docs: fix model i/o index links (langchain-ai#15421)

docs/docs/modules/agents/index.ipynb

@@ -21,7 +21,7 @@
     "In chains, a sequence of actions is hardcoded (in code).\n",
     "In agents, a language model is used as a reasoning engine to determine which actions to take and in which order.\n",
     "\n",
-    "## [Quick Start](/docs/modules/agents/quick_start)\n",
+    "## [Quickstart](/docs/modules/agents/quick_start)\n",
     "\n",
     "For a quick start to working with agents, please check out [this getting started guide](/docs/modules/agents/quick_start). This covers basics like initializing an agent, creating tools, and adding memory.\n",
     "\n",

docs/docs/modules/agents/quick_start.ipynb

@@ -7,7 +7,7 @@
    "source": [
     "---\n",
     "sidebar_position: 0\n",
-    "title: Quick Start\n",
+    "title: Quickstart\n",
     "---"
    ]
   },
@@ -16,7 +16,7 @@
    "id": "f4c03f40-1328-412d-8a48-1db0cd481b77",
    "metadata": {},
    "source": [
-    "# Quick Start\n",
+    "# Quickstart\n",
     "\n",
     "To best understand the agent framework, let's build an agent that has two tools: one to look things up online, and one to look up specific data that we've loaded into a index.\n",
     "\n",
@@ -686,7 +686,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.1"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

docs/docs/modules/model_io/chat/index.mdx

@@ -25,4 +25,4 @@ This includes:
 
 - [How to cache ChatModel responses](./chat_model_caching)
 - [How to stream responses from a ChatModel](./streaming)
-- [How to track token usage in a ChatModel call)(./token_usage_tracking)
+- [How to track token usage in a ChatModel call](./token_usage_tracking)

docs/docs/modules/model_io/index.mdx

@@ -11,27 +11,27 @@ The core element of any language model application is...the model. LangChain giv
 
 ![model_io_diagram](/img/model_io.jpg)
 
-## [Conceptual Guide](./concepts)
+## [Conceptual Guide](/docs/modules/model_io/concepts)
 
 A conceptual explanation of messages, prompts, LLMs vs ChatModels, and output parsers. You should read this before getting started.
 
-## [Quick Start](./quick_start)
+## [Quickstart](/docs/modules/model_io/quick_start)
 
 Covers the basics of getting started working with different types of models. You should walk through [this section] if you want to get an overview of the functionality.
 
-## [Prompts](./prompts)
+## [Prompts](/docs/modules/model_io/prompts/)
 
-[This section](./prompts) deep dives into the different types of prompt templates and how to use them.
+[This section](/docs/modules/model_io/prompts/) deep dives into the different types of prompt templates and how to use them.
 
-## [LLMs](./llms)
+## [LLMs](/docs/modules/model_io/llms/)
 
-[This section](./llms) covers functionality related to the LLM class. This is a type of model that takes a text string as input and returns a text string.
+[This section](/docs/modules/model_io/llms/) covers functionality related to the LLM class. This is a type of model that takes a text string as input and returns a text string.
 
-## [ChatModels](./chat)
+## [ChatModels](/docs/modules/model_io/chat/)
 
-[This section](./chat) covers functionality related to the ChatModel class. This is a type of model that takes a list of messages as input and returns a message.
+[This section](/docs/modules/model_io/chat/) covers functionality related to the ChatModel class. This is a type of model that takes a list of messages as input and returns a message.
 
-## [Output Parsers](./output_parsers)
+## [Output Parsers](/docs/modules/model_io/output_parsers/)
 
-Output parsers are responsible for transforming the output of LLMs and ChatModels into more structured data. [This section](./output_parsers) covers the different types of output parsers.
+Output parsers are responsible for transforming the output of LLMs and ChatModels into more structured data. [This section](/docs/modules/model_io/output_parsers/) covers the different types of output parsers.
 

docs/docs/modules/model_io/prompts/index.mdx

@@ -8,7 +8,7 @@ guide the model's response, helping it understand the context and generate relev
 and coherent language-based output, such as answering questions, completing sentences,
 or engaging in a conversation.
 
-## [Quick Start](./quick_start)
+## [Quickstart](./quick_start)
 
 This [quick start](./quick_start) provides a basic overview of how to work with prompts.
 

docs/docs/modules/model_io/quick_start.mdx

@@ -1,3 +1,7 @@
+---
+sidebar_position: 0
+---
+
 # Quickstart
 
 The quick start will cover the basics of working with language models. It will introduce the two different types of models - LLMs and ChatModels. It will then cover how to use PromptTemplates to format the inputs to these models, and how to use Output Parsers to work with the outputs. For a deeper conceptual guide into these topics - please see [this documentation](./concepts)