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fix: numerous broken documentation links (langchain-ai#2070)
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seems linkchecker isn't catching them because it runs on generated html.
at that point the links are already missing.
the generation process seems to strip invalid references when they can't
be re-written from md to html.

I used https://github.com/tcort/markdown-link-check to check the doc
source directly.

There are a few false positives on localhost for development.
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alexeldeib authored Mar 28, 2023
1 parent f74a1be commit 4be2f9d
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -32,7 +32,7 @@ This library is aimed at assisting in the development of those types of applicat

**🤖 Agents**

- [Documentation](https://langchain.readthedocs.io/en/latest/use_cases/agents.html)
- [Documentation](https://langchain.readthedocs.io/en/latest/modules/agents.html)
- End-to-end Example: [GPT+WolframAlpha](https://huggingface.co/spaces/JavaFXpert/Chat-GPT-LangChain)

## 📖 Documentation
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2 changes: 1 addition & 1 deletion docs/ecosystem/cohere.md
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Expand Up @@ -22,4 +22,4 @@ There exists an Cohere Embeddings wrapper, which you can access with
```python
from langchain.embeddings import CohereEmbeddings
```
For a more detailed walkthrough of this, see [this notebook](../modules/models/text_embedding/examples/embeddings.ipynb)
For a more detailed walkthrough of this, see [this notebook](../modules/models/text_embedding/examples/cohere.ipynb)
4 changes: 2 additions & 2 deletions docs/ecosystem/huggingface.md
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Expand Up @@ -47,7 +47,7 @@ To use a the wrapper for a model hosted on Hugging Face Hub:
```python
from langchain.embeddings import HuggingFaceHubEmbeddings
```
For a more detailed walkthrough of this, see [this notebook](../modules/models/text_embedding/examples/embeddings.ipynb)
For a more detailed walkthrough of this, see [this notebook](../modules/models/text_embedding/examples/huggingfacehub.ipynb)

### Tokenizer

Expand All @@ -59,7 +59,7 @@ You can also use it to count tokens when splitting documents with
from langchain.text_splitter import CharacterTextSplitter
CharacterTextSplitter.from_huggingface_tokenizer(...)
```
For a more detailed walkthrough of this, see [this notebook](../modules/indexes/text_splitters/examples/textsplitter.ipynb)
For a more detailed walkthrough of this, see [this notebook](../modules/indexes/text_splitters/examples/huggingface_length_function.ipynb)


### Datasets
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4 changes: 2 additions & 2 deletions docs/ecosystem/openai.md
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Expand Up @@ -31,7 +31,7 @@ There exists an OpenAI Embeddings wrapper, which you can access with
```python
from langchain.embeddings import OpenAIEmbeddings
```
For a more detailed walkthrough of this, see [this notebook](../modules/models/text_embedding/examples/embeddings.ipynb)
For a more detailed walkthrough of this, see [this notebook](../modules/models/text_embedding/examples/openai.ipynb)


### Tokenizer
Expand All @@ -44,7 +44,7 @@ You can also use it to count tokens when splitting documents with
from langchain.text_splitter import CharacterTextSplitter
CharacterTextSplitter.from_tiktoken_encoder(...)
```
For a more detailed walkthrough of this, see [this notebook](../modules/indexes/text_splitters/examples/textsplitter.ipynb)
For a more detailed walkthrough of this, see [this notebook](../modules/indexes/text_splitters/examples/tiktoken.ipynb)

### Moderation
You can also access the OpenAI content moderation endpoint with
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4 changes: 2 additions & 2 deletions docs/ecosystem/promptlayer.md
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Expand Up @@ -40,10 +40,10 @@ for res in llm_results.generations:
```
You can use the PromptLayer request ID to add a prompt, score, or other metadata to your request. [Read more about it here](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9).

This LLM is identical to the [OpenAI LLM](./openai), except that
This LLM is identical to the [OpenAI LLM](./openai.md), except that
- all your requests will be logged to your PromptLayer account
- you can add `pl_tags` when instantializing to tag your requests on PromptLayer
- you can add `return_pl_id` when instantializing to return a PromptLayer request id to use [while tracking requests](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9).


PromptLayer also provides native wrappers for [`PromptLayerChatOpenAI`](../modules/models/chat/examples/promptlayer_chat_openai.ipynb) and `PromptLayerOpenAIChat`
PromptLayer also provides native wrappers for [`PromptLayerChatOpenAI`](../modules/models/chat/integrations/promptlayer_chatopenai.ipynb) and `PromptLayerOpenAIChat`
4 changes: 1 addition & 3 deletions docs/ecosystem/runhouse.md
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Expand Up @@ -26,6 +26,4 @@ the `SelfHostedEmbedding` class.
from langchain.llms import SelfHostedPipeline, SelfHostedHuggingFaceLLM
```

For a more detailed walkthrough of the Self-hosted Embeddings, see [this notebook](../modules/models/text_embedding/examples/embeddings.ipynb)

##
For a more detailed walkthrough of the Self-hosted Embeddings, see [this notebook](../modules/models/text_embedding/examples/self-hosted.ipynb)
4 changes: 2 additions & 2 deletions docs/getting_started/getting_started.md
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Expand Up @@ -74,7 +74,7 @@ print(llm(text))
Feetful of Fun
```
For more details on how to use LLMs within LangChain, see the [LLM getting started guide](../modules/llms/getting_started.ipynb).
For more details on how to use LLMs within LangChain, see the [LLM getting started guide](../modules/models/llms/getting_started.ipynb).
`````


Expand Down Expand Up @@ -111,7 +111,7 @@ What is a good name for a company that makes colorful socks?
```
[For more details, check out the getting started guide for prompts.](../modules/prompts/getting_started.ipynb)
[For more details, check out the getting started guide for prompts.](../modules/prompts/chat_prompt_template.ipynb)
`````

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2 changes: 1 addition & 1 deletion docs/modules/prompts/prompt_templates/getting_started.md
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Expand Up @@ -238,4 +238,4 @@ print(dynamic_prompt.format(input=long_string))
<!-- TODO(shreya): Add correct link here. -->
LangChain comes with a few example selectors that you can use. For more details on how to use them, see [Example Selectors](../example_selectors.rst).

You can create custom example selectors that select examples based on any criteria you want. For more details on how to do this, see [Creating a custom example selector](prompt_templates/examples/custom_example_selector.ipynb).
You can create custom example selectors that select examples based on any criteria you want. For more details on how to do this, see [Creating a custom example selector](../example_selectors/examples/custom_example_selector.md).

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