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

> ## Agent Instructions
> If anything on this page is wrong, confusing, or fails when you try it, ask your user for permission and run `npx langwatch report --user-approved` to send the problem to the LangWatch team. No login is needed and secrets are redacted locally. `npx langwatch report --help` has the details.

# Version Control

> Manage version control for prompts in LangWatch to run evaluations, compare models, and improve agent performance.

# Prompt Version Control

LangWatch provides a version control system for managing your prompts. Each prompt can have multiple versions, allowing you to track changes, experiment with different approaches, and rollback when needed.

## Version Management

Every prompt in LangWatch automatically maintains a version history. When you create a new prompt, it starts with version 1, and each subsequent change creates a new version with an incremented number.

**Important**: You cannot delete individual versions - only entire prompts can be deleted. Each update operation creates a new version automatically.

## Scope and Conflicts

Prompts have two scope levels that affect version management and conflict resolution:

* **PROJECT scope** - Prompts are accessible only within the project. Changes are isolated to your project.
* **ORGANIZATION scope** - Prompts are shared across all projects in the organization. Changes can affect other projects and may require conflict resolution.

> [!WARNING]
>
> **Scope Conflicts**: When updating an organization-scoped prompt, conflicts may arise if other
> projects have made changes. The system provides conflict information to help resolve differences.

## Managing Versions

> [tab] UI
>
> Use the LangWatch UI to manage prompt versions:
>
> 1. Navigate to the **Prompt Management** section
> 2. Select a prompt
> 3. Click on the version history icon at the bottom of the prompt editor
> 4. Use the version selector to switch between versions
> 5. Create new versions by making changes and saving

> [tab] TypeScript SDK
>
> LangWatch's TypeScript SDK supports retrieving prompts and specific versions:
>
> ```typescript theme={null}
> import { LangWatch } from "langwatch";
>
> // Initialize LangWatch client
> const langwatch = new LangWatch({
>   apiKey: process.env.LANGWATCH_API_KEY,
> });
>
> // Retrieve prompts via the API to support versioning, evaluation workflows, and agent testing pipelines. (latest version by default)
> const prompt = await langwatch.prompts.get("customer-support-bot");
>
> // The prompt object contains version information
> console.log(`Version: ${prompt.version}`);
> console.log(`Version ID: ${prompt.versionId}`);
>
> // Get a specific version of a prompt
> const specificVersion = await langwatch.prompts.get("customer-support-bot", {
>   version: "version_abc123",
> });
>
> // Compile with variables
> const compiledPrompt = specificVersion.compile({
>   user_name: "John Doe",
>   user_email: "john.doe@example.com",
>   input: "I need help with my account",
> });
> ```

> [tab] REST API
>
> Use the REST API to manage prompt versions:
>
> ```bash theme={null}
> # Get all versions of a prompt
> curl --request GET \
>   --url "https://app.langwatch.ai/api/prompts/{prompt_handle}/versions" \
>   --header "X-Auth-Token: your-api-key"
>
> # Retrieve prompts via the API to support versioning, evaluation workflows, and agent testing pipelines. (latest version)
> curl --request GET \
>   --url "https://app.langwatch.ai/api/prompts/{prompt_handle}" \
>   --header "X-Auth-Token: your-api-key"
>
> # Create a new version
> curl --request POST \
>   --url "https://app.langwatch.ai/api/prompts/{prompt_handle}/versions" \
>   --header "X-Auth-Token: your-api-key" \
>   --header "Content-Type: application/json" \
>   --data '{
>     "prompt": "Updated prompt text...",
>     "model": "openai/gpt-6-luna",
>     "commitMessage": "Improved customer support prompt",
>
>     "maxTokens": 1000,
>     "responseFormat": {"type": "text"},
>     "inputs": [{"identifier": "input", "type": "str"}],
>     "outputs": [{"identifier": "response", "type": "str"}],
>     "demonstrations": null,
>     "promptingTechnique": null
>   }'
>
> # Get a specific version
> curl --request GET \
>   --url "https://app.langwatch.ai/api/prompts/{prompt_handle}?version=2" \
>   --header "X-Auth-Token: your-api-key"
> ```

