docs: added additional_resources folder (#4748)

# docs: added `additional_resources` folder

The additional resource files were inside the doc top-level folder,
which polluted the top-level folder.
- added the `additional_resources` folder and moved correspondent files
to this folder;
- fixed a broken link to the "Model comparison" page (model_laboratory
notebook)
- fixed a broken link to one of the YouTube videos (sorry, it is not
directly related to this PR)

## Who can review?

@dev2049

docs/additional_resources/tracing.md

@@ -6,8 +6,8 @@ First, you should install tracing and set up your environment properly.
 You can use either a locally hosted version of this (uses Docker) or a cloud hosted version (in closed alpha).
 If you're interested in using the hosted platform, please fill out the form [here](https://forms.gle/tRCEMSeopZf6TE3b6).
 
-- [Locally Hosted Setup](./tracing/local_installation.md)
-- [Cloud Hosted Setup](./tracing/hosted_installation.md)
+- [Locally Hosted Setup](../tracing/local_installation.md)
+- [Cloud Hosted Setup](../tracing/hosted_installation.md)
 
 ## Tracing Walkthrough
 
@@ -17,32 +17,32 @@ A session is just a way to group traces together.
 If you click on a session, it will take you to a page with no recorded traces that says "No Runs."
 You can create a new session with the new session form.
 
-![](tracing/homepage.png)
+![](../tracing/homepage.png)
 
 If we click on the `default` session, we can see that to start we have no traces stored.
 
-![](tracing/default_empty.png)
+![](../tracing/default_empty.png)
 
 If we now start running chains and agents with tracing enabled, we will see data show up here.
-To do so, we can run [this notebook](tracing/agent_with_tracing.ipynb) as an example.
+To do so, we can run [this notebook](../tracing/agent_with_tracing.ipynb) as an example.
 After running it, we will see an initial trace show up.
 
-![](tracing/first_trace.png)
+![](../tracing/first_trace.png)
 
 From here we can explore the trace at a high level by clicking on the arrow to show nested runs.
 We can keep on clicking further and further down to explore deeper and deeper.
 
-![](tracing/explore.png)
+![](../tracing/explore.png)
 
 We can also click on the "Explore" button of the top level run to dive even deeper.
 Here, we can see the inputs and outputs in full, as well as all the nested traces.
 
-![](tracing/explore_trace.png)
+![](../tracing/explore_trace.png)
 
 We can keep on exploring each of these nested traces in more detail.
 For example, here is the lowest level trace with the exact inputs/outputs to the LLM.
 
-![](tracing/explore_llm.png)
+![](../tracing/explore_llm.png)
 
 ## Changing Sessions
 

docs/additional_resources/youtube.md

@@ -54,7 +54,7 @@ This is a collection of `LangChain` videos on `YouTube`.
 - ⛓️ [LangChain: Level up `ChatGPT` !? | LangChain Tutorial Part 1](https://youtu.be/vxUGx8aZpDE) by [Code Affinity](https://www.youtube.com/@codeaffinitydev)
 - ⛓️ [KI schreibt krasses Youtube Skript 😲😳 | LangChain Tutorial Deutsch](https://youtu.be/QpTiXyK1jus) by [SimpleKI](https://www.youtube.com/@simpleki)
 - ⛓️ [Chat with Audio: Langchain, `Chroma DB`, OpenAI, and `Assembly AI`](https://youtu.be/Kjy7cx1r75g) by [AI Anytime](https://www.youtube.com/@AIAnytime)
-- ⛓️ [QA over documents with Auto vector index selection with Langchain router chains]() by [echohive](https://www.youtube.com/@echohive)
+- ⛓️ [QA over documents with Auto vector index selection with Langchain router chains](https://youtu.be/9G05qybShv8) by [echohive](https://www.youtube.com/@echohive)
 - ⛓️ [Build your own custom LLM application with `Bubble.io` & Langchain (No Code & Beginner friendly)](https://youtu.be/O7NhQGu1m6c) by [No Code Blackbox](https://www.youtube.com/@nocodeblackbox)
 - ⛓️ [Simple App to Question Your Docs: Leveraging `Streamlit`, `Hugging Face Spaces`, LangChain, and `Claude`!](https://youtu.be/X4YbNECRr7o) by [Chris Alexiuk](https://www.youtube.com/@chrisalexiuk)
 - ⛓️ [LANGCHAIN AI- `ConstitutionalChainAI` + Databutton AI ASSISTANT Web App](https://youtu.be/5zIU6_rdJCU) by [Avra](https://www.youtube.com/@Avra_b)

