# katanemo/plano

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5,120 stars · 290 forks · Rust · apache-2.0

## Links

- GitHub: https://github.com/katanemo/plano
- Homepage: https://planoai.dev
- awesome-repositories: https://awesome-repositories.com/repository/katanemo-plano.md

## Topics

`ai-gateway` `ai-gateway-support` `envoy` `envoyproxy` `gateway` `generative-ai` `llm-gateway` `llm-inference` `llm-proxy` `llm-routing` `llmops` `llms` `openai` `prompt` `proxy` `proxy-server` `routing`

## Description

Plano is an AI agent orchestrator and LLM gateway proxy that unifies access to multiple AI providers through a single interoperable interface. It functions as a model routing engine that decouples applications from specific vendors using semantic aliases, allowing traffic to be shifted between providers without modifying application code.

The system distinguishes itself with intent-based agent routing, which directs prompts to specialized agents based on semantic analysis. It features an interceptor-based filter chain system that acts as guardrail middleware to enforce safety policies, rewrite prompts, and validate inputs before they reach a model.

The project covers a broad operational surface, including automated OpenTelemetry-driven observability for tracing agentic signals, conversational state management for session affinity, and reliability tools such as automatic model fallbacks and endpoint load balancing. It also provides capabilities for converting natural language into structured backend function calls.

The server can be deployed as a containerized image in Docker or Kubernetes.

