diff --git a/_downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml b/_downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml index 808d0a98..99eb4510 100755 --- a/_downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml +++ b/_downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml @@ -1,5 +1,5 @@ # Plano Gateway configuration version -version: v0.3.0 +version: v0.4.0 # External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions) agents: @@ -32,17 +32,8 @@ model_providers: - model: mistral/ministral-3b-latest access_key: $MISTRAL_API_KEY - # routing_preferences: tags a model with named capabilities so Plano's LLM router - # can select the best model for each request based on intent. Requires the - # Plano-Orchestrator model (or equivalent) to be configured in overrides.llm_routing_model. - # Each preference has a name (short label) and a description (used for intent matching). - model: groq/llama-3.3-70b-versatile access_key: $GROQ_API_KEY - routing_preferences: - - name: code generation - description: generating new code snippets, functions, or boilerplate based on user prompts or requirements - - name: code review - description: reviewing, analyzing, and suggesting improvements to existing code # passthrough_auth: forwards the client's Authorization header upstream instead of # using the configured access_key. Useful for LiteLLM or similar proxy setups. @@ -64,6 +55,29 @@ model_aliases: smart-llm: target: gpt-4o +# routing_preferences: top-level list that tags named task categories with an +# ordered pool of candidate models. Plano's LLM router matches incoming requests +# against these descriptions and returns an ordered list of models; the client +# uses models[0] as primary and retries with models[1], models[2]... on 429/5xx. +# Requires overrides.llm_routing_model to point at Plano-Orchestrator (or equivalent). +# Each model in `models` must be declared in model_providers above. +# selection_policy is optional: {prefer: cheapest|fastest|none} lets the router +# reorder candidates using live cost/latency data from model_metrics_sources. +routing_preferences: + - name: code generation + description: generating new code snippets, functions, or boilerplate based on user prompts or requirements + models: + - anthropic/claude-sonnet-4-0 + - openai/gpt-4o + - groq/llama-3.3-70b-versatile + - name: code review + description: reviewing, analyzing, and suggesting improvements to existing code + models: + - anthropic/claude-sonnet-4-0 + - groq/llama-3.3-70b-versatile + selection_policy: + prefer: cheapest + # HTTP listeners - entry points for agent routing, prompt targets, and direct LLM access listeners: # Agent listener for routing requests to multiple agents diff --git a/concepts/llm_providers/supported_providers.html b/concepts/llm_providers/supported_providers.html index 9bb74fa7..f315feee 100755 --- a/concepts/llm_providers/supported_providers.html +++ b/concepts/llm_providers/supported_providers.html @@ -330,29 +330,35 @@ Any provider that implements the OpenAI API interface can be configured using cu

Configuration Examples:

-
llm_providers:
-  # Configure all Anthropic models with wildcard
-  - model: anthropic/*
-    access_key: $ANTHROPIC_API_KEY
-
-  # Or configure specific models
-  - model: anthropic/claude-opus-4-5
-    access_key: $ANTHROPIC_API_KEY
-
-  - model: anthropic/claude-sonnet-4-5
-    access_key: $ANTHROPIC_API_KEY
-
-  - model: anthropic/claude-haiku-4-5
-    access_key: $ANTHROPIC_API_KEY
-
-  # Override specific model with custom routing
-  - model: anthropic/*
-    access_key: $ANTHROPIC_API_KEY
-
-  - model: anthropic/claude-sonnet-4-20250514
-    access_key: $ANTHROPIC_PROD_API_KEY
-    routing_preferences:
-      - name: code_generation
+
version: v0.4.0
+
+model_providers:
+  # Configure all Anthropic models with wildcard
+  - model: anthropic/*
+    access_key: $ANTHROPIC_API_KEY
+
+  # Or configure specific models
+  - model: anthropic/claude-opus-4-5
+    access_key: $ANTHROPIC_API_KEY
+
+  - model: anthropic/claude-sonnet-4-5
+    access_key: $ANTHROPIC_API_KEY
+
+  - model: anthropic/claude-haiku-4-5
+    access_key: $ANTHROPIC_API_KEY
+
+  # Override specific model with custom routing
+  - model: anthropic/*
+    access_key: $ANTHROPIC_API_KEY
+
+  - model: anthropic/claude-sonnet-4-20250514
+    access_key: $ANTHROPIC_PROD_API_KEY
+
+routing_preferences:
+  - name: code_generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+    models:
+      - anthropic/claude-sonnet-4-20250514
 

 

 
@@ -969,22 +975,27 @@ Any provider that implements the OpenAI API interface can be configured using cu
 
 
Overriding Wildcard Models:

 
You can configure specific models with custom settings even when using wildcards. Specific configurations take precedence and are excluded from wildcard expansion:

-
llm_providers:
-  # Expand to all Anthropic models
-  - model: anthropic/*
-    access_key: $ANTHROPIC_API_KEY
-
-  # Override specific model with custom settings
-  # This model will NOT be included in the wildcard expansion above
-  - model: anthropic/claude-sonnet-4-20250514
-    access_key: $ANTHROPIC_PROD_API_KEY
-    routing_preferences:
-      - name: code_generation
-        priority: 1
-
-  # Another specific override
-  - model: anthropic/claude-3-haiku-20240307
-    access_key: $ANTHROPIC_DEV_API_KEY
+
version: v0.4.0
+
+model_providers:
+  # Expand to all Anthropic models
+  - model: anthropic/*
+    access_key: $ANTHROPIC_API_KEY
+
+  # Override specific model with custom settings
+  # This model will NOT be included in the wildcard expansion above
+  - model: anthropic/claude-sonnet-4-20250514
+    access_key: $ANTHROPIC_PROD_API_KEY
+
+  # Another specific override
+  - model: anthropic/claude-3-haiku-20240307
+    access_key: $ANTHROPIC_DEV_API_KEY
+
+routing_preferences:
+  - name: code_generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+    models:
+      - anthropic/claude-sonnet-4-20250514
 

