Rename all arch references to plano across the codebase

Complete rebrand from "Arch"/"archgw" to "Plano" including:
- Config files: arch_config_schema.yaml, workflow, demo configs
- Environment variables: ARCH_CONFIG_* → PLANO_CONFIG_*
- Python CLI: variables, functions, file paths, docker mounts
- Rust crates: config paths, log messages, metadata keys
- Docker/build: Dockerfile, supervisord, .dockerignore, .gitignore
- Docker Compose: volume mounts and env vars across all demos/tests
- GitHub workflows: job/step names
- Shell scripts: log messages
- Demos: Python code, READMEs, VS Code configs, Grafana dashboard
- Docs: RST includes, code comments, config references
- Package metadata: package.json, pyproject.toml, uv.lock

External URLs (docs.archgw.com, github.com/katanemo/archgw) left as-is.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

docs/source/concepts/llm_providers/client_libraries.rst

@@ -54,7 +54,7 @@ The OpenAI SDK works with any provider through Plano's OpenAI-compatible endpoin
         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,
@@ -231,7 +231,7 @@ The Anthropic SDK works with any provider through Plano's Anthropic-compatible e
         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,

docs/source/concepts/prompt_target.rst

@@ -114,7 +114,7 @@ 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.
 
@@ -130,13 +130,13 @@ 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.
 
@@ -172,7 +172,7 @@ Once the prompt targets are configured as above, handle parameters across multi-
 Demo App
 --------
 
-For your convenience, we've built a `demo app <https://github.com/katanemo/archgw/tree/main/demos/samples_python/multi_turn_rag_agent>`_
+For your convenience, we've built a `demo app <https://github.com/katanemo/plano/tree/main/demos/samples_python/multi_turn_rag_agent>`_
 that you can test and modify locally for multi-turn RAG scenarios.
 
 .. figure:: ../build_with_plano/includes/multi_turn/mutli-turn-example.png

docs/source/guides/state.rst

@@ -57,7 +57,7 @@ Configuration Overview
 
 State storage is configured in the ``state_storage`` section of your ``plano_config.yaml``:
 
-.. literalinclude:: ../resources/includes/arch_config_state_storage_example.yaml
+.. literalinclude:: ../resources/includes/plano_config_state_storage_example.yaml
     :language: yaml
     :lines: 21-30
     :linenos:

docs/source/resources/configuration_reference.rst

@@ -7,7 +7,7 @@ The following is a complete reference of the ``plano_config.yml`` that controls
 the Arch 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.
 
-.. literalinclude:: includes/arch_config_full_reference.yaml
+.. literalinclude:: includes/plano_config_full_reference.yaml
     :language: yaml
     :linenos:
-    :caption: :download:`Plano Configuration - Full Reference <includes/arch_config_full_reference.yaml>`
+    :caption: :download:`Plano Configuration - Full Reference <includes/plano_config_full_reference.yaml>`