fmt

docs/.local_build.sh

@@ -21,4 +21,7 @@ wget -q https://raw.githubusercontent.com/langchain-ai/langgraph/main/README.md
 
 yarn
 
-poetry run quarto preview docs
+poetry run quarto render versioned_docs
+poetry run quarto render docs
+
+yarn start

docs/docs/modules/model_io/chat/function_calling.mdx

@@ -12,7 +12,7 @@ etc., have a function-calling API that lets you describe functions and
 their arguments, and have the model return a JSON object with a function
 to invoke and the inputs to that function. Function-calling is extremely
 useful for building [tool-using chains and
-agents](../../../../docs/use_cases/tool_use/), and for getting
+agents](/docs/use_cases/tool_use/), and for getting
 structured outputs from models more generally.
 
 LangChain comes with a number of utilities to make function-calling
@@ -28,9 +28,9 @@ easy. Namely, it comes with:
 
 We’ll focus here on the first two points. For a detailed guide on output
 parsing check out the [OpenAI Tools output
-parsers](../../../../docs/modules/model_io/output_parsers/types/openai_tools)
+parsers](/docs/modules/model_io/output_parsers/types/openai_tools)
 and to see the structured output chains check out the [Structured output
-guide](../../../../docs/guides/structured_output).
+guide](/docs/guides/structured_output).
 
 Before getting started make sure you have `langchain-core` installed.
 
@@ -523,13 +523,13 @@ print(json.dumps(convert_to_openai_tool(Multiply()), indent=2))
 ## Next steps
 
 -   **Output parsing**: See [OpenAI Tools output
-    parsers](../../../../docs/modules/model_io/output_parsers/types/openai_tools)
+    parsers](/docs/modules/model_io/output_parsers/types/openai_tools)
     and [OpenAI Functions output
-    parsers](../../../../docs/modules/model_io/output_parsers/types/openai_functions)
+    parsers](/docs/modules/model_io/output_parsers/types/openai_functions)
     to learn about extracting the function calling API responses into
     various formats.
--   **Structured output chains**: [Some models have constructors](../../../../docs/guides/structured_output) that
+-   **Structured output chains**: [Some models have constructors](/docs/guides/structured_output) that
     handle creating a structured output chain for you.
 -   **Tool use**: See how to construct chains and agents that actually
     call the invoked tools in [these
-    guides](../../../../docs/use_cases/tool_use/).
+    guides](/docs/use_cases/tool_use/).

docs/docs/use_cases/question_answering/quickstart.mdx

@@ -20,7 +20,7 @@ complexity.
 ## Architecture
 
 We’ll create a typical RAG application as outlined in the [Q&A
-introduction](../../../docs/use_cases/question_answering/), which has
+introduction](/docs/use_cases/question_answering/), which has
 two main components:
 
 **Indexing**: a pipeline for ingesting data from a source and indexing
@@ -35,28 +35,28 @@ The full sequence from raw data to answer will look like:
 #### Indexing
 
 1.  **Load**: First we need to load our data. We’ll use
-    [DocumentLoaders](../../../docs/modules/data_connection/document_loaders/)
+    [DocumentLoaders](/docs/modules/data_connection/document_loaders/)
     for this.
 2.  **Split**: [Text
-    splitters](../../../docs/modules/data_connection/document_transformers/)
+    splitters](/docs/modules/data_connection/document_transformers/)
     break large `Documents` into smaller chunks. This is useful both for
     indexing data and for passing it in to a model, since large chunks
     are harder to search over and won’t fit in a model’s finite context
     window.
 3.  **Store**: We need somewhere to store and index our splits, so that
     they can later be searched over. This is often done using a
-    [VectorStore](../../../docs/modules/data_connection/vectorstores/)
+    [VectorStore](/docs/modules/data_connection/vectorstores/)
     and
-    [Embeddings](../../../docs/modules/data_connection/text_embedding/)
+    [Embeddings](/docs/modules/data_connection/text_embedding/)
     model.
 
 #### Retrieval and generation
 
 1.  **Retrieve**: Given a user input, relevant splits are retrieved from
     storage using a
-    [Retriever](../../../docs/modules/data_connection/retrievers/).
-2.  **Generate**: A [ChatModel](../../../docs/modules/model_io/chat/) /
-    [LLM](../../../docs/modules/model_io/llms/) produces an answer using
+    [Retriever](/docs/modules/data_connection/retrievers/).
+2.  **Generate**: A [ChatModel](/docs/modules/model_io/chat/) /
+    [LLM](/docs/modules/model_io/llms/) produces an answer using
     a prompt that includes the question and the retrieved data
 
 ## Setup
@@ -65,11 +65,11 @@ The full sequence from raw data to answer will look like:
 
 We’ll use an OpenAI chat model and embeddings and a Chroma vector store
 in this walkthrough, but everything shown here works with any
-[ChatModel](../../../docs/modules/model_io/chat/) or
-[LLM](../../../docs/modules/model_io/llms/),
-[Embeddings](../../../docs/modules/data_connection/text_embedding/), and
-[VectorStore](../../../docs/modules/data_connection/vectorstores/) or
-[Retriever](../../../docs/modules/data_connection/retrievers/).
+[ChatModel](/docs/modules/model_io/chat/) or
+[LLM](/docs/modules/model_io/llms/),
+[Embeddings](/docs/modules/data_connection/text_embedding/), and
+[VectorStore](/docs/modules/data_connection/vectorstores/) or
+[Retriever](/docs/modules/data_connection/retrievers/).
 
 We’ll use the following packages:
 
@@ -189,7 +189,7 @@ going on.
 ## 1. Indexing: Load {#indexing-load}
 
 We need to first load the blog post contents. We can use
-[DocumentLoaders](../../../docs/modules/data_connection/document_loaders/)
+[DocumentLoaders](/docs/modules/data_connection/document_loaders/)
 for this, which are objects that load in data from a source and return a
 list of
 [Documents](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html).
@@ -197,7 +197,7 @@ A `Document` is an object with some `page_content` (str) and `metadata`
 (dict).
 
 In this case we’ll use the
-[WebBaseLoader](../../../docs/integrations/document_loaders/web_base),
+[WebBaseLoader](/docs/integrations/document_loaders/web_base),
 which uses `urllib` to load HTML from web URLs and `BeautifulSoup` to
 parse it to text. We can customize the HTML -\> text parsing by passing
 in parameters to the `BeautifulSoup` parser via `bs_kwargs` (see
@@ -249,9 +249,9 @@ In
 
 `DocumentLoader`: Object that loads data from a source as list of
 `Documents`. 
-- [Docs](../../../docs/modules/data_connection/document_loaders/):
+- [Docs](/docs/modules/data_connection/document_loaders/):
 Detailed documentation on how to use `DocumentLoaders`. 
-- [Integrations](../../../docs/integrations/document_loaders/): 160+
+- [Integrations](/docs/integrations/document_loaders/): 160+
 integrations to choose from. 
 - [Interface](https://api.python.langchain.com/en/latest/document_loaders/langchain_community.document_loaders.base.BaseLoader.html):
 API reference  for the base interface.
@@ -271,7 +271,7 @@ In this case we’ll split our documents into chunks of 1000 characters
 with 200 characters of overlap between chunks. The overlap helps
 mitigate the possibility of separating a statement from important
 context related to it. We use the
-[RecursiveCharacterTextSplitter](../../../docs/modules/data_connection/document_transformers/recursive_text_splitter),
+[RecursiveCharacterTextSplitter](/docs/modules/data_connection/document_transformers/recursive_text_splitter),
 which will recursively split the document using common separators like
 new lines until each chunk is the appropriate size. This is the
 recommended text splitter for generic text use cases.
@@ -321,15 +321,15 @@ all_splits[10].metadata
 chunks. Subclass of `DocumentTransformer`s. 
 - Explore `Context-aware splitters`, which keep the location (“context”) of each
 split in the original `Document`: - [Markdown
-files](../../../docs/modules/data_connection/document_transformers/markdown_header_metadata) 
-- [Code (py or js)](../../../docs/integrations/document_loaders/source_code) 
-- [Scientific papers](../../../docs/integrations/document_loaders/grobid) 
+files](/docs/modules/data_connection/document_transformers/markdown_header_metadata) 
+- [Code (py or js)](/docs/integrations/document_loaders/source_code) 
+- [Scientific papers](/docs/integrations/document_loaders/grobid) 
 - [Interface](https://api.python.langchain.com/en/latest/text_splitter/langchain_text_splitters.TextSplitter.html): API reference for the base interface.
 
 `DocumentTransformer`: Object that performs a transformation on a list
 of `Document`s. 
-- [Docs](../../../docs/modules/data_connection/document_transformers/): Detailed documentation on how to use `DocumentTransformers` 
-- [Integrations](../../../docs/integrations/document_transformers/) 
+- [Docs](/docs/modules/data_connection/document_transformers/): Detailed documentation on how to use `DocumentTransformers` 
+- [Integrations](/docs/integrations/document_transformers/) 
 - [Interface](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.transformers.BaseDocumentTransformer.html): API reference for the base interface.
 
 ## 3. Indexing: Store {#indexing-store}
@@ -345,9 +345,9 @@ similarity — we measure the cosine of the angle between each pair of
 embeddings (which are high dimensional vectors).
 
 We can embed and store all of our document splits in a single command
-using the [Chroma](../../../docs/integrations/vectorstores/chroma)
+using the [Chroma](/docs/integrations/vectorstores/chroma)
 vector store and
-[OpenAIEmbeddings](../../../docs/integrations/text_embedding/openai)
+[OpenAIEmbeddings](/docs/integrations/text_embedding/openai)
 model.
 
 ```python
@@ -361,14 +361,14 @@ vectorstore = Chroma.from_documents(documents=all_splits, embedding=OpenAIEmbedd
 
 `Embeddings`: Wrapper around a text embedding model, used for converting
 text to embeddings. 
-- [Docs](../../../docs/modules/data_connection/text_embedding): Detailed documentation on how to use embeddings. 
-- [Integrations](../../../docs/integrations/text_embedding/): 30+ integrations to choose from. 
+- [Docs](/docs/modules/data_connection/text_embedding): Detailed documentation on how to use embeddings. 
+- [Integrations](/docs/integrations/text_embedding/): 30+ integrations to choose from. 
 - [Interface](https://api.python.langchain.com/en/latest/embeddings/langchain_core.embeddings.Embeddings.html): API reference for the base interface.
 
 `VectorStore`: Wrapper around a vector database, used for storing and
 querying embeddings. 
-- [Docs](../../../docs/modules/data_connection/vectorstores/): Detailed documentation on how to use vector stores. 
-- [Integrations](../../../docs/integrations/vectorstores/): 40+ integrations to choose from. 
+- [Docs](/docs/modules/data_connection/vectorstores/): Detailed documentation on how to use vector stores. 
+- [Integrations](/docs/integrations/vectorstores/): 40+ integrations to choose from. 
 - [Interface](https://api.python.langchain.com/en/latest/vectorstores/langchain_core.vectorstores.VectorStore.html): API reference for the base interface.
 
 This completes the **Indexing** portion of the pipeline. At this point
@@ -385,12 +385,12 @@ a model, and returns an answer.
 
 First we need to define our logic for searching over documents.
 LangChain defines a
-[Retriever](../../../docs/modules/data_connection/retrievers/) interface
+[Retriever](/docs/modules/data_connection/retrievers/) interface
 which wraps an index that can return relevant `Documents` given a string
 query.
 
 The most common type of `Retriever` is the
-[VectorStoreRetriever](../../../docs/modules/data_connection/retrievers/vectorstore),
+[VectorStoreRetriever](/docs/modules/data_connection/retrievers/vectorstore),
 which uses the similarity search capabilities of a vector store to
 facilitate retrieval. Any `VectorStore` can easily be turned into a
 `Retriever` with `VectorStore.as_retriever()`:
@@ -429,15 +429,15 @@ to do retrieval, too.
 
 `Retriever`: An object that returns `Document`s given a text query
 
--   [Docs](../../../docs/modules/data_connection/retrievers/): Further
+-   [Docs](/docs/modules/data_connection/retrievers/): Further
     documentation on the interface and built-in retrieval techniques.
     Some of which include:
     -   `MultiQueryRetriever` [generates variants of the input
-        question](../../../docs/modules/data_connection/retrievers/MultiQueryRetriever)
+        question](/docs/modules/data_connection/retrievers/MultiQueryRetriever)
         to improve retrieval hit rate.
     -   `MultiVectorRetriever` (diagram below) instead generates
         [variants of the
-        embeddings](../../../docs/modules/data_connection/retrievers/multi_vector),
+        embeddings](/docs/modules/data_connection/retrievers/multi_vector),
         also in order to improve retrieval hit rate.
     -   `Max marginal relevance` selects for [relevance and
         diversity](https://www.cs.cmu.edu/~jgc/publication/The_Use_MMR_Diversity_Based_LTMIR_1998.pdf)
@@ -445,8 +445,8 @@ to do retrieval, too.
         context.
     -   Documents can be filtered during vector store retrieval using
         metadata filters, such as with a [Self Query
-        Retriever](../../../docs/modules/data_connection/retrievers/self_query).
--   [Integrations](../../../docs/integrations/retrievers/): Integrations
+        Retriever](/docs/modules/data_connection/retrievers/self_query).
+-   [Integrations](/docs/integrations/retrievers/): Integrations
     with retrieval services.
 -   [Interface](https://api.python.langchain.com/en/latest/retrievers/langchain_core.retrievers.BaseRetriever.html):
     API reference for the base interface.
@@ -521,7 +521,7 @@ Context: filler context
 Answer:
 ```
 
-We’ll use the [LCEL Runnable](../../../docs/expression_language/)
+We’ll use the [LCEL Runnable](/docs/expression_language/)
 protocol to define the chain, allowing us to - pipe together components
 and functions in a transparent way - automatically trace our chain in
 LangSmith - get streaming, async, and batched calling out of the box
@@ -562,17 +562,17 @@ trace](https://smith.langchain.com/public/1799e8db-8a6d-4eb2-84d5-46e8d7d5a99b/r
 
 `ChatModel`: An LLM-backed chat model. Takes in a sequence of messages
 and returns a message. 
-- [Docs](../../../docs/modules/model_io/chat/)
-- [Integrations](../../../docs/integrations/chat/): 25+ integrations to choose from. 
+- [Docs](/docs/modules/model_io/chat/)
+- [Integrations](/docs/integrations/chat/): 25+ integrations to choose from. 
 - [Interface](https://api.python.langchain.com/en/latest/language_models/langchain_core.language_models.chat_models.BaseChatModel.html): API reference for the base interface.
 
 `LLM`: A text-in-text-out LLM. Takes in a string and returns a string. 
-- [Docs](../../../docs/modules/model_io/llms) 
-- [Integrations](../../../docs/integrations/llms): 75+ integrations to choose from. 
+- [Docs](/docs/modules/model_io/llms) 
+- [Integrations](/docs/integrations/llms): 75+ integrations to choose from. 
 - [Interface](https://api.python.langchain.com/en/latest/language_models/langchain_core.language_models.llms.BaseLLM.html): API reference for the base interface.
 
 See a guide on RAG with locally-running models
-[here](../../../docs/use_cases/question_answering/local_retrieval_qa).
+[here](/docs/use_cases/question_answering/local_retrieval_qa).
 
