oss(contributing): refinements (#2983)

Author: mdrxy

src/oss/contributing/code.mdx

@@ -3,7 +3,7 @@ title: Contributing to code
 sidebarTitle: Code
 ---
 
-Code contributions are always welcome! Whether you're fixing bugs, adding features, or improving performance, your contributions help deliver a better developer experience for thousands of developers.
+Code contributions are welcome! Whether you're fixing bugs, adding features, or improving performance, your contributions help deliver a better developer experience for thousands of developers.
 
 ## Getting started
 
@@ -384,7 +384,7 @@ Once you've reviewed the [contribution guidelines](#contribution-guidelines), fi
         <AccordionGroup>
             <Accordion title="Core packages" defaultOpen>
                 - **[`deepagents`](https://github.com/langchain-ai/deepagents/tree/main/libs/deepagents#readme)** (located in `libs/deepagents/`): Core framework for building deep agents with planning, filesystem, and subagent capabilities
-                - **[`deepagents-cli`](https://github.com/langchain-ai/deepagents/tree/main/libs/deepagents-cli#readme)** (located in `libs/deepagents-cli/`): Interactive terminal interface with conversation resume, web search, and sandboxes
+                - **[`deepagents-cli`](https://github.com/langchain-ai/deepagents/tree/main/libs/cli#readme)** (located in `libs/cli/`): Interactive terminal interface with conversation resume, web search, and sandboxes
             </Accordion>
 
             <Accordion title="Integration packages">

src/oss/contributing/implement-langchain.mdx

@@ -14,7 +14,12 @@ Your integration package will typically implement a subclass of at least one of
         Chat models are subclasses of the @[`BaseChatModel`] class. They implement methods for generating chat completions, handling message formatting, and managing model parameters.
 
         <Warning>
-            The chat model integration guide is currently WIP. In the meantime, read the [chat model conceptual guide](/oss/langchain/models) for details on how LangChain chat models function.
+            :::python
+            The chat model integration guide is currently WIP. In the meantime, read the [chat model conceptual guide](/oss/langchain/models) for details on how LangChain chat models function. You may also refer to existing integrations in the [LangChain repo](https://github.com/langchain-ai/langchain/tree/master/libs/partners)
+            :::
+            :::js
+            The chat model integration guide is currently WIP. In the meantime, read the [chat model conceptual guide](/oss/langchain/models) for details on how LangChain chat models function. You may also refer to existing integrations in the [LangChain repo](https://github.com/langchain-ai/langchainjs/tree/main/libs/providers)
+            :::
         </Warning>
     </Tab>
     <Tab title="Tools">

src/oss/contributing/integrations-langchain.mdx

@@ -5,12 +5,12 @@ sidebarTitle: Guide
 
 **Integrations are a core component of LangChain.**
 
-LangChain provides standard interfaces for several different components (language models, vector stores, etc) that are crucial when building LLM applications. Contributing an integration helps expand LangChain's ecosystem and makes your service discoverable to millions of developers.
+LangChain provides standard interfaces for several different components (language models, vector stores, etc) that are crucial when building LLM applications. Implementing a new integration helps expand LangChain's ecosystem and makes your service discoverable to millions of developers.
 
-## Why contribute an integration to LangChain?
+## Why implement a LangChain integration?
 
 <Card title="Discoverability" icon="search">
-    LangChain is the most used framework for building LLM applications, with over 20 million monthly downloads.
+    LangChain is the most used framework for building LLM applications, with over 200 million monthly downloads.
 </Card>
 
 <Card title="Interoperability" icon="refresh">
@@ -26,6 +26,7 @@ LangChain provides standard interfaces for several different components (languag
 While any component can be integrated into LangChain, there are specific types of integrations we encourage more:
 
 **Integrate these ✅**:
+
 - [**Chat Models**](/oss/integrations/chat): Most actively used component type
 - [**Tools/Toolkits**](/oss/integrations/tools): Enable agent capabilities
 - [**Retrievers**](/oss/integrations/retrievers): Core to RAG applications
@@ -41,6 +42,7 @@ Be aware that we feature third-party sandbox integrations only when:
 </Accordion>
 
 **Not these ❌**:
+
 - **LLMs (Text-Completion Models)**: Deprecated in favor of [Chat Models](/oss/integrations/chat)
 - [**Document Loaders**](/oss/integrations/document_loaders): High maintenance burden
 - [**Key-Value Stores**](/oss/integrations/stores): Limited usage
@@ -55,10 +57,6 @@ Be aware that we feature third-party sandbox integrations only when:
 ## How to contribute an integration
 
