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+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# LiteLLM AI Gateway Prompt Management
+
+Use the LiteLLM AI Gateway to create, manage and version your prompts.
+
+## Quick Start
+
+### Accessing the Prompts Interface
+
+1. Navigate to **Experimental > Prompts** in your LiteLLM dashboard
+2. You'll see a table displaying all your existing prompts with the following columns:
+ - **Prompt ID**: Unique identifier for each prompt
+ - **Model**: The LLM model configured for the prompt
+ - **Created At**: Timestamp when the prompt was created
+ - **Updated At**: Timestamp of the last update
+ - **Type**: Prompt type (e.g., db)
+ - **Actions**: Delete and manage prompt options (admin only)
+
+
+
+## Create a Prompt
+
+Click the **+ Add New Prompt** button to create a new prompt.
+
+### Step 1: Select Your Model
+
+Choose the LLM model you want to use from the dropdown menu at the top. You can select from any of your configured models (e.g., `aws/anthropic/bedrock-claude-3-5-sonnet`, `gpt-4o`, etc.).
+
+### Step 2: Set the Developer Message
+
+The **Developer message** section allows you to set optional system instructions for the model. This acts as the system prompt that guides the model's behavior.
+
+For example:
+
+```
+Respond as jack sparrow would
+```
+
+This will instruct the model to respond in the style of Captain Jack Sparrow from Pirates of the Caribbean.
+
+
+
+### Step 3: Add Prompt Messages
+
+In the **Prompt messages** section, you can add the actual prompt content. Click **+ Add message** to add additional messages to your prompt template.
+
+### Step 4: Use Variables in Your Prompts
+
+Variables allow you to create dynamic prompts that can be customized at runtime. Use the `{{variable_name}}` syntax to insert variables into your prompts.
+
+For example:
+
+```
+Give me a recipe for {{dish}}
+```
+
+The UI will automatically detect variables in your prompt and display them in the **Detected variables** section.
+
+
+
+### Step 5: Test Your Prompt
+
+Before saving, you can test your prompt directly in the UI:
+
+1. Fill in the template variables in the right panel (e.g., set `dish` to `cookies`)
+2. Type a message in the chat interface to test the prompt
+3. The assistant will respond using your configured model, developer message, and substituted variables
+
+
+
+The result will show the model's response with your variables substituted:
+
+
+
+### Step 6: Save Your Prompt
+
+Once you're satisfied with your prompt, click the **Save** button in the top right corner to save it to your prompt library.
+
+## Using Your Prompts
+
+Now that your prompt is published, you can use it in your application via the LiteLLM proxy API. Click the **Get Code** button in the UI to view code snippets customized for your prompt.
+
+### Basic Usage
+
+Call a prompt using just the prompt ID and model:
+
+
+
+
+```bash showLineNumbers title="Basic Prompt Call"
+curl -X POST 'http://localhost:4000/chat/completions' \
+ -H 'Content-Type: application/json' \
+ -H 'Authorization: Bearer sk-1234' \
+ -d '{
+ "model": "gpt-4",
+ "prompt_id": "your-prompt-id"
+ }' | jq
+```
+
+
+
+
+```python showLineNumbers title="basic_prompt.py"
+import openai
+
+client = openai.OpenAI(
+ api_key="sk-1234",
+ base_url="http://localhost:4000"
+)
+
+response = client.chat.completions.create(
+ model="gpt-4",
+ extra_body={
+ "prompt_id": "your-prompt-id"
+ }
+)
+
+print(response)
+```
+
+
+
+
+```javascript showLineNumbers title="basicPrompt.js"
+import OpenAI from 'openai';
+
+const client = new OpenAI({
+ apiKey: "sk-1234",
+ baseURL: "http://localhost:4000"
+});
+
+async function main() {
+ const response = await client.chat.completions.create({
