docs: LangGraph

Signed-off-by: Anush008 <anushshetty90@gmail.com>

qdrant-landing/content/documentation/frameworks/_index.md

@@ -22,6 +22,7 @@ partition: build
 | [Langchain](/documentation/frameworks/langchain/)             | Python framework for building context-aware, reasoning applications using LLMs.                                      |
 | [Langchain-Go](/documentation/frameworks/langchain-go/)       | Go framework for building context-aware, reasoning applications using LLMs.                                          |
 | [Langchain4j](/documentation/frameworks/langchain4j/)         | Java framework for building context-aware, reasoning applications using LLMs.                                        |
+| [LangGraph](/documentation/frameworks/langgraph/)             | Python, Javascript libraries for building stateful, multi-actor applications.                                        |
 | [LlamaIndex](/documentation/frameworks/llama-index/)          | A data framework for building LLM applications with modular integrations.                                            |
 | [Mem0](/documentation/frameworks/mem0/)                       | Self-improving memory layer for LLM applications, enabling personalized AI experiences.                              |
 | [MemGPT](/documentation/frameworks/memgpt/)                   | System to build LLM agents with long term memory & custom tools                                                      |
@@ -33,5 +34,6 @@ partition: build
 | [Spring AI](/documentation/frameworks/spring-ai/)             | Java AI framework for building with Spring design principles such as portability and modular design.                 |
 | [Swarm](/documentation/frameworks/swarm/)                     | Python framework for managing multiple AI agents that can work together.                                             |
 | [Sycamore](/documentation/frameworks/sycamore/)               | Document processing engine for ETL, RAG, LLM-based applications, and analytics on unstructured data.                 |
+| [Testcontainers](/documentation/frameworks/testcontainers/)   | Framework for providing throwaway, lightweight instances of systems for testing                                      |
 | [txtai](/documentation/frameworks/txtai/)                     | Python library for semantic search, LLM orchestration and language model workflows.                                  |
 | [Vanna AI](/documentation/frameworks/vanna-ai/)               | Python RAG framework for SQL generation and querying.                                                                |

qdrant-landing/content/documentation/frameworks/langgraph.md

@@ -0,0 +1,104 @@
+---
+title: LangGraph
+aliases: [ ../integrations/autogen/ ]
+---
+
+# LangGraph
+
+[LangGraph](https://github.com/langchain-ai/langgraph) is a library for building stateful, multi-actor applications, ideal for creating agentic workflows. It provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents.
+
+You can define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. Additionally, LangGraph includes built-in persistence, enabling advanced human-in-the-loop and memory features.
+
+LangGraph works seamlessly with all the components of LangChain. This means we can utilize Qdrant's [Langchain integration](/documentation/frameworks/langchain/) to create retrieval nodes in LangGraph, available in both Python and Javascript!
+
+## Usage
+
+- Install the required dependencies
+
+```python
+$ pip install langgraph langchain_community langchain_qdrant
+```
+
+- Create a retriever tool to add to the LangGraph workflow.
+
+```python
+
+from langchain.tools.retriever import create_retriever_tool
+from langchain_community.embeddings import FastEmbedEmbeddings
+
+from langchain_qdrant import FastEmbedSparse, QdrantVectorStore, RetrievalMode
+
+# We'll set up Qdrant to retrieve documents using Hybrid search.
+# Learn more at https://qdrant.tech/articles/hybrid-search/
+retriever = QdrantVectorStore.from_texts(
+    url="http://localhost:6333/",
+    collection_name="langgraph-collection",
+    embedding=FastEmbedEmbeddings(model_name="BAAI/bge-small-en-v1.5"),
+    sparse_embedding=FastEmbedSparse(model_name="Qdrant/bm25"),
+    retrieval_mode=RetrievalMode.HYBRID,
+    texts=["<SOME_KNOWLEDGE_TEXT>", "<SOME_OTHER_TEXT>", ...]
+).as_retriever()
+
+retriever_tool = create_retriever_tool(
+    retriever,
+    "retrieve_my_texts",
+    "Retrieve texts stored in the Qdrant collection",
+)
+```
+
+```typescript
+import { QdrantVectorStore } from "@