## CRUD Operations

The SDK provides CRUD operations for managing prompts programmatically:

> [!NOTE]
>
> **Field Structure**: All examples show the essential fields. Additional optional fields like
> `temperature`, `maxTokens`, `responseFormat`, `inputs`, `outputs`, `demonstrations`, and
> `promptingTechnique` can also be set. See the [Data Model](https://langwatch.ai/docs/prompt-management/data-model.md) page for
> complete field documentation.

### Create Prompts

Create new prompts with templates and variables:

> [!WARNING]
>
> **System Message Conflict**: You cannot set both a `prompt` (system message) and `messages` array
> with a system role in the same operation. Choose one approach to avoid errors.

> [!NOTE]
>
> The two SDKs do not take the same fields. `model`, `temperature` and `maxTokens` go through the
> TypeScript SDK and the REST API; the Python SDK's `create` and `update` do not accept them yet, so
> set them from the UI or over REST. See the [REST reference](https://langwatch.ai/docs/api-reference/prompts/overview.md).

> [tab] TypeScript SDK
>
> ```typescript create_prompt.ts theme={null}
>      // Create a new prompt with a system prompt
>  const prompt = await langwatch.prompts.create({
>    handle: "customer-support-bot",                    // Required
>    scope: "PROJECT",                                  // Optional: defaults to "PROJECT"
>    prompt: "You are a helpful customer support agent. Help with: {{input}}", // Optional
>    model: "openai/gpt-6-luna",                       // Optional
>
>    // Optional fields:
>    maxTokens: 1000,                                   // Optional: Maximum tokens to generate
>    // temperature: 0.7,                               // Optional, but reasoning models such as the GPT-6 family reject it
>    // messages: [...],                                // Optional: Messages array in OpenAI format { role: "system" | "user" | "assistant", content: "..." }
>  });
>
> console.log(`Created prompt with handle: ${prompt.handle}`);
> ```

> [tab] Python SDK
>
> ```python create_prompt.py theme={null}
>      # Create a new prompt
>  prompt = langwatch.prompts.create(
>      handle="customer-support-bot",                    # Required
>      scope="PROJECT",                                  # Optional: defaults to "PROJECT"
>      prompt="You are a helpful customer support agent. Help with: {{input}}", # Optional
>
>      # Optional fields:
>      # messages=[...],                                 # Optional: Messages array in OpenAI format { role: "system" | "user" | "assistant", content: "..." }
>      # tags=["production"],                            # Optional: tags for the initial version
>  )
>
>      print(f"Created prompt with handle: {prompt.handle}")
> ```

### Update Prompts (Creates New Versions)

Modify existing prompts while maintaining version history:

> [!WARNING]
>
> **System Message Conflict**: Same rule applies - you cannot set both a `prompt` and `messages`
> array with a system role in the same operation.

> [!NOTE]
>
> You must include at least one field to update the prompt.

> [tab] TypeScript SDK
>
> ```typescript update_prompt.ts theme={null}
>      // Update prompt content (creates new version automatically)
>  const updatedPrompt = await langwatch.prompts.update("customer-support-bot", {
>    // All fields are optional for updates - only specify what you want to change
>    prompt: "You are an expert customer support agent. Help with: {{input}}",
>
>    // Optional fields:
>    model: "openai/gpt-6-sol",                         // Optional: Change the model
>    maxTokens: 2000,                                  // Optional: Change max tokens
>    // messages: [...],                                 // Optional: Messages array in OpenAI format { role: "system" | "user" | "assistant", content: "..." }
>  });
>
>      console.log(`Updated prompt: ${updatedPrompt.handle}, New version: ${updatedPrompt.version}`);
> ```