## Tags

### Artificial Intelligence & ML

- [Agentic Traffic Routing](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-traffic-routing.md) — The product inspects prompts and conversation state to decide which models, tools, or APIs to call. ([source](https://docs.planoai.dev/resources/tech_overview/model_serving.html))
- [AI Agent Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-agent-orchestration.md) — Orchestrates specialized AI agents by coordinating custom instructions, tools, and intent-based routing.
- [Agent Orchestration](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-application-orchestrators/agent-orchestration.md) — Centralizes the orchestration of traffic between clients and AI agents to decouple application logic from framework abstractions. ([source](https://docs.planoai.dev))
- [LLM Gateways](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-gateways.md) — Provides a centralized gateway to unify multiple LLM providers into a single interoperable API.
- [Guardrailed Inference Executions](https://awesome-repositories.com/f/artificial-intelligence-ml/agent-deployment-servers/llm-inference-servers/guardrail-servers/guardrailed-inference-executions.md) — Executes LLM inference through a guardrails layer that enforces safety policies on inbound and outbound traffic. ([source](https://docs.planoai.dev/concepts/listeners.html))
- [AI Agent Orchestrators](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/agent-orchestration-multi-agent/coordination-and-routing/ai-agent-orchestrators.md) — Ships a routing layer that organizes and coordinates specialized agents based on semantic user intent.
- [Model Provider Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/agentic-systems-frameworks/model-integration-serving/ai-model-orchestration/model-provider-integrations.md) — Provides unified interfaces for connecting and configuring multiple AI model providers using API keys and base URLs. ([source](https://docs.planoai.dev/concepts/llm_providers/supported_providers.html))
- [Model Request Routing](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-model-clients/model-request-routing.md) — Implements mechanisms for directing API requests to different AI backends via a centralized routing engine. ([source](https://docs.planoai.dev))
- [AI Safety Guardrails](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-safety-guardrails.md) — Implements safety guardrails through filter chains to detect jailbreaks and enforce content policies.
- [Guardrail-Enforced](https://awesome-repositories.com/f/artificial-intelligence-ml/chat-completion-services/guardrail-enforced.md) — Enforces safety guardrails on requests and responses through filter chains attached to AI agents. ([source](https://docs.planoai.dev/guides/orchestration.html))
- [LLM Jailbreak Protections](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-jailbreak-protections.md) — Implements jailbreak protection and content policies using centralized filter chains to ensure consistent model behavior. ([source](https://docs.planoai.dev/get_started/intro_to_plano.html))
- [LLM Observability](https://awesome-repositories.com/f/artificial-intelligence-ml/llm-observability.md) — Implements monitoring and tracing tools specifically designed for LLM-specific metrics and agentic workflows.
- [Model Abstraction Layers](https://awesome-repositories.com/f/artificial-intelligence-ml/model-abstraction-layers.md) — Provides a unified interface that decouples application logic from specific AI vendors using semantic aliases.
- [Model Alias Resolvers](https://awesome-repositories.com/f/artificial-intelligence-ml/model-alias-resolvers.md) — Maps semantic aliases to specific LLM instances to decouple client code from provider-specific model identifiers. ([source](https://docs.planoai.dev/concepts/llm_providers/model_aliases.html))
- [Model Format Translators](https://awesome-repositories.com/f/artificial-intelligence-ml/model-format-translators.md) — Translates request and response schemas between common SDKs and various LLM provider APIs. ([source](https://docs.planoai.dev/concepts/llm_providers/client_libraries.html))
- [Runtime Interoperability Layers](https://awesome-repositories.com/f/artificial-intelligence-ml/model-interoperability-layers/runtime-interoperability-layers.md) — Enables any supported SDK to call models from different providers through a single interoperable interface. ([source](https://docs.planoai.dev/concepts/llm_providers/client_libraries.html))
- [Model Provider Abstractions](https://awesome-repositories.com/f/artificial-intelligence-ml/model-provider-abstractions.md) — Provides interfaces that normalize API interactions across multiple AI service providers to hide vendor-specific details. ([source](https://docs.planoai.dev/concepts/llm_providers/llm_providers.html))
- [Model Provider Configurations](https://awesome-repositories.com/f/artificial-intelligence-ml/model-provider-configurations.md) — Manages provider configurations and aliases to swap AI vendors without refactoring application code. ([source](https://docs.planoai.dev/get_started/intro_to_plano.html))
- [Multi-Provider Abstractions](https://awesome-repositories.com/f/artificial-intelligence-ml/model-provider-integrations/multi-provider-abstractions.md) — Implements a common interface layer that routes requests across multiple AI providers to optimize cost and performance. ([source](https://docs.planoai.dev/concepts/llm_providers/llm_providers.html))
- [Model Provider Proxies](https://awesome-repositories.com/f/artificial-intelligence-ml/model-provider-proxies.md) — Provides a proxy layer that unifies requests between local and remote AI model providers. ([source](https://docs.planoai.dev/get_started/quickstart.html))
- [Model Routing](https://awesome-repositories.com/f/artificial-intelligence-ml/model-routing.md) — Manages traffic by mapping specific tasks and semantic aliases to optimal AI models.
- [Model Fallbacks](https://awesome-repositories.com/f/artificial-intelligence-ml/model-task-retries/model-fallbacks.md) — The product defines ordered pools of candidate models to allow automatic retries with alternative models upon failure. ([source](https://docs.planoai.dev/resources/configuration_reference.html))
- [Traffic Management](https://awesome-repositories.com/f/artificial-intelligence-ml/traffic-management.md) — Proxies, audits, and secures inbound traffic to AI models, including TLS termination and agent routing. ([source](https://docs.planoai.dev/concepts/listeners.html))
- [Provider Redundancy](https://awesome-repositories.com/f/artificial-intelligence-ml/traffic-management/provider-redundancy.md) — The product manages retries, fallbacks, and traffic splitting across multiple providers to ensure reliability. ([source](https://docs.planoai.dev/resources/tech_overview/model_serving.html))
- [External API Tool Exposures](https://awesome-repositories.com/f/artificial-intelligence-ml/ai-agent-integrations/ai-agent-tool-integrations/external-api-tool-exposures.md) — Exposes application operations as callable tools so AI agents can fetch data or execute workflows. ([source](https://docs.planoai.dev/get_started/intro_to_plano.html))
- [Conversation State Management](https://awesome-repositories.com/f/artificial-intelligence-ml/conversation-state-management.md) — Tracks context and history across multi-turn interactions to remove the need for clients to send full history. ([source](https://docs.planoai.dev/concepts/llm_providers/client_libraries.html))
- [External Service Integrations](https://awesome-repositories.com/f/artificial-intelligence-ml/external-service-integrations.md) — Connects to external HTTP endpoints or protocol services to execute reusable workflow steps as filters. ([source](https://docs.planoai.dev/concepts/filter_chain.html))
- [Language Model Observability](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/model-evaluation-analysis/language-model-observability.md) — Provides operational tracking of token consumption, financial costs, and response latency. ([source](https://docs.planoai.dev/get_started/quickstart.html))
- [Provider-Specific Routing Policies](https://awesome-repositories.com/f/artificial-intelligence-ml/provider-response-routing/provider-specific-routing-policies.md) — Directs incoming requests to specific upstream providers using configured API keys, base URLs, and model aliases. ([source](https://docs.planoai.dev/resources/configuration_reference.html))
- [Custom API Endpoints](https://awesome-repositories.com/f/artificial-intelligence-ml/self-hosted-ai-models/custom-api-endpoints.md) — Allows overriding default provider paths with custom URLs to route queries to self-hosted or internal AI endpoints. ([source](https://docs.planoai.dev/concepts/llm_providers/supported_providers.html))
- [Stateful Routing](https://awesome-repositories.com/f/artificial-intelligence-ml/workflow-state-management/stateful-routing.md) — The product shares session affinity data across server replicas using an external store to maintain consistent routing. ([source](https://docs.planoai.dev/guides/llm_router.html))

