# 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
@ -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)
- ⛓️ [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)
- `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.
@ -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.
Leonid Ganeline
1 year ago
committed by
GitHub