diff --git a/docs.json b/docs.json
index d6dcc9df..b01de064 100644
--- a/docs.json
+++ b/docs.json
@@ -10,7 +10,7 @@
},
"favicon": "/favicon.png",
"navigation": {
- "versions":[
+ "versions": [
{
"version": "Using Model Catalog",
"tabs": [
@@ -87,9 +87,7 @@
},
{
"group": "Model Catalog",
- "pages": [
- "product/model-catalog"
- ]
+ "pages": ["product/model-catalog"]
},
{
"group": "Integrations",
@@ -406,6 +404,7 @@
"integrations/libraries/claude-code",
"integrations/libraries/anthropic-computer-use",
"integrations/libraries/cline",
+ "integrations/libraries/langflow",
"integrations/libraries/goose",
"integrations/libraries/janhq",
{
@@ -932,7 +931,11 @@
},
{
"group": "Enterprise Releases",
- "pages": ["changelog/enterprise", "changelog/helm-chart", "changelog/data-service"]
+ "pages": [
+ "changelog/enterprise",
+ "changelog/helm-chart",
+ "changelog/data-service"
+ ]
},
{
"group": "Product Releases",
@@ -1836,7 +1839,11 @@
},
{
"group": "Enterprise Releases",
- "pages": ["changelog/enterprise", "changelog/helm-chart", "changelog/data-service"]
+ "pages": [
+ "changelog/enterprise",
+ "changelog/helm-chart",
+ "changelog/data-service"
+ ]
},
{
"group": "Product Releases",
diff --git a/images/libraries/langflow-main.png b/images/libraries/langflow-main.png
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diff --git a/integrations/ai-apps.mdx b/integrations/ai-apps.mdx
index 65027a52..a128d027 100644
--- a/integrations/ai-apps.mdx
+++ b/integrations/ai-apps.mdx
@@ -24,6 +24,7 @@ title: "Overview"
+
diff --git a/integrations/libraries/langflow.mdx b/integrations/libraries/langflow.mdx
new file mode 100644
index 00000000..f010e640
--- /dev/null
+++ b/integrations/libraries/langflow.mdx
@@ -0,0 +1,398 @@
+---
+title: 'Langflow'
+description: 'Add enterprise-grade features to your Langflow AI workflows with Portkey'
+---
+
+Langflow is an open-source visual framework for building multi-agent and RAG applications. Its intuitive drag-and-drop interface allows developers to create complex AI workflows without writing extensive code.
+
+While Langflow provides powerful visual AI development capabilities, Portkey adds essential enterprise controls for production deployments:
+
+- **Unified AI Gateway** - Single interface for 1600+ LLMs with API key management (not just OpenAI)
+- **Centralized AI observability**: Real-time usage tracking for 40+ key metrics and logs for every request
+- **Governance** - Real-time spend tracking, set budget limits and RBAC in your Langflow workflows
+- **Security Guardrails** - PII detection, content filtering, and compliance controls
+
+This guide will walk you through integrating Portkey with Langflow and setting up essential enterprise features including usage tracking, access controls, and budget management.
+
+
+ If you are an enterprise looking to use Langflow in your organisation, [check out this section](#3-set-up-enterprise-governance-for-langflow).
+
+
+# 1. Setting up Portkey
+Portkey allows you to use 1600+ LLMs with your Langflow setup, with minimal configuration required. Let's set up the core components in Portkey that you'll need for integration.
+
+
+
+Virtual Keys are Portkey's secure way to manage your LLM provider API keys. Think of them like disposable credit cards for your LLM API keys, providing essential controls like:
+- Budget limits for API usage
+- Rate limiting capabilities
+- Secure API key storage
+
+To create a virtual key:
+Go to [Virtual Keys](https://app.portkey.ai/virtual-keys) in the Portkey App. Save and copy the virtual key ID
+
+
+
+
+
+
+Save your virtual key ID - you'll need it for the next step.
+
+
+
+
+
+Configs in Portkey are JSON objects that define how your requests are routed. They help with implementing features like advanced routing, fallbacks, and retries.
+
+We need to create a default config to route our requests to the virtual key created in Step 1.
+
+To create your config:
+1. Go to [Configs](https://app.portkey.ai/configs) in Portkey dashboard
+2. Create new config with:
+ ```json
+ {
+ "virtual_key": "YOUR_VIRTUAL_KEY_FROM_STEP1",
+ "override_params": {
+ "model": "gpt-4o" // Your preferred model name
+ }
+ }
+ ```
+3. Save and note the Config ID for the next step
+
+
+
+
+
+
+This basic config connects to your virtual key. You can add more advanced portkey features later.
+
+
+
+
+
+Now create Portkey API key access point and attach the config you created in Step 2:
+
+1. Go to [API Keys](https://app.portkey.ai/api-keys) in Portkey and Create new API key
+2. Select your config from `Step 2`
+3. Generate and save your API key
+
+
+
+
+
+
+Save your API key securely - you'll need it for Langflow integration.
