### Description
renamed several repository links from `hwchase17` to `langchain-ai`.
### Why
I discovered that the README file in the devcontainer contains an old
repository name, so I took the opportunity to rename the old repository
name in all files within the repository, excluding those that do not
require changes.
### Dependencies
none
### Tag maintainer
@baskaryan
### Twitter handle
[kzk_maeda](https://twitter.com/kzk_maeda)
@ -5,10 +5,10 @@ This project includes a [dev container](https://containers.dev/), which lets you
You can use the dev container configuration in this folder to build and run the app without needing to install any of its tools locally! You can use it in [GitHub Codespaces](https://github.com/features/codespaces) or the [VS Code Dev Containers extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers).
## GitHub Codespaces
[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/hwchase17/langchain)
[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/langchain-ai/langchain)
You may use the button above, or follow these steps to open this repo in a Codespace:
1. Click the **Code** drop-down menu at the top of https://github.com/hwchase17/langchain.
1. Click the **Code** drop-down menu at the top of https://github.com/langchain-ai/langchain.
Our [issues](https://github.com/hwchase17/langchain/issues) page is kept up to date
Our [issues](https://github.com/langchain-ai/langchain/issues) page is kept up to date
with bugs, improvements, and feature requests.
There is a taxonomy of labels to help with sorting and discovery of issues of interest. Please use these to help
@ -60,7 +60,7 @@ we do not want these to get in the way of getting good code into the codebase.
## 🚀 Quick Start
This quick start describes running the repository locally.
For a [development container](https://containers.dev/), see the [.devcontainer folder](https://github.com/hwchase17/langchain/tree/master/.devcontainer).
For a [development container](https://containers.dev/), see the [.devcontainer folder](https://github.com/langchain-ai/langchain/tree/master/.devcontainer).
### Dependency Management: Poetry and other env/dependency managers
Is there any way that you could help, e.g. by submitting a PR? Make sure to read the CONTRIBUTING.MD [readme](https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md)
Is there any way that you could help, e.g. by submitting a PR? Make sure to read the CONTRIBUTING.MD [readme](https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md)
Looking for the JS/TS version? Check out [LangChain.js](https://github.com/hwchase17/langchainjs).
Looking for the JS/TS version? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
**Production Support:** As you move your LangChains into production, we'd love to offer more hands-on support.
Fill out [this form](https://airtable.com/appwQzlErAS2qiP0L/shrGtGaVBVAz7NcV2) to share more about what you're building, and our team will get in touch.
@ -26,7 +26,7 @@ Fill out [this form](https://airtable.com/appwQzlErAS2qiP0L/shrGtGaVBVAz7NcV2) t
In an effort to make `langchain` leaner and safer, we are moving select chains to `langchain_experimental`.
This migration has already started, but we are remaining backwards compatible until 7/28.
On that date, we will remove functionality from `langchain`.
Read more about the motivation and the progress [here](https://github.com/hwchase17/langchain/discussions/8043).
Read more about the motivation and the progress [here](https://github.com/langchain-ai/langchain/discussions/8043).
Read how to migrate your code [here](MIGRATE.md).
## Quick Install
@ -49,7 +49,7 @@ This library aims to assist in the development of those types of applications. C
@ -20,7 +20,7 @@ Off-the-shelf chains make it easy to get started. For complex applications, comp
We recommend following our [Quickstart](/docs/get_started/quickstart) guide to familiarize yourself with the framework by building your first LangChain application.
_**Note**: These docs are for the LangChain [Python package](https://github.com/hwchase17/langchain). For documentation on [LangChain.js](https://github.com/hwchase17/langchainjs), the JS/TS version, [head here](https://js.langchain.com/docs)._
_**Note**: These docs are for the LangChain [Python package](https://github.com/langchain-ai/langchain). For documentation on [LangChain.js](https://github.com/langchain-ai/langchainjs), the JS/TS version, [head here](https://js.langchain.com/docs)._
"The [`langchain.llms.modal.Modal`](https://github.com/hwchase17/langchain/blame/master/langchain/llms/modal.py) integration class requires that you deploy a Modal application with a web endpoint that complies with the following JSON interface:\n",
"The [`langchain.llms.modal.Modal`](https://github.com/langchain-ai/langchain/blame/master/langchain/llms/modal.py) integration class requires that you deploy a Modal application with a web endpoint that complies with the following JSON interface:\n",
"\n",
"1. The LLM prompt is accepted as a `str` value under the key `\"prompt\"`\n",
"2. The LLM response returned as a `str` value under the key `\"prompt\"`\n",
"This notebook is based on the [chat_vector_db](https://github.com/hwchase17/langchain/blob/master/docs/modules/chains/index_examples/chat_vector_db.html) notebook, but using Vectara as the vector database."
"This notebook is based on the [chat_vector_db](https://github.com/langchain-ai/langchain/blob/master/docs/modules/chains/index_examples/chat_vector_db.html) notebook, but using Vectara as the vector database."
"This notebook is based on [text generation](https://github.com/hwchase17/langchain/blob/master/docs/modules/chains/index_examples/vector_db_text_generation.ipynb) notebook and adapted to Vectara."
"This notebook is based on [text generation](https://github.com/langchain-ai/langchain/blob/master/docs/modules/chains/index_examples/vector_db_text_generation.ipynb) notebook and adapted to Vectara."