 

 
Custom Provider Wildcards:

@@ -1023,23 +1034,36 @@ Any provider that implements the OpenAI API interface can be configured using cu
 
 

 
Routing Preferences

-
Configure routing preferences for dynamic model selection:

-
llm_providers:
-  - model: openai/gpt-5.2
-    access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: complex_reasoning
-        description: deep analysis, mathematical problem solving, and logical reasoning
-      - name: code_review
-        description: reviewing and analyzing existing code for bugs and improvements
+
Starting in v0.4.0, configure routing preferences at the top level of the config. Each preference declares an ordered models candidate pool; the first entry is primary and the rest are fallbacks the client tries on 429/5xx errors. Multiple providers can serve the same route — just list them all under models. See LLM Routing for the full routing model.

+
version: v0.4.0
+
+model_providers:
+  - model: openai/gpt-5.2
+    access_key: $OPENAI_API_KEY
+
+  - model: anthropic/claude-sonnet-4-5
+    access_key: $ANTHROPIC_API_KEY
 
-  - model: anthropic/claude-sonnet-4-5
-    access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative_writing
-        description: creative content generation, storytelling, and writing assistance
+routing_preferences:
+  - name: complex_reasoning
+    description: deep analysis, mathematical problem solving, and logical reasoning
+    models:
+      - openai/gpt-5.2
+      - anthropic/claude-sonnet-4-5
+  - name: code_review
+    description: reviewing and analyzing existing code for bugs and improvements
+    models:
+      - openai/gpt-5.2
+  - name: creative_writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
 

 

+

+
Note

+
v0.3.0 configs that declare routing_preferences inline under each model_provider are auto-migrated to this top-level shape by the Plano CLI at compile time, with a deprecation warning. Update to the form above to silence the warning and gain the multi-model fallback behavior.

+

 

 

 
Passthrough Authentication

diff --git a/guides/llm_router.html b/guides/llm_router.html
index f1c7a7a8..896f297a 100755
--- a/guides/llm_router.html
+++ b/guides/llm_router.html
@@ -292,39 +292,55 @@
 
Plano-Orchestrator analyzes each prompt to infer domain and action, then applies your preferences to select a model. This decouples routing policy (how to choose) from model assignment (what to run), making routing transparent, controllable, and easy to extend as you add or swap models.

 

 
Configuration

-
To configure preference-aligned dynamic routing, define routing preferences that map domains and actions to specific models:

+
To configure preference-aligned dynamic routing, declare a top-level routing_preferences list and attach an ordered models candidate pool to each route. Starting in v0.4.0, routing_preferences lives at the root of the config (not inline under model_providers), which lets multiple models serve the same route — the first entry in models is primary, the rest are fallbacks that the client tries on 429/5xx errors.

 

 
Preference-Aligned Dynamic Routing Configuration

-
listeners:
-  egress_traffic:
-    address: 0.0.0.0
-    port: 12000
-    message_format: openai
-    timeout: 30s
-
-llm_providers:
-  - model: openai/gpt-5.2
-    access_key: $OPENAI_API_KEY
-    default: true
-
-  - model: openai/gpt-5
-    access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: code understanding
-        description: understand and explain existing code snippets, functions, or libraries
-      - name: complex reasoning
-        description: deep analysis, mathematical problem solving, and logical reasoning
+
version: v0.4.0
+
+listeners:
+  - name: egress_traffic
+    type: model
+    address: 0.0.0.0
+    port: 12000
+    timeout: 30s
+
+model_providers:
+  - model: openai/gpt-5.2
+    access_key: $OPENAI_API_KEY
+    default: true
+
+  - model: openai/gpt-5
+    access_key: $OPENAI_API_KEY
+
+  - model: anthropic/claude-sonnet-4-5
+    access_key: $ANTHROPIC_API_KEY
 
-  - model: anthropic/claude-sonnet-4-5
-    access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative writing
-        description: creative content generation, storytelling, and writing assistance
-      - name: code generation
-        description: generating new code snippets, functions, or boilerplate based on user prompts
+routing_preferences:
+  - name: code understanding
+    description: understand and explain existing code snippets, functions, or libraries
+    models:
+      - openai/gpt-5
+      - anthropic/claude-sonnet-4-5
+  - name: complex reasoning
+    description: deep analysis, mathematical problem solving, and logical reasoning
+    models:
+      - openai/gpt-5
+  - name: creative writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
+  - name: code generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts
+    models:
+      - anthropic/claude-sonnet-4-5
+      - openai/gpt-5
 

 

 

+

+
Note

+
Configs still using the v0.3.0 inline style (routing_preferences nested under each model_provider) are auto-migrated to this top-level shape by the Plano CLI at compile time, with a deprecation warning. Update your config to the form above to silence the warning.

