diff --git a/README.md b/README.md index 8e65b17d..8b2673eb 100644 --- a/README.md +++ b/README.md @@ -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 diff --git a/docs/ecosystem/cohere.md b/docs/ecosystem/cohere.md index 082c58ae..83607f55 100644 --- a/docs/ecosystem/cohere.md +++ b/docs/ecosystem/cohere.md @@ -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) diff --git a/docs/ecosystem/huggingface.md b/docs/ecosystem/huggingface.md index ed5abaac..f6ff7d40 100644 --- a/docs/ecosystem/huggingface.md +++ b/docs/ecosystem/huggingface.md @@ -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 @@ -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 diff --git a/docs/ecosystem/openai.md b/docs/ecosystem/openai.md index e37afc2a..2e26b58b 100644 --- a/docs/ecosystem/openai.md +++ b/docs/ecosystem/openai.md @@ -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 @@ -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 diff --git a/docs/ecosystem/promptlayer.md b/docs/ecosystem/promptlayer.md index e013792d..762e181e 100644 --- a/docs/ecosystem/promptlayer.md +++ b/docs/ecosystem/promptlayer.md @@ -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` diff --git a/docs/ecosystem/runhouse.md b/docs/ecosystem/runhouse.md index 78f9683e..d96b0976 100644 --- a/docs/ecosystem/runhouse.md +++ b/docs/ecosystem/runhouse.md @@ -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) - -## \ No newline at end of file +For a more detailed walkthrough of the Self-hosted Embeddings, see [this notebook](../modules/models/text_embedding/examples/self-hosted.ipynb) diff --git a/docs/getting_started/getting_started.md b/docs/getting_started/getting_started.md index 0e651cc6..9988b3c4 100644 --- a/docs/getting_started/getting_started.md +++ b/docs/getting_started/getting_started.md @@ -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). ````` @@ -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) ````` diff --git a/docs/modules/prompts/prompt_templates/getting_started.md b/docs/modules/prompts/prompt_templates/getting_started.md index 1c6649bb..d0cfedbd 100644 --- a/docs/modules/prompts/prompt_templates/getting_started.md +++ b/docs/modules/prompts/prompt_templates/getting_started.md @@ -238,4 +238,4 @@ print(dynamic_prompt.format(input=long_string)) 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).