+
+
+
+
+# 2. Integrate Portkey with Langflow
+
+Now that you have your Portkey components set up, let's connect them to Langflow. Since Portkey provides OpenAI API compatibility, integration is straightforward and requires just a few configuration steps in your Langflow interface.
+
+
+You need your Portkey API Key from [Step 1](#1-setting-up-portkey) before going further.
+
+
+
+
+First, ensure you have Langflow installed. You can install it via:
+- Docker
+- pip
+- Desktop app
+
+Follow the [official Langflow installation guide](https://docs.langflow.org/get-started/install-langflow) for detailed instructions.
+
+
+
+Launch Langflow and create a new flow or open an existing one that uses an OpenAI model component.
+
+
+
+1. Find the **OpenAI** model component in your flow
+2. Click on the component to select it
+3. Click on **Controls** in the component settings
+
+
+
+
+
+
+
+
+In the OpenAI model component settings, configure the following:
+
+- **Base URL**: `https://api.portkey.ai/v1`
+- **API Key**: Your Portkey API key from the setup
+
+
+
+
+
+
+Make sure your virtual key has sufficient budget and rate limits for your expected usage. Also use the complete model name given by the provider.
+
+
+
+
+That's it! Your Langflow workflows are now powered by Portkey. You can monitor your requests and usage in the [Portkey Dashboard](https://app.portkey.ai/dashboard).
+
+# 3. Set Up Enterprise Governance for Langflow
+
+**Why Enterprise Governance?**
+If you are using Langflow inside your organization, you need to consider several governance aspects:
+- **Cost Management**: Controlling and tracking AI spending across teams
+- **Access Control**: Managing which teams can use specific models
+- **Usage Analytics**: Understanding how AI is being used across the organization
+- **Security & Compliance**: Maintaining enterprise security standards
+- **Reliability**: Ensuring consistent service across all users
+
+Portkey adds a comprehensive governance layer to address these enterprise needs. Let's implement these controls step by step.
+
+**Enterprise Implementation Guide**
+
+
+
+### Step 1: Implement Budget Controls & Rate Limits
+
+Virtual Keys enable granular control over LLM access at the team/department level. This helps you:
+- Set up [budget limits](/product/ai-gateway/virtual-keys/budget-limits)
+- Prevent unexpected usage spikes using Rate limits
+- Track departmental spending
+
+#### Setting Up Department-Specific Controls:
+1. Navigate to [Virtual Keys](https://app.portkey.ai/virtual-keys) in Portkey dashboard
+2. Create new Virtual Key for each department with budget limits and rate limits
+3. Configure department-specific limits
+
+
+
+
+
+
+
+
+### Step 2: Define Model Access Rules
+
+As your AI usage scales, controlling which teams can access specific models becomes crucial. Portkey Configs provide this control layer with features like:
+
+#### Access Control Features:
+- **Model Restrictions**: Limit access to specific models
+- **Data Protection**: Implement guardrails for sensitive data
+- **Reliability Controls**: Add fallbacks and retry logic
+
+#### Example Configuration:
+Here's a basic configuration to route requests to OpenAI, specifically using GPT-4o:
+
+```json
+{
+ "strategy": {
+ "mode": "single"
+ },
+ "targets": [
+ {
+ "virtual_key": "YOUR_OPENAI_VIRTUAL_KEY",
+ "override_params": {
+ "model": "gpt-4o"
+ }
+ }
+ ]
+}
+```
+
+Create your config on the [Configs page](https://app.portkey.ai/configs) in your Portkey dashboard. You'll need the config ID for connecting to Langflow's setup.
+
+
+Configs can be updated anytime to adjust controls without affecting running workflows.
+
+
+
+
+### Step 3: Implement Access Controls
+
+Create User-specific API keys that automatically:
+- Track usage per user/team with the help of virtual keys
+- Apply appropriate configs to route requests
+- Collect relevant metadata to filter logs
+- Enforce access permissions
+
+Create API keys through:
+- [Portkey App](https://app.portkey.ai/)
+- [API Key Management API](/api-reference/admin-api/control-plane/api-keys/create-api-key)
+
+Example using Python SDK:
+```python
+from portkey_ai import Portkey
+
+portkey = Portkey(api_key="YOUR_ADMIN_API_KEY")
+
+api_key = portkey.api_keys.create(
+ name="engineering-team",
+ type="organisation",
+ workspace_id="YOUR_WORKSPACE_ID",
+ defaults={
+ "config_id": "your-config-id",
+ "metadata": {
+ "environment": "production",
+ "department": "engineering"
+ }
+ },
+ scopes=["logs.view", "configs.read"]
+)
+```
+
+For detailed key management instructions, see our [API Keys documentation](/api-reference/admin-api/control-plane/api-keys/create-api-key).