### Data & Databases

- [Provider-Agnostic Request Normalization](https://awesome-repositories.com/f/data-databases/data-format-converters/trace-format-normalization/provider-agnostic-request-normalization.md) — Normalizes outgoing requests into a provider-agnostic format and enforces rate limits to protect upstream providers. ([source](https://docs.planoai.dev/resources/tech_overview/request_lifecycle.html))
- [Agent-Specific Query Routing](https://awesome-repositories.com/f/data-databases/semantic-query-routing/agent-specific-query-routing.md) — Directs user prompts to specialized AI agents by analyzing semantic intent and conversation history.
- [Request Routing by Model ID](https://awesome-repositories.com/f/data-databases/model-as-a-table-integrations/request-routing-by-model-id.md) — The product designates a specific model to handle requests when no specific model is requested by the client. ([source](https://docs.planoai.dev/concepts/llm_providers/supported_providers.html))

### DevOps & Infrastructure

- [Preference-Based Routing](https://awesome-repositories.com/f/devops-infrastructure/api-service-management/api-management/ai-traffic-routing/safety-based-routing/preference-based-routing.md) — The product defines candidate pools of models and automatically falls back to alternatives upon receiving errors. ([source](https://docs.planoai.dev/concepts/llm_providers/supported_providers.html))
- [Failure Threshold Markers](https://awesome-repositories.com/f/devops-infrastructure/feature-flags/chromium-flag-monitors/failure-threshold-markers.md) — Appends visual markers to spans that meet specific failure thresholds for immediate identification. ([source](https://docs.planoai.dev/concepts/signals.html))
- [Traffic Load Balancers](https://awesome-repositories.com/f/devops-infrastructure/traffic-load-balancers.md) — The product distributes traffic across multiple provider instances using health checks and circuit breakers. ([source](https://docs.planoai.dev/resources/tech_overview/request_lifecycle.html))

### Networking & Communication

- [AI Provider Proxies](https://awesome-repositories.com/f/networking-communication/api-proxies/ai-provider-proxies.md) — Functions as a provider-agnostic proxy that normalizes outgoing requests and manages retries and fallbacks.
- [Request Processing](https://awesome-repositories.com/f/networking-communication/communication-protocols-architectures/request-processing-architectures/request-processing.md) — Implements middleware flows to inspect, rewrite, and enrich request data before delivery to the provider. ([source](https://docs.planoai.dev/concepts/filter_chain.html))
- [Model Connectivity Resilience](https://awesome-repositories.com/f/networking-communication/model-connectivity-resilience.md) — Handles model connectivity with retry and fail-over mechanisms to ensure high availability for model requests. ([source](https://docs.planoai.dev/concepts/llm_providers/llm_providers.html))
- [Concurrent Network Workers](https://awesome-repositories.com/f/networking-communication/concurrent-network-workers.md) — Utilizes non-blocking worker threads to handle high-volume network traffic and filtering tasks with low latency.