+ model: "gpt-4",
+ prompt_id: "your-prompt-id"
+ });
+
+ console.log(response);
+}
+
+main();
+```
+
+
+
+
+### With Custom Messages
+
+Add custom messages to your prompt:
+
+
+
+
+```bash showLineNumbers title="Prompt with Custom Messages"
+curl -X POST 'http://localhost:4000/chat/completions' \
+ -H 'Content-Type: application/json' \
+ -H 'Authorization: Bearer sk-1234' \
+ -d '{
+ "model": "gpt-4",
+ "prompt_id": "your-prompt-id",
+ "messages": [
+ {
+ "role": "user",
+ "content": "hi"
+ }
+ ]
+ }' | jq
+```
+
+
+
+
+```python showLineNumbers title="prompt_with_messages.py"
+import openai
+
+client = openai.OpenAI(
+ api_key="sk-1234",
+ base_url="http://localhost:4000"
+)
+
+response = client.chat.completions.create(
+ model="gpt-4",
+ messages=[
+ {"role": "user", "content": "hi"}
+ ],
+ extra_body={
+ "prompt_id": "your-prompt-id"
+ }
+)
+
+print(response)
+```
+
+
+
+
+```javascript showLineNumbers title="promptWithMessages.js"
+import OpenAI from 'openai';
+
+const client = new OpenAI({
+ apiKey: "sk-1234",
+ baseURL: "http://localhost:4000"
+});
+
+async function main() {
+ const response = await client.chat.completions.create({
+ model: "gpt-4",
+ messages: [
+ { role: "user", content: "hi" }
+ ],
+ prompt_id: "your-prompt-id"
+ });
+
+ console.log(response);
+}
+
+main();
+```
+
+
+
+
+### With Prompt Variables
+
+Pass variables to your prompt template using `prompt_variables`:
+
+
+
+
+```bash showLineNumbers title="Prompt with Variables"
+curl -X POST 'http://localhost:4000/chat/completions' \
+ -H 'Content-Type: application/json' \
+ -H 'Authorization: Bearer sk-1234' \
+ -d '{
+ "model": "gpt-4",
+ "prompt_id": "your-prompt-id",
+ "prompt_variables": {
+ "dish": "cookies"
+ }
+ }' | jq
+```
+
+
+
+
+```python showLineNumbers title="prompt_with_variables.py"
+import openai
+
+client = openai.OpenAI(
+ api_key="sk-1234",
+ base_url="http://localhost:4000"
+)
+
+response = client.chat.completions.create(
+ model="gpt-4",
+ extra_body={
+ "prompt_id": "your-prompt-id",
+ "prompt_variables": {
+ "dish": "cookies"
+ }
+ }
+)
+
+print(response)
+```
+
+
+
+
+```javascript showLineNumbers title="promptWithVariables.js"
+import OpenAI from 'openai';
+
+const client = new OpenAI({
+ apiKey: "sk-1234",
+ baseURL: "http://localhost:4000"
+});
+
+async function main() {
+ const response = await client.chat.completions.create({
+ model: "gpt-4",
+ prompt_id: "your-prompt-id",
+ prompt_variables: {
+ "dish": "cookies"
+ }
+ });
+
+ console.log(response);
+}
+
+main();
+```
+
+
+
+
+## Prompt Versioning
+
+LiteLLM automatically versions your prompts each time you update them. This allows you to maintain a complete history of changes and roll back to previous versions if needed.
+
+### View Prompt Details
+
+Click on any prompt ID in the prompts table to view its details page. This page shows:
+- **Prompt ID**: The unique identifier for your prompt
+- **Version**: The current version number (e.g., v4)
+- **Prompt Type**: The storage type (e.g., db)
+- **Created At**: When the prompt was first created
+- **Last Updated**: Timestamp of the most recent update
+- **LiteLLM Parameters**: The raw JSON configuration
+
+
+
+### Update a Prompt
+
+To update an existing prompt:
+
+1. Click on the prompt you want to update from the prompts table
+2. Click the **Prompt Studio** button in the top right
+3. Make your changes to:
+ - Model selection
+ - Developer message (system instructions)
+ - Prompt messages
+ - Variables
+4. Test your changes in the chat interface on the right
+5. Click the **Update** button to save the new version
+
+
+
+Each time you click **Update**, a new version is created (v1 → v2 → v3, etc.) while maintaining the same prompt ID.