 #### Customizing the prompt
 
@@ -620,10 +620,10 @@ the above sections. Along from the **Go deeper** sources mentioned
 above, good next steps include:
 
 -   [Return
-    sources](../../../docs/use_cases/question_answering/sources): Learn
+    sources](/docs/use_cases/question_answering/sources): Learn
     how to return source documents
--   [Streaming](../../../docs/use_cases/question_answering/streaming):
+-   [Streaming](/docs/use_cases/question_answering/streaming):
     Learn how to stream outputs and intermediate steps
 -   [Add chat
-    history](../../../docs/use_cases/question_answering/chat_history):
+    history](/docs/use_cases/question_answering/chat_history):
     Learn how to add chat history to your app

docs/docusaurus.config.js

@@ -82,6 +82,12 @@ const config = {
       ({
         docs: {
           sidebarPath: require.resolve("./sidebars.js"),
+          lastVersion: "current",
+          versions: {
+            current: {
+              label: '0.2.x',
+            }
+          },
           remarkPlugins: [
             [require("@docusaurus/remark-plugin-npm2yarn"), { sync: true }],
           ],
@@ -149,9 +155,10 @@ const config = {
         logo: {src: "img/brand/wordmark.png", srcDark: "img/brand/wordmark-dark.png"},
         items: [
           {
-            to: "/docs/get_started/introduction",
-            label: "Docs",
-            position: "left",
+            type: 'doc',
+            docId: 'get_started/introduction',
+            label: 'Docs',
+            position: 'left',
           },
           {
             type: "docSidebar",
@@ -182,11 +189,13 @@ const config = {
             position: "left",
             items: [
               {
-                to: "/docs/people/",
+                type: 'doc',
+                docId: 'people',
                 label: "People",
               },
               {
-                to: "/docs/packages",
+                docId: "packages",
+                type: 'doc',
                 label: "Versioning",
               },
               {
@@ -195,7 +204,8 @@ const config = {
                 label: "Changelog",
               },
               {
-                to: "/docs/contributing",
+                docId: "contributing/index",
+                type: 'doc',
                 label: "Contributing",
               },
               {
@@ -208,15 +218,21 @@ const config = {
                 href: "https://github.com/langchain-ai/langchain/blob/master/cookbook/README.md"
               },
               {
-                to: "/docs/additional_resources/tutorials",
+                docId: "additional_resources/tutorials",
+                type: "doc",
                 label: "Tutorials"
               },
               {
-                to: "/docs/additional_resources/youtube",
+                docId: "additional_resources/youtube",
+                type: "doc",
                 label: "YouTube"
               },
             ]
           },
+          {
+            type: 'docsVersionDropdown',
+            position: 'right'
+          },
           {
             type: "dropdown",
             label: "🦜️🔗",
@@ -234,10 +250,6 @@ const config = {
                 href: "https://github.com/langchain-ai/langserve",
                 label: "LangServe GitHub",
               },
-              {
-                href: "https://github.com/langchain-ai/langchain/tree/master/templates",
-                label: "Templates GitHub",
-              },
               {
                 label: "Templates Hub",
                 href: "https://templates.langchain.com",

docs/vercel_build.sh

@@ -33,3 +33,4 @@ python3 scripts/resolve_local_links.py docs/langgraph.md https://github.com/lang
 
 # render
 quarto render docs/
+quarto render versioned_docs/

docs/versioned_docs/static/js/google_analytics.js

@@ -0,0 +1,5 @@
+window.dataLayer = window.dataLayer || [];
+function gtag(){dataLayer.push(arguments);}
+gtag('js', new Date());
+
+gtag('config', 'G-9B66JQQH2F');

docs/versioned_docs/version-0.1.x/.gitignore

@@ -0,0 +1,7 @@
+.yarn/
+
+node_modules/
+
+.docusaurus
+.cache-loader
+docs/api

docs/versioned_docs/version-0.1.x/_templates/integration.mdx

@@ -0,0 +1,60 @@
+[comment: Please, a reference example here "docs/integrations/arxiv.md"]::
+[comment: Use this template to create a new .md file in "docs/integrations/"]::
+
+# Title_REPLACE_ME
+
+[comment: Only one Tile/H1 is allowed!]::
+
+>
+[comment: Description: After reading this description, a reader should decide if this integration is good enough to try/follow reading OR]::
+[comment: go to read the next integration doc. ]::
+[comment: Description should include a link to the source for follow reading.]::
+
+## Installation and Setup
+
+[comment: Installation and Setup: All necessary additional package installations and setups for Tokens, etc]::
+
+```bash
+pip install package_name_REPLACE_ME
+```
+
+[comment: OR this text:]::
+
+There isn't any special setup for it.
+
+[comment: The next H2/## sections with names of the integration modules, like "LLM", "Text Embedding Models", etc]::
+[comment: see "Modules" in the "index.html" page]::
+[comment: Each H2 section should include a link to an example(s) and a Python code with the import of the integration class]::
+[comment: Below are several example sections. Remove all unnecessary sections. Add all necessary sections not provided here.]::
+
+## LLM
+
+See a [usage example](/docs/integrations/llms/INCLUDE_REAL_NAME).
+
+```python
+from langchain_community.llms import integration_class_REPLACE_ME
+```
+
+## Text Embedding Models
+
+See a [usage example](/docs/integrations/text_embedding/INCLUDE_REAL_NAME).
+
+```python
+from langchain_community.embeddings import integration_class_REPLACE_ME
+```
+
+## Chat models
+
+See a [usage example](/docs/integrations/chat/INCLUDE_REAL_NAME).
+
+```python
+from langchain_community.chat_models import integration_class_REPLACE_ME
+```
+
+## Document Loader
+
+See a [usage example](/docs/integrations/document_loaders/INCLUDE_REAL_NAME).
+
+```python
+from langchain_community.document_loaders import integration_class_REPLACE_ME
+```