+

 

 

 
Client usage

@@ -380,22 +396,27 @@ Provides a practical mechanism to encode user preferences through domain-action
 
This downloads the quantized GGUF model from HuggingFace and starts serving on http://localhost:11434.

 
 
  • Configure Plano to use local routing model
    
-
    overrides:
-  llm_routing_model: plano/hf.co/katanemo/Arch-Router-1.5B.gguf:Q4_K_M
-
-model_providers:
-  - model: plano/hf.co/katanemo/Arch-Router-1.5B.gguf:Q4_K_M
-    base_url: http://localhost:11434
-
-  - model: openai/gpt-5.2
-    access_key: $OPENAI_API_KEY
-    default: true
-
-  - model: anthropic/claude-sonnet-4-5
-    access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative writing
-        description: creative content generation, storytelling, and writing assistance
+
    version: v0.4.0
+
+overrides:
+  llm_routing_model: plano/hf.co/katanemo/Arch-Router-1.5B.gguf:Q4_K_M
+
+model_providers:
+  - model: plano/hf.co/katanemo/Arch-Router-1.5B.gguf:Q4_K_M
+    base_url: http://localhost:11434
+
+  - model: openai/gpt-5.2
+    access_key: $OPENAI_API_KEY
+    default: true
+
+  - model: anthropic/claude-sonnet-4-5
+    access_key: $ANTHROPIC_API_KEY
+
+routing_preferences:
+  - name: creative writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
 
    
 
    
 
    • 
@@ -442,22 +463,27 @@ Provides a practical mechanism to encode user preferences through domain-action
 
    
 
 
  • Configure Plano to use the vLLM endpoint
    
-
    overrides:
-  llm_routing_model: plano/Plano-Orchestrator
-
-model_providers:
-  - model: plano/Plano-Orchestrator
-    base_url: http://<your-server-ip>:10000
-
-  - model: openai/gpt-5.2
-    access_key: $OPENAI_API_KEY
-    default: true
-
-  - model: anthropic/claude-sonnet-4-5
-    access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative writing
-        description: creative content generation, storytelling, and writing assistance
+
    version: v0.4.0
+
+overrides:
+  llm_routing_model: plano/Plano-Orchestrator
+
+model_providers:
+  - model: plano/Plano-Orchestrator
+    base_url: http://<your-server-ip>:10000
+
+  - model: openai/gpt-5.2
+    access_key: $OPENAI_API_KEY
+    default: true
+
+  - model: anthropic/claude-sonnet-4-5
+    access_key: $ANTHROPIC_API_KEY
+
+routing_preferences:
+  - name: creative writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
 
    
 
    
 
    • 
@@ -565,34 +591,42 @@ instead of a file.
    
 
    You can combine static model selection with dynamic routing preferences for maximum flexibility:
    
 
    
 
    Hybrid Routing Configuration
    
-
    llm_providers:
-  - model: openai/gpt-5.2
-    access_key: $OPENAI_API_KEY
-    default: true
-
-  - model: openai/gpt-5
-    access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: complex_reasoning
-        description: deep analysis and complex problem solving
-
-  - model: anthropic/claude-sonnet-4-5
-    access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative_tasks
-        description: creative writing and content generation
-
-model_aliases:
-  # Model aliases - friendly names that map to actual provider names
-  fast-model:
-    target: gpt-5.2
-
-  reasoning-model:
-    target: gpt-5
+
    version: v0.4.0
+
+model_providers:
+  - model: openai/gpt-5.2
+    access_key: $OPENAI_API_KEY
+    default: true
+
+  - model: openai/gpt-5
+    access_key: $OPENAI_API_KEY
+
+  - model: anthropic/claude-sonnet-4-5
+    access_key: $ANTHROPIC_API_KEY
+
+routing_preferences:
+  - name: complex_reasoning
+    description: deep analysis and complex problem solving
+    models:
+      - openai/gpt-5
+      - anthropic/claude-sonnet-4-5
+  - name: creative_tasks
+    description: creative writing and content generation
+    models:
+      - anthropic/claude-sonnet-4-5
+      - openai/gpt-5
 
-  # Aliases that can also participate in dynamic routing
-  creative-model:
-    target: claude-sonnet-4-5
+model_aliases:
+  # Model aliases - friendly names that map to actual provider names
+  fast-model:
+    target: gpt-5.2
+
+  reasoning-model:
+    target: gpt-5
+
+  # Aliases that can also participate in dynamic routing
+  creative-model:
+    target: claude-sonnet-4-5
 
    
 
    
 
    
diff --git a/includes/llms.txt b/includes/llms.txt
index f0b5c135..ed889b10 100755
--- a/includes/llms.txt
+++ b/includes/llms.txt
@@ -1,6 +1,6 @@
 Plano Docs v0.4.20
 llms.txt (auto-generated)
-Generated (UTC): 2026-04-24T19:31:46.972805+00:00
+Generated (UTC): 2026-04-24T19:32:12.216149+00:00
 
 Table of contents
 - Agents (concepts/agents)
@@ -1381,7 +1381,9 @@ Complex agents and coding
 
 Configuration Examples:
 
-llm_providers:
+version: v0.4.0
+
+model_providers:
   # Configure all Anthropic models with wildcard
   - model: anthropic/*
     access_key: $ANTHROPIC_API_KEY
@@ -1402,8 +1404,12 @@ llm_providers:
 