+
+### View Version History
+
+To view all versions of a prompt:
+
+1. Open the prompt in **Prompt Studio**
+2. Click the **History** button in the top right
+3. A **Version History** panel will open on the right side
+
+
+
+The version history panel displays:
+- **Latest version** (marked with a "Latest" badge and "Active" status)
+- All previous versions (v4, v3, v2, v1, etc.)
+- Timestamps for each version
+- Database save status ("Saved to Database")
+
+### View and Restore Older Versions
+
+To view or restore an older version:
+
+1. In the **Version History** panel, click on any previous version (e.g., v2)
+2. The prompt studio will load that version's configuration
+3. You can see:
+ - The developer message from that version
+ - The prompt messages from that version
+ - The model and parameters used
+ - All variables defined at that time
+
+
+
+The selected version will be highlighted with an "Active" badge in the version history panel.
+
+To restore an older version:
+1. View the older version you want to restore
+2. Click the **Update** button
+3. This will create a new version with the content from the older version
+
+### Use Specific Versions in API Calls
+
+By default, API calls use the latest version of a prompt. To use a specific version, pass the `prompt_version` parameter:
+
+
+
+
+```bash showLineNumbers title="Use Specific Prompt Version"
+curl -X POST 'http://localhost:4000/chat/completions' \
+ -H 'Content-Type: application/json' \
+ -H 'Authorization: Bearer sk-1234' \
+ -d '{
+ "model": "gpt-4",
+ "prompt_id": "jack-sparrow",
+ "prompt_version": 2,
+ "messages": [
+ {
+ "role": "user",
+ "content": "Who are u"
+ }
+ ]
+ }' | jq
+```
+
+
+
+
+```python showLineNumbers title="prompt_version.py"
+import openai
+
+client = openai.OpenAI(
+ api_key="sk-1234",
+ base_url="http://localhost:4000"
+)
+
+response = client.chat.completions.create(
+ model="gpt-4",
+ messages=[
+ {"role": "user", "content": "Who are u"}
+ ],
+ extra_body={
+ "prompt_id": "jack-sparrow",
+ "prompt_version": 2
+ }
+)
+
+print(response)
+```
+
+
+
+
+```javascript showLineNumbers title="promptVersion.js"
+import OpenAI from 'openai';
+
+const client = new OpenAI({
+ apiKey: "sk-1234",
+ baseURL: "http://localhost:4000"
+});
+
+async function main() {
+ const response = await client.chat.completions.create({
+ model: "gpt-4",
+ messages: [
+ { role: "user", content: "Who are u" }
+ ],
+ prompt_id: "jack-sparrow",
+ prompt_version: 2
+ });
+
+ console.log(response);
+}
+
+main();
+```
+
+
+
+
+
+
+
+
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diff --git a/docs/my-website/release_notes/v1.80.5-stable/index.md b/docs/my-website/release_notes/v1.80.5-stable/index.md
index 5a6aa998f8..72c3c9b627 100644
--- a/docs/my-website/release_notes/v1.80.5-stable/index.md
+++ b/docs/my-website/release_notes/v1.80.5-stable/index.md
@@ -53,7 +53,7 @@ pip install litellm==1.80.5
- **Logging Callback Controls** - [Admin-level controls to prevent callers from disabling logging callbacks in compliance environments](../../docs/proxy/dynamic_logging#disabling-dynamic-callback-management-enterprise)
- **Proxy CLI JWT Authentication** - [Enable developers to authenticate to LiteLLM AI Gateway using the Proxy CLI](../../docs/proxy/cli_sso)
- **Batch API Routing** - [Route batch operations to different provider accounts using model-specific credentials from your config.yaml](../../docs/batches#multi-account--model-based-routing)
-- **Prompt Management** - Full prompt versioning support with UI for editing, testing, and version history
+- **Prompt Management** - [Full prompt versioning support with UI for editing, testing, and version history](../../docs/proxy/litellm_prompt_management)
---
diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js
index 7f8a46b409..ecd5a01999 100644
--- a/docs/my-website/sidebars.js
+++ b/docs/my-website/sidebars.js
@@ -82,6 +82,7 @@ const sidebars = {
type: "category",
label: "[Beta] Prompt Management",
items: [
+ "proxy/litellm_prompt_management",
"proxy/custom_prompt_management",
"proxy/native_litellm_prompt",
"proxy/prompt_management"