diff --git a/_downloads/ca9d3b7116524473d8adbde7cf15d167/arch_config_full_reference.yaml b/_downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml similarity index 98% rename from _downloads/ca9d3b7116524473d8adbde7cf15d167/arch_config_full_reference.yaml rename to _downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml index be3c18a2..cc3973e0 100755 --- a/_downloads/ca9d3b7116524473d8adbde7cf15d167/arch_config_full_reference.yaml +++ b/_downloads/c86f9e8fb1f2994b1ba4a0b98481410e/plano_config_full_reference.yaml @@ -1,4 +1,4 @@ -# Arch Gateway configuration version +# Plano Gateway configuration version version: v0.3.0 # External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions) diff --git a/concepts/filter_chain.html b/concepts/filter_chain.html index 38c08835..eaa42302 100755 --- a/concepts/filter_chain.html +++ b/concepts/filter_chain.html @@ -221,7 +221,7 @@ and a context builder that prepares retrieval context before the agent runs.

30 - type: agent 31 name: agent_1 32 port: 8001 -33 router: arch_agent_router +33 router: plano_agent_router 34 agents: 35 - id: rag_agent 36 description: virtual assistant for retrieval augmented generation tasks diff --git a/concepts/llm_providers/client_libraries.html b/concepts/llm_providers/client_libraries.html index 70bd5435..95ccb14e 100755 --- a/concepts/llm_providers/client_libraries.html +++ b/concepts/llm_providers/client_libraries.html @@ -214,7 +214,7 @@ base_url="http://127.0.0.1:12000/v1" ) -# Use any model configured in your arch_config.yaml +# Use any model configured in your plano_config.yaml completion = client.chat.completions.create( model="gpt-4o-mini", # Or use :ref:`model aliases <model_aliases>` like "fast-model" max_tokens=50, @@ -372,7 +372,7 @@ base_url="http://127.0.0.1:12000" ) -# Use any model configured in your arch_config.yaml +# Use any model configured in your plano_config.yaml message = client.messages.create( model="claude-3-5-sonnet-20241022", max_tokens=50, diff --git a/concepts/prompt_target.html b/concepts/prompt_target.html index fcfb9fba..14ad27b4 100755 --- a/concepts/prompt_target.html +++ b/concepts/prompt_target.html @@ -289,7 +289,7 @@ processess conversational messages on your behalf.

Example 1: Adjusting Retrieval

User: What are the benefits of renewable energy?
 **[Plano]**: Check if there is an available <prompt_target> that can handle this user query.
-**[Plano]**: Found "get_info_for_energy_source" prompt_target in arch_config.yaml. Forward prompt to the endpoint configured in "get_info_for_energy_source"
+**[Plano]**: Found "get_info_for_energy_source" prompt_target in plano_config.yaml. Forward prompt to the endpoint configured in "get_info_for_energy_source"
 ...
 Assistant: Renewable energy reduces greenhouse gas emissions, lowers air pollution, and provides sustainable power sources like solar and wind.
 
@@ -303,13 +303,13 @@ processess conversational messages on your behalf.

 
Example 2: Switching Intent

 
User: What are the symptoms of diabetes?
 **[Plano]**: Check if there is an available <prompt_target> that can handle this user query.
-**[Plano]**: Found "diseases_symptoms" prompt_target in arch_config.yaml. Forward disease=diabeteres to "diseases_symptoms" prompt target
+**[Plano]**: Found "diseases_symptoms" prompt_target in plano_config.yaml. Forward disease=diabeteres to "diseases_symptoms" prompt target
 ...
 Assistant: Common symptoms include frequent urination, excessive thirst, fatigue, and blurry vision.
 
 User: How is it diagnosed?
 **[Plano]**: New intent detected.
-**[Plano]**: Found "disease_diagnoses" prompt_target in arch_config.yaml. Forward disease=diabeteres to "disease_diagnoses" prompt target
+**[Plano]**: Found "disease_diagnoses" prompt_target in plano_config.yaml. Forward disease=diabeteres to "disease_diagnoses" prompt target
 ...
 Assistant: Diabetes is diagnosed through blood tests like fasting blood sugar, A1C, or an oral glucose tolerance test.
 