 <Steps>
-    <Step title="Confirm eligibility">
-        Verify that your integration is in the list of [encouraged components](#components-to-integrate) we are currently accepting.
-    </Step>
-
     <Step title="Implement your package">
         <Card title="How to implement a LangChain integration" icon="link" href="/oss/contributing/implement-langchain" arrow />
     </Step>
@@ -81,14 +79,12 @@ Be aware that we feature third-party sandbox integrations only when:
 
             - [Chat models](https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/chat/TEMPLATE.mdx)
             - [Tools and toolkits](https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/tools/TEMPLATE.mdx)
-            - [Retrievers](https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/retrievers/TEMPLATE.mdx)
+            - Retrievers - Coming soon
             - Text splitters - Coming soon
             - Embedding models - Coming soon
             - [Vector stores](https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/vectorstores/TEMPLATE.mdx)
             - Document loaders - Coming soon
             - Key-value stores - Coming soon
-
-            For reference docs, please open an issue on the repo so that a maintainer can add them.
         </Accordion>
     </Step>
 

src/oss/contributing/overview.mdx

@@ -40,7 +40,7 @@ LangChain has helped form the largest developer community in generative AI, and
             </Step>
         </Steps>
 
-        If you are adding an issue, please try to keep it focused on a single topic. If two issues are related, or blocking, please [link them](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) rather than combining them. For example,
+        If you are adding an issue, please try to keep it focused on a single topic. If two issues are related, or blocking, please [link them](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword) rather than combining them. For example:
 
         ```text
         This issue is blocked by #123 and related to #456.
@@ -70,12 +70,7 @@ LangChain has helped form the largest developer community in generative AI, and
                 :::
             </Step>
             <Step title="Discuss">
-                :::python
-                If no requests exist, start a new discussion under the [relevant category](https://forum.langchain.com/c/help/langchain/14) so that project maintainers and the community can provide feedback.
-                :::
-                :::js
-                If no requests exist, start a new discussion under the [relevant category](https://forum.langchain.com/c/help/langchain/13) so that project maintainers and the community can provide feedback.
-                :::
+                If no requests exist, start a new discussion under the [relevant category](https://forum.langchain.com/c/oss-product-help-lc-and-lg/16) so that project maintainers and the community can provide feedback.
             </Step>
             <Step title="Describe">
                 Be sure to describe the use case and why it would be valuable to others. If possible, provide examples or mockups where applicable. Outline test cases that should pass.
@@ -84,7 +79,7 @@ LangChain has helped form the largest developer community in generative AI, and
     </Accordion>
 
     <Accordion title="Improve documentation" icon="book">
-        Documentation improvements are always welcome! We strive to keep our docs clear and comprehensive, and your perspective can make a big difference.
+        Documentation improvements are welcome! We strive to keep our docs clear and comprehensive, and your perspective can make a big difference.
 
         <Card title="How to propose changes to the documentation" href="/oss/contributing/documentation" arrow>Guide</Card>
     </Accordion>
@@ -100,16 +95,16 @@ LangChain has helped form the largest developer community in generative AI, and
 
         :::python
         <Columns cols={3}>
-            <Card title="LangChain" icon="link" href="https://github.com/langchain-ai/langchain/labels">Labels</Card>
-            <Card title="LangGraph" icon="topology-ring" href="https://github.com/langchain-ai/langgraph/labels">Labels</Card>
-            <Card title="Deep Agents" icon="robot" href="https://github.com/langchain-ai/deepagents/labels">Labels</Card>
+            <Card title="LangChain" icon="link" href="https://github.com/langchain-ai/langchain/labels?q=help+wanted">Labels</Card>
+            <Card title="LangGraph" icon="topology-ring" href="https://github.com/langchain-ai/langgraph/labels?q=help+wanted">Labels</Card>
+            <Card title="Deep Agents" icon="robot" href="https://github.com/langchain-ai/deepagents/labels?q=help+wanted">Labels</Card>
         </Columns>
         :::
         :::js
         <Columns cols={3}>
-            <Card title="LangChain" icon="link" href="https://github.com/langchain-ai/langchainjs/labels">Labels</Card>
-            <Card title="LangGraph" icon="topology-ring" href="https://github.com/langchain-ai/langgraphjs/labels">Labels</Card>
-            <Card title="Deep Agents" icon="robot" href="https://github.com/langchain-ai/deepagentsjs/labels">Labels</Card>
+            <Card title="LangChain" icon="link" href="https://github.com/langchain-ai/deepagents/labels?q=help+wanted">Labels</Card>
+            <Card title="LangGraph" icon="topology-ring" href="https://github.com/langchain-ai/langgraphjs/labels?q=help+wanted">Labels</Card>
+            <Card title="Deep Agents" icon="robot" href="https://github.com/langchain-ai/deepagentsjs/labels?q=help+wanted">Labels</Card>
         </Columns>
         :::
     </Accordion>
@@ -123,10 +118,14 @@ LangChain has helped form the largest developer community in generative AI, and
 
 Generative AI can be a useful tool for contributors, but like any tool should be used with critical thinking and good judgement.
 