### Security & Cryptography

- [Middleware-Style Guardrail Pipelines](https://awesome-repositories.com/f/security-cryptography/content-guardrails/middleware-style-guardrail-pipelines.md) — Implements sequential chains of guardrail modules to inspect, modify, or block LLM requests and responses.
- [Input Guardrail Integrations](https://awesome-repositories.com/f/security-cryptography/llm-input-guardrails/input-guardrail-integrations.md) — Filters requests through external services to perform input validation and query rewriting before model execution. ([source](https://docs.planoai.dev/concepts/agents.html))
- [Request Filter Integrations](https://awesome-repositories.com/f/security-cryptography/request-authentication/request-filter-integrations.md) — Executes a sequence of interceptor filters to apply guardrails, rewrite prompts, and enrich context. ([source](https://docs.planoai.dev/resources/tech_overview/request_lifecycle.html))
- [Agent Behavioral Flags](https://awesome-repositories.com/f/security-cryptography/behavioral-threat-detection/agent-behavioral-flags.md) — Attaches visual flags and attributes to traces to identify quality issues or tool failures. ([source](https://docs.planoai.dev/concepts/signals.html))
- [Model-Pinning](https://awesome-repositories.com/f/security-cryptography/identity-access-management/session-management/session-identifiers/model-pinning.md) — Locks a specific model for a session using a unique identifier to ensure behavioral consistency. ([source](https://docs.planoai.dev/guides/llm_router.html))
- [Conversational Affinity](https://awesome-repositories.com/f/security-cryptography/identity-access-management/session-management/stateful-session-persistence/conversational-affinity.md) — Persists conversational context and model pinning across requests to maintain consistency without client-side history.
- [Access Control](https://awesome-repositories.com/f/security-cryptography/security/policies/access-control.md) — Enforces consistent security policies and access controls across all agents and AI providers. ([source](https://docs.planoai.dev))

### Software Engineering & Architecture

- [Intent-Based Workflow Determination](https://awesome-repositories.com/f/software-engineering-architecture/concurrency-schedulers/deterministic-runners/workflow-determinism/intent-based-workflow-determination.md) — Determines whether an incoming request should trigger a complex agent workflow or a simple task-specific prompt. ([source](https://docs.planoai.dev/resources/tech_overview/request_lifecycle.html))
- [Request-Response Filter Chains](https://awesome-repositories.com/f/software-engineering-architecture/interceptor-sequences/request-response-filter-chains.md) — Implements interceptor-based filter chains for prompt rewriting, context enrichment, and safety guardrail enforcement.
- [Unified Model Interfaces](https://awesome-repositories.com/f/software-engineering-architecture/unified-model-interfaces.md) — Provides a standardized API that offers a consistent execution interface for processing and streaming across different model providers. ([source](https://docs.planoai.dev/concepts/listeners.html))
- [Natural Language Tool Interfaces](https://awesome-repositories.com/f/software-engineering-architecture/api-abstraction-layers/natural-language-tool-interfaces.md) — Provides interfaces that map natural language instructions into structured and validated calls to backend services. ([source](https://docs.planoai.dev/get_started/quickstart.html))
- [Non-blocking I/O](https://awesome-repositories.com/f/software-engineering-architecture/concurrent-task-execution/non-blocking-i-o.md) — Uses non-blocking I/O and worker threads to execute filtering and forwarding tasks for high-performance request handling. ([source](https://docs.planoai.dev/resources/tech_overview/threading_model.html))
- [System Reliability](https://awesome-repositories.com/f/software-engineering-architecture/performance-reliability/system-reliability.md) — The product handles request retries and failovers across various agent instances to ensure system reliability. ([source](https://docs.planoai.dev/concepts/agents.html))
- [Information-Density Filters](https://awesome-repositories.com/f/software-engineering-architecture/tracing-instrumentation/trace-filters/information-density-filters.md) — Uses signal attributes to prioritize high-information traces for identifying sessions that require prompt updates. ([source](https://docs.planoai.dev/concepts/signals.html))
- [OTLP](https://awesome-repositories.com/f/software-engineering-architecture/tracing-instrumentation/trace-filters/otlp.md) — Enables analysis of request flows by filtering OTLP traces by specific identifiers, attributes, or time windows. ([source](https://docs.planoai.dev/resources/cli_reference.html))