docs/versioned_docs/version-0.1.x/additional_resources/dependents.mdx

@@ -0,0 +1,556 @@
+# Dependents
+
+Dependents stats for `langchain-ai/langchain`
+
+[![](https://img.shields.io/static/v1?label=Used%20by&message=41717&color=informational&logo=slickpic)](https://github.com/langchain-ai/langchain/network/dependents)
+[![](https://img.shields.io/static/v1?label=Used%20by%20(public)&message=538&color=informational&logo=slickpic)](https://github.com/langchain-ai/langchain/network/dependents)
+[![](https://img.shields.io/static/v1?label=Used%20by%20(private)&message=41179&color=informational&logo=slickpic)](https://github.com/langchain-ai/langchain/network/dependents)
+
+
+[update: `2023-12-08`; only dependent repositories with Stars > 100]
+
+
+| Repository | Stars  |
+| :--------  | -----: |
+|[AntonOsika/gpt-engineer](https://github.com/AntonOsika/gpt-engineer) | 46514 |
+|[imartinez/privateGPT](https://github.com/imartinez/privateGPT) | 44439 |
+|[LAION-AI/Open-Assistant](https://github.com/LAION-AI/Open-Assistant) | 35906 |
+|[hpcaitech/ColossalAI](https://github.com/hpcaitech/ColossalAI) | 35528 |
+|[moymix/TaskMatrix](https://github.com/moymix/TaskMatrix) | 34342 |
+|[geekan/MetaGPT](https://github.com/geekan/MetaGPT) | 31126 |
+|[streamlit/streamlit](https://github.com/streamlit/streamlit) | 28911 |
+|[reworkd/AgentGPT](https://github.com/reworkd/AgentGPT) | 27833 |
+|[StanGirard/quivr](https://github.com/StanGirard/quivr) | 26032 |
+|[OpenBB-finance/OpenBBTerminal](https://github.com/OpenBB-finance/OpenBBTerminal) | 24946 |
+|[run-llama/llama_index](https://github.com/run-llama/llama_index) | 24859 |
+|[jmorganca/ollama](https://github.com/jmorganca/ollama) | 20849 |
+|[openai/chatgpt-retrieval-plugin](https://github.com/openai/chatgpt-retrieval-plugin) | 20249 |
+|[chatchat-space/Langchain-Chatchat](https://github.com/chatchat-space/Langchain-Chatchat) | 19305 |
+|[mindsdb/mindsdb](https://github.com/mindsdb/mindsdb) | 19172 |
+|[PromtEngineer/localGPT](https://github.com/PromtEngineer/localGPT) | 17528 |
+|[cube-js/cube](https://github.com/cube-js/cube) | 16575 |
+|[mlflow/mlflow](https://github.com/mlflow/mlflow) | 16000 |
+|[mudler/LocalAI](https://github.com/mudler/LocalAI) | 14067 |
+|[logspace-ai/langflow](https://github.com/logspace-ai/langflow) | 13679 |
+|[GaiZhenbiao/ChuanhuChatGPT](https://github.com/GaiZhenbiao/ChuanhuChatGPT) | 13648 |
+|[arc53/DocsGPT](https://github.com/arc53/DocsGPT) | 13423 |
+|[openai/evals](https://github.com/openai/evals) | 12649 |
+|[airbytehq/airbyte](https://github.com/airbytehq/airbyte) | 12460 |
+|[langgenius/dify](https://github.com/langgenius/dify) | 11859 |
+|[databrickslabs/dolly](https://github.com/databrickslabs/dolly) | 10672 |
+|[AIGC-Audio/AudioGPT](https://github.com/AIGC-Audio/AudioGPT) | 9437 |
+|[langchain-ai/langchainjs](https://github.com/langchain-ai/langchainjs) | 9227 |
+|[gventuri/pandas-ai](https://github.com/gventuri/pandas-ai) | 9203 |
+|[aws/amazon-sagemaker-examples](https://github.com/aws/amazon-sagemaker-examples) | 9079 |
+|[h2oai/h2ogpt](https://github.com/h2oai/h2ogpt) | 8945 |
+|[PipedreamHQ/pipedream](https://github.com/PipedreamHQ/pipedream) | 7550 |
+|[bentoml/OpenLLM](https://github.com/bentoml/OpenLLM) | 6957 |
+|[THUDM/ChatGLM3](https://github.com/THUDM/ChatGLM3) | 6801 |
+|[microsoft/promptflow](https://github.com/microsoft/promptflow) | 6776 |
+|[cpacker/MemGPT](https://github.com/cpacker/MemGPT) | 6642 |
+|[joshpxyne/gpt-migrate](https://github.com/joshpxyne/gpt-migrate) | 6482 |
+|[zauberzeug/nicegui](https://github.com/zauberzeug/nicegui) | 6037 |
+|[embedchain/embedchain](https://github.com/embedchain/embedchain) | 6023 |
+|[mage-ai/mage-ai](https://github.com/mage-ai/mage-ai) | 6019 |
+|[assafelovic/gpt-researcher](https://github.com/assafelovic/gpt-researcher) | 5936 |
+|[sweepai/sweep](https://github.com/sweepai/sweep) | 5855 |
+|[wenda-LLM/wenda](https://github.com/wenda-LLM/wenda) | 5766 |
+|[zilliztech/GPTCache](https://github.com/zilliztech/GPTCache) | 5710 |
+|[pdm-project/pdm](https://github.com/pdm-project/pdm) | 5665 |
+|[GreyDGL/PentestGPT](https://github.com/GreyDGL/PentestGPT) | 5568 |
+|[gkamradt/langchain-tutorials](https://github.com/gkamradt/langchain-tutorials) | 5507 |
+|[Shaunwei/RealChar](https://github.com/Shaunwei/RealChar) | 5501 |
+|[facebookresearch/llama-recipes](https://github.com/facebookresearch/llama-recipes) | 5477 |
+|[serge-chat/serge](https://github.com/serge-chat/serge) | 5221 |
+|[run-llama/rags](https://github.com/run-llama/rags) | 4916 |
+|[openchatai/OpenChat](https://github.com/openchatai/OpenChat) | 4870 |
+|[danswer-ai/danswer](https://github.com/danswer-ai/danswer) | 4774 |
+|[langchain-ai/opengpts](https://github.com/langchain-ai/opengpts) | 4709 |
+|[postgresml/postgresml](https://github.com/postgresml/postgresml) | 4639 |
+|[MineDojo/Voyager](https://github.com/MineDojo/Voyager) | 4582 |
+|[intel-analytics/BigDL](https://github.com/intel-analytics/BigDL) | 4581 |
+|[yihong0618/xiaogpt](https://github.com/yihong0618/xiaogpt) | 4359 |
+|[RayVentura/ShortGPT](https://github.com/RayVentura/ShortGPT) | 4357 |
+|[Azure-Samples/azure-search-openai-demo](https://github.com/Azure-Samples/azure-search-openai-demo) | 4317 |
+|[madawei2699/myGPTReader](https://github.com/madawei2699/myGPTReader) | 4289 |
+|[apache/nifi](https://github.com/apache/nifi) | 4098 |
+|[langchain-ai/chat-langchain](https://github.com/langchain-ai/chat-langchain) | 4091 |
+|[aiwaves-cn/agents](https://github.com/aiwaves-cn/agents) | 4073 |
+|[krishnaik06/The-Grand-Complete-Data-Science-Materials](https://github.com/krishnaik06/The-Grand-Complete-Data-Science-Materials) | 4065 |
+|[khoj-ai/khoj](https://github.com/khoj-ai/khoj) | 4016 |
+|[Azure/azure-sdk-for-python](https://github.com/Azure/azure-sdk-for-python) | 3941 |
+|[PrefectHQ/marvin](https://github.com/PrefectHQ/marvin) | 3915 |
+|[OpenBMB/ToolBench](https://github.com/OpenBMB/ToolBench) | 3799 |
+|[marqo-ai/marqo](https://github.com/marqo-ai/marqo) | 3771 |
+|[kyegomez/tree-of-thoughts](https://github.com/kyegomez/tree-of-thoughts) | 3688 |
+|[Unstructured-IO/unstructured](https://github.com/Unstructured-IO/unstructured) | 3543 |
+|[llm-workflow-engine/llm-workflow-engine](https://github.com/llm-workflow-engine/llm-workflow-engine) | 3515 |
+|[shroominic/codeinterpreter-api](https://github.com/shroominic/codeinterpreter-api) | 3425 |
+|[openchatai/OpenCopilot](https://github.com/openchatai/OpenCopilot) | 3418 |
+|[josStorer/RWKV-Runner](https://github.com/josStorer/RWKV-Runner) | 3297 |
+|[whitead/paper-qa](https://github.com/whitead/paper-qa) | 3280 |
+|[homanp/superagent](https://github.com/homanp/superagent) | 3258 |
+|[ParisNeo/lollms-webui](https://github.com/ParisNeo/lollms-webui) | 3199 |
+|[OpenBMB/AgentVerse](https://github.com/OpenBMB/AgentVerse) | 3099 |
+|[project-baize/baize-chatbot](https://github.com/project-baize/baize-chatbot) | 3090 |
+|[OpenGVLab/InternGPT](https://github.com/OpenGVLab/InternGPT) | 2989 |
+|[xlang-ai/OpenAgents](https://github.com/xlang-ai/OpenAgents) | 2825 |
+|[dataelement/bisheng](https://github.com/dataelement/bisheng) | 2797 |
+|[Mintplex-Labs/anything-llm](https://github.com/Mintplex-Labs/anything-llm) | 2784 |
+|[OpenBMB/BMTools](https://github.com/OpenBMB/BMTools) | 2734 |
+|[run-llama/llama-hub](https://github.com/run-llama/llama-hub) | 2721 |
+|[SamurAIGPT/EmbedAI](https://github.com/SamurAIGPT/EmbedAI) | 2647 |
+|[NVIDIA/NeMo-Guardrails](https://github.com/NVIDIA/NeMo-Guardrails) | 2637 |
+|[X-D-Lab/LangChain-ChatGLM-Webui](https://github.com/X-D-Lab/LangChain-ChatGLM-Webui) | 2532 |
+|[GerevAI/gerev](https://github.com/GerevAI/gerev) | 2517 |
+|[keephq/keep](https://github.com/keephq/keep) | 2448 |
+|[yanqiangmiffy/Chinese-LangChain](https://github.com/yanqiangmiffy/Chinese-LangChain) | 2397 |
+|[OpenGVLab/Ask-Anything](https://github.com/OpenGVLab/Ask-Anything) | 2324 |
+|[IntelligenzaArtificiale/Free-Auto-GPT](https://github.com/IntelligenzaArtificiale/Free-Auto-GPT) | 2241 |
+|[YiVal/YiVal](https://github.com/YiVal/YiVal) | 2232 |
+|[jupyterlab/jupyter-ai](https://github.com/jupyterlab/jupyter-ai) | 2189 |
+|[Farama-Foundation/PettingZoo](https://github.com/Farama-Foundation/PettingZoo) | 2136 |
+|[microsoft/TaskWeaver](https://github.com/microsoft/TaskWeaver) | 2126 |
+|[hwchase17/notion-qa](https://github.com/hwchase17/notion-qa) | 2083 |
+|[FlagOpen/FlagEmbedding](https://github.com/FlagOpen/FlagEmbedding) | 2053 |
+|[paulpierre/RasaGPT](https://github.com/paulpierre/RasaGPT) | 1999 |
+|[hegelai/prompttools](https://github.com/hegelai/prompttools) | 1984 |
+|[mckinsey/vizro](https://github.com/mckinsey/vizro) | 1951 |
+|[vocodedev/vocode-python](https://github.com/vocodedev/vocode-python) | 1868 |
+|[dot-agent/openAMS](https://github.com/dot-agent/openAMS) | 1796 |
+|[explodinggradients/ragas](https://github.com/explodinggradients/ragas) | 1766 |
+|[AI-Citizen/SolidGPT](https://github.com/AI-Citizen/SolidGPT) | 1761 |
+|[Kav-K/GPTDiscord](https://github.com/Kav-K/GPTDiscord) | 1696 |
+|[run-llama/sec-insights](https://github.com/run-llama/sec-insights) | 1654 |
+|[avinashkranjan/Amazing-Python-Scripts](https://github.com/avinashkranjan/Amazing-Python-Scripts) | 1635 |
+|[microsoft/WhatTheHack](https://github.com/microsoft/WhatTheHack) | 1629 |
+|[noahshinn/reflexion](https://github.com/noahshinn/reflexion) | 1625 |
+|[psychic-api/psychic](https://github.com/psychic-api/psychic) | 1618 |
+|[Forethought-Technologies/AutoChain](https://github.com/Forethought-Technologies/AutoChain) | 1611 |
+|[pinterest/querybook](https://github.com/pinterest/querybook) | 1586 |
+|[refuel-ai/autolabel](https://github.com/refuel-ai/autolabel) | 1553 |
+|[jina-ai/langchain-serve](https://github.com/jina-ai/langchain-serve) | 1537 |
+|[jina-ai/dev-gpt](https://github.com/jina-ai/dev-gpt) | 1522 |
+|[agiresearch/OpenAGI](https://github.com/agiresearch/OpenAGI) | 1493 |
+|[ttengwang/Caption-Anything](https://github.com/ttengwang/Caption-Anything) | 1484 |
+|[greshake/llm-security](https://github.com/greshake/llm-security) | 1483 |
+|[promptfoo/promptfoo](https://github.com/promptfoo/promptfoo) | 1480 |
+|[milvus-io/bootcamp](https://github.com/milvus-io/bootcamp) | 1477 |
+|[richardyc/Chrome-GPT](https://github.com/richardyc/Chrome-GPT) | 1475 |
+|[melih-unsal/DemoGPT](https://github.com/melih-unsal/DemoGPT) | 1428 |
+|[YORG-AI/Open-Assistant](https://github.com/YORG-AI/Open-Assistant) | 1419 |
+|[101dotxyz/GPTeam](https://github.com/101dotxyz/GPTeam) | 1416 |
+|[jina-ai/thinkgpt](https://github.com/jina-ai/thinkgpt) | 1408 |
+|[mmz-001/knowledge_gpt](https://github.com/mmz-001/knowledge_gpt) | 1398 |
+|[intel/intel-extension-for-transformers](https://github.com/intel/intel-extension-for-transformers) | 1387 |
+|[Azure/azureml-examples](https://github.com/Azure/azureml-examples) | 1385 |
+|[lunasec-io/lunasec](https://github.com/lunasec-io/lunasec) | 1367 |
+|[eyurtsev/kor](https://github.com/eyurtsev/kor) | 1355 |
+|[xusenlinzy/api-for-open-llm](https://github.com/xusenlinzy/api-for-open-llm) | 1325 |
+|[griptape-ai/griptape](https://github.com/griptape-ai/griptape) | 1323 |
+|[SuperDuperDB/superduperdb](https://github.com/SuperDuperDB/superduperdb) | 1290 |
+|[cofactoryai/textbase](https://github.com/cofactoryai/textbase) | 1284 |
+|[psychic-api/rag-stack](https://github.com/psychic-api/rag-stack) | 1260 |
+|[filip-michalsky/SalesGPT](https://github.com/filip-michalsky/SalesGPT) | 1250 |
+|[nod-ai/SHARK](https://github.com/nod-ai/SHARK) | 1237 |
+|[pluralsh/plural](https://github.com/pluralsh/plural) | 1234 |
+|[cheshire-cat-ai/core](https://github.com/cheshire-cat-ai/core) | 1194 |
+|[LC1332/Chat-Haruhi-Suzumiya](https://github.com/LC1332/Chat-Haruhi-Suzumiya) | 1184 |
+|[poe-platform/server-bot-quick-start](https://github.com/poe-platform/server-bot-quick-start) | 1182 |
+|[microsoft/X-Decoder](https://github.com/microsoft/X-Decoder) | 1180 |
+|[juncongmoo/chatllama](https://github.com/juncongmoo/chatllama) | 1171 |
+|[visual-openllm/visual-openllm](https://github.com/visual-openllm/visual-openllm) | 1156 |
+|[alejandro-ao/ask-multiple-pdfs](https://github.com/alejandro-ao/ask-multiple-pdfs) | 1153 |
+|[ThousandBirdsInc/chidori](https://github.com/ThousandBirdsInc/chidori) | 1152 |
+|[irgolic/AutoPR](https://github.com/irgolic/AutoPR) | 1137 |
+|[SamurAIGPT/Camel-AutoGPT](https://github.com/SamurAIGPT/Camel-AutoGPT) | 1083 |
+|[ray-project/llm-applications](https://github.com/ray-project/llm-applications) | 1080 |
+|[run-llama/llama-lab](https://github.com/run-llama/llama-lab) | 1072 |
+|[jiran214/GPT-vup](https://github.com/jiran214/GPT-vup) | 1041 |
+|[MetaGLM/FinGLM](https://github.com/MetaGLM/FinGLM) | 1035 |
+|[peterw/Chat-with-Github-Repo](https://github.com/peterw/Chat-with-Github-Repo) | 1020 |
+|[Anil-matcha/ChatPDF](https://github.com/Anil-matcha/ChatPDF) | 991 |
+|[langchain-ai/langserve](https://github.com/langchain-ai/langserve) | 983 |
+|[THUDM/AgentTuning](https://github.com/THUDM/AgentTuning) | 976 |
+|[rlancemartin/auto-evaluator](https://github.com/rlancemartin/auto-evaluator) | 975 |
+|[codeacme17/examor](https://github.com/codeacme17/examor) | 964 |
+|[all-in-aigc/gpts-works](https://github.com/all-in-aigc/gpts-works) | 946 |
+|[Ikaros-521/AI-Vtuber](https://github.com/Ikaros-521/AI-Vtuber) | 946 |
+|[microsoft/Llama-2-Onnx](https://github.com/microsoft/Llama-2-Onnx) | 898 |
+|[cirediatpl/FigmaChain](https://github.com/cirediatpl/FigmaChain) | 895 |
+|[ricklamers/shell-ai](https://github.com/ricklamers/shell-ai) | 893 |
+|[modelscope/modelscope-agent](https://github.com/modelscope/modelscope-agent) | 893 |
+|[seanpixel/Teenage-AGI](https://github.com/seanpixel/Teenage-AGI) | 886 |
+|[ajndkr/lanarky](https://github.com/ajndkr/lanarky) | 880 |
+|[kennethleungty/Llama-2-Open-Source-LLM-CPU-Inference](https://github.com/kennethleungty/Llama-2-Open-Source-LLM-CPU-Inference) | 872 |
+|[corca-ai/EVAL](https://github.com/corca-ai/EVAL) | 846 |
+|[hwchase17/chat-your-data](https://github.com/hwchase17/chat-your-data) | 841 |
+|[kreneskyp/ix](https://github.com/kreneskyp/ix) | 821 |
+|[Link-AGI/AutoAgents](https://github.com/Link-AGI/AutoAgents) | 820 |
+|[truera/trulens](https://github.com/truera/trulens) | 794 |
+|[Dataherald/dataherald](https://github.com/Dataherald/dataherald) | 788 |
+|[sunlabuiuc/PyHealth](https://github.com/sunlabuiuc/PyHealth) | 783 |
+|[jondurbin/airoboros](https://github.com/jondurbin/airoboros) | 783 |
+|[pyspark-ai/pyspark-ai](https://github.com/pyspark-ai/pyspark-ai) | 782 |
