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changelog/2025/apr.mdx

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---
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title: "April"
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---
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**April in review ◀️✨**
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We kicked off April with an announcement— we make 95% of LLM costs vanish overnight. Just a bait, some of you bit (≧ᗜ≦)
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While we can’t make bills disappear with a snap, we’ve delivered some powerful upgrades this month that will help you build and ship robust, reliable GenAI apps, faster!
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This month, we introduced updates to the platform and gateway around governance, security & guardrails, new integrations, and all the latest models! Along with this, we’re working on something bigger: [the missing piece](https://x.com/PortkeyAI/status/1912491547653701891) in the AI agents stack!
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Here’s what we shipped last month:
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## Summary
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| Area | Key Updates |
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| :-- | :-- |
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| Platform | • Prompt CRUD APIs<br/>• Export logs to your internal stack<br/>• Budget limits and rate limits on workspace<br/>• n8n integration<br/>• OpenAI Codex CLI integration<br/>• New retry setting to determine wait times<br/>• Milvus for Semantic Cache<br/>• Plugins moved to org-level Settings<br/>• Virtual Key exhaustion alert includes workspace<br/>• Workspace control setup option |
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| Gateway & Providers | • OpenAI embeddings latency improvement (200ms)<br/>• Responses API for OpenAI & Azure OpenAI<br/>• Bedrock prompt caching via unified API<br/>• Virtual keys for self-hosted models<br/>• Tool calling support for Groq, OpenRouter, and Ollama<br/>• New providers: Dashscope, Recraft AI, Replicate, Azure AI Foundry<br/>• Enhanced parameter support: Openrouter, Vertex AI, Perplexity, Bedrock<br/>• Claude’s `anthropic_beta` parameter for Computer use beta |
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| Technical Improvements | • Unified caching/logging of thinking responses<br/>• Strict metadata logging: Workspace > API Key > Request<br/>• Prompt render endpoint available on Gateway URL<br/>• API key default config now locked from overrides |
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| New Models & Integrations | • GPT-4.1<br/>• Gemini 2.5 Pro and Flash<br/>• LLaMA 4 via Fireworks, Together, Groq<br/>• o1-pro<br/>• gpt-image-1<br/>• Qwen 3<br/>• Audio models via Groq |
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| Guardrails | • Azure AI Content Safety integration<br/>• Exa Online Search as a Guardrail |
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---
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## Platform
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**Prompt CRUD APIs**
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Prompt CRUD APIs give you the control to scale by enabling you to:
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- Programmatically create, update, and delete prompts
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- Manage prompts in bulk or version-control them
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- Integrate prompt updates into your own tools and workflows
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- Automate updates for A/B testing and rapid experimentation
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Read more about this [here](https://portkey.ai/docs/api-reference/admin-api/control-plane/prompts/create-prompt).
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**Export logs to your internal stack**
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Enterprises can now push analytics logs to any OTEL-compliant store through Portkey to centralize monitoring, maintain compliance, and ensure efficient operations.
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See how it's done [here](https://portkey.ai/docs/product/enterprise-offering/components#analytics-store)
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**Budget limits and rate limts on workspace**
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Configure budget and rate limits at the workspace level to:
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- Allocate specific budgets to different departments, teams, or projects
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- Prevent individual workspaces from consuming disproportionate resources
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- Ensure equitable API access and complete visibility
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**n8n integration**
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Add enterprise-grade controls to your n8n workflows with:
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- **Unified AI Gateway**: Connect to 1600+ models with full API key management—not just OpenAI or Anthropic.
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- **Centralized observability**: Track 40+ metrics and request logs in real time.
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- **Governance**: Monitor spend, set budgets, and apply RBAC across workflows.
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- **Security guardrails**: Enable PII detection, content filtering, and compliance controls.
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Read more about the integration[here](https://portkey.ai/docs/integrations/libraries/n8n)
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**OpenAI Codex CLI integration**
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OpenAI Codex CLI gives developers a streamlined way to analyze, modify, and execute code directly from their terminal. Portkey's integration enhances this experience with:
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- Access to 250+ additional models beyond OpenAI Codex CLI's standard offerings
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- Content filtering and PII detection with guardrails
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- Real-time analytics and logging
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- Cost attribution, budget controls, RBAC, and more!
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Read more about the integration[here](https://portkey.ai/docs/integrations/libraries/codex#openai-codex-cli)
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**Other updates**
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- Introduced a new retry setting `use_retry_after_header`. When set to true, if the provider returns the `retry-after` or `retry-after-ms headers`, the Gateway will use these headers to determine retry wait times, rather than applying the default exponential backoff for 429 responses.
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- You can now store and retrieve vector embeddings for semantic cache using Milvus in Portkey. Read more about semantic cache store [here](https://portkey.ai/docs/product/enterprise-offering/components#semantic-cache-store)
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- Plugins have now been moved under Settings (org-level) in the Portkey app.
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- Virtual Key exhaustion alert emails now include which workspace the exhausted key belonged to.
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- Set up your workspace with Workspace control on the Portkey app.
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## Gateway & Providers
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**OpenAI embeddings response**
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We’ve optimized the Gateway’s handling of OpenAI embeddings requests, leading to around 200ms improvement in response latency.
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**Responses API**
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You can now use the Responses API to access OpenAI and Azure OpenAI models on Portkey, enabling a flexible and easier way to create agentic experiences.
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- Complete observability and usage tracking
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- Caching support for streaming requests
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- Access to advanced tools — web search, file search, and code execution, with per-tool cost tracking
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**Bedrock prompt caching**
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You can now implement Amazon Bedrock’s prompt caching through our OpenAI-compliant unified API and prompt templates.
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- Cache specific portions of your requests for repeated use
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- Reduce inference response latency and input token costs
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Read more about the implementation [here](https://portkey.ai/docs/integrations/llms/bedrock/prompt-caching)
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**Virtual keys for self-hosted models**
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You can now create a virtual key for any self-hosted model - whether you're running Ollama, vLLM, or any custom/private model.
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- No extra setup required
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- Stay in control with logs, traces, and key metrics
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- Manage all your LLM interactions through one interface