-We encourage contributors to use AI tools efficiently where they help. However, AI assistance must be paired with meaningful human intervention, judgement, and contextual understanding. **If the human effort required to create a pull request is less than the effort required for maintainers to review it, that contribution should not be submitted.**
+AI assistance must be paired with meaningful human intervention, judgement, and contextual understanding. **If the human effort required to create a pull request is less than the effort required for maintainers to review it, that contribution should not be submitted.**
+
+We struggle when contributors' entire work (code changes, documentation updates, pull request descriptions) are LLM-generated. These drive-by contributions often mean well but miss the mark in terms of contextual relevance, accuracy, and quality. Mass automated contributions represent a denial-of-service attack on our human effort.
 
-We struggle when contributors' entire work (code changes, documentation updates, pull request descriptions) are LLM-generated. These drive-by contributions often mean well but miss the mark in terms of contextual relevance, accuracy, and quality. Mass automated contributions like these represent a denial-of-service attack on our human effort.
+The following guidelines must be met for Pull Requests that include AI-generated content:
 
-**We will close pull requests and issues that appear to be low-effort, AI-generated spam.**
+* The Pull Request must fill in the repository's pull request template.
+* The Pull Request must identify itself as AI generated, including the name of the agent used.
+* The Pull Request must link to a issue or discussion where a solution has been approved by a maintainer.
 
-With great tools comes great responsibility.
+The maintainer reserves the right to close PRs without comment if the above are not met. **We will close pull requests and issues that appear to be low-effort, AI-generated spam.**

src/oss/contributing/publish-langchain.mdx

@@ -72,9 +72,7 @@ Depending on the type of integration you have built, you will need to create dif
 <CardGroup>
     <Card title="Chat models" icon="message" href="https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/chat/TEMPLATE.mdx" arrow/>
     <Card title="Tools/toolkits" icon="tool" href="https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/tools/TEMPLATE.mdx" arrow/>
-    <Card title="Retrievers" icon="search" href="https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/retrievers/TEMPLATE.mdx" arrow/>
     <Card title="Vector stores" icon="database" href="https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/vectorstores/TEMPLATE.mdx" arrow/>
-    <Card title="Embedding models" icon="stack-2" href="https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/text_embedding/TEMPLATE.mdx" arrow/>
 </CardGroup>
 
 <Tip>

src/oss/deepagents/cli/overview.mdx

@@ -96,12 +96,12 @@ The Deep Agents CLI has the following built-in capabilities:
     <Step title="Install and run the CLI" icon="terminal">
         <CodeGroup>
             ```bash Quick install (recommended)
-            curl -LsSf https://raw.githubusercontent.com/langchain-ai/deepagents/main/scripts/install.sh | bash
+            curl -LsSf https://raw.githubusercontent.com/langchain-ai/deepagents/refs/heads/main/libs/cli/scripts/install.sh | bash
             ```
 
             ```bash Quick install with extra model providers
             # (OpenAI is included by default)
-            DEEPAGENTS_EXTRAS="anthropic,groq" curl -LsSf https://raw.githubusercontent.com/langchain-ai/deepagents/main/scripts/install.sh | bash
+            DEEPAGENTS_EXTRAS="anthropic,groq" curl -LsSf https://raw.githubusercontent.com/langchain-ai/deepagents/refs/heads/main/libs/cli/scripts/install.sh | bash
             ```
 
             ```bash Install globally with uv

src/oss/deepagents/cli/providers.mdx

@@ -16,7 +16,7 @@ The CLI integrates automatically with the [following model providers](#provider-
 
     ```bash
     # Quick install with chosen providers (OpenAI included automatically)
-    DEEPAGENTS_EXTRAS="anthropic,groq" curl -LsSf https://raw.githubusercontent.com/langchain-ai/deepagents/main/scripts/install.sh | bash
+    DEEPAGENTS_EXTRAS="anthropic,groq" curl -LsSf https://raw.githubusercontent.com/langchain-ai/deepagents/refs/heads/main/libs/cli/scripts/install.sh | bash
 
     # Or install directly with uv
     uv tool install 'deepagents-cli[anthropic,groq]'