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

# Prompts

> Complete reference for the Swarms prompts module including the Prompt class and pre-built prompt templates

## Overview

The `swarms.prompts` module provides tools for creating, managing, and versioning prompts with comprehensive history tracking, autosaving capabilities, and integration with agent systems.

## Prompt Class

A powerful class for managing prompts with version control, edit history, and autosaving features.

```python theme={null}
from swarms.prompts import Prompt

prompt = Prompt(
    name="analysis_prompt",
    description="Financial analysis prompt",
    content="Analyze the following financial data...",
    autosave=True,
    autosave_folder="prompts"
)
```

### Constructor

<ParamField path="id" type="str" default="uuid.uuid4().hex">
  Unique identifier for the prompt
</ParamField>

<ParamField path="name" type="str" default="prompt">
  Name of your prompt
</ParamField>

<ParamField path="description" type="str" default="Simple Prompt">
  Description of the prompt
</ParamField>

<ParamField path="content" type="str" required>
  The main content of the prompt (minimum 1 character)
</ParamField>

<ParamField path="created_at" type="str" default="current_time">
  Timestamp when the prompt was created
</ParamField>

<ParamField path="last_modified_at" type="str" default="current_time">
  Timestamp when the prompt was last modified
</ParamField>

<ParamField path="edit_count" type="int" default="0">
  Number of times the prompt has been edited
</ParamField>

<ParamField path="edit_history" type="List[str]" default="[]">
  History of all prompt versions
</ParamField>

<ParamField path="autosave" type="bool" default="False">
  Enable automatic saving of the prompt
</ParamField>

<ParamField path="autosave_folder" type="str" default="prompts">
  Folder path within WORKSPACE\_DIR for autosaving
</ParamField>

<ParamField path="auto_generate_prompt" type="bool" default="False">
  Enable auto-generation of prompts
</ParamField>

<ParamField path="parent_folder" type="str" default="workspace_dir">
  Parent folder for the autosave folder
</ParamField>

<ParamField path="llm" type="Any" default="None">
  Optional LLM instance for prompt generation
</ParamField>

### Methods

#### edit\_prompt

Edit the prompt content and update version control.

```python theme={null}
prompt.edit_prompt("Updated prompt content here")
```

<ParamField path="new_content" type="str" required>
  The updated content of the prompt
</ParamField>

**Raises:**

* `ValueError`: If the new content is identical to the current content

**Thread-safe**: This method is safe for concurrent access.

#### rollback

Roll back the prompt to a previous version.

```python theme={null}
# Rollback to the first version
prompt.rollback(version=0)
```

<ParamField path="version" type="int" required>
  The version index to roll back to (0 is the first version)
</ParamField>

**Raises:**

* `IndexError`: If the version number is out of range

#### get\_prompt

Return the current prompt content as a string.

```python theme={null}
content = prompt.get_prompt()
print(content)
```

<ResponseField name="return" type="str">
  The current prompt content
</ResponseField>

#### return\_json

Return the prompt as a JSON string.

```python theme={null}
json_data = prompt.return_json()
print(json_data)
```

<ResponseField name="return" type="str">
  JSON representation of the prompt with all metadata
</ResponseField>

#### add\_tools

Add tool schemas to the prompt content.

```python theme={null}
from swarms.tools import BaseTool

def my_tool(x: int) -> int:
    """Double the input."""
    return x * 2

prompt.add_tools([my_tool])
```

<ParamField path="tools" type="List[Callable]" required>
  List of callable functions to add as tools
</ParamField>

## Pre-built Prompt Templates

The module includes numerous pre-built prompt templates for common agent roles:

### Finance Prompts

#### FINANCE\_AGENT\_PROMPT

Comprehensive prompt for financial analysis agents.

```python theme={null}
from swarms.prompts import FINANCE_AGENT_PROMPT

agent = Agent(
    agent_name="Financial-Analyst",
    system_prompt=FINANCE_AGENT_PROMPT,
    # ... other config
)
```

### Legal Prompts

#### LEGAL\_AGENT\_PROMPT

Prompt template for legal analysis and research agents.

```python theme={null}
from swarms.prompts import LEGAL_AGENT_PROMPT

agent = Agent(
    agent_name="Legal-Advisor",
    system_prompt=LEGAL_AGENT_PROMPT,
    # ... other config
)
```

### Product & Operations

#### PRODUCT\_AGENT\_PROMPT

Prompt for product management agents.

```python theme={null}
from swarms.prompts import PRODUCT_AGENT_PROMPT
```

#### OPERATIONS\_AGENT\_PROMPT

Prompt for operations management agents.

```python theme={null}
from swarms.prompts import OPERATIONS_AGENT_PROMPT
```