+|[confident-ai/deepeval](https://github.com/confident-ai/deepeval) | 780 |
+|[billxbf/ReWOO](https://github.com/billxbf/ReWOO) | 777 |
+|[langchain-ai/streamlit-agent](https://github.com/langchain-ai/streamlit-agent) | 776 |
+|[akshata29/entaoai](https://github.com/akshata29/entaoai) | 771 |
+|[LambdaLabsML/examples](https://github.com/LambdaLabsML/examples) | 770 |
+|[getmetal/motorhead](https://github.com/getmetal/motorhead) | 768 |
+|[Dicklesworthstone/swiss_army_llama](https://github.com/Dicklesworthstone/swiss_army_llama) | 757 |
+|[ruoccofabrizio/azure-open-ai-embeddings-qna](https://github.com/ruoccofabrizio/azure-open-ai-embeddings-qna) | 757 |
+|[msoedov/langcorn](https://github.com/msoedov/langcorn) | 754 |
+|[e-johnstonn/BriefGPT](https://github.com/e-johnstonn/BriefGPT) | 753 |
+|[microsoft/sample-app-aoai-chatGPT](https://github.com/microsoft/sample-app-aoai-chatGPT) | 749 |
+|[explosion/spacy-llm](https://github.com/explosion/spacy-llm) | 731 |
+|[MiuLab/Taiwan-LLM](https://github.com/MiuLab/Taiwan-LLM) | 716 |
+|[whyiyhw/chatgpt-wechat](https://github.com/whyiyhw/chatgpt-wechat) | 702 |
+|[Azure-Samples/openai](https://github.com/Azure-Samples/openai) | 692 |
+|[iusztinpaul/hands-on-llms](https://github.com/iusztinpaul/hands-on-llms) | 687 |
+|[safevideo/autollm](https://github.com/safevideo/autollm) | 682 |
+|[OpenGenerativeAI/GenossGPT](https://github.com/OpenGenerativeAI/GenossGPT) | 669 |
+|[NoDataFound/hackGPT](https://github.com/NoDataFound/hackGPT) | 663 |
+|[AILab-CVC/GPT4Tools](https://github.com/AILab-CVC/GPT4Tools) | 662 |
+|[langchain-ai/auto-evaluator](https://github.com/langchain-ai/auto-evaluator) | 657 |
+|[yvann-ba/Robby-chatbot](https://github.com/yvann-ba/Robby-chatbot) | 639 |
+|[alexanderatallah/window.ai](https://github.com/alexanderatallah/window.ai) | 635 |
+|[amosjyng/langchain-visualizer](https://github.com/amosjyng/langchain-visualizer) | 630 |
+|[microsoft/PodcastCopilot](https://github.com/microsoft/PodcastCopilot) | 621 |
+|[aws-samples/aws-genai-llm-chatbot](https://github.com/aws-samples/aws-genai-llm-chatbot) | 616 |
+|[NeumTry/NeumAI](https://github.com/NeumTry/NeumAI) | 605 |
+|[namuan/dr-doc-search](https://github.com/namuan/dr-doc-search) | 599 |
+|[plastic-labs/tutor-gpt](https://github.com/plastic-labs/tutor-gpt) | 595 |
+|[marimo-team/marimo](https://github.com/marimo-team/marimo) | 591 |
+|[yakami129/VirtualWife](https://github.com/yakami129/VirtualWife) | 586 |
+|[xuwenhao/geektime-ai-course](https://github.com/xuwenhao/geektime-ai-course) | 584 |
+|[jonra1993/fastapi-alembic-sqlmodel-async](https://github.com/jonra1993/fastapi-alembic-sqlmodel-async) | 573 |
+|[dgarnitz/vectorflow](https://github.com/dgarnitz/vectorflow) | 568 |
+|[yeagerai/yeagerai-agent](https://github.com/yeagerai/yeagerai-agent) | 564 |
+|[daveebbelaar/langchain-experiments](https://github.com/daveebbelaar/langchain-experiments) | 563 |
+|[traceloop/openllmetry](https://github.com/traceloop/openllmetry) | 559 |
+|[Agenta-AI/agenta](https://github.com/Agenta-AI/agenta) | 546 |
+|[michaelthwan/searchGPT](https://github.com/michaelthwan/searchGPT) | 545 |
+|[jina-ai/agentchain](https://github.com/jina-ai/agentchain) | 544 |
+|[mckaywrigley/repo-chat](https://github.com/mckaywrigley/repo-chat) | 533 |
+|[marella/chatdocs](https://github.com/marella/chatdocs) | 532 |
+|[opentensor/bittensor](https://github.com/opentensor/bittensor) | 532 |
+|[DjangoPeng/openai-quickstart](https://github.com/DjangoPeng/openai-quickstart) | 527 |
+|[freddyaboulton/gradio-tools](https://github.com/freddyaboulton/gradio-tools) | 517 |
+|[sidhq/Multi-GPT](https://github.com/sidhq/Multi-GPT) | 515 |
+|[alejandro-ao/langchain-ask-pdf](https://github.com/alejandro-ao/langchain-ask-pdf) | 514 |
+|[sajjadium/ctf-archives](https://github.com/sajjadium/ctf-archives) | 507 |
+|[continuum-llms/chatgpt-memory](https://github.com/continuum-llms/chatgpt-memory) | 502 |
+|[llmOS/opencopilot](https://github.com/llmOS/opencopilot) | 495 |
+|[steamship-core/steamship-langchain](https://github.com/steamship-core/steamship-langchain) | 494 |
+|[mpaepper/content-chatbot](https://github.com/mpaepper/content-chatbot) | 493 |
+|[langchain-ai/langchain-aiplugin](https://github.com/langchain-ai/langchain-aiplugin) | 492 |
+|[logan-markewich/llama_index_starter_pack](https://github.com/logan-markewich/llama_index_starter_pack) | 483 |
+|[datawhalechina/llm-universe](https://github.com/datawhalechina/llm-universe) | 475 |
+|[leondz/garak](https://github.com/leondz/garak) | 464 |
+|[RedisVentures/ArXivChatGuru](https://github.com/RedisVentures/ArXivChatGuru) | 461 |
+|[Anil-matcha/Chatbase](https://github.com/Anil-matcha/Chatbase) | 455 |
+|[Aiyu-awa/luna-ai](https://github.com/Aiyu-awa/luna-ai) | 450 |
+|[DataDog/dd-trace-py](https://github.com/DataDog/dd-trace-py) | 450 |
+|[Azure-Samples/miyagi](https://github.com/Azure-Samples/miyagi) | 449 |
+|[poe-platform/poe-protocol](https://github.com/poe-platform/poe-protocol) | 447 |
+|[onlyphantom/llm-python](https://github.com/onlyphantom/llm-python) | 446 |
+|[junruxiong/IncarnaMind](https://github.com/junruxiong/IncarnaMind) | 441 |
+|[CarperAI/OpenELM](https://github.com/CarperAI/OpenELM) | 441 |
+|[daodao97/chatdoc](https://github.com/daodao97/chatdoc) | 437 |
+|[showlab/VLog](https://github.com/showlab/VLog) | 436 |
+|[wandb/weave](https://github.com/wandb/weave) | 420 |
+|[QwenLM/Qwen-Agent](https://github.com/QwenLM/Qwen-Agent) | 419 |
+|[huchenxucs/ChatDB](https://github.com/huchenxucs/ChatDB) | 416 |
+|[jerlendds/osintbuddy](https://github.com/jerlendds/osintbuddy) | 411 |
+|[monarch-initiative/ontogpt](https://github.com/monarch-initiative/ontogpt) | 408 |
+|[mallorbc/Finetune_LLMs](https://github.com/mallorbc/Finetune_LLMs) | 406 |
+|[JayZeeDesign/researcher-gpt](https://github.com/JayZeeDesign/researcher-gpt) | 405 |
+|[rsaryev/talk-codebase](https://github.com/rsaryev/talk-codebase) | 401 |
+|[langchain-ai/langsmith-cookbook](https://github.com/langchain-ai/langsmith-cookbook) | 398 |
+|[mtenenholtz/chat-twitter](https://github.com/mtenenholtz/chat-twitter) | 398 |
+|[morpheuslord/GPT_Vuln-analyzer](https://github.com/morpheuslord/GPT_Vuln-analyzer) | 391 |
+|[MagnivOrg/prompt-layer-library](https://github.com/MagnivOrg/prompt-layer-library) | 387 |
+|[JohnSnowLabs/langtest](https://github.com/JohnSnowLabs/langtest) | 384 |
+|[mrwadams/attackgen](https://github.com/mrwadams/attackgen) | 381 |
+|[codefuse-ai/Test-Agent](https://github.com/codefuse-ai/Test-Agent) | 380 |
+|[personoids/personoids-lite](https://github.com/personoids/personoids-lite) | 379 |
+|[mosaicml/examples](https://github.com/mosaicml/examples) | 378 |
+|[steamship-packages/langchain-production-starter](https://github.com/steamship-packages/langchain-production-starter) | 370 |
+|[FlagAI-Open/Aquila2](https://github.com/FlagAI-Open/Aquila2) | 365 |
+|[Mintplex-Labs/vector-admin](https://github.com/Mintplex-Labs/vector-admin) | 365 |
+|[NimbleBoxAI/ChainFury](https://github.com/NimbleBoxAI/ChainFury) | 357 |
+|[BlackHC/llm-strategy](https://github.com/BlackHC/llm-strategy) | 354 |
+|[lilacai/lilac](https://github.com/lilacai/lilac) | 352 |
+|[preset-io/promptimize](https://github.com/preset-io/promptimize) | 351 |
+|[yuanjie-ai/ChatLLM](https://github.com/yuanjie-ai/ChatLLM) | 347 |
+|[andylokandy/gpt-4-search](https://github.com/andylokandy/gpt-4-search) | 346 |
+|[zhoudaquan/ChatAnything](https://github.com/zhoudaquan/ChatAnything) | 343 |
+|[rgomezcasas/dotfiles](https://github.com/rgomezcasas/dotfiles) | 343 |
+|[tigerlab-ai/tiger](https://github.com/tigerlab-ai/tiger) | 342 |
+|[HumanSignal/label-studio-ml-backend](https://github.com/HumanSignal/label-studio-ml-backend) | 334 |
+|[nasa-petal/bidara](https://github.com/nasa-petal/bidara) | 334 |
+|[momegas/megabots](https://github.com/momegas/megabots) | 334 |
+|[Cheems-Seminar/grounded-segment-any-parts](https://github.com/Cheems-Seminar/grounded-segment-any-parts) | 330 |
+|[CambioML/pykoi](https://github.com/CambioML/pykoi) | 326 |
+|[Nuggt-dev/Nuggt](https://github.com/Nuggt-dev/Nuggt) | 326 |
+|[wandb/edu](https://github.com/wandb/edu) | 326 |
+|[Haste171/langchain-chatbot](https://github.com/Haste171/langchain-chatbot) | 324 |
+|[sugarforever/LangChain-Tutorials](https://github.com/sugarforever/LangChain-Tutorials) | 322 |
+|[liangwq/Chatglm_lora_multi-gpu](https://github.com/liangwq/Chatglm_lora_multi-gpu) | 321 |
+|[ur-whitelab/chemcrow-public](https://github.com/ur-whitelab/chemcrow-public) | 320 |
+|[itamargol/openai](https://github.com/itamargol/openai) | 318 |
+|[gia-guar/JARVIS-ChatGPT](https://github.com/gia-guar/JARVIS-ChatGPT) | 304 |
+|[SpecterOps/Nemesis](https://github.com/SpecterOps/Nemesis) | 302 |
+|[facebookresearch/personal-timeline](https://github.com/facebookresearch/personal-timeline) | 302 |
+|[hnawaz007/pythondataanalysis](https://github.com/hnawaz007/pythondataanalysis) | 301 |
+|[Chainlit/cookbook](https://github.com/Chainlit/cookbook) | 300 |
+|[airobotlab/KoChatGPT](https://github.com/airobotlab/KoChatGPT) | 300 |
+|[GPT-Fathom/GPT-Fathom](https://github.com/GPT-Fathom/GPT-Fathom) | 299 |
+|[kaarthik108/snowChat](https://github.com/kaarthik108/snowChat) | 299 |
+|[kyegomez/swarms](https://github.com/kyegomez/swarms) | 296 |
+|[LangStream/langstream](https://github.com/LangStream/langstream) | 295 |
+|[genia-dev/GeniA](https://github.com/genia-dev/GeniA) | 294 |
+|[shamspias/customizable-gpt-chatbot](https://github.com/shamspias/customizable-gpt-chatbot) | 291 |
+|[TsinghuaDatabaseGroup/DB-GPT](https://github.com/TsinghuaDatabaseGroup/DB-GPT) | 290 |
+|[conceptofmind/toolformer](https://github.com/conceptofmind/toolformer) | 283 |
+|[sullivan-sean/chat-langchainjs](https://github.com/sullivan-sean/chat-langchainjs) | 283 |
+|[AutoPackAI/beebot](https://github.com/AutoPackAI/beebot) | 282 |
+|[pablomarin/GPT-Azure-Search-Engine](https://github.com/pablomarin/GPT-Azure-Search-Engine) | 282 |
+|[gkamradt/LLMTest_NeedleInAHaystack](https://github.com/gkamradt/LLMTest_NeedleInAHaystack) | 280 |
+|[gustavz/DataChad](https://github.com/gustavz/DataChad) | 280 |
+|[Safiullah-Rahu/CSV-AI](https://github.com/Safiullah-Rahu/CSV-AI) | 278 |
+|[hwchase17/chroma-langchain](https://github.com/hwchase17/chroma-langchain) | 275 |
+|[AkshitIreddy/Interactive-LLM-Powered-NPCs](https://github.com/AkshitIreddy/Interactive-LLM-Powered-NPCs) | 268 |
+|[ennucore/clippinator](https://github.com/ennucore/clippinator) | 267 |
+|[artitw/text2text](https://github.com/artitw/text2text) | 264 |
+|[anarchy-ai/LLM-VM](https://github.com/anarchy-ai/LLM-VM) | 263 |
+|[wpydcr/LLM-Kit](https://github.com/wpydcr/LLM-Kit) | 262 |
+|[streamlit/llm-examples](https://github.com/streamlit/llm-examples) | 262 |
+|[paolorechia/learn-langchain](https://github.com/paolorechia/learn-langchain) | 262 |
+|[yym68686/ChatGPT-Telegram-Bot](https://github.com/yym68686/ChatGPT-Telegram-Bot) | 261 |
+|[PradipNichite/Youtube-Tutorials](https://github.com/PradipNichite/Youtube-Tutorials) | 259 |
+|[radi-cho/datasetGPT](https://github.com/radi-cho/datasetGPT) | 259 |
+|[ur-whitelab/exmol](https://github.com/ur-whitelab/exmol) | 259 |
+|[ml6team/fondant](https://github.com/ml6team/fondant) | 254 |
+|[bborn/howdoi.ai](https://github.com/bborn/howdoi.ai) | 254 |
+|[rahulnyk/knowledge_graph](https://github.com/rahulnyk/knowledge_graph) | 253 |
+|[recalign/RecAlign](https://github.com/recalign/RecAlign) | 248 |
+|[hwchase17/langchain-streamlit-template](https://github.com/hwchase17/langchain-streamlit-template) | 248 |
+|[fetchai/uAgents](https://github.com/fetchai/uAgents) | 247 |
+|[arthur-ai/bench](https://github.com/arthur-ai/bench) | 247 |
+|[miaoshouai/miaoshouai-assistant](https://github.com/miaoshouai/miaoshouai-assistant) | 246 |
+|[RoboCoachTechnologies/GPT-Synthesizer](https://github.com/RoboCoachTechnologies/GPT-Synthesizer) | 244 |
+|[langchain-ai/web-explorer](https://github.com/langchain-ai/web-explorer) | 242 |
+|[kaleido-lab/dolphin](https://github.com/kaleido-lab/dolphin) | 242 |
+|[PJLab-ADG/DriveLikeAHuman](https://github.com/PJLab-ADG/DriveLikeAHuman) | 241 |
+|[stepanogil/autonomous-hr-chatbot](https://github.com/stepanogil/autonomous-hr-chatbot) | 238 |
+|[WongSaang/chatgpt-ui-server](https://github.com/WongSaang/chatgpt-ui-server) | 236 |
+|[nexus-stc/stc](https://github.com/nexus-stc/stc) | 235 |
+|[yeagerai/genworlds](https://github.com/yeagerai/genworlds) | 235 |
+|[Gentopia-AI/Gentopia](https://github.com/Gentopia-AI/Gentopia) | 235 |
+|[alphasecio/langchain-examples](https://github.com/alphasecio/langchain-examples) | 235 |
+|[grumpyp/aixplora](https://github.com/grumpyp/aixplora) | 232 |
+|[shaman-ai/agent-actors](https://github.com/shaman-ai/agent-actors) | 232 |
+|[darrenburns/elia](https://github.com/darrenburns/elia) | 231 |
+|[orgexyz/BlockAGI](https://github.com/orgexyz/BlockAGI) | 231 |
+|[handrew/browserpilot](https://github.com/handrew/browserpilot) | 226 |
+|[su77ungr/CASALIOY](https://github.com/su77ungr/CASALIOY) | 225 |
+|[nicknochnack/LangchainDocuments](https://github.com/nicknochnack/LangchainDocuments) | 225 |
+|[dbpunk-labs/octogen](https://github.com/dbpunk-labs/octogen) | 224 |
+|[langchain-ai/weblangchain](https://github.com/langchain-ai/weblangchain) | 222 |
+|[CL-lau/SQL-GPT](https://github.com/CL-lau/SQL-GPT) | 222 |
+|[alvarosevilla95/autolang](https://github.com/alvarosevilla95/autolang) | 221 |
+|[showlab/UniVTG](https://github.com/showlab/UniVTG) | 220 |
+|[edreisMD/plugnplai](https://github.com/edreisMD/plugnplai) | 219 |
+|[hardbyte/qabot](https://github.com/hardbyte/qabot) | 216 |
+|[microsoft/azure-openai-in-a-day-workshop](https://github.com/microsoft/azure-openai-in-a-day-workshop) | 215 |
+|[Azure-Samples/chat-with-your-data-solution-accelerator](https://github.com/Azure-Samples/chat-with-your-data-solution-accelerator) | 214 |
+|[amadad/agentcy](https://github.com/amadad/agentcy) | 213 |
+|[snexus/llm-search](https://github.com/snexus/llm-search) | 212 |
+|[afaqueumer/DocQA](https://github.com/afaqueumer/DocQA) | 206 |
+|[plchld/InsightFlow](https://github.com/plchld/InsightFlow) | 205 |
+|[yasyf/compress-gpt](https://github.com/yasyf/compress-gpt) | 205 |
+|[benthecoder/ClassGPT](https://github.com/benthecoder/ClassGPT) | 205 |
+|[voxel51/voxelgpt](https://github.com/voxel51/voxelgpt) | 204 |
+|[jbrukh/gpt-jargon](https://github.com/jbrukh/gpt-jargon) | 204 |
+|[emarco177/ice_breaker](https://github.com/emarco177/ice_breaker) | 204 |
+|[tencentmusic/supersonic](https://github.com/tencentmusic/supersonic) | 202 |