@@ -415,7 +415,7 @@ response from your APIs.

 
 

 
Demo App

-
For your convenience, we’ve built a demo app
+
For your convenience, we’ve built a demo app
 that you can test and modify locally for multi-turn RAG scenarios.

 

 ../_images/mutli-turn-example.png
diff --git a/guides/observability/access_logging.html b/guides/observability/access_logging.html
index b460cf44..8ed1da6a 100755
--- a/guides/observability/access_logging.html
+++ b/guides/observability/access_logging.html
@@ -161,7 +161,7 @@
 
 

 

-
Access Logging

+
Access Logging

 
Access logging in Plano refers to the logging of detailed information about each request and response that flows through Plano.
 It provides visibility into the traffic passing through Plano, which is crucial for monitoring, debugging, and analyzing the
 behavior of AI applications and their interactions.

diff --git a/guides/observability/tracing.html b/guides/observability/tracing.html
index fb8b2544..ad2a1f80 100755
--- a/guides/observability/tracing.html
+++ b/guides/observability/tracing.html
@@ -161,7 +161,7 @@
 
 

 

-
Tracing

+
Tracing

 

 
Overview

 
OpenTelemetry is an open-source observability framework providing APIs
diff --git a/includes/llms.txt b/includes/llms.txt
index 3895ef33..4236c1ae 100755
--- a/includes/llms.txt
+++ b/includes/llms.txt
@@ -1,6 +1,6 @@
 Plano Docs v0.4.6
 llms.txt (auto-generated)
-Generated (UTC): 2026-02-13T23:08:39.285024+00:00
+Generated (UTC): 2026-02-13T23:17:22.564025+00:00
 
 Table of contents
 - Agents (concepts/agents)
@@ -199,7 +199,7 @@ listeners:
   - type: agent
     name: agent_1
     port: 8001
-    router: arch_agent_router
+    router: plano_agent_router
     agents:
       - id: rag_agent
         description: virtual assistant for retrieval augmented generation tasks
@@ -396,7 +396,7 @@ client = OpenAI(
     base_url="http://127.0.0.1:12000/v1"
 )
 
-# Use any model configured in your arch_config.yaml
+# Use any model configured in your plano_config.yaml
 completion = client.chat.completions.create(
     model="gpt-4o-mini",  # Or use :ref:`model aliases ` like "fast-model"
     max_tokens=50,
@@ -560,7 +560,7 @@ client = anthropic.Anthropic(
     base_url="http://127.0.0.1:12000"
 )
 
-# Use any model configured in your arch_config.yaml
+# Use any model configured in your plano_config.yaml
 message = client.messages.create(
     model="claude-3-5-sonnet-20241022",
     max_tokens=50,
@@ -2319,7 +2319,7 @@ Example 1: Adjusting Retrieval
 
 User: What are the benefits of renewable energy?
 **[Plano]**: Check if there is an available  that can handle this user query.
-**[Plano]**: Found "get_info_for_energy_source" prompt_target in arch_config.yaml. Forward prompt to the endpoint configured in "get_info_for_energy_source"
+**[Plano]**: Found "get_info_for_energy_source" prompt_target in plano_config.yaml. Forward prompt to the endpoint configured in "get_info_for_energy_source"
 ...
 Assistant: Renewable energy reduces greenhouse gas emissions, lowers air pollution, and provides sustainable power sources like solar and wind.
 
@@ -2332,13 +2332,13 @@ Example 2: Switching Intent
 
 User: What are the symptoms of diabetes?
 **[Plano]**: Check if there is an available  that can handle this user query.
-**[Plano]**: Found "diseases_symptoms" prompt_target in arch_config.yaml. Forward disease=diabeteres to "diseases_symptoms" prompt target
+**[Plano]**: Found "diseases_symptoms" prompt_target in plano_config.yaml. Forward disease=diabeteres to "diseases_symptoms" prompt target
 ...
 Assistant: Common symptoms include frequent urination, excessive thirst, fatigue, and blurry vision.
 