   - model: anthropic/claude-sonnet-4-20250514
     access_key: $ANTHROPIC_PROD_API_KEY
-    routing_preferences:
-      - name: code_generation
+
+routing_preferences:
+  - name: code_generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+    models:
+      - anthropic/claude-sonnet-4-20250514
 
 DeepSeek
 
@@ -2084,7 +2090,9 @@ Overriding Wildcard Models:
 
 You can configure specific models with custom settings even when using wildcards. Specific configurations take precedence and are excluded from wildcard expansion:
 
-llm_providers:
+version: v0.4.0
+
+model_providers:
   # Expand to all Anthropic models
   - model: anthropic/*
     access_key: $ANTHROPIC_API_KEY
@@ -2093,14 +2101,17 @@ llm_providers:
   # This model will NOT be included in the wildcard expansion above
   - model: anthropic/claude-sonnet-4-20250514
     access_key: $ANTHROPIC_PROD_API_KEY
-    routing_preferences:
-      - name: code_generation
-        priority: 1
 
   # Another specific override
   - model: anthropic/claude-3-haiku-20240307
     access_key: $ANTHROPIC_DEV_API_KEY
 
+routing_preferences:
+  - name: code_generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+    models:
+      - anthropic/claude-sonnet-4-20250514
+
 Custom Provider Wildcards:
 
 For providers not in Plano’s registry, wildcards enable dynamic model routing:
@@ -2139,22 +2150,33 @@ llm_providers:
 
 Routing Preferences
 
-Configure routing preferences for dynamic model selection:
+Starting in v0.4.0, configure routing preferences at the top level of the config. Each preference declares an ordered models candidate pool; the first entry is primary and the rest are fallbacks the client tries on 429/5xx errors. Multiple providers can serve the same route — just list them all under models. See /guides/llm_router for the full routing model.
 
-llm_providers:
+version: v0.4.0
+
+model_providers:
   - model: openai/gpt-5.2
     access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: complex_reasoning
-        description: deep analysis, mathematical problem solving, and logical reasoning
-      - name: code_review
-        description: reviewing and analyzing existing code for bugs and improvements
 
   - model: anthropic/claude-sonnet-4-5
     access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative_writing
-        description: creative content generation, storytelling, and writing assistance
+
+routing_preferences:
+  - name: complex_reasoning
+    description: deep analysis, mathematical problem solving, and logical reasoning
+    models:
+      - openai/gpt-5.2
+      - anthropic/claude-sonnet-4-5
+  - name: code_review
+    description: reviewing and analyzing existing code for bugs and improvements
+    models:
+      - openai/gpt-5.2
+  - name: creative_writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
+
+v0.3.0 configs that declare routing_preferences inline under each model_provider are auto-migrated to this top-level shape by the Plano CLI at compile time, with a deprecation warning. Update to the form above to silence the warning and gain the multi-model fallback behavior.
 
 
 
@@ -4179,37 +4201,51 @@ Plano-Orchestrator analyzes each prompt to infer domain and action, then applies
 
 Configuration
 
-To configure preference-aligned dynamic routing, define routing preferences that map domains and actions to specific models:
+To configure preference-aligned dynamic routing, declare a top-level routing_preferences list and attach an ordered models candidate pool to each route. Starting in v0.4.0, routing_preferences lives at the root of the config (not inline under model_providers), which lets multiple models serve the same route — the first entry in models is primary, the rest are fallbacks that the client tries on 429/5xx errors.
 
 Preference-Aligned Dynamic Routing Configuration
 
+version: v0.4.0
+
 listeners:
-  egress_traffic:
+  - name: egress_traffic
+    type: model
     address: 0.0.0.0
     port: 12000
-    message_format: openai
     timeout: 30s
 
-llm_providers:
+model_providers:
   - model: openai/gpt-5.2
     access_key: $OPENAI_API_KEY
     default: true
 
   - model: openai/gpt-5
     access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: code understanding
-        description: understand and explain existing code snippets, functions, or libraries
-      - name: complex reasoning
-        description: deep analysis, mathematical problem solving, and logical reasoning
 
   - model: anthropic/claude-sonnet-4-5
     access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative writing
-        description: creative content generation, storytelling, and writing assistance
-      - name: code generation
-        description: generating new code snippets, functions, or boilerplate based on user prompts
+
+routing_preferences:
+  - name: code understanding
+    description: understand and explain existing code snippets, functions, or libraries
+    models:
+      - openai/gpt-5
+      - anthropic/claude-sonnet-4-5
+  - name: complex reasoning
+    description: deep analysis, mathematical problem solving, and logical reasoning
+    models:
+      - openai/gpt-5
+  - name: creative writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
+  - name: code generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts
+    models:
+      - anthropic/claude-sonnet-4-5
+      - openai/gpt-5
+
+Configs still using the v0.3.0 inline style (routing_preferences nested under each model_provider) are auto-migrated to this top-level shape by the Plano CLI at compile time, with a deprecation warning. Update your config to the form above to silence the warning.
 