+|[Azure-Samples/azure-search-power-skills](https://github.com/Azure-Samples/azure-search-power-skills) | 202 |
+|[blob42/Instrukt](https://github.com/blob42/Instrukt) | 201 |
+|[langchain-ai/langsmith-sdk](https://github.com/langchain-ai/langsmith-sdk) | 200 |
+|[SamPink/dev-gpt](https://github.com/SamPink/dev-gpt) | 200 |
+|[ju-bezdek/langchain-decorators](https://github.com/ju-bezdek/langchain-decorators) | 198 |
+|[KMnO4-zx/huanhuan-chat](https://github.com/KMnO4-zx/huanhuan-chat) | 196 |
+|[Azure-Samples/jp-azureopenai-samples](https://github.com/Azure-Samples/jp-azureopenai-samples) | 192 |
+|[hongbo-miao/hongbomiao.com](https://github.com/hongbo-miao/hongbomiao.com) | 190 |
+|[CakeCrusher/openplugin](https://github.com/CakeCrusher/openplugin) | 190 |
+|[PaddlePaddle/ERNIE-Bot-SDK](https://github.com/PaddlePaddle/ERNIE-Bot-SDK) | 189 |
+|[retr0reg/Ret2GPT](https://github.com/retr0reg/Ret2GPT) | 189 |
+|[AmineDiro/cria](https://github.com/AmineDiro/cria) | 187 |
+|[lancedb/vectordb-recipes](https://github.com/lancedb/vectordb-recipes) | 186 |
+|[vaibkumr/prompt-optimizer](https://github.com/vaibkumr/prompt-optimizer) | 185 |
+|[aws-ia/ecs-blueprints](https://github.com/aws-ia/ecs-blueprints) | 184 |
+|[ethanyanjiali/minChatGPT](https://github.com/ethanyanjiali/minChatGPT) | 183 |
+|[MuhammadMoinFaisal/LargeLanguageModelsProjects](https://github.com/MuhammadMoinFaisal/LargeLanguageModelsProjects) | 182 |
+|[shauryr/S2QA](https://github.com/shauryr/S2QA) | 181 |
+|[summarizepaper/summarizepaper](https://github.com/summarizepaper/summarizepaper) | 180 |
+|[NomaDamas/RAGchain](https://github.com/NomaDamas/RAGchain) | 179 |
+|[pnkvalavala/repochat](https://github.com/pnkvalavala/repochat) | 179 |
+|[ibiscp/LLM-IMDB](https://github.com/ibiscp/LLM-IMDB) | 177 |
+|[fengyuli-dev/multimedia-gpt](https://github.com/fengyuli-dev/multimedia-gpt) | 177 |
+|[langchain-ai/text-split-explorer](https://github.com/langchain-ai/text-split-explorer) | 175 |
+|[iMagist486/ElasticSearch-Langchain-Chatglm2](https://github.com/iMagist486/ElasticSearch-Langchain-Chatglm2) | 175 |
+|[limaoyi1/Auto-PPT](https://github.com/limaoyi1/Auto-PPT) | 175 |
+|[Open-Swarm-Net/GPT-Swarm](https://github.com/Open-Swarm-Net/GPT-Swarm) | 175 |
+|[morpheuslord/HackBot](https://github.com/morpheuslord/HackBot) | 174 |
+|[v7labs/benchllm](https://github.com/v7labs/benchllm) | 174 |
+|[Coding-Crashkurse/Langchain-Full-Course](https://github.com/Coding-Crashkurse/Langchain-Full-Course) | 174 |
+|[dongyh20/Octopus](https://github.com/dongyh20/Octopus) | 173 |
+|[kimtth/azure-openai-llm-vector-langchain](https://github.com/kimtth/azure-openai-llm-vector-langchain) | 173 |
+|[mayooear/private-chatbot-mpt30b-langchain](https://github.com/mayooear/private-chatbot-mpt30b-langchain) | 173 |
+|[zilliztech/akcio](https://github.com/zilliztech/akcio) | 172 |
+|[jmpaz/promptlib](https://github.com/jmpaz/promptlib) | 172 |
+|[ccurme/yolopandas](https://github.com/ccurme/yolopandas) | 172 |
+|[joaomdmoura/CrewAI](https://github.com/joaomdmoura/CrewAI) | 170 |
+|[katanaml/llm-mistral-invoice-cpu](https://github.com/katanaml/llm-mistral-invoice-cpu) | 170 |
+|[chakkaradeep/pyCodeAGI](https://github.com/chakkaradeep/pyCodeAGI) | 170 |
+|[mudler/LocalAGI](https://github.com/mudler/LocalAGI) | 167 |
+|[dssjon/biblos](https://github.com/dssjon/biblos) | 165 |
+|[kjappelbaum/gptchem](https://github.com/kjappelbaum/gptchem) | 165 |
+|[xxw1995/chatglm3-finetune](https://github.com/xxw1995/chatglm3-finetune) | 164 |
+|[ArjanCodes/examples](https://github.com/ArjanCodes/examples) | 163 |
+|[AIAnytime/Llama2-Medical-Chatbot](https://github.com/AIAnytime/Llama2-Medical-Chatbot) | 163 |
+|[RCGAI/SimplyRetrieve](https://github.com/RCGAI/SimplyRetrieve) | 162 |
+|[langchain-ai/langchain-teacher](https://github.com/langchain-ai/langchain-teacher) | 162 |
+|[menloparklab/falcon-langchain](https://github.com/menloparklab/falcon-langchain) | 162 |
+|[flurb18/AgentOoba](https://github.com/flurb18/AgentOoba) | 162 |
+|[homanp/vercel-langchain](https://github.com/homanp/vercel-langchain) | 161 |
+|[jiran214/langup-ai](https://github.com/jiran214/langup-ai) | 160 |
+|[JorisdeJong123/7-Days-of-LangChain](https://github.com/JorisdeJong123/7-Days-of-LangChain) | 160 |
+|[GoogleCloudPlatform/data-analytics-golden-demo](https://github.com/GoogleCloudPlatform/data-analytics-golden-demo) | 159 |
+|[positive666/Prompt-Can-Anything](https://github.com/positive666/Prompt-Can-Anything) | 159 |
+|[luisroque/large_laguage_models](https://github.com/luisroque/large_laguage_models) | 159 |
+|[mlops-for-all/mlops-for-all.github.io](https://github.com/mlops-for-all/mlops-for-all.github.io) | 158 |
+|[wandb/wandbot](https://github.com/wandb/wandbot) | 158 |
+|[elastic/elasticsearch-labs](https://github.com/elastic/elasticsearch-labs) | 157 |
+|[shroominic/funcchain](https://github.com/shroominic/funcchain) | 157 |
+|[deeppavlov/dream](https://github.com/deeppavlov/dream) | 156 |
+|[mluogh/eastworld](https://github.com/mluogh/eastworld) | 154 |
+|[georgesung/llm_qlora](https://github.com/georgesung/llm_qlora) | 154 |
+|[RUC-GSAI/YuLan-Rec](https://github.com/RUC-GSAI/YuLan-Rec) | 153 |
+|[KylinC/ChatFinance](https://github.com/KylinC/ChatFinance) | 152 |
+|[Dicklesworthstone/llama2_aided_tesseract](https://github.com/Dicklesworthstone/llama2_aided_tesseract) | 152 |
+|[c0sogi/LLMChat](https://github.com/c0sogi/LLMChat) | 152 |
+|[eunomia-bpf/GPTtrace](https://github.com/eunomia-bpf/GPTtrace) | 152 |
+|[ErikBjare/gptme](https://github.com/ErikBjare/gptme) | 152 |
+|[Klingefjord/chatgpt-telegram](https://github.com/Klingefjord/chatgpt-telegram) | 152 |
+|[RoboCoachTechnologies/ROScribe](https://github.com/RoboCoachTechnologies/ROScribe) | 151 |
+|[Aggregate-Intellect/sherpa](https://github.com/Aggregate-Intellect/sherpa) | 151 |
+|[3Alan/DocsMind](https://github.com/3Alan/DocsMind) | 151 |
+|[tangqiaoyu/ToolAlpaca](https://github.com/tangqiaoyu/ToolAlpaca) | 150 |
+|[kulltc/chatgpt-sql](https://github.com/kulltc/chatgpt-sql) | 150 |
+|[mallahyari/drqa](https://github.com/mallahyari/drqa) | 150 |
+|[MedalCollector/Orator](https://github.com/MedalCollector/Orator) | 149 |
+|[Teahouse-Studios/akari-bot](https://github.com/Teahouse-Studios/akari-bot) | 149 |
+|[realminchoi/babyagi-ui](https://github.com/realminchoi/babyagi-ui) | 148 |
+|[ssheng/BentoChain](https://github.com/ssheng/BentoChain) | 148 |
+|[lmstudio-ai/examples](https://github.com/lmstudio-ai/examples) | 147 |
+|[solana-labs/chatgpt-plugin](https://github.com/solana-labs/chatgpt-plugin) | 147 |
+|[aurelio-labs/arxiv-bot](https://github.com/aurelio-labs/arxiv-bot) | 147 |
+|[Jaseci-Labs/jaseci](https://github.com/Jaseci-Labs/jaseci) | 146 |
+|[menloparklab/langchain-cohere-qdrant-doc-retrieval](https://github.com/menloparklab/langchain-cohere-qdrant-doc-retrieval) | 146 |
+|[trancethehuman/entities-extraction-web-scraper](https://github.com/trancethehuman/entities-extraction-web-scraper) | 144 |
+|[peterw/StoryStorm](https://github.com/peterw/StoryStorm) | 144 |
+|[grumpyp/chroma-langchain-tutorial](https://github.com/grumpyp/chroma-langchain-tutorial) | 144 |
+|[gh18l/CrawlGPT](https://github.com/gh18l/CrawlGPT) | 142 |
+|[langchain-ai/langchain-aws-template](https://github.com/langchain-ai/langchain-aws-template) | 142 |
+|[yasyf/summ](https://github.com/yasyf/summ) | 141 |
+|[petehunt/langchain-github-bot](https://github.com/petehunt/langchain-github-bot) | 141 |
+|[hirokidaichi/wanna](https://github.com/hirokidaichi/wanna) | 140 |
+|[jina-ai/fastapi-serve](https://github.com/jina-ai/fastapi-serve) | 139 |
+|[zenml-io/zenml-projects](https://github.com/zenml-io/zenml-projects) | 139 |
+|[jlonge4/local_llama](https://github.com/jlonge4/local_llama) | 139 |
+|[smyja/blackmaria](https://github.com/smyja/blackmaria) | 138 |
+|[ChuloAI/BrainChulo](https://github.com/ChuloAI/BrainChulo) | 137 |
+|[log1stics/voice-generator-webui](https://github.com/log1stics/voice-generator-webui) | 137 |
+|[davila7/file-gpt](https://github.com/davila7/file-gpt) | 137 |
+|[dcaribou/transfermarkt-datasets](https://github.com/dcaribou/transfermarkt-datasets) | 136 |
+|[ciare-robotics/world-creator](https://github.com/ciare-robotics/world-creator) | 135 |
+|[Undertone0809/promptulate](https://github.com/Undertone0809/promptulate) | 134 |
+|[fixie-ai/fixie-examples](https://github.com/fixie-ai/fixie-examples) | 134 |
+|[run-llama/ai-engineer-workshop](https://github.com/run-llama/ai-engineer-workshop) | 133 |
+|[definitive-io/code-indexer-loop](https://github.com/definitive-io/code-indexer-loop) | 131 |
+|[mortium91/langchain-assistant](https://github.com/mortium91/langchain-assistant) | 131 |
+|[baidubce/bce-qianfan-sdk](https://github.com/baidubce/bce-qianfan-sdk) | 130 |
+|[Ngonie-x/langchain_csv](https://github.com/Ngonie-x/langchain_csv) | 130 |
+|[IvanIsCoding/ResuLLMe](https://github.com/IvanIsCoding/ResuLLMe) | 130 |
+|[AnchoringAI/anchoring-ai](https://github.com/AnchoringAI/anchoring-ai) | 129 |
+|[Azure/business-process-automation](https://github.com/Azure/business-process-automation) | 128 |
+|[athina-ai/athina-sdk](https://github.com/athina-ai/athina-sdk) | 126 |
+|[thunlp/ChatEval](https://github.com/thunlp/ChatEval) | 126 |
+|[prof-frink-lab/slangchain](https://github.com/prof-frink-lab/slangchain) | 126 |
+|[vietanhdev/pautobot](https://github.com/vietanhdev/pautobot) | 125 |
+|[awslabs/generative-ai-cdk-constructs](https://github.com/awslabs/generative-ai-cdk-constructs) | 124 |
+|[sdaaron/QueryGPT](https://github.com/sdaaron/QueryGPT) | 124 |
+|[rabbitmetrics/langchain-13-min](https://github.com/rabbitmetrics/langchain-13-min) | 124 |
+|[AutoLLM/AutoAgents](https://github.com/AutoLLM/AutoAgents) | 122 |
+|[nicknochnack/Nopenai](https://github.com/nicknochnack/Nopenai) | 122 |
+|[wombyz/HormoziGPT](https://github.com/wombyz/HormoziGPT) | 122 |
+|[dotvignesh/PDFChat](https://github.com/dotvignesh/PDFChat) | 122 |
+|[topoteretes/PromethAI-Backend](https://github.com/topoteretes/PromethAI-Backend) | 121 |
+|[nftblackmagic/flask-langchain](https://github.com/nftblackmagic/flask-langchain) | 121 |
+|[vishwasg217/finsight](https://github.com/vishwasg217/finsight) | 120 |
+|[snap-stanford/MLAgentBench](https://github.com/snap-stanford/MLAgentBench) | 120 |
+|[Azure/app-service-linux-docs](https://github.com/Azure/app-service-linux-docs) | 120 |
+|[nyanp/chat2plot](https://github.com/nyanp/chat2plot) | 120 |
+|[ant4g0nist/polar](https://github.com/ant4g0nist/polar) | 119 |
+|[aws-samples/cdk-eks-blueprints-patterns](https://github.com/aws-samples/cdk-eks-blueprints-patterns) | 119 |
+|[aws-samples/amazon-kendra-langchain-extensions](https://github.com/aws-samples/amazon-kendra-langchain-extensions) | 119 |
+|[Xueheng-Li/SynologyChatbotGPT](https://github.com/Xueheng-Li/SynologyChatbotGPT) | 119 |
+|[CodeAlchemyAI/ViLT-GPT](https://github.com/CodeAlchemyAI/ViLT-GPT) | 117 |
+|[Lin-jun-xiang/docGPT-langchain](https://github.com/Lin-jun-xiang/docGPT-langchain) | 117 |
+|[ademakdogan/ChatSQL](https://github.com/ademakdogan/ChatSQL) | 116 |
+|[aniketmaurya/llm-inference](https://github.com/aniketmaurya/llm-inference) | 115 |
+|[xuwenhao/mactalk-ai-course](https://github.com/xuwenhao/mactalk-ai-course) | 115 |
+|[cmooredev/RepoReader](https://github.com/cmooredev/RepoReader) | 115 |
+|[abi/autocommit](https://github.com/abi/autocommit) | 115 |
+|[MIDORIBIN/langchain-gpt4free](https://github.com/MIDORIBIN/langchain-gpt4free) | 114 |
+|[finaldie/auto-news](https://github.com/finaldie/auto-news) | 114 |
+|[Anil-matcha/Youtube-to-chatbot](https://github.com/Anil-matcha/Youtube-to-chatbot) | 114 |
+|[avrabyt/MemoryBot](https://github.com/avrabyt/MemoryBot) | 114 |
+|[Capsize-Games/airunner](https://github.com/Capsize-Games/airunner) | 113 |
+|[atisharma/llama_farm](https://github.com/atisharma/llama_farm) | 113 |
+|[mbchang/data-driven-characters](https://github.com/mbchang/data-driven-characters) | 112 |
+|[fiddler-labs/fiddler-auditor](https://github.com/fiddler-labs/fiddler-auditor) | 112 |
+|[dirkjbreeuwer/gpt-automated-web-scraper](https://github.com/dirkjbreeuwer/gpt-automated-web-scraper) | 111 |
+|[Appointat/Chat-with-Document-s-using-ChatGPT-API-and-Text-Embedding](https://github.com/Appointat/Chat-with-Document-s-using-ChatGPT-API-and-Text-Embedding) | 111 |
+|[hwchase17/langchain-gradio-template](https://github.com/hwchase17/langchain-gradio-template) | 111 |
+|[artas728/spelltest](https://github.com/artas728/spelltest) | 110 |
+|[NVIDIA/GenerativeAIExamples](https://github.com/NVIDIA/GenerativeAIExamples) | 109 |
+|[Azure/aistudio-copilot-sample](https://github.com/Azure/aistudio-copilot-sample) | 108 |
+|[codefuse-ai/codefuse-chatbot](https://github.com/codefuse-ai/codefuse-chatbot) | 108 |
+|[apirrone/Memento](https://github.com/apirrone/Memento) | 108 |
+|[e-johnstonn/GPT-Doc-Summarizer](https://github.com/e-johnstonn/GPT-Doc-Summarizer) | 108 |
+|[salesforce/BOLAA](https://github.com/salesforce/BOLAA) | 107 |
+|[Erol444/gpt4-openai-api](https://github.com/Erol444/gpt4-openai-api) | 106 |
+|[linjungz/chat-with-your-doc](https://github.com/linjungz/chat-with-your-doc) | 106 |
+|[crosleythomas/MirrorGPT](https://github.com/crosleythomas/MirrorGPT) | 106 |
+|[panaverse/learn-generative-ai](https://github.com/panaverse/learn-generative-ai) | 105 |
+|[Azure/azure-sdk-tools](https://github.com/Azure/azure-sdk-tools) | 105 |
+|[malywut/gpt_examples](https://github.com/malywut/gpt_examples) | 105 |
+|[ritun16/chain-of-verification](https://github.com/ritun16/chain-of-verification) | 104 |
+|[langchain-ai/langchain-benchmarks](https://github.com/langchain-ai/langchain-benchmarks) | 104 |
+|[lightninglabs/LangChainBitcoin](https://github.com/lightninglabs/LangChainBitcoin) | 104 |
+|[flepied/second-brain-agent](https://github.com/flepied/second-brain-agent) | 103 |
+|[llmapp/openai.mini](https://github.com/llmapp/openai.mini) | 102 |
+|[gimlet-ai/tddGPT](https://github.com/gimlet-ai/tddGPT) | 102 |
+|[jlonge4/gpt_chatwithPDF](https://github.com/jlonge4/gpt_chatwithPDF) | 102 |
+|[agentification/RAFA_code](https://github.com/agentification/RAFA_code) | 101 |
+|[pacman100/DHS-LLM-Workshop](https://github.com/pacman100/DHS-LLM-Workshop) | 101 |
+|[aws-samples/private-llm-qa-bot](https://github.com/aws-samples/private-llm-qa-bot) | 101 |
+
+
+_Generated by [github-dependents-info](https://github.com/nvuillam/github-dependents-info)_
+
+`github-dependents-info --repo "langchain-ai/langchain" --markdownfile dependents.md --minstars 100 --sort stars`