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**Advanced capabilities**
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- **Openrouter**: Added mapping for new parameters - modalities, reasoning, transforms, provider, models, response_format.
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- **Vertex AI**: Added support for explicitly mentioning mime_type for urls sent in the request. Gemini 2.5 thinking parameters are now available.
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- **Perplexity**: Added support for response_format and search_recency_filter request parameters.
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- **Bedrock**: You can now pass the `anthropic_beta` parameter in Bedrock’s Anthropic API via Portkey to enable Claude's Computer use beta feature.
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**Tool calling**
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Portkey now supports tool calling for Groq, OpenRouter, and Ollama
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**New Providers**
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<CardGroup cols={2}>
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<Card title="Dashscope">
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Integrate with Dashscope
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</Card>
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<Card title="Recraft AI">
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Generate production-ready visuals with Recraft
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</Card>
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</CardGroup>
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<CardGroup cols={2}>
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<Card title="Replicate">
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Run open-source models via simple APIs with Replicate
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</Card>
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<Card title="Azure AI Foundry">
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Access over 1,800 models with Azure AI Foundry
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</Card>
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</CardGroup>
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**Technical Improvements**
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- **Caching and Logging Unified Thinking Responses**: Unified thinking response (content_blocks) now logged and cached for stream responses.
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- **Strict Metadata Enforcement**: The metalogging preference order now is `Workspace Default > API Key Default > Incoming Request`. This is provide better control to org admins and ensure values set by them are not overridden.
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- **Prompt render endpoint**: Previously only available via the control plane, the prompt render endpoint is now supported directly on the Gateway URL.
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- Default config in an API key can no longer be overridden.
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## New Models & Integrations
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<CardGroup cols={2}>
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<Card title="GPT-4.1">
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OpenAI’s new model for faster and improved responses
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</Card>
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<Card title="Gemini 2.5 Pro">
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Google's most advanced model
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</Card>
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<Card title="Gemini 2.5 Flash">
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Google's fast, coest-efficient thinking model
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</Card>
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<Card title="Llama 4">
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Meta's latest model via Fireworks, Together, and Groq
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</Card>
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<Card title="o1-pro">
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OpenAI's model for better reasoning and consistent answers
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</Card>
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<Card title="gpt-image-1">
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OpenAI's latest image generation capabilities
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</Card>
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<Card title="Qwen 3">
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Alibaba's latest model with hybrid reasoning
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</Card>
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<Card title="Audio models">
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Access audio models via Groq
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</Card>
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</CardGroup>
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## Guardrails
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- **Azure AI content safety**: Use Microsoft’s content filtering solution to moderate inputs and outputs across supported models.
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- **Exa Online Search**: You can now configure Exa Online Search as a Guardrail in Portkey to enable real-time, grounded search across the web before answering. This makes any LLM capable of handling current events or live queries without needing model retraining.
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## Documentation
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<Card icon="book" title="Administration Docs" href="https://portkey.ai/docs/product/administration/enforcing-request-metadata" horizontal />
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We've made significant improvements to our documentation:
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- **Virtual keys access**: Defining who can view and manage virtual keys within workspaces. [Learn more](https://portkey.ai/docs/product/administration/configure-virtual-key-access-permissions)
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- **API keys access**: Control how workspace managers and members interact with API keys within their workspaces. [Learn more](https://portkey.ai/docs/product/administration/configure-api-key-access-permissions)
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## Community
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Here's a tutorial on how to build a customer supporr agent using Langraph and Portkey. Shoutout to [Nerding I/O](https://www.youtube.com/@nerding_io)!!
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<iframe width="560" height="315" src="https://www.youtube.com/embed/6MgPd3O3FXs?si=3FOPtlbTd9ayGN-1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
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**Customer love!**
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| <img src="/images/changelog/testimonial.jpeg" width="100%"/> | <img src="/images/changelog/testimonial2.png" width="100%" /> |
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| :-- | :-- |
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**Partner blog**
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[See](https://portkey.ai/blog/securing-your-ai-via-ai-gateways/) how Portkey and Pillar together can help you build secure GenAI apps for production.
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### Community Contributors
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A special thanks to our community contributors this month:
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- [unsync](https://github.com/unsync)
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- [francescov1](https://github.com/francescov1)
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- [Ajay Satish](https://github.com/Ajay-Satish-01)
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## Coming this month!
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We're changing how agents go to production, from first principles. [Watch out for this](https://x.com/PortkeyAI/status/1912491547653701891) 👀
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## Support
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<CardGroup cols={2}>
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<Card title="Need Help?" icon="bug" href="https://github.com/Portkey-AI/gateway/issues">
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Open an issue on GitHub
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</Card>
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<Card title="Join Us" icon="discord" href="https://portkey.wiki/community">
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Get support in our Discord
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</Card>
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</CardGroup>

docs.json

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{
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"group": "2025",
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"pages": [
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"changelog/2025/apr",
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"changelog/2025/mar",
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"changelog/2025/feb",
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"changelog/2025/jan"

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package-lock.json

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