### System Administration & Monitoring

- [Agent Execution Tracing](https://awesome-repositories.com/f/system-administration-monitoring/agent-execution-tracing.md) — Automatically captures reasoning traces, tool calls, and behavior metrics across all agents. ([source](https://docs.planoai.dev/get_started/intro_to_plano.html))
- [Automatic Tracing Instrumentation](https://awesome-repositories.com/f/system-administration-monitoring/automatic-tracing-instrumentation.md) — Generates automatic OpenTelemetry traces for every request without requiring manual instrumentation code. ([source](https://cdn.jsdelivr.net/gh/katanemo/plano@main/README.md))
- [OpenTelemetry-Integrated Monitors](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/real-time-process-monitors/agent-interaction-monitors/opentelemetry-integrated-monitors.md) — Integrates OpenTelemetry to capture end-to-end request lifecycles and agentic signals as structured spans.
- [OpenTelemetry Exporters](https://awesome-repositories.com/f/system-administration-monitoring/opentelemetry-exporters.md) — Exports request spans and routing decisions to external collectors using OpenTelemetry standards. ([source](https://docs.planoai.dev/resources/deployment.html))
- [Trace Metadata](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/execution-tracing-analysis/trace-metadata.md) — Attaches detected signals and contextual information as OpenTelemetry attributes and span events to execution traces. ([source](https://docs.planoai.dev/concepts/signals.html))
- [LLM Performance Monitoring](https://awesome-repositories.com/f/system-administration-monitoring/monitoring-and-observability/observability-platforms/metric-performance-monitors/llm-performance-monitoring.md) — Tracks LLM-specific performance metrics including token usage and time-to-first-token. ([source](https://docs.planoai.dev/guides/observability/tracing.html))
- [Request Tracing](https://awesome-repositories.com/f/system-administration-monitoring/request-tracing.md) — Provides utilities for monitoring and visualizing the end-to-end lifecycle of network requests through application layers. ([source](https://docs.planoai.dev/guides/observability/tracing.html))

### Web Development

- [Intent-Based Routing](https://awesome-repositories.com/f/web-development/request-routing/intent-based-routing.md) — Uses semantic analysis and classification to direct requests to specific models based on user intent. ([source](https://cdn.jsdelivr.net/gh/katanemo/plano@main/README.md))
- [Parameter Coercion and Validation](https://awesome-repositories.com/f/web-development/backend-development/request-response-handling/query-parameter-validations/parameter-coercion-and-validation.md) — Parses natural language prompts to extract and validate structured parameters against defined API constraints. ([source](https://docs.planoai.dev/resources/tech_overview/request_lifecycle.html))

### Development Tools & Productivity

- [Natural Language Function Executions](https://awesome-repositories.com/f/development-tools-productivity/local-function-execution/agent-integrated-functions/multi-caller-function-executions/natural-language-function-executions.md) — Translates natural language prompts into structured calls to perform transactional operations via backend functions. ([source](https://docs.planoai.dev/guides/function_calling.html))

### Testing & Quality Assurance

- [Policy Violation Blocking](https://awesome-repositories.com/f/testing-quality-assurance/contract-violation-filtering/policy-violation-blocking.md) — Blocks requests and returns early responses when an input filter detects a policy violation. ([source](https://docs.planoai.dev/concepts/filter_chain.html))

### Part of an Awesome List

- [Artificial Intelligence](https://awesome-repositories.com/f/awesome-lists/ai/artificial-intelligence.md) — AI-native proxy server and data plane for agentic applications.