 Client usage
 
@@ -4273,6 +4309,8 @@ This downloads the quantized GGUF model from HuggingFace and starts serving on h
 
 Configure Plano to use local routing model
 
+version: v0.4.0
+
 overrides:
   llm_routing_model: plano/hf.co/katanemo/Arch-Router-1.5B.gguf:Q4_K_M
 
@@ -4286,9 +4324,12 @@ model_providers:
 
   - model: anthropic/claude-sonnet-4-5
     access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative writing
-        description: creative content generation, storytelling, and writing assistance
+
+routing_preferences:
+  - name: creative writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
 
 Verify the model is running
 
@@ -4331,6 +4372,8 @@ vllm serve ${SNAPSHOT_DIR}Arch-Router-1.5B-Q4_K_M.gguf \
 
 Configure Plano to use the vLLM endpoint
 
+version: v0.4.0
+
 overrides:
   llm_routing_model: plano/Plano-Orchestrator
 
@@ -4344,9 +4387,12 @@ model_providers:
 
   - model: anthropic/claude-sonnet-4-5
     access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative writing
-        description: creative content generation, storytelling, and writing assistance
+
+routing_preferences:
+  - name: creative writing
+    description: creative content generation, storytelling, and writing assistance
+    models:
+      - anthropic/claude-sonnet-4-5
 
 Verify the server is running
 
@@ -4460,22 +4506,30 @@ You can combine static model selection with dynamic routing preferences for maxi
 
 Hybrid Routing Configuration
 
-llm_providers:
+version: v0.4.0
+
+model_providers:
   - model: openai/gpt-5.2
     access_key: $OPENAI_API_KEY
     default: true
 
   - model: openai/gpt-5
     access_key: $OPENAI_API_KEY
-    routing_preferences:
-      - name: complex_reasoning
-        description: deep analysis and complex problem solving
 
   - model: anthropic/claude-sonnet-4-5
     access_key: $ANTHROPIC_API_KEY
-    routing_preferences:
-      - name: creative_tasks
-        description: creative writing and content generation
+
+routing_preferences:
+  - name: complex_reasoning
+    description: deep analysis and complex problem solving
+    models:
+      - openai/gpt-5
+      - anthropic/claude-sonnet-4-5
+  - name: creative_tasks
+    description: creative writing and content generation
+    models:
+      - anthropic/claude-sonnet-4-5
+      - openai/gpt-5
 
 model_aliases:
   # Model aliases - friendly names that map to actual provider names
@@ -6895,7 +6949,7 @@ where prompts get routed to, apply guardrails, and enable critical agent observa
 Plano Configuration - Full Reference
 
 # Plano Gateway configuration version
-version: v0.3.0
+version: v0.4.0
 
 # External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)
 agents:
@@ -6928,17 +6982,8 @@ model_providers:
   - model: mistral/ministral-3b-latest
     access_key: $MISTRAL_API_KEY
 
-  # routing_preferences: tags a model with named capabilities so Plano's LLM router
-  # can select the best model for each request based on intent. Requires the
-  # Plano-Orchestrator model (or equivalent) to be configured in overrides.llm_routing_model.
-  # Each preference has a name (short label) and a description (used for intent matching).
   - model: groq/llama-3.3-70b-versatile
     access_key: $GROQ_API_KEY
-    routing_preferences:
-      - name: code generation
-        description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
-      - name: code review
-        description: reviewing, analyzing, and suggesting improvements to existing code
 
   # passthrough_auth: forwards the client's Authorization header upstream instead of
   # using the configured access_key. Useful for LiteLLM or similar proxy setups.
@@ -6960,6 +7005,29 @@ model_aliases:
   smart-llm:
     target: gpt-4o
 
+# routing_preferences: top-level list that tags named task categories with an
+# ordered pool of candidate models. Plano's LLM router matches incoming requests
+# against these descriptions and returns an ordered list of models; the client
+# uses models[0] as primary and retries with models[1], models[2]... on 429/5xx.
+# Requires overrides.llm_routing_model to point at Plano-Orchestrator (or equivalent).
+# Each model in `models` must be declared in model_providers above.
+# selection_policy is optional: {prefer: cheapest|fastest|none} lets the router
+# reorder candidates using live cost/latency data from model_metrics_sources.
+routing_preferences:
+  - name: code generation
+    description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+    models:
+      - anthropic/claude-sonnet-4-0
+      - openai/gpt-4o
+      - groq/llama-3.3-70b-versatile
+  - name: code review
+    description: reviewing, analyzing, and suggesting improvements to existing code
+    models:
+      - anthropic/claude-sonnet-4-0
+      - groq/llama-3.3-70b-versatile
+    selection_policy:
+      prefer: cheapest
+
 # HTTP listeners - entry points for agent routing, prompt targets, and direct LLM access
 listeners:
   # Agent listener for routing requests to multiple agents
diff --git a/resources/configuration_reference.html b/resources/configuration_reference.html
index 6c6d993c..c9843fa3 100755
--- a/resources/configuration_reference.html
+++ b/resources/configuration_reference.html
@@ -168,7 +168,7 @@ where prompts get routed to, apply guardrails, and enable critical agent observa
 
    
 
