Merge pull request #589 from guardrails-ai/classic-docs-restructure

restructuring and conosolidating minus getting started

Author: zsimjee

docs/concepts/prompts_instructions.md …aveyard/concepts/prompts_instructions.mddocs/concepts/prompts_instructions.md renamed to docs-graveyard/concepts/prompts_instructions.md docs/concepts/prompts_instructions.md renamed to docs-graveyard/concepts/prompts_instructions.md

@@ -1,4 +1,4 @@
-# Environment Variables
+# Set API Keys and other Environment Variables
 
 Guardrails recognize a handful of environment variables that can be used at runtime.  Most of these correlate to envinronment variables used or expected by the various LLM clients.  Below you can find a list of these and their uses.
 

docs/concepts/reasking.md docs-graveyard/concepts/reasking.mddocs/concepts/reasking.md renamed to docs-graveyard/concepts/reasking.md

@@ -1,4 +1,4 @@
-# Custom LLMs
+# Guard Custom LLMs
 
 Guardrails' `Guard` wrappers provide a simple way to add Guardrails to your LLM API calls. The wrappers are designed to be used with any LLM API.
 

docs/defining_guards/pydantic.ipynb …graveyard/defining_guards/pydantic.ipynbdocs/defining_guards/pydantic.ipynb renamed to docs-graveyard/defining_guards/pydantic.ipynb docs/defining_guards/pydantic.ipynb renamed to docs-graveyard/defining_guards/pydantic.ipynb

@@ -1,8 +1,8 @@
-# Logs
+# Inspect Guard Run History and Logs
 
 All `Guard` calls are logged internally, and can be accessed via the guard history.
 
-## 🇻🇦 Accessing logs via `Guard.history`
+## Accessing logs via `Guard.history`
 
 `history` is an attribute of the `Guard` class. It implements a standard `Stack` interface with a few extra helper methods and properties.  For more information on our `Stack` implementation see the [Helper Classes](/docs/api_reference_markdown/helper_classes) page.
 

docs/defining_guards/strings.ipynb …-graveyard/defining_guards/strings.ipynbdocs/defining_guards/strings.ipynb renamed to docs-graveyard/defining_guards/strings.ipynb docs/defining_guards/strings.ipynb renamed to docs-graveyard/defining_guards/strings.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Example of using OpenAI streaming with Guardrails\n"
+    "# Validate Streamed LLM Responses\n"
    ]
   },
   {

docs/how_to_guides/envars.md docs/how_to_guides/envvars.mddocs/how_to_guides/envars.md renamed to docs/how_to_guides/envvars.md

@@ -1,13 +1,12 @@
-# Guard
-
+# The Guard
 
 The guard object is the main interface for GuardRails. It is seeded with a RailSpec, and then used to run the GuardRails AI engine. It is the object that accepts changing prompts, wraps LLM prompts, and keeps track of call history.
 
 
 ## How it works
 
-![Guardrails Logo](../img/guardrails_arch_white_vertical.png#only-light)
-![Guardrails Logo](../img/guardrails_arch_dark_vertical.png#only-dark)
+![Guardrails Logo](./img/guardrails_arch_white_vertical.png#only-light)
+![Guardrails Logo](./img/guardrails_arch_dark_vertical.png#only-dark)
 
 
 ## Two main flows