#### GROWTH\_AGENT\_PROMPT

Prompt for growth and marketing agents.

```python theme={null}
from swarms.prompts import GROWTH_AGENT_PROMPT
```

### Development Prompts

#### CODE\_INTERPRETER

Prompt for code interpretation and execution agents.

```python theme={null}
from swarms.prompts import CODE_INTERPRETER

agent = Agent(
    agent_name="Code-Interpreter",
    system_prompt=CODE_INTERPRETER,
    # ... other config
)
```

#### DOCUMENTATION\_WRITER\_SOP

Standard operating procedure for documentation writing agents.

```python theme={null}
from swarms.prompts import DOCUMENTATION_WRITER_SOP
```

### Autonomous Agent Prompts

#### AUTONOMOUS\_AGENT\_SYSTEM\_PROMPT

Base system prompt for autonomous agents.

```python theme={null}
from swarms.prompts import AUTONOMOUS_AGENT_SYSTEM_PROMPT
```

#### get\_autonomous\_agent\_prompt

Generate an autonomous agent prompt.

```python theme={null}
from swarms.prompts import get_autonomous_agent_prompt

prompt = get_autonomous_agent_prompt()
```

#### get\_autonomous\_agent\_prompt\_with\_context

Generate an autonomous agent prompt with additional context.

```python theme={null}
from swarms.prompts import get_autonomous_agent_prompt_with_context

prompt = get_autonomous_agent_prompt_with_context(
    context="Analyze financial markets with focus on tech stocks"
)
```

## Example: Complete Prompt Management

```python theme={null}
from swarms.prompts import Prompt
from swarms.tools import BaseTool
import os

# Set workspace directory
os.environ["WORKSPACE_DIR"] = "./workspace"

# Create a prompt with autosave
prompt = Prompt(
    name="market_analysis",
    description="Financial market analysis prompt",
    content="""You are a financial analyst. Analyze the following:
    1. Market trends
    2. Risk factors
    3. Investment opportunities
    """,
    autosave=True,
    autosave_folder="financial_prompts"
)

# Edit the prompt
prompt.edit_prompt("""
You are an expert financial analyst specializing in equity markets.

Analyze the following aspects:
1. Current market trends and momentum
2. Key risk factors and hedging strategies
3. High-conviction investment opportunities
4. Portfolio allocation recommendations

Provide detailed analysis with supporting data.
""")

print(f"Edit count: {prompt.edit_count}")  # 1
print(f"Total versions: {len(prompt.edit_history)}")  # 2

# Add tools to the prompt
def calculate_sharpe_ratio(returns: float, risk_free_rate: float, std_dev: float) -> float:
    """Calculate Sharpe ratio for investment analysis."""
    return (returns - risk_free_rate) / std_dev

prompt.add_tools([calculate_sharpe_ratio])

# Rollback if needed
prompt.rollback(version=0)  # Back to original version

# Get the current prompt
current = prompt.get_prompt()
print(current)

# Export as JSON
json_export = prompt.return_json()
print(json_export)
```

## Best Practices

1. **Enable autosave**: Always enable autosave for important prompts to prevent data loss
2. **Use descriptive names**: Give prompts clear, descriptive names for easy identification
3. **Version control**: Leverage the built-in version control to track prompt evolution
4. **Add context**: Include detailed descriptions to document the prompt's purpose
5. **Organize by folder**: Use the `autosave_folder` parameter to organize prompts by category
6. **Regular rollbacks**: Test different prompt versions using rollback functionality
7. **Tool integration**: Use `add_tools()` to seamlessly integrate function calling

## Thread Safety

The Prompt class implements thread-safe operations for:

* Edit operations
* Rollback operations
* Autosaving

This makes it safe to use in concurrent environments and multi-agent systems.

## Autosave Behavior

When autosave is enabled:

1. Prompts are saved to `{WORKSPACE_DIR}/{autosave_folder}/prompt-id-{id}.json`
2. Each edit automatically triggers a save
3. Rollback operations also trigger saves
4. The entire prompt state (including history) is preserved

## Integration with Agents

```python theme={null}
from swarms import Agent
from swarms.prompts import Prompt, FINANCE_AGENT_PROMPT

# Using pre-built prompts
agent1 = Agent(
    agent_name="Financial-Analyst",
    system_prompt=FINANCE_AGENT_PROMPT,
    model_name="gpt-4"
)

# Using custom Prompt class
custom_prompt = Prompt(
    name="custom_analyst",
    content="You are a specialized quantitative analyst...",
    autosave=True
)

agent2 = Agent(
    agent_name="Quant-Analyst",
    system_prompt=custom_prompt.get_prompt(),
    model_name="gpt-4"
)
```