    Plano Configuration - Full Reference
    
 
      1# Plano Gateway configuration version
-  2version: v0.3.0
+  2version: v0.4.0
   3
   4# External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)
   5agents:
@@ -201,195 +201,209 @@ where prompts get routed to, apply guardrails, and enable critical agent observa
  32  - model: mistral/ministral-3b-latest
  33    access_key: $MISTRAL_API_KEY
  34
- 35  # routing_preferences: tags a model with named capabilities so Plano's LLM router
- 36  # can select the best model for each request based on intent. Requires the
- 37  # Plano-Orchestrator model (or equivalent) to be configured in overrides.llm_routing_model.
- 38  # Each preference has a name (short label) and a description (used for intent matching).
- 39  - model: groq/llama-3.3-70b-versatile
- 40    access_key: $GROQ_API_KEY
- 41    routing_preferences:
- 42      - name: code generation
- 43        description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
- 44      - name: code review
- 45        description: reviewing, analyzing, and suggesting improvements to existing code
- 46
- 47  # passthrough_auth: forwards the client's Authorization header upstream instead of
- 48  # using the configured access_key. Useful for LiteLLM or similar proxy setups.
- 49  - model: openai/gpt-4o-litellm
- 50    base_url: https://litellm.example.com
- 51    passthrough_auth: true
- 52
- 53  # Custom/self-hosted endpoint with explicit http_host override
- 54  - model: openai/llama-3.3-70b
- 55    base_url: https://api.custom-provider.com
- 56    http_host: api.custom-provider.com
- 57    access_key: $CUSTOM_API_KEY
- 58
- 59# Model aliases - use friendly names instead of full provider model names
- 60model_aliases:
- 61  fast-llm:
- 62    target: gpt-4o-mini
- 63
- 64  smart-llm:
- 65    target: gpt-4o
- 66
- 67# HTTP listeners - entry points for agent routing, prompt targets, and direct LLM access
- 68listeners:
- 69  # Agent listener for routing requests to multiple agents
- 70  - type: agent
- 71    name: travel_booking_service
- 72    port: 8001
- 73    router: plano_orchestrator_v1
- 74    address: 0.0.0.0
- 75    agents:
- 76      - id: rag_agent
- 77        description: virtual assistant for retrieval augmented generation tasks
- 78        input_filters:
- 79          - input_guards
+ 35  - model: groq/llama-3.3-70b-versatile
+ 36    access_key: $GROQ_API_KEY
+ 37
+ 38  # passthrough_auth: forwards the client's Authorization header upstream instead of
+ 39  # using the configured access_key. Useful for LiteLLM or similar proxy setups.
+ 40  - model: openai/gpt-4o-litellm
+ 41    base_url: https://litellm.example.com
+ 42    passthrough_auth: true
+ 43
+ 44  # Custom/self-hosted endpoint with explicit http_host override
+ 45  - model: openai/llama-3.3-70b
+ 46    base_url: https://api.custom-provider.com
+ 47    http_host: api.custom-provider.com
+ 48    access_key: $CUSTOM_API_KEY
+ 49
+ 50# Model aliases - use friendly names instead of full provider model names
+ 51model_aliases:
+ 52  fast-llm:
+ 53    target: gpt-4o-mini
+ 54
+ 55  smart-llm:
+ 56    target: gpt-4o
+ 57
+ 58# routing_preferences: top-level list that tags named task categories with an
+ 59# ordered pool of candidate models. Plano's LLM router matches incoming requests
+ 60# against these descriptions and returns an ordered list of models; the client
+ 61# uses models[0] as primary and retries with models[1], models[2]... on 429/5xx.
+ 62# Requires overrides.llm_routing_model to point at Plano-Orchestrator (or equivalent).
+ 63# Each model in `models` must be declared in model_providers above.
+ 64# selection_policy is optional: {prefer: cheapest|fastest|none} lets the router
+ 65# reorder candidates using live cost/latency data from model_metrics_sources.
+ 66routing_preferences:
+ 67  - name: code generation
+ 68    description: generating new code snippets, functions, or boilerplate based on user prompts or requirements
+ 69    models:
+ 70      - anthropic/claude-sonnet-4-0
+ 71      - openai/gpt-4o
+ 72      - groq/llama-3.3-70b-versatile
+ 73  - name: code review
+ 74    description: reviewing, analyzing, and suggesting improvements to existing code
+ 75    models:
+ 76      - anthropic/claude-sonnet-4-0
+ 77      - groq/llama-3.3-70b-versatile
+ 78    selection_policy:
+ 79      prefer: cheapest
  80
- 81  # Model listener for direct LLM access
- 82  - type: model
- 83    name: model_1
- 84    address: 0.0.0.0
- 85    port: 12000
- 86    timeout: 30s          # Request timeout (e.g. "30s", "60s")
- 87    max_retries: 3        # Number of retries on upstream failure
- 88    input_filters:        # Filters applied before forwarding to LLM
- 89      - input_guards
- 90    output_filters:       # Filters applied to LLM responses before returning to client
- 91      - input_guards
- 92
- 93  # Prompt listener for function calling (for prompt_targets)
- 94  - type: prompt
- 95    name: prompt_function_listener
- 96    address: 0.0.0.0
- 97    port: 10000
- 98
- 99# Reusable service endpoints
-100endpoints:
-101  app_server:
-102    endpoint: 127.0.0.1:80
-103    connect_timeout: 0.005s
-104    protocol: http        # http or https
-105
-106  mistral_local:
-107    endpoint: 127.0.0.1:8001
-108
-109  secure_service:
-110    endpoint: api.example.com:443
-111    protocol: https
-112    http_host: api.example.com  # Override the Host header sent upstream
-113
-114# Optional top-level system prompt applied to all prompt_targets
-115system_prompt: |
-116  You are a helpful assistant. Always respond concisely and accurately.
-117
-118# Prompt targets for function calling and API orchestration
-119prompt_targets:
-120  - name: get_current_weather