+
+
+
+### Step 4: Deploy & Monitor
+After distributing API keys to your team members, your enterprise-ready Langflow setup is ready to go. Each team member can now use their designated API keys with appropriate access levels and budget controls.
+
+Apply your governance setup using the integration steps from earlier sections
+Monitor usage in Portkey dashboard:
+- Cost tracking by department
+- Model usage patterns
+- Request volumes
+- Error rates
+
+
+
+
+
+### Enterprise Features Now Available
+**Langflow now has:**
+
+- Departmental budget controls
+- Model access governance
+- Usage tracking & attribution
+- Security guardrails
+- Reliability features
+
+
+
+# Portkey Features
+Now that you have enterprise-grade Langflow setup, let's explore the comprehensive features Portkey provides to ensure secure, efficient, and cost-effective AI operations.
+
+### 1. Comprehensive Metrics
+Using Portkey you can track 40+ key metrics including cost, token usage, response time, and performance across all your LLM providers in real time. You can also filter these metrics based on custom metadata that you can set in your configs. Learn more about metadata [here](/product/ai-gateway/metadata).
+
+
+ 
+
+
+### 2. Advanced Logs
+Portkey's logging dashboard provides detailed logs for every request made to your LLMs. These logs include:
+- Complete request and response tracking
+- Metadata tags for filtering
+- Cost attribution and much more...
+
+
+
+
+
+### 3. Unified Access to 1600+ LLMs
+
+You can easily switch between 1600+ LLMs. Call various LLMs such as Anthropic, Gemini, Mistral, Azure OpenAI, Google Vertex AI, AWS Bedrock, and many more by simply changing the `virtual key` in your default `config` object.
+
+### 4. Advanced Metadata Tracking
+Using Portkey, you can add custom metadata to your LLM requests for detailed tracking and analytics. Use metadata tags to filter logs, track usage, and attribute costs across departments and teams.
+
+
+
+
+### 5. Enterprise Access Management
+
+
+
+Set and manage spending limits across teams and departments. Control costs with granular budget limits and usage tracking.
+
+
+
+Enterprise-grade SSO integration with support for SAML 2.0, Okta, Azure AD, and custom providers for secure authentication.
+
+
+
+Hierarchical organization structure with workspaces, teams, and role-based access control for enterprise-scale deployments.
+
+
+
+Comprehensive access control rules and detailed audit logging for security compliance and usage tracking.
+
+
+
+### 6. Reliability Features
+
+
+ Automatically switch to backup targets if the primary target fails.
+
+
+ Route requests to different targets based on specified conditions.
+
+
+ Distribute requests across multiple targets based on defined weights.
+
+
+ Enable caching of responses to improve performance and reduce costs.
+
+
+Automatic retry handling with exponential backoff for failed requests
+
+
+ Set and manage budget limits across teams and departments. Control costs with granular budget limits and usage tracking.
+
+
+
+### 7. Advanced Guardrails
+
+Protect your Langflow workflows and enhance reliability with real-time checks on LLM inputs and outputs. Leverage guardrails to:
+- Prevent sensitive data leaks
+- Enforce compliance with organizational policies
+- PII detection and masking
+- Content filtering
+- Custom security rules
+- Data compliance checks
+
+
+Implement real-time protection for your LLM interactions with automatic detection and filtering of sensitive content, PII, and custom security rules. Enable comprehensive data protection while maintaining compliance with organizational policies.
+
+
+# FAQs
+
+
+ You can update your Virtual Key limits at any time from the Portkey dashboard:
+ 1. Go to Virtual Keys section
+ 2. Click on the Virtual Key you want to modify
+ 3. Update the budget or rate limits
+ 4. Save your changes
+
+
+ Yes! You can create multiple Virtual Keys (one for each provider) and attach them to a single config. This config can then be connected to your API key, allowing you to use multiple providers through a single API key.
+
+
+Portkey provides several ways to track team costs:
+- Create separate Virtual Keys for each team
+- Use metadata tags in your configs
+- Set up team-specific API keys
+- Monitor usage in the analytics dashboard
+
+
+When a team reaches their budget limit:
+1. Further requests will be blocked
+2. Team admins receive notifications
+3. Usage statistics remain available in dashboard
+4. Limits can be adjusted if needed
+
+
+Yes! While this guide focuses on the OpenAI component, Portkey can work with any model component that supports custom base URLs. Simply configure the base URL to `https://api.portkey.ai/v1` and use your Portkey API key.
+
+
+
+# Next Steps
+
+ **Join our Community**
+- [Discord Community](https://portkey.sh/discord-report)
+- [GitHub Repository](https://github.com/Portkey-AI)
+
+
+For enterprise support and custom features, contact our [enterprise team](https://calendly.com/portkey-ai).
+