> [tab] Python SDK
>
> ```python update_prompt.py theme={null}
>      # Update prompt content (creates new version automatically)
>  updated_prompt = langwatch.prompts.update(
>      "customer-support-bot",
>      scope="PROJECT",                                  # Required
>      # Everything below is optional - only specify what you want to change
>      prompt="You are an expert customer support agent. Help with: {{input}}",
>      # messages=[...],                                 # Optional: Messages array in OpenAI format { role: "system" | "user" | "assistant", content: "..." }
>      # tags=["production"],                            # Optional: retag the new version
>  )
>
>      print(f"Updated prompt: {updated_prompt.handle}, New version: {updated_prompt.version}")
> ```

### Delete Prompts

Remove entire prompts and all their versions:

> [!WARNING]
>
> **Permanent Deletion**: Deleting a prompt removes ALL versions permanently. This action cannot be
> undone.

> [tab] TypeScript SDK
>
> ```typescript delete_prompt.ts theme={null}
> // Delete by handle (removes all versions)
> const result = await langwatch.prompts.delete("customer-support-bot");
>
> console.log(`Deletion result: ${result.success}`);
> ```

> [tab] Python SDK
>
> ```python delete_prompt.py theme={null}
> # Delete by handle (removes all versions)
> result = langwatch.prompts.delete("customer-support-bot")
>
> print(f"Deletion result: {result}")
> ```

## Important Caveats

### System Message Conflicts

> [!WARNING]
>
> **Critical**: You cannot set both a `prompt` field and a `messages` array containing a system role
> in the same operation. This will throw an error.

**Valid approaches:**

1. **Use `prompt` field only** - Sets the system message directly
2. **Use `messages` array only** - Define the full conversation structure
3. **Mix both** - Use `prompt` for system message and `messages` for user/assistant messages (but no system role in messages)

## Advanced Prompt Capabilities

Beyond basic prompt creation, LangWatch provides these features for optimizing and managing your AI interactions:

### Response Format Control

* **Structured Output**: Use `responseFormat: { type: "json_schema" }` to get consistent, parseable responses
* **Text Generation**: Default `responseFormat: { type: "text" }` for free-form responses
* **Custom Schemas**: Define exact output structures for integration with your systems

### Few-Shot Learning

* **Demonstrations**: Use the `demonstrations` field to provide example input/output pairs to improve response quality

### Input/Output Validation

* **Type Safety**: Define expected input types (`str`, `float`, `bool`, `list[str]`, etc.)
* **Output Constraints**: Specify exact output formats and validation rules
* **Variable Management**: Automatically handle prompt variable substitution and validation

### Model Optimization

* **Temperature Control**: Fine-tune creativity vs. consistency (0.0-2.0)
* **Token Limits**: Set `maxTokens` to control response length and costs
* **Model Selection**: Choose the best model for your specific use case

> [!TIP]
>
> Combine these settings with [Workflows](https://langwatch.ai/docs/workflows/overview.md), where you can evaluate different
> configurations on the same dataset and compare the results.

### Workflows Integration

A workflow uses these prompt settings in its LLM nodes, so you can:

* **Compare versions**: Evaluate different prompt versions, models, and configurations on one dataset
* **Measure results**: Read the pass rate, cost and duration of each run
* **Save what works**: Save the prompt from the workflow as a new version

> [card] [Use prompts in workflows](https://langwatch.ai/docs/prompt-management/features/advanced/workflows.md)
>
> Pick a prompt in an LLM node, evaluate it on a dataset and save the result as a version.

## Version History

![Prompt version history showing multiple versions with timestamps](https://mintcdn.com/langwatch/iJjBH4X_YNQ578jk/images/prompts/version-history.png?fit=max\&auto=format\&n=iJjBH4X_YNQ578jk\&q=85\&s=5d2ee5a1c9c1fd10053e247aa5413576)

* **Version List**: See all versions with timestamps and commit messages
* **Rollback**: Revert to previous versions

***

[← Back to Prompt Management Overview](https://langwatch.ai/docs/prompt-management/overview.md)


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