-121    description: Get current weather at a location.
-122    parameters:
-123      - name: location
-124        description: The location to get the weather for
-125        required: true
-126        type: string
-127        format: City, State
-128      - name: days
-129        description: the number of days for the request
-130        required: true
-131        type: int
-132    endpoint:
-133      name: app_server
-134      path: /weather
-135      http_method: POST
-136    # Per-target system prompt (overrides top-level system_prompt for this target)
-137    system_prompt: You are a weather expert. Provide accurate and concise weather information.
-138    # auto_llm_dispatch_on_response: when true, the LLM is called again with the
-139    # function response to produce a final natural-language answer for the user
-140    auto_llm_dispatch_on_response: true
-141
-142# Rate limits - control token usage per model and request selector
-143ratelimits:
-144  - model: openai/gpt-4o
-145    selector:
-146      key: x-user-id       # HTTP header key used to identify the rate-limit subject
-147      value: "*"           # Wildcard matches any value; use a specific string to target one
-148    limit:
-149      tokens: 100000       # Maximum tokens allowed in the given time unit
-150      unit: hour           # Time unit: "minute", "hour", or "day"
-151
-152  - model: openai/gpt-4o-mini
-153    selector:
-154      key: x-org-id
-155      value: acme-corp
-156    limit:
-157      tokens: 500000
-158      unit: day
-159
-160# Global behavior overrides
-161overrides:
-162  # Threshold for routing a request to a prompt_target (0.0–1.0). Lower = more permissive.
-163  prompt_target_intent_matching_threshold: 0.7
-164  # Trim conversation history to fit within the model's context window
-165  optimize_context_window: true
-166  # Use Plano's agent orchestrator for multi-agent request routing
-167  use_agent_orchestrator: false
-168  # Connect timeout for upstream provider clusters (e.g., "5s", "10s"). Default: "5s"
-169  upstream_connect_timeout: 10s
-170  # Path to the trusted CA bundle for upstream TLS verification
-171  upstream_tls_ca_path: /etc/ssl/certs/ca-certificates.crt
-172  # Model used for intent-based LLM routing (must be listed in model_providers)
-173  llm_routing_model: Plano-Orchestrator
-174  # Model used for agent orchestration (must be listed in model_providers)
-175  agent_orchestration_model: Plano-Orchestrator
-176  # Disable agentic signal analysis (frustration, repetition, escalation, etc.)
-177  # on LLM responses to save CPU. Default: false.
-178  disable_signals: false
-179
-180# Model affinity — pin routing decisions for agentic loops
-181routing:
-182  session_ttl_seconds: 600    # How long a pinned session lasts (default: 600s / 10 min)
-183  session_max_entries: 10000  # Max cached sessions before eviction (upper limit: 10000)
-184  # session_cache controls the backend used to store affinity state.
-185  # "memory" (default) is in-process and works for single-instance deployments.
-186  # "redis" shares state across replicas — required for multi-replica / Kubernetes setups.
-187  session_cache:
-188    type: memory              # "memory" (default) or "redis"
-189    # url is required when type is "redis". Supports redis:// and rediss:// (TLS).
-190    # url: redis://localhost:6379
-191    # tenant_header: x-org-id  # optional; when set, keys are scoped as plano:affinity:{tenant_id}:{session_id}
-192
-193# State storage for multi-turn conversation history
-194state_storage:
-195  type: memory            # "memory" (in-process) or "postgres" (persistent)
-196  # connection_string is required when type is postgres.
-197  # Supports environment variable substitution: $VAR or ${VAR}
-198  # connection_string: postgresql://user:$DB_PASS@localhost:5432/plano
-199
-200# Input guardrails applied globally to all incoming requests
-201prompt_guards:
-202  input_guards:
-203    jailbreak:
-204      on_exception:
-205        message: "I'm sorry, I can't help with that request."
+ 81# HTTP listeners - entry points for agent routing, prompt targets, and direct LLM access
+ 82listeners:
+ 83  # Agent listener for routing requests to multiple agents
+ 84  - type: agent
+ 85    name: travel_booking_service
+ 86    port: 8001
+ 87    router: plano_orchestrator_v1
+ 88    address: 0.0.0.0
+ 89    agents:
+ 90      - id: rag_agent
+ 91        description: virtual assistant for retrieval augmented generation tasks
+ 92        input_filters:
+ 93          - input_guards
+ 94
+ 95  # Model listener for direct LLM access
+ 96  - type: model
+ 97    name: model_1
+ 98    address: 0.0.0.0
+ 99    port: 12000
+100    timeout: 30s          # Request timeout (e.g. "30s", "60s")
+101    max_retries: 3        # Number of retries on upstream failure
+102    input_filters:        # Filters applied before forwarding to LLM
+103      - input_guards
+104    output_filters:       # Filters applied to LLM responses before returning to client
+105      - input_guards
+106
+107  # Prompt listener for function calling (for prompt_targets)
+108  - type: prompt
+109    name: prompt_function_listener
+110    address: 0.0.0.0
+111    port: 10000
+112
+113# Reusable service endpoints
+114endpoints:
+115  app_server:
+116    endpoint: 127.0.0.1:80
+117    connect_timeout: 0.005s
+118    protocol: http        # http or https
+119
+120  mistral_local:
+121    endpoint: 127.0.0.1:8001
+122
+123  secure_service:
+124    endpoint: api.example.com:443
+125    protocol: https
+126    http_host: api.example.com  # Override the Host header sent upstream
+127
+128# Optional top-level system prompt applied to all prompt_targets
+129system_prompt: |