Currently, only `jinja2` and `f-string` are supported. For other formats, kindly raise an issue on the [Github page](https://github.com/hwchase17/langchain/issues).
Currently, only `jinja2` and `f-string` are supported. For other formats, kindly raise an issue on the [Github page](https://github.com/langchain-ai/langchain/issues).
"1. define a format they will produce their outputs in\n",
"2. parse their outputs\n",
"\n",
"We can subclass the [RegexParser](https://github.com/hwchase17/langchain/blob/master/langchain/output_parsers/regex.py) to implement our own custom output parser for bids."
"We can subclass the [RegexParser](https://github.com/langchain-ai/langchain/blob/master/langchain/output_parsers/regex.py) to implement our own custom output parser for bids."
"Here, we show how the AI Sales Agent can use a **Product Knowledge Base** to speak about a particular's company offerings,\n",
"hence increasing relevance and reducing hallucinations.\n",
"\n",
"We leverage the [`langchain`](https://github.com/hwchase17/langchain) library in this implementation, specifically [Custom Agent Configuration](https://langchain-langchain.vercel.app/docs/modules/agents/how_to/custom_agent_with_tool_retrieval) and are inspired by [BabyAGI](https://github.com/yoheinakajima/babyagi) architecture ."
"We leverage the [`langchain`](https://github.com/langchain-ai/langchain) library in this implementation, specifically [Custom Agent Configuration](https://langchain-langchain.vercel.app/docs/modules/agents/how_to/custom_agent_with_tool_retrieval) and are inspired by [BabyAGI](https://github.com/yoheinakajima/babyagi) architecture ."
"The CPAL chain builds on the recent PAL to stop LLM hallucination. The problem with the PAL approach is that it hallucinates on a math problem with a nested chain of dependence. The innovation here is that this new CPAL approach includes causal structure to fix hallucination.\n",
"\n",
"The original [PR's description](https://github.com/hwchase17/langchain/pull/6255) contains a full overview.\n",
"The original [PR's description](https://github.com/langchain-ai/langchain/pull/6255) contains a full overview.\n",
"\n",
"Using the CPAL chain, the LLM translated this\n",
"This will use a QA default prompt (shown [here](https://github.com/hwchase17/langchain/blob/275b926cf745b5668d3ea30236635e20e7866442/langchain/chains/retrieval_qa/prompt.py#L4)) and will retrieve from the vectorDB.\n",
"This will use a QA default prompt (shown [here](https://github.com/langchain-ai/langchain/blob/275b926cf745b5668d3ea30236635e20e7866442/langchain/chains/retrieval_qa/prompt.py#L4)) and will retrieve from the vectorDB.\n",
"\n",
"But, you can still pass in a prompt, as before, if desired."
@ -66,7 +66,7 @@ from langchain.chains import RetrievalQA
from langchain.llms import OpenAI
```
Next in the generic setup, let's specify the document loader we want to use. You can download the `state_of_the_union.txt` file [here](https://github.com/hwchase17/langchain/blob/master/docs/extras/modules/state_of_the_union.txt).
Next in the generic setup, let's specify the document loader we want to use. You can download the `state_of_the_union.txt` file [here](https://github.com/langchain-ai/langchain/blob/master/docs/extras/modules/state_of_the_union.txt).
Currently, we support streaming for a broad range of LLM implementations, including but not limited to `OpenAI`, `ChatOpenAI`, `ChatAnthropic`, `Hugging Face Text Generation Inference`, and `Replicate`. This feature has been expanded to accommodate most of the models. To utilize streaming, use a [`CallbackHandler`](https://github.com/hwchase17/langchain/blob/master/langchain/callbacks/base.py) that implements `on_llm_new_token`. In this example, we are using `StreamingStdOutCallbackHandler`.
Currently, we support streaming for a broad range of LLM implementations, including but not limited to `OpenAI`, `ChatOpenAI`, `ChatAnthropic`, `Hugging Face Text Generation Inference`, and `Replicate`. This feature has been expanded to accommodate most of the models. To utilize streaming, use a [`CallbackHandler`](https://github.com/langchain-ai/langchain/blob/master/langchain/callbacks/base.py) that implements `on_llm_new_token`. In this example, we are using `StreamingStdOutCallbackHandler`.
```python
from langchain.llms import OpenAI
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
[![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/hwchase17/langchain)
[![Open in Dev Containers](https://img.shields.io/static/v1?label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/langchain-ai/langchain)
[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/hwchase17/langchain)
[![GitHub star chart](https://img.shields.io/github/stars/hwchase17/langchain?style=social)](https://star-history.com/#hwchase17/langchain)
Looking for the JS/TS version? Check out [LangChain.js](https://github.com/hwchase17/langchainjs).
Looking for the JS/TS version? Check out [LangChain.js](https://github.com/langchain-ai/langchainjs).
**Production Support:** As you move your LangChains into production, we'd love to offer more hands-on support.
Fill out [this form](https://airtable.com/appwQzlErAS2qiP0L/shrGtGaVBVAz7NcV2) to share more about what you're building, and our team will get in touch.
@ -41,7 +41,7 @@ This library aims to assist in the development of those types of applications. C