 User: How is it diagnosed?
 **[Plano]**: New intent detected.
-**[Plano]**: Found "disease_diagnoses" prompt_target in arch_config.yaml. Forward disease=diabeteres to "disease_diagnoses" prompt target
+**[Plano]**: Found "disease_diagnoses" prompt_target in plano_config.yaml. Forward disease=diabeteres to "disease_diagnoses" prompt target
 ...
 Assistant: Diabetes is diagnosed through blood tests like fasting blood sugar, A1C, or an oral glucose tolerance test.
 
@@ -5723,12 +5723,12 @@ Doc: resources/configuration_reference
 Configuration Reference
 
 The following is a complete reference of the plano_config.yml that controls the behavior of a single instance of
-the Arch gateway. This where you enable capabilities like routing to upstream LLm providers, defining prompt_targets
+the Plano gateway. This where you enable capabilities like routing to upstream LLm providers, defining prompt_targets
 where prompts get routed to, apply guardrails, and enable critical agent observability features.
 
 Plano Configuration - Full Reference
 
-# Arch Gateway configuration version
+# Plano Gateway configuration version
 version: v0.3.0
 
 # External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)
@@ -6142,7 +6142,7 @@ prompt_targets:
     endpoint:
       name: app_server
       path: /agent/summary
-    # Arch uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
+    # Plano uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
     auto_llm_dispatch_on_response: true
     # override system prompt for this prompt target
     system_prompt: You are a helpful information extraction assistant. Use the information that is provided to you.
@@ -6163,7 +6163,7 @@ prompt_targets:
         default: false
         enum: [true, false]
 
-# Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
+# Plano creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
 endpoints:
   app_server:
     # value could be ip address or a hostname with port
diff --git a/objects.inv b/objects.inv
index c8402f75..632a93cc 100755
Binary files a/objects.inv and b/objects.inv differ
diff --git a/resources/configuration_reference.html b/resources/configuration_reference.html
index a712da5f..04a6b5de 100755
--- a/resources/configuration_reference.html
+++ b/resources/configuration_reference.html
@@ -162,11 +162,11 @@
 

 
Configuration Reference

 
The following is a complete reference of the plano_config.yml that controls the behavior of a single instance of
-the Arch gateway. This where you enable capabilities like routing to upstream LLm providers, defining prompt_targets
+the Plano gateway. This where you enable capabilities like routing to upstream LLm providers, defining prompt_targets
 where prompts get routed to, apply guardrails, and enable critical agent observability features.

 

-
Plano Configuration - Full Reference

-
  1# Arch Gateway configuration version
+
Plano Configuration - Full Reference

+
  1# Plano Gateway configuration version
   2version: v0.3.0
   3
   4# External HTTP agents - API type is controlled by request path (/v1/responses, /v1/messages, /v1/chat/completions)
diff --git a/resources/tech_overview/request_lifecycle.html b/resources/tech_overview/request_lifecycle.html
index 430321b4..78cb6523 100755
--- a/resources/tech_overview/request_lifecycle.html
+++ b/resources/tech_overview/request_lifecycle.html
@@ -191,7 +191,7 @@ processing. It is responsible for managing the inbound(edge) and outbound(egress
 
  • Bright Staff controller subsystem is Plano’s memory-efficient, lightweight controller for agentic traffic. It sits inside the Plano data plane and makes real-time decisions about how prompts are handled, forwarded, and processed.
    • 
 
 
    These two subsystems are bridged with either the HTTP router filter, and the cluster manager subsystems of Envoy.
    
-
    Also, Plano utilizes Envoy event-based thread model. A main thread is responsible for the server lifecycle, configuration processing, stats, etc. and some number of worker threads process requests. All threads operate around an event loop (libevent) and any given downstream TCP connection will be handled by exactly one worker thread for its lifetime. Each worker thread maintains its own pool of TCP connections to upstream endpoints.
    
+
    Also, Plano utilizes Envoy event-based thread model. A main thread is responsible for the server lifecycle, configuration processing, stats, etc. and some number of worker threads process requests. All threads operate around an event loop (libevent) and any given downstream TCP connection will be handled by exactly one worker thread for its lifetime. Each worker thread maintains its own pool of TCP connections to upstream endpoints.
    
 
    Worker threads rarely share state and operate in a trivially parallel fashion. This threading model
 enables scaling to very high core count CPUs.
    