docs/versioned_docs/version-0.1.x/additional_resources/tutorials.mdx

@@ -0,0 +1,50 @@
+# Tutorials
+
+## Books and Handbooks
+
+- [Generative AI with LangChain](https://www.amazon.com/Generative-AI-LangChain-language-ChatGPT/dp/1835083463/ref=sr_1_1?crid=1GMOMH0G7GLR&keywords=generative+ai+with+langchain&qid=1703247181&sprefix=%2Caps%2C298&sr=8-1) by [Ben Auffrath](https://www.amazon.com/stores/Ben-Auffarth/author/B08JQKSZ7D?ref=ap_rdr&store_ref=ap_rdr&isDramIntegrated=true&shoppingPortalEnabled=true), ©️ 2023 Packt Publishing
+- [LangChain AI Handbook](https://www.pinecone.io/learn/langchain/) By **James Briggs** and **Francisco Ingham**
+- [LangChain Cheatsheet](https://pub.towardsai.net/langchain-cheatsheet-all-secrets-on-a-single-page-8be26b721cde) by **Ivan Reznikov**
+
+
+##  Tutorials
+
+### [by Greg Kamradt](https://www.youtube.com/playlist?list=PLqZXAkvF1bPNQER9mLmDbntNfSpzdDIU5)
+### [by Sam Witteveen](https://www.youtube.com/playlist?list=PL8motc6AQftk1Bs42EW45kwYbyJ4jOdiZ)
+### [by James Briggs](https://www.youtube.com/playlist?list=PLIUOU7oqGTLieV9uTIFMm6_4PXg-hlN6F)
+### [by Prompt Engineering](https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr)
+### [by Mayo Oshin](https://www.youtube.com/@chatwithdata/search?query=langchain)
+### [by 1 little Coder](https://www.youtube.com/playlist?list=PLpdmBGJ6ELUK-v0MK-t4wZmVEbxM5xk6L)
+
+
+## Courses
+
+### Featured courses on Deeplearning.AI
+
+- [LangChain for LLM Application Development](https://learn.deeplearning.ai/langchain)
+- [LangChain Chat with Your Data](https://learn.deeplearning.ai/langchain-chat-with-your-data)
+- [Functions, Tools and Agents with LangChain](https://learn.deeplearning.ai/functions-tools-agents-langchain)
+- [Build LLM Apps with LangChain.js](https://learn.deeplearning.ai/courses/build-llm-apps-with-langchain-js)
+
+### Online courses
+
+- [Udemy](https://www.udemy.com/courses/search/?q=langchain)
+- [Pluralsight](https://www.pluralsight.com/search?q=langchain)
+- [Coursera](https://www.coursera.org/search?query=langchain)
+- [Maven](https://maven.com/courses?query=langchain)
+- [Udacity](https://www.udacity.com/catalog/all/any-price/any-school/any-skill/any-difficulty/any-duration/any-type/relevance/page-1?searchValue=langchain)
+- [LinkedIn Learning](https://www.linkedin.com/search/results/learning/?keywords=langchain)
+- [edX](https://www.edx.org/search?q=langchain)
+
+## Short Tutorials
+
+- [by Nicholas Renotte](https://youtu.be/MlK6SIjcjE8)
+- [by Patrick Loeber](https://youtu.be/LbT1yp6quS8)
+- [by Rabbitmetrics](https://youtu.be/aywZrzNaKjs)
+- [by Ivan Reznikov](https://medium.com/@ivanreznikov/langchain-101-course-updated-668f7b41d6cb)
+
+## [Documentation: Use cases](/docs/use_cases)
+
+---------------------
+
+

