPrompt(' ').join([prompt1, prompt2])
print(prompt4)
# >>> "Hello, {name}! Welcome, {name}!"
print(isinstance(prompt4, TextPrompt)) # >>> True
print(prompt4.key_words) # >>> {'name'}
# String methods
prompt5 = prompt4.upper()
print(prompt5)
# >>> "HELLO, {NAME}! WELCOME, {NAME}!"
print(isinstance(prompt5, TextPrompt)) # >>> True
print(prompt5.key_words) # >>> {'NAME'}
```
## Supported Prompt Templates
This class defines prompt templates for the AI Society role-playing and task handling workflow.
**Templates include:**
* GENERATE\_ASSISTANTS: List roles the AI assistant can play.
* GENERATE\_USERS: List common user groups or occupations.
* GENERATE\_TASKS: List diverse tasks for assistants.
* TASK\_SPECIFY\_PROMPT: Detail a task given assistant and user roles.
* ASSISTANT\_PROMPT: Rules for assistants to complete tasks.
* USER\_PROMPT: Rules for giving instructions to assistants.
* CRITIC\_PROMPT: Criteria for critics choosing among proposals.
This class provides prompts for code-related tasks (language, domain, code task generation, and instructions for coders).
**Templates include:**
* GENERATE\_LANGUAGES: List computer programming languages.
* GENERATE\_DOMAINS: List common programming domains.
* GENERATE\_TASKS: List tasks for programmers.
* TASK\_SPECIFY\_PROMPT: Specify a programming-related task.
* ASSISTANT\_PROMPT: Rules for completing code tasks.
* USER\_PROMPT: User instructions for coding agents.
Prompts for generating questions to evaluate knowledge.
**Templates include:**
* GENERATE\_QUESTIONS: Create question sets for evaluating knowledge emergence, with optional field-specific examples.
Prompts for generating text embedding tasks and synthetic data for embedding model improvement.
**Templates include:**
* GENERATE\_TASKS: Generate synthetic text embedding tasks.
* ASSISTANT\_PROMPT: Generate synthetic queries (JSON), positive docs, and hard negatives.
Prompts to test model alignment by introducing misleading or jailbreak tasks.
**Templates include:**
* DAN\_PROMPT: Do-Anything-Now jailbreak prompt.
* GENERATE\_TASKS: List unique malicious tasks.
* TASK\_SPECIFY\_PROMPT: Specify a malicious task in detail.
* ASSISTANT\_PROMPT: Rules for misaligned assistant tasks.
* USER\_PROMPT: User instructions in misalignment contexts.
Prompts for object recognition tasks.
**Templates include:**
* ASSISTANT\_PROMPT: Detect all objects in images, minimizing redundancy.
Inherits from AISocietyPromptTemplateDict and adds prompts for describing roles and responsibilities.
**Templates include:**
* ROLE\_DESCRIPTION\_PROMPT: Explain roles and responsibilities for agents.
Prompts to focus AI on finding solutions using particular knowledge.
**Templates include:**
* ASSISTANT\_PROMPT: Rules for extracting and presenting solutions.
Prompts for translation assistants (English → target language).
**Templates include:**
* ASSISTANT\_PROMPT: Rules for completing translation tasks.
Prompts for describing video content.
**Templates include:**
* ASSISTANT\_PROMPT: Rules for generating video descriptions.