 
    
@@ -275,8 +275,8 @@ Once the LLM processes the prompt, Plano receives the response from the LLM serv
 
  • The post-request monitoring are updated (e.g. timing, active requests, upgrades, health checks).
 Some statistics are updated earlier however, during request processing. Stats are batched and written by the main
 thread periodically.
    • 
-
  • Access logs are written to the access log
    • 
-
  • Trace spans are finalized. If our example request was traced, a
+
  • Access logs are written to the access log
    • 
+
  • Trace spans are finalized. If our example request was traced, a
 trace span, describing the duration and details of the request would be created by the HCM when
 processing request headers and then finalized by the HCM during post-request processing.
    • 
 
@@ -305,7 +305,7 @@ processing request headers and then finalized by the HCM during post-request pro
     endpoint:
       name: app_server
       path: /agent/summary
-    # Arch uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
+    # Plano uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
     auto_llm_dispatch_on_response: true
     # override system prompt for this prompt target
     system_prompt: You are a helpful information extraction assistant. Use the information that is provided to you.
@@ -326,7 +326,7 @@ processing request headers and then finalized by the HCM during post-request pro
         default: false
         enum: [true, false]
 
-# Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
+# Plano creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
 endpoints:
   app_server:
     # value could be ip address or a hostname with port
diff --git a/resources/tech_overview/threading_model.html b/resources/tech_overview/threading_model.html
index 265fdf82..b3b03a5f 100755
--- a/resources/tech_overview/threading_model.html
+++ b/resources/tech_overview/threading_model.html
@@ -161,7 +161,7 @@
 
 
    
 
    
-
    Threading Model
    
+
    Threading Model
    
 
    Plano builds on top of Envoy’s single process with multiple threads architecture.
    
 
    A single primary thread controls various sporadic coordination tasks while some number of worker
 threads perform filtering, and forwarding.
    
diff --git a/searchindex.js b/searchindex.js
index ae778503..7bf55b51 100755
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles":{"AWS X-Ray":[[17,"aws-x-ray"]],"Access Logging":[[14,null]],"Additional Resources":[[17,"additional-resources"]],"Advanced Configuration":[[6,"advanced-configuration"]],"Advanced Features":[[4,"advanced-features"]],"Advanced Features (Coming Soon)":[[5,"advanced-features-coming-soon"]],"Agent Orchestration":[[0,"agent-orchestration"]],"Agent Processing":[[17,"agent-processing"]],"Agent Structure":[[18,"agent-structure"]],"Agents":[[0,null]],"Alias-based routing":[[13,"alias-based-routing"]],"Amazon Bedrock":[[6,"amazon-bedrock"]],"Anthropic":[[6,"anthropic"]],"Anthropic (Python) SDK":[[3,"anthropic-python-sdk"]],"Arch-Function":[[12,"arch-function"]],"Arch-Router":[[13,"id7"]],"Azure OpenAI":[[6,"azure-openai"]],"Base URL Configuration":[[6,"base-url-configuration"]],"Basic Configuration":[[5,"basic-configuration"],[7,"basic-configuration"]],"Behavioral Signals in Traces":[[17,"behavioral-signals-in-traces"]],"Benefits of Using Traceparent Headers":[[17,"benefits-of-using-traceparent-headers"]],"Best Practices":[[3,"best-practices"],[8,"best-practices"],[17,"best-practices"],[18,"best-practices"],[20,"best-practices"]],"Best Practices and Tips":[[12,"best-practices-and-tips"]],"Best practices":[[13,"best-practices"]],"Bright Staff":[[25,null]],"Build Agentic Apps with Plano":[[11,"build-agentic-apps-with-plano"]],"Build Multi-Turn RAG Apps":[[7,"build-multi-turn-rag-apps"]],"Build with Plano":[[10,"build-with-plano"]],"Building agents with Plano orchestration":[[11,"building-agents-with-plano-orchestration"]],"CLI Reference":[[17,"cli-reference"]],"Calling External APIs":[[18,"calling-external-apis"]],"Client Libraries":[[3,null]],"Client usage":[[13,"client-usage"],[13,"id4"],[13,"id6"]],"Combining Routing Methods":[[13,"combining-routing-methods"]],"Common Issues and Solutions":[[23,"common-issues-and-solutions"]],"Common Use 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