docs/versioned_docs/version-0.1.x/additional_resources/youtube.mdx

@@ -0,0 +1,137 @@
+# YouTube videos
+
+⛓ icon marks a new addition [last update 2023-09-21]
+
+### [Official LangChain YouTube channel](https://www.youtube.com/@LangChain)
+
+### Introduction to LangChain with Harrison Chase, creator of LangChain
+- [Building the Future with LLMs, `LangChain`, & `Pinecone`](https://youtu.be/nMniwlGyX-c) by [Pinecone](https://www.youtube.com/@pinecone-io)
+- [LangChain and Weaviate with Harrison Chase and Bob van Luijt - Weaviate Podcast #36](https://youtu.be/lhby7Ql7hbk) by [Weaviate • Vector Database](https://www.youtube.com/@Weaviate)
+- [LangChain Demo + Q&A with Harrison Chase](https://youtu.be/zaYTXQFR0_s?t=788) by [Full Stack Deep Learning](https://www.youtube.com/@FullStackDeepLearning)
+- [LangChain Agents: Build Personal Assistants For Your Data (Q&A with Harrison Chase and Mayo Oshin)](https://youtu.be/gVkF8cwfBLI) by [Chat with data](https://www.youtube.com/@chatwithdata)
+
+## Videos (sorted by views)
+
+- [Using `ChatGPT` with YOUR OWN Data. This is magical. (LangChain OpenAI API)](https://youtu.be/9AXP7tCI9PI) by [TechLead](https://www.youtube.com/@TechLead)
+- [First look - `ChatGPT` + `WolframAlpha` (`GPT-3.5` and Wolfram|Alpha via LangChain by James Weaver)](https://youtu.be/wYGbY811oMo) by [Dr Alan D. Thompson](https://www.youtube.com/@DrAlanDThompson) 
+- [LangChain explained - The hottest new Python framework](https://youtu.be/RoR4XJw8wIc) by [AssemblyAI](https://www.youtube.com/@AssemblyAI)
+- [Chatbot with INFINITE MEMORY using `OpenAI` & `Pinecone` - `GPT-3`, `Embeddings`, `ADA`, `Vector DB`, `Semantic`](https://youtu.be/2xNzB7xq8nk) by [David Shapiro ~ AI](https://www.youtube.com/@DavidShapiroAutomator)
+- [LangChain for LLMs is... basically just an Ansible playbook](https://youtu.be/X51N9C-OhlE) by [David Shapiro ~ AI](https://www.youtube.com/@DavidShapiroAutomator)
+- [Build your own LLM Apps with LangChain & `GPT-Index`](https://youtu.be/-75p09zFUJY) by [1littlecoder](https://www.youtube.com/@1littlecoder)
+- [`BabyAGI` - New System of Autonomous AI Agents with LangChain](https://youtu.be/lg3kJvf1kXo) by [1littlecoder](https://www.youtube.com/@1littlecoder)
+- [Run `BabyAGI` with Langchain Agents (with Python Code)](https://youtu.be/WosPGHPObx8) by [1littlecoder](https://www.youtube.com/@1littlecoder)
+- [How to Use Langchain With `Zapier` | Write and Send Email with GPT-3 | OpenAI API Tutorial](https://youtu.be/p9v2-xEa9A0) by [StarMorph AI](https://www.youtube.com/@starmorph)
+- [Use Your Locally Stored Files To Get Response From GPT - `OpenAI` | Langchain | Python](https://youtu.be/NC1Ni9KS-rk) by [Shweta Lodha](https://www.youtube.com/@shweta-lodha)
+- [`Langchain JS` | How to Use GPT-3, GPT-4 to Reference your own Data | `OpenAI Embeddings` Intro](https://youtu.be/veV2I-NEjaM) by [StarMorph AI](https://www.youtube.com/@starmorph)
+- [The easiest way to work with large language models | Learn LangChain in 10min](https://youtu.be/kmbS6FDQh7c) by [Sophia Yang](https://www.youtube.com/@SophiaYangDS)
+- [4 Autonomous AI Agents: “Westworld” simulation `BabyAGI`, `AutoGPT`, `Camel`, `LangChain`](https://youtu.be/yWbnH6inT_U) by [Sophia Yang](https://www.youtube.com/@SophiaYangDS)
+- [AI CAN SEARCH THE INTERNET? Langchain Agents + OpenAI ChatGPT](https://youtu.be/J-GL0htqda8) by [tylerwhatsgood](https://www.youtube.com/@tylerwhatsgood)
+- [Query Your Data with GPT-4 | Embeddings, Vector Databases | Langchain JS Knowledgebase](https://youtu.be/jRnUPUTkZmU) by [StarMorph AI](https://www.youtube.com/@starmorph)
+- [`Weaviate` + LangChain for LLM apps presented by Erika Cardenas](https://youtu.be/7AGj4Td5Lgw) by [`Weaviate` • Vector Database](https://www.youtube.com/@Weaviate)
+- [Langchain Overview — How to Use Langchain & `ChatGPT`](https://youtu.be/oYVYIq0lOtI) by [Python In Office](https://www.youtube.com/@pythoninoffice6568)
+- [Langchain Overview - How to Use Langchain & `ChatGPT`](https://youtu.be/oYVYIq0lOtI) by [Python In Office](https://www.youtube.com/@pythoninoffice6568)
+- [LangChain Tutorials](https://www.youtube.com/watch?v=FuqdVNB_8c0&list=PL9V0lbeJ69brU-ojMpU1Y7Ic58Tap0Cw6) by [Edrick](https://www.youtube.com/@edrickdch):
+  - [LangChain, Chroma DB, OpenAI Beginner Guide | ChatGPT with your PDF](https://youtu.be/FuqdVNB_8c0)
+  - [LangChain 101: The Complete Beginner's Guide](https://youtu.be/P3MAbZ2eMUI)
+- [Custom langchain Agent & Tools with memory. Turn any `Python function` into langchain tool with Gpt 3](https://youtu.be/NIG8lXk0ULg) by [echohive](https://www.youtube.com/@echohive)
+- [Building AI LLM Apps with LangChain (and more?) - LIVE STREAM](https://www.youtube.com/live/M-2Cj_2fzWI?feature=share) by [Nicholas Renotte](https://www.youtube.com/@NicholasRenotte)
+- [`ChatGPT` with any `YouTube` video using langchain and `chromadb`](https://youtu.be/TQZfB2bzVwU) by [echohive](https://www.youtube.com/@echohive)
+- [How to Talk to a `PDF` using LangChain and `ChatGPT`](https://youtu.be/v2i1YDtrIwk) by [Automata Learning Lab](https://www.youtube.com/@automatalearninglab)
+- [Langchain Document Loaders Part 1: Unstructured Files](https://youtu.be/O5C0wfsen98) by [Merk](https://www.youtube.com/@merksworld) 
+- [LangChain - Prompt Templates (what all the best prompt engineers use)](https://youtu.be/1aRu8b0XNOQ) by [Nick Daigler](https://www.youtube.com/@nick_daigs)
+- [LangChain. Crear aplicaciones Python impulsadas por GPT](https://youtu.be/DkW_rDndts8) by [Jesús Conde](https://www.youtube.com/@0utKast)
+- [Easiest Way to Use GPT In Your Products | LangChain Basics Tutorial](https://youtu.be/fLy0VenZyGc) by [Rachel Woods](https://www.youtube.com/@therachelwoods)
+- [`BabyAGI` + `GPT-4` Langchain Agent with Internet Access](https://youtu.be/wx1z_hs5P6E) by [tylerwhatsgood](https://www.youtube.com/@tylerwhatsgood)
+- [Learning LLM Agents. How does it actually work? LangChain, AutoGPT & OpenAI](https://youtu.be/mb_YAABSplk) by [Arnoldas Kemeklis](https://www.youtube.com/@processusAI)
+- [Get Started with LangChain in `Node.js`](https://youtu.be/Wxx1KUWJFv4) by [Developers Digest](https://www.youtube.com/@DevelopersDigest)
+- [LangChain + `OpenAI` tutorial: Building a Q&A system w/ own text data](https://youtu.be/DYOU_Z0hAwo) by [Samuel Chan](https://www.youtube.com/@SamuelChan)
+- [Langchain + `Zapier` Agent](https://youtu.be/yribLAb-pxA) by [Merk](https://www.youtube.com/@merksworld)
+- [Connecting the Internet with `ChatGPT` (LLMs) using Langchain And Answers Your Questions](https://youtu.be/9Y0TBC63yZg) by [Kamalraj M M](https://www.youtube.com/@insightbuilder)
+- [Build More Powerful LLM Applications for Business’s with LangChain (Beginners Guide)](https://youtu.be/sp3-WLKEcBg) by[ No Code Blackbox](https://www.youtube.com/@nocodeblackbox)
+- [LangFlow LLM Agent Demo for 🦜🔗LangChain](https://youtu.be/zJxDHaWt-6o) by [Cobus Greyling](https://www.youtube.com/@CobusGreylingZA)
+- [Chatbot Factory: Streamline Python Chatbot Creation with LLMs and Langchain](https://youtu.be/eYer3uzrcuM) by [Finxter](https://www.youtube.com/@CobusGreylingZA)
+- [LangChain Tutorial - ChatGPT mit eigenen Daten](https://youtu.be/0XDLyY90E2c) by [Coding Crashkurse](https://www.youtube.com/@codingcrashkurse6429)
+- [Chat with a `CSV` | LangChain Agents Tutorial (Beginners)](https://youtu.be/tjeti5vXWOU) by [GoDataProf](https://www.youtube.com/@godataprof)
+- [Introdução ao Langchain - #Cortes - Live DataHackers](https://youtu.be/fw8y5VRei5Y) by [Prof. João Gabriel Lima](https://www.youtube.com/@profjoaogabriellima)
+- [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](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)
+- [LANGCHAIN AI AUTONOMOUS AGENT WEB APP - 👶 `BABY AGI` 🤖 with EMAIL AUTOMATION using `DATABUTTON`](https://youtu.be/cvAwOGfeHgw) by [Avra](https://www.youtube.com/@Avra_b)
+- [The Future of Data Analysis: Using A.I. Models in Data Analysis (LangChain)](https://youtu.be/v_LIcVyg5dk) by [Absent Data](https://www.youtube.com/@absentdata)
+- [Memory in LangChain | Deep dive (python)](https://youtu.be/70lqvTFh_Yg) by [Eden Marco](https://www.youtube.com/@EdenMarco)
+- [9 LangChain UseCases | Beginner's Guide | 2023](https://youtu.be/zS8_qosHNMw) by [Data Science Basics](https://www.youtube.com/@datasciencebasics)
+- [Use Large Language Models in Jupyter Notebook | LangChain | Agents & Indexes](https://youtu.be/JSe11L1a_QQ) by [Abhinaw Tiwari](https://www.youtube.com/@AbhinawTiwariAT)
+- [How to Talk to Your Langchain Agent | `11 Labs` + `Whisper`](https://youtu.be/N4k459Zw2PU) by [VRSEN](https://www.youtube.com/@vrsen)
+- [LangChain Deep Dive: 5 FUN AI App Ideas To Build Quickly and Easily](https://youtu.be/mPYEPzLkeks) by [James NoCode](https://www.youtube.com/@jamesnocode)
+- [LangChain 101: Models](https://youtu.be/T6c_XsyaNSQ) by [Mckay Wrigley](https://www.youtube.com/@realmckaywrigley)
+- [LangChain with JavaScript Tutorial #1 | Setup & Using LLMs](https://youtu.be/W3AoeMrg27o) by [Leon van Zyl](https://www.youtube.com/@leonvanzyl)
+- [LangChain Overview & Tutorial for Beginners: Build Powerful AI Apps Quickly & Easily (ZERO CODE)](https://youtu.be/iI84yym473Q) by [James NoCode](https://www.youtube.com/@jamesnocode)
+- [LangChain In Action: Real-World Use Case With Step-by-Step Tutorial](https://youtu.be/UO699Szp82M) by [Rabbitmetrics](https://www.youtube.com/@rabbitmetrics)
+- [Summarizing and Querying Multiple Papers with LangChain](https://youtu.be/p_MQRWH5Y6k) by [Automata Learning Lab](https://www.youtube.com/@automatalearninglab)
+- [Using Langchain (and `Replit`) through `Tana`, ask `Google`/`Wikipedia`/`Wolfram Alpha` to fill out a table](https://youtu.be/Webau9lEzoI) by [Stian Håklev](https://www.youtube.com/@StianHaklev)
+- [Langchain PDF App (GUI) | Create a ChatGPT For Your `PDF` in Python](https://youtu.be/wUAUdEw5oxM) by [Alejandro AO - Software & Ai](https://www.youtube.com/@alejandro_ao)
+- [Auto-GPT with LangChain 🔥 | Create Your Own Personal AI Assistant](https://youtu.be/imDfPmMKEjM) by [Data Science Basics](https://www.youtube.com/@datasciencebasics)
+- [Create Your OWN Slack AI Assistant with Python & LangChain](https://youtu.be/3jFXRNn2Bu8) by [Dave Ebbelaar](https://www.youtube.com/@daveebbelaar)
+- [How to Create LOCAL Chatbots with GPT4All and LangChain [Full Guide]](https://youtu.be/4p1Fojur8Zw) by [Liam Ottley](https://www.youtube.com/@LiamOttley)
+- [Build a `Multilingual PDF` Search App with LangChain, `Cohere` and `Bubble`](https://youtu.be/hOrtuumOrv8) by [Menlo Park Lab](https://www.youtube.com/@menloparklab)
+- [Building a LangChain Agent (code-free!) Using `Bubble` and `Flowise`](https://youtu.be/jDJIIVWTZDE) by [Menlo Park Lab](https://www.youtube.com/@menloparklab)
+- [Build a LangChain-based Semantic PDF Search App with No-Code Tools Bubble and Flowise](https://youtu.be/s33v5cIeqA4) by [Menlo Park Lab](https://www.youtube.com/@menloparklab)
+- [LangChain Memory Tutorial | Building a ChatGPT Clone in Python](https://youtu.be/Cwq91cj2Pnc) by [Alejandro AO - Software & Ai](https://www.youtube.com/@alejandro_ao)
+- [ChatGPT For Your DATA | Chat with Multiple Documents Using LangChain](https://youtu.be/TeDgIDqQmzs) by [Data Science Basics](https://www.youtube.com/@datasciencebasics)
+- [`Llama Index`: Chat with Documentation using URL Loader](https://youtu.be/XJRoDEctAwA) by [Merk](https://www.youtube.com/@merksworld)
+- [Using OpenAI, LangChain, and `Gradio` to Build Custom GenAI Applications](https://youtu.be/1MsmqMg3yUc) by [David Hundley](https://www.youtube.com/@dkhundley)
+- [LangChain, Chroma DB, OpenAI Beginner Guide | ChatGPT with your PDF](https://youtu.be/FuqdVNB_8c0)
+- [Build AI chatbot with custom knowledge base using OpenAI API and GPT Index](https://youtu.be/vDZAZuaXf48) by [Irina Nik](https://www.youtube.com/@irina_nik)
+- [Build Your Own Auto-GPT Apps with LangChain (Python Tutorial)](https://youtu.be/NYSWn1ipbgg) by [Dave Ebbelaar](https://www.youtube.com/@daveebbelaar)
+- [Chat with Multiple `PDFs` | LangChain App Tutorial in Python (Free LLMs and Embeddings)](https://youtu.be/dXxQ0LR-3Hg) by [Alejandro AO - Software & Ai](https://www.youtube.com/@alejandro_ao)
+- [Chat with a `CSV` | `LangChain Agents` Tutorial (Beginners)](https://youtu.be/tjeti5vXWOU) by [Alejandro AO - Software & Ai](https://www.youtube.com/@alejandro_ao)
+- [Create Your Own ChatGPT with `PDF` Data in 5 Minutes (LangChain Tutorial)](https://youtu.be/au2WVVGUvc8) by [Liam Ottley](https://www.youtube.com/@LiamOttley)
+- [Build a Custom Chatbot with OpenAI: `GPT-Index` & LangChain | Step-by-Step Tutorial](https://youtu.be/FIDv6nc4CgU) by [Fabrikod](https://www.youtube.com/@fabrikod)
+- [`Flowise` is an open-source no-code UI visual tool to build 🦜🔗LangChain applications](https://youtu.be/CovAPtQPU0k) by [Cobus Greyling](https://www.youtube.com/@CobusGreylingZA)
+- [LangChain & GPT 4 For Data Analysis: The `Pandas` Dataframe Agent](https://youtu.be/rFQ5Kmkd4jc) by [Rabbitmetrics](https://www.youtube.com/@rabbitmetrics)
+- [`GirlfriendGPT` - AI girlfriend with LangChain](https://youtu.be/LiN3D1QZGQw) by [Toolfinder AI](https://www.youtube.com/@toolfinderai)
+- [How to build with Langchain 10x easier | ⛓️ LangFlow & `Flowise`](https://youtu.be/Ya1oGL7ZTvU) by [AI Jason](https://www.youtube.com/@AIJasonZ)
+- [Getting Started With LangChain In 20 Minutes- Build Celebrity Search Application](https://youtu.be/_FpT1cwcSLg) by [Krish Naik](https://www.youtube.com/@krishnaik06)
+- ⛓ [Vector Embeddings Tutorial – Code Your Own AI Assistant with `GPT-4 API` + LangChain + NLP](https://youtu.be/yfHHvmaMkcA?si=5uJhxoh2tvdnOXok) by [FreeCodeCamp.org](https://www.youtube.com/@freecodecamp)
+- ⛓ [Fully LOCAL `Llama 2` Q&A with LangChain](https://youtu.be/wgYctKFnQ74?si=UX1F3W-B3MqF4-K-) by [1littlecoder](https://www.youtube.com/@1littlecoder)
+- ⛓ [Fully LOCAL `Llama 2` Langchain on CPU](https://youtu.be/yhECvKMu8kM?si=IvjxwlA1c09VwHZ4) by [1littlecoder](https://www.youtube.com/@1littlecoder)
+- ⛓ [Build LangChain Audio Apps with Python in 5 Minutes](https://youtu.be/7w7ysaDz2W4?si=BvdMiyHhormr2-vr) by [AssemblyAI](https://www.youtube.com/@AssemblyAI)
+- ⛓ [`Voiceflow` & `Flowise`: Want to Beat Competition? New Tutorial with Real AI Chatbot](https://youtu.be/EZKkmeFwag0?si=-4dETYDHEstiK_bb) by [AI SIMP](https://www.youtube.com/@aisimp)
+- ⛓ [THIS Is How You Build Production-Ready AI Apps (`LangSmith` Tutorial)](https://youtu.be/tFXm5ijih98?si=lfiqpyaivxHFyI94) by [Dave Ebbelaar](https://www.youtube.com/@daveebbelaar)
+- ⛓ [Build POWERFUL LLM Bots EASILY with Your Own Data - `Embedchain` - Langchain 2.0? (Tutorial)](https://youtu.be/jE24Y_GasE8?si=0yEDZt3BK5Q-LIuF) by [WorldofAI](https://www.youtube.com/@intheworldofai)
+- ⛓ [`Code Llama` powered Gradio App for Coding: Runs on CPU](https://youtu.be/AJOhV6Ryy5o?si=ouuQT6IghYlc1NEJ) by [AI Anytime](https://www.youtube.com/@AIAnytime)
+- ⛓ [LangChain Complete Course in One Video | Develop LangChain (AI) Based Solutions for Your Business](https://youtu.be/j9mQd-MyIg8?si=_wlNT3nP2LpDKztZ) by [UBprogrammer](https://www.youtube.com/@UBprogrammer)
+- ⛓ [How to Run `LLaMA` Locally on CPU or GPU | Python & Langchain & CTransformers Guide](https://youtu.be/SvjWDX2NqiM?si=DxFml8XeGhiLTzLV) by [Code With Prince](https://www.youtube.com/@CodeWithPrince)
+- ⛓ [PyData Heidelberg #11 - TimeSeries Forecasting & LLM Langchain](https://www.youtube.com/live/Glbwb5Hxu18?si=PIEY8Raq_C9PCHuW) by [PyData](https://www.youtube.com/@PyDataTV)
+- ⛓ [Prompt Engineering in Web Development | Using LangChain and Templates with OpenAI](https://youtu.be/pK6WzlTOlYw?si=fkcDQsBG2h-DM8uQ) by [Akamai Developer
+](https://www.youtube.com/@AkamaiDeveloper)
+- ⛓ [Retrieval-Augmented Generation (RAG) using LangChain and `Pinecone` - The RAG Special Episode](https://youtu.be/J_tCD_J6w3s?si=60Mnr5VD9UED9bGG) by [Generative AI and Data Science On AWS](https://www.youtube.com/@GenerativeAIDataScienceOnAWS)
+- ⛓ [`LLAMA2 70b-chat` Multiple Documents Chatbot with Langchain & Streamlit |All OPEN SOURCE|Replicate API](https://youtu.be/vhghB81vViM?si=dszzJnArMeac7lyc) by [DataInsightEdge](https://www.youtube.com/@DataInsightEdge01)
+- ⛓ [Chatting with 44K Fashion Products: LangChain Opportunities and Pitfalls](https://youtu.be/Zudgske0F_s?si=8HSshHoEhh0PemJA) by [Rabbitmetrics](https://www.youtube.com/@rabbitmetrics)
+- ⛓ [Structured Data Extraction from `ChatGPT` with LangChain](https://youtu.be/q1lYg8JISpQ?si=0HctzOHYZvq62sve) by [MG](https://www.youtube.com/@MG_cafe)
+- ⛓ [Chat with Multiple PDFs using `Llama 2`, `Pinecone` and LangChain (Free LLMs and Embeddings)](https://youtu.be/TcJ_tVSGS4g?si=FZYnMDJyoFfL3Z2i) by [Muhammad Moin](https://www.youtube.com/@muhammadmoinfaisal)
+- ⛓ [Integrate Audio into `LangChain.js` apps in 5 Minutes](https://youtu.be/hNpUSaYZIzs?si=Gb9h7W9A8lzfvFKi) by [AssemblyAI](https://www.youtube.com/@AssemblyAI)
+- ⛓ [`ChatGPT` for your data with Local LLM](https://youtu.be/bWrjpwhHEMU?si=uM6ZZ18z9og4M90u) by [Jacob Jedryszek](https://www.youtube.com/@jj09)
+- ⛓ [Training `Chatgpt` with your personal data using langchain step by step in detail](https://youtu.be/j3xOMde2v9Y?si=179HsiMU-hEPuSs4) by [NextGen Machines](https://www.youtube.com/@MayankGupta-kb5yc)
+- ⛓ [Use ANY language in `LangSmith` with REST](https://youtu.be/7BL0GEdMmgY?si=iXfOEdBLqXF6hqRM) by [Nerding I/O](https://www.youtube.com/@nerding_io)
+- ⛓ [How to Leverage the Full Potential of LLMs for Your Business with Langchain - Leon Ruddat](https://youtu.be/vZmoEa7oWMg?si=ZhMmydq7RtkZd56Q) by [PyData](https://www.youtube.com/@PyDataTV)
+- ⛓ [`ChatCSV` App: Chat with CSV files using LangChain and `Llama 2`](https://youtu.be/PvsMg6jFs8E?si=Qzg5u5gijxj933Ya) by [Muhammad Moin](https://www.youtube.com/@muhammadmoinfaisal)
+- ⛓ [Build Chat PDF app in Python with LangChain, OpenAI, Streamlit | Full project | Learn Coding](https://www.youtube.com/watch?v=WYzFzZg4YZI) by [Jutsupoint](https://www.youtube.com/@JutsuPoint)
+- ⛓ [Build Eminem Bot App with LangChain, Streamlit, OpenAI | Full Python Project | Tutorial | AI ChatBot](https://www.youtube.com/watch?v=a2shHB4MRZ4) by [Jutsupoint](https://www.youtube.com/@JutsuPoint)
+
+
+### [Prompt Engineering and LangChain](https://www.youtube.com/watch?v=muXbPpG_ys4&list=PLEJK-H61Xlwzm5FYLDdKt_6yibO33zoMW) by [Venelin Valkov](https://www.youtube.com/@venelin_valkov)
+- [Getting Started with LangChain: Load Custom Data, Run OpenAI Models, Embeddings and `ChatGPT`](https://www.youtube.com/watch?v=muXbPpG_ys4)
+- [Loaders, Indexes & Vectorstores in LangChain: Question Answering on `PDF` files with `ChatGPT`](https://www.youtube.com/watch?v=FQnvfR8Dmr0)
+- [LangChain Models: `ChatGPT`, `Flan Alpaca`, `OpenAI Embeddings`, Prompt Templates & Streaming](https://www.youtube.com/watch?v=zy6LiK5F5-s)
+- [LangChain Chains: Use `ChatGPT` to Build Conversational Agents, Summaries and Q&A on Text With LLMs](https://www.youtube.com/watch?v=h1tJZQPcimM)
+- [Analyze Custom CSV Data with `GPT-4` using Langchain](https://www.youtube.com/watch?v=Ew3sGdX8at4)
+- [Build ChatGPT Chatbots with LangChain Memory: Understanding and Implementing Memory in Conversations](https://youtu.be/CyuUlf54wTs)
+
+
+---------------------
+⛓ icon marks a new addition [last update 2024-02-04]

docs/versioned_docs/version-0.1.x/changelog/core.mdx

@@ -0,0 +1,27 @@
+# langchain-core
+
+## 0.1.7 (Jan 5, 2024)
+
+#### Deleted
+
+No deletions.
+
+#### Deprecated
+
+- `BaseChatModel` methods `__call__`, `call_as_llm`, `predict`, `predict_messages`. Will be removed in 0.2.0. Use `BaseChatModel.invoke` instead.
+- `BaseChatModel` methods `apredict`, `apredict_messages`. Will be removed in 0.2.0. Use `BaseChatModel.ainvoke` instead.
+- `BaseLLM` methods `__call__, `predict`, `predict_messages`. Will be removed in 0.2.0. Use `BaseLLM.invoke` instead.
+- `BaseLLM` methods `apredict`, `apredict_messages`. Will be removed in 0.2.0. Use `BaseLLM.ainvoke` instead.
+
+#### Fixed
+
+- Restrict recursive URL scraping: [#15559](https://github.com/langchain-ai/langchain/pull/15559)
+
+#### Added
+
+No additions.
+
+#### Beta
+
+- Marked `langchain_core.load.load` and `langchain_core.load.loads` as beta.
+- Marked `langchain_core.beta.runnables.context.ContextGet` and `langchain_core.beta.runnables.context.ContextSet` as beta.