docs/index.rst

@@ -162,17 +162,17 @@ Additional Resources
 
 - `LangChainHub <https://github.com/hwchase17/langchain-hub>`_: The LangChainHub is a place to share and explore other prompts, chains, and agents.
 
-- `Gallery <./gallery.html>`_: A collection of our favorite projects that use LangChain. Useful for finding inspiration or seeing how things were done in other applications.
+- `Gallery <./additional_resources/gallery.html>`_: A collection of our favorite projects that use LangChain. Useful for finding inspiration or seeing how things were done in other applications.
 
-- `Deployments <./deployments.html>`_: A collection of instructions, code snippets, and template repositories for deploying LangChain apps.
+- `Deployments <./additional_resources/deployments.html>`_: A collection of instructions, code snippets, and template repositories for deploying LangChain apps.
 
-- `Tracing <./tracing.html>`_: A guide on using tracing in LangChain to visualize the execution of chains and agents.
+- `Tracing <./additional_resources/tracing.html>`_: A guide on using tracing in LangChain to visualize the execution of chains and agents.
 
-- `Model Laboratory <./model_laboratory.html>`_: Experimenting with different prompts, models, and chains is a big part of developing the best possible application. The ModelLaboratory makes it easy to do so.
+- `Model Laboratory <./additional_resources/model_laboratory.html>`_: Experimenting with different prompts, models, and chains is a big part of developing the best possible application. The ModelLaboratory makes it easy to do so.
 
 - `Discord <https://discord.gg/6adMQxSpJS>`_: Join us on our Discord to discuss all things LangChain!
 
-- `YouTube <./youtube.html>`_: A collection of the LangChain tutorials and videos.
+- `YouTube <./additional_resources/youtube.html>`_: A collection of the LangChain tutorials and videos.
 
 - `Production Support <https://forms.gle/57d8AmXBYp8PP8tZA>`_: As you move your LangChains into production, we'd love to offer more comprehensive support. Please fill out this form and we'll set up a dedicated support Slack channel.
 
@@ -184,11 +184,10 @@ Additional Resources
    :hidden:
 
    LangChainHub <https://github.com/hwchase17/langchain-hub>
-   ./glossary.md
-   ./gallery.rst
-   ./deployments.md
-   ./tracing.md
-   ./use_cases/model_laboratory.ipynb
+   ./additional_resources/gallery.rst
+   ./additional_resources/deployments.md
+   ./additional_resources/tracing.md
+   ./additional_resources/model_laboratory.ipynb
    Discord <https://discord.gg/6adMQxSpJS>
-   ./youtube.md
+   ./additional_resources/youtube.md
    Production Support <https://forms.gle/57d8AmXBYp8PP8tZA>

docs/use_cases/evaluation.rst

@@ -55,7 +55,7 @@ See `this notebook <./evaluation/qa_generation.html>`_ for an example of how to
 We have two solutions to the lack of metrics.
 
 The first solution is to use no metrics, and rather just rely on looking at results by eye to get a sense for how the chain/agent is performing.
-To assist in this, we have developed (and will continue to develop) `tracing <../tracing.html>`_, a UI-based visualizer of your chain and agent runs.
+To assist in this, we have developed (and will continue to develop) `tracing <../additional_resources/tracing.html>`_, a UI-based visualizer of your chain and agent runs.
 
 The second solution we recommend is to use Language Models themselves to evaluate outputs.
 For this we have a few different chains and prompts aimed at tackling this issue.