+130  You are a helpful assistant. Always respond concisely and accurately.
+131
+132# Prompt targets for function calling and API orchestration
+133prompt_targets:
+134  - name: get_current_weather
+135    description: Get current weather at a location.
+136    parameters:
+137      - name: location
+138        description: The location to get the weather for
+139        required: true
+140        type: string
+141        format: City, State
+142      - name: days
+143        description: the number of days for the request
+144        required: true
+145        type: int
+146    endpoint:
+147      name: app_server
+148      path: /weather
+149      http_method: POST
+150    # Per-target system prompt (overrides top-level system_prompt for this target)
+151    system_prompt: You are a weather expert. Provide accurate and concise weather information.
+152    # auto_llm_dispatch_on_response: when true, the LLM is called again with the
+153    # function response to produce a final natural-language answer for the user
+154    auto_llm_dispatch_on_response: true
+155
+156# Rate limits - control token usage per model and request selector
+157ratelimits:
+158  - model: openai/gpt-4o
+159    selector:
+160      key: x-user-id       # HTTP header key used to identify the rate-limit subject
+161      value: "*"           # Wildcard matches any value; use a specific string to target one
+162    limit:
+163      tokens: 100000       # Maximum tokens allowed in the given time unit
+164      unit: hour           # Time unit: "minute", "hour", or "day"
+165
+166  - model: openai/gpt-4o-mini
+167    selector:
+168      key: x-org-id
+169      value: acme-corp
+170    limit:
+171      tokens: 500000
+172      unit: day
+173
+174# Global behavior overrides
+175overrides:
+176  # Threshold for routing a request to a prompt_target (0.0–1.0). Lower = more permissive.
+177  prompt_target_intent_matching_threshold: 0.7
+178  # Trim conversation history to fit within the model's context window
+179  optimize_context_window: true
+180  # Use Plano's agent orchestrator for multi-agent request routing
+181  use_agent_orchestrator: false
+182  # Connect timeout for upstream provider clusters (e.g., "5s", "10s"). Default: "5s"
+183  upstream_connect_timeout: 10s
+184  # Path to the trusted CA bundle for upstream TLS verification
+185  upstream_tls_ca_path: /etc/ssl/certs/ca-certificates.crt
+186  # Model used for intent-based LLM routing (must be listed in model_providers)
+187  llm_routing_model: Plano-Orchestrator
+188  # Model used for agent orchestration (must be listed in model_providers)
+189  agent_orchestration_model: Plano-Orchestrator
+190  # Disable agentic signal analysis (frustration, repetition, escalation, etc.)
+191  # on LLM responses to save CPU. Default: false.
+192  disable_signals: false
+193
+194# Model affinity — pin routing decisions for agentic loops
+195routing:
+196  session_ttl_seconds: 600    # How long a pinned session lasts (default: 600s / 10 min)
+197  session_max_entries: 10000  # Max cached sessions before eviction (upper limit: 10000)
+198  # session_cache controls the backend used to store affinity state.
+199  # "memory" (default) is in-process and works for single-instance deployments.
+200  # "redis" shares state across replicas — required for multi-replica / Kubernetes setups.
+201  session_cache:
+202    type: memory              # "memory" (default) or "redis"
+203    # url is required when type is "redis". Supports redis:// and rediss:// (TLS).
+204    # url: redis://localhost:6379
+205    # tenant_header: x-org-id  # optional; when set, keys are scoped as plano:affinity:{tenant_id}:{session_id}
 206
-207# OpenTelemetry tracing configuration
-208tracing:
-209  # Random sampling percentage (1-100)
-210  random_sampling: 100
-211  # Include internal Plano spans in traces
-212  trace_arch_internal: false
-213  # gRPC endpoint for OpenTelemetry collector (e.g., Jaeger, Tempo)
-214  opentracing_grpc_endpoint: http://localhost:4317
-215  span_attributes:
-216    # Propagate request headers whose names start with these prefixes as span attributes
-217    header_prefixes:
-218      - x-user-
-219      - x-org-
-220    # Static key/value pairs added to every span
-221    static:
-222      environment: production
-223      service.team: platform
+207# State storage for multi-turn conversation history
+208state_storage:
+209  type: memory            # "memory" (in-process) or "postgres" (persistent)
+210  # connection_string is required when type is postgres.
+211  # Supports environment variable substitution: $VAR or ${VAR}
+212  # connection_string: postgresql://user:$DB_PASS@localhost:5432/plano
+213
+214# Input guardrails applied globally to all incoming requests
+215prompt_guards:
+216  input_guards:
+217    jailbreak:
+218      on_exception:
+219        message: "I'm sorry, I can't help with that request."
+220
+221# OpenTelemetry tracing configuration
+222tracing:
+223  # Random sampling percentage (1-100)
+224  random_sampling: 100
+225  # Include internal Plano spans in traces
+226  trace_arch_internal: false
+227  # gRPC endpoint for OpenTelemetry collector (e.g., Jaeger, Tempo)
+228  opentracing_grpc_endpoint: http://localhost:4317
+229  span_attributes:
+230    # Propagate request headers whose names start with these prefixes as span attributes
+231    header_prefixes:
+232      - x-user-
+233      - x-org-
+234    # Static key/value pairs added to every span
+235    static:
+236      environment: production
+237      service.team: platform
 
    
 
    
 
    
diff --git a/searchindex.js b/searchindex.js
index 0bab8b69..72d78276 100755
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
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