docs/versioned_docs/version-0.1.x/changelog/langchain.mdx

@@ -0,0 +1,36 @@
+# langchain
+
+## 0.1.0 (Jan 5, 2024)
+
+#### Deleted
+
+No deletions.
+
+#### Deprecated
+
+Deprecated classes and methods will be removed in 0.2.0
+
+| Deprecated                | Alternative                       | Reason                                         |
+|---------------------------------|-----------------------------------|------------------------------------------------|
+| ChatVectorDBChain               | ConversationalRetrievalChain      | More general to all retrievers                 |
+| create_ernie_fn_chain           | create_ernie_fn_runnable          | Use LCEL under the hood                        |
+| created_structured_output_chain | create_structured_output_runnable | Use LCEL under the hood                        |
+| NatBotChain                     |                                   | Not used                                       |
+| create_openai_fn_chain          | create_openai_fn_runnable         | Use LCEL under the hood                        |
+| create_structured_output_chain  | create_structured_output_runnable | Use LCEL under the hood                        |
+| load_query_constructor_chain    | load_query_constructor_runnable   | Use LCEL under the hood                        |
+| VectorDBQA                      | RetrievalQA                       | More general to all retrievers                 |
+| Sequential Chain                | LCEL                              | Obviated by LCEL                               |
+| SimpleSequentialChain           | LCEL                              | Obviated by LCEL                               |
+| TransformChain                  | LCEL/RunnableLambda               | Obviated by LCEL                               |
+| create_tagging_chain            | create_structured_output_runnable | Use LCEL under the hood                        |
+| ChatAgent                       | create_react_agent                | Use LCEL builder over a class                  |
+| ConversationalAgent             | create_react_agent                | Use LCEL builder over a class                  |
+| ConversationalChatAgent         | create_json_chat_agent            | Use LCEL builder over a class                  |
+| initialize_agent                | Individual create agent methods   | Individual create agent methods are more clear |
+| ZeroShotAgent                   | create_react_agent                | Use LCEL builder over a class                  |
+| OpenAIFunctionsAgent            | create_openai_functions_agent     | Use LCEL builder over a class                  |
+| OpenAIMultiFunctionsAgent       | create_openai_tools_agent         | Use LCEL builder over a class                  |
+| SelfAskWithSearchAgent          | create_self_ask_with_search       | Use LCEL builder over a class                  |
+| StructuredChatAgent             | create_structured_chat_agent      | Use LCEL builder over a class                  |
+| XMLAgent                        | create_xml_agent                  | Use LCEL builder over a class                  |

docs/versioned_docs/version-0.1.x/contributing/code.mdx

@@ -0,0 +1,250 @@
+---
+sidebar_position: 1
+---
+# Contribute Code
+
+To contribute to this project, please follow the ["fork and pull request"](https://docs.github.com/en/get-started/quickstart/contributing-to-projects) workflow.
+Please do not try to push directly to this repo unless you are a maintainer.
+
+Please follow the checked-in pull request template when opening pull requests. Note related issues and tag relevant
+maintainers.
+
+Pull requests cannot land without passing the formatting, linting, and testing checks first. See [Testing](#testing) and
+[Formatting and Linting](#formatting-and-linting) for how to run these checks locally.
+
+It's essential that we maintain great documentation and testing. If you:
+- Fix a bug
+  - Add a relevant unit or integration test when possible. These live in `tests/unit_tests` and `tests/integration_tests`.
+- Make an improvement
+  - Update any affected example notebooks and documentation. These live in `docs`.
+  - Update unit and integration tests when relevant.
+- Add a feature
+  - Add a demo notebook in `docs/docs/`.
+  - Add unit and integration tests.
+
+We are a small, progress-oriented team. If there's something you'd like to add or change, opening a pull request is the
+best way to get our attention.
+
+## 🚀 Quick Start
+
+This quick start guide explains how to run the repository locally.
+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
+
+This project utilizes [Poetry](https://python-poetry.org/) v1.7.1+ as a dependency manager.
+
+❗Note: *Before installing Poetry*, if you use `Conda`, create and activate a new Conda env (e.g. `conda create -n langchain python=3.9`)
+
+Install Poetry: **[documentation on how to install it](https://python-poetry.org/docs/#installation)**.
+
+❗Note: If you use `Conda` or `Pyenv` as your environment/package manager, after installing Poetry,
+tell Poetry to use the virtualenv python environment (`poetry config virtualenvs.prefer-active-python true`)
+
+### Different packages
+
+This repository contains multiple packages:
+- `langchain-core`: Base interfaces for key abstractions as well as logic for combining them in chains (LangChain Expression Language).
+- `langchain-community`: Third-party integrations of various components.
+- `langchain`: Chains, agents, and retrieval logic that makes up the cognitive architecture of your applications.
+- `langchain-experimental`: Components and chains that are experimental, either in the sense that the techniques are novel and still being tested, or they require giving the LLM more access than would be possible in most production systems.
+- Partner integrations: Partner packages in `libs/partners` that are independently version controlled.
+
+Each of these has its own development environment. Docs are run from the top-level makefile, but development
+is split across separate test & release flows.
+
+For this quickstart, start with langchain-community:
+
+```bash
+cd libs/community
+```
+
+### Local Development Dependencies
+
+Install langchain-community development requirements (for running langchain, running examples, linting, formatting, tests, and coverage):
+
+```bash
+poetry install --with lint,typing,test,test_integration
+```
+
+Then verify dependency installation:
+
+```bash
+make test
+```
+
+If during installation you receive a `WheelFileValidationError` for `debugpy`, please make sure you are running
+Poetry v1.6.1+. This bug was present in older versions of Poetry (e.g. 1.4.1) and has been resolved in newer releases.
+If you are still seeing this bug on v1.6.1+, you may also try disabling "modern installation"
+(`poetry config installer.modern-installation false`) and re-installing requirements.
+See [this `debugpy` issue](https://github.com/microsoft/debugpy/issues/1246) for more details.
+
+### Testing
+
+_In `langchain`, `langchain-community`, and `langchain-experimental`, some test dependencies are optional; see section about optional dependencies_.
+
+Unit tests cover modular logic that does not require calls to outside APIs.
+If you add new logic, please add a unit test.
+
+To run unit tests:
+
+```bash
+make test
+```
+
+To run unit tests in Docker:
+
+```bash
+make docker_tests
+```
+
+There are also [integration tests and code-coverage](./testing) available.
+
+### Only develop langchain_core or langchain_experimental
+
+If you are only developing `langchain_core` or `langchain_experimental`, you can simply install the dependencies for the respective projects and run tests:
+
+```bash
+cd libs/core
+poetry install --with test
+make test
+```
+
+Or:
+
+```bash
+cd libs/experimental
+poetry install --with test
+make test
+```
+
+### Formatting and Linting
+
+Run these locally before submitting a PR; the CI system will check also.
+
+#### Code Formatting
+
+Formatting for this project is done via [ruff](https://docs.astral.sh/ruff/rules/).
+
+To run formatting for docs, cookbook and templates:
+
+```bash
+make format
+```
+
+To run formatting for a library, run the same command from the relevant library directory:
+
+```bash
+cd libs/{LIBRARY}
+make format
+```
+
+Additionally, you can run the formatter only on the files that have been modified in your current branch as compared to the master branch using the format_diff command:
+
+```bash
+make format_diff
+```
+
+This is especially useful when you have made changes to a subset of the project and want to ensure your changes are properly formatted without affecting the rest of the codebase.
+
+#### Linting
+
+Linting for this project is done via a combination of [ruff](https://docs.astral.sh/ruff/rules/) and [mypy](http://mypy-lang.org/).
+
+To run linting for docs, cookbook and templates:
+
+```bash
+make lint
+```
+
+To run linting for a library, run the same command from the relevant library directory:
+
+```bash
+cd libs/{LIBRARY}
+make lint
+```
+
+In addition, you can run the linter only on the files that have been modified in your current branch as compared to the master branch using the lint_diff command:
+
+```bash
+make lint_diff
+```
+
+This can be very helpful when you've made changes to only certain parts of the project and want to ensure your changes meet the linting standards without having to check the entire codebase.
+
+We recognize linting can be annoying - if you do not want to do it, please contact a project maintainer, and they can help you with it. We do not want this to be a blocker for good code getting contributed.
+
+#### Spellcheck
+
+Spellchecking for this project is done via [codespell](https://github.com/codespell-project/codespell).
+Note that `codespell` finds common typos, so it could have false-positive (correctly spelled but rarely used) and false-negatives (not finding misspelled) words.
+
+To check spelling for this project:
+
+```bash
+make spell_check
+```
+
+To fix spelling in place:
+
+```bash
+make spell_fix
+```
+
+If codespell is incorrectly flagging a word, you can skip spellcheck for that word by adding it to the codespell config in the `pyproject.toml` file.
+
+```python
+[tool.codespell]
+...
+# Add here:
+ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure'
+```
+
+## Working with Optional Dependencies
+
+`langchain`, `langchain-community`, and `langchain-experimental` rely on optional dependencies to keep these packages lightweight.
+
+`langchain-core` and partner packages **do not use** optional dependencies in this way.
+
+You only need to add a new dependency if a **unit test** relies on the package.
+If your package is only required for **integration tests**, then you can skip these
+steps and leave all pyproject.toml and poetry.lock files alone.
+
+If you're adding a new dependency to Langchain, assume that it will be an optional dependency, and
+that most users won't have it installed.
+
+Users who do not have the dependency installed should be able to **import** your code without
+any side effects (no warnings, no errors, no exceptions).
+
+To introduce the dependency to the pyproject.toml file correctly, please do the following:
+
+1. Add the dependency to the main group as an optional dependency
+  ```bash
+  poetry add --optional [package_name]
+  ```
+2. Open pyproject.toml and add the dependency to the `extended_testing` extra
+3. Relock the poetry file to update the extra.
+  ```bash
+  poetry lock --no-update
+  ```
+4. Add a unit test that the very least attempts to import the new code. Ideally, the unit
+test makes use of lightweight fixtures to test the logic of the code.
+5. Please use the `@pytest.mark.requires(package_name)` decorator for any tests that require the dependency.
+
+## Adding a Jupyter Notebook
+
+If you are adding a Jupyter Notebook example, you'll want to install the optional `dev` dependencies.
+
+To install dev dependencies:
+
+```bash
+poetry install --with dev
+```
+
+Launch a notebook:
+
+```bash
+poetry run jupyter notebook
+```
+
+When you run `poetry install`, the `langchain` package is installed as editable in the virtualenv, so your new logic can be imported into the notebook.

docs/versioned_docs/version-0.1.x/contributing/documentation.mdx

@@ -0,0 +1,174 @@
+---
+sidebar_position: 3
+---
+# Contribute Documentation
+
+LangChain documentation consists of two components:
+
+1. Main Documentation: Hosted at [python.langchain.com](https://python.langchain.com/),
+this comprehensive resource serves as the primary user-facing documentation.
+It covers a wide array of topics, including tutorials, use cases, integrations,
+and more, offering extensive guidance on building with LangChain.
+The content for this documentation lives in the `/docs` directory of the monorepo.
+2. In-code Documentation: This is documentation of the codebase itself, which is also
+used to generate the externally facing [API Reference](https://api.python.langchain.com/en/latest/langchain_api_reference.html).
+The content for the API reference is autogenerated by scanning the docstrings in the codebase. For this reason we ask that
+developers document their code well.
+
+The main documentation is built using [Quarto](https://quarto.org) and [Docusaurus 2](https://docusaurus.io/).
+
+The `API Reference` is largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/)
+from the code and is hosted by [Read the Docs](https://readthedocs.org/).
+
+We appreciate all contributions to the documentation, whether it be fixing a typo,
+adding a new tutorial or example and whether it be in the main documentation or the API Reference.
+
+Similar to linting, we recognize documentation can be annoying. If you do not want
+to do it, please contact a project maintainer, and they can help you with it. We do not want this to be a blocker for good code getting contributed.
+
+## 📜 Main Documentation
+
+The content for the main documentation is located in the `/docs` directory of the monorepo.
+
+The documentation is written using a combination of ipython notebooks (`.ipynb` files)
+and markdown (`.mdx` files). The notebooks are converted to markdown
+using [Quarto](https://quarto.org) and then built using [Docusaurus 2](https://docusaurus.io/).
+
+Feel free to make contributions to the main documentation! 🥰
+
+After modifying the documentation:
+
+1. Run the linting and formatting commands (see below) to ensure that the documentation is well-formatted and free of errors.
+2. Optionally build the documentation locally to verify that the changes look good.
+3. Make a pull request with the changes.
+4. You can preview and verify that the changes are what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page. This will take you to a preview of the documentation changes.
+
+## ⚒️ Linting and Building Documentation Locally
+
+After writing up the documentation, you may want to lint and build the documentation
+locally to ensure that it looks good and is free of errors.
+
+If you're unable to build it locally that's okay as well, as you will be able to
+see a preview of the documentation on the pull request page.
+
+### Install dependencies
+
+- [Quarto](https://quarto.org) - package that converts Jupyter notebooks (`.ipynb` files) into mdx files for serving in Docusaurus. [Download link](https://quarto.org/docs/download/).
+
+From the **monorepo root**, run the following command to install the dependencies:
+
+```bash
+poetry install --with lint,docs --no-root
+````
+
+### Building
+
+The code that builds the documentation is located in the `/docs` directory of the monorepo.
+
+In the following commands, the prefix `api_` indicates that those are operations for the API Reference.
+
+Before building the documentation, it is always a good idea to clean the build directory:
+
+```bash
+make docs_clean
+make api_docs_clean
+```
+
+Next, you can build the documentation as outlined below:
+
+```bash
+make docs_build
+make api_docs_build
+```
+
+Finally, run the link checker to ensure all links are valid:
+
+```bash
+make docs_linkcheck
+make api_docs_linkcheck
+```
+
+### Linting and Formatting
+
+The Main Documentation is linted from the **monorepo root**. To lint the main documentation, run the following from there:
+
+```bash
+make lint
+```
+
+If you have formatting-related errors, you can fix them automatically with:
+
+```bash
+make format
+```
+
+## ⌨️ In-code Documentation
+
+The in-code documentation is largely autogenerated by [sphinx](https://www.sphinx-doc.org/en/master/) from the code and is hosted by [Read the Docs](https://readthedocs.org/).
+
+For the API reference to be useful, the codebase must be well-documented. This means that all functions, classes, and methods should have a docstring that explains what they do, what the arguments are, and what the return value is. This is a good practice in general, but it is especially important for LangChain because the API reference is the primary resource for developers to understand how to use the codebase.
+
+We generally follow the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings) for docstrings.
+
+Here is an example of a well-documented function:
+
+```python
+
+def my_function(arg1: int, arg2: str) -> float:
+    """This is a short description of the function. (It should be a single sentence.)
+
+    This is a longer description of the function. It should explain what
+    the function does, what the arguments are, and what the return value is.
+    It should wrap at 88 characters.
+
+    Examples:
+        This is a section for examples of how to use the function.
+
+        .. code-block:: python
+
+            my_function(1, "hello")
+
+    Args:
+        arg1: This is a description of arg1. We do not need to specify the type since
+            it is already specified in the function signature.
+        arg2: This is a description of arg2.
+
+    Returns:
+        This is a description of the return value.
+    """
+    return 3.14
+```
+
+### Linting and Formatting
+
+The in-code documentation is linted from the directories belonging to the packages
+being documented.
+
+For example, if you're working on the `langchain-community` package, you would change
+the working directory to the `langchain-community` directory:
+
+```bash
+cd [root]/libs/langchain-community
+```
+
+Set up a virtual environment for the package if you haven't done so already.
+
+Install the dependencies for the package.
+
+```bash
+poetry install --with lint
+```
+
+Then you can run the following commands to lint and format the in-code documentation:
+
+```bash
+make format
+make lint
+```
+
+## Verify Documentation Changes
+
+After pushing documentation changes to the repository, you can preview and verify that the changes are
+what you wanted by clicking the `View deployment` or `Visit Preview` buttons on the pull request `Conversation` page.
+This will take you to a preview of the documentation changes.
+This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel).

docs/versioned_docs/version-0.1.x/contributing/faq.mdx

@@ -0,0 +1,26 @@
+---
+sidebar_position: 6
+sidebar_label: FAQ
+---
+# Frequently Asked Questions
+
+## Pull Requests (PRs)
+
+### How do I allow maintainers to edit my PR?
+
+When you submit a pull request, there may be additional changes
+necessary before merging it. Oftentimes, it is more efficient for the
+maintainers to make these changes themselves before merging, rather than asking you
+to do so in code review.
+
+By default, most pull requests will have a 
+`✅ Maintainers are allowed to edit this pull request.`
+badge in the right-hand sidebar.
+
+If you do not see this badge, you may have this setting off for the fork you are
+pull-requesting from. See [this Github docs page](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/allowing-changes-to-a-pull-request-branch-created-from-a-fork)
+for more information.
+
+Notably, Github doesn't allow this setting to be enabled for forks in **organizations** ([issue](https://github.com/orgs/community/discussions/5634)).
+If you are working in an organization, we recommend submitting your PR from a personal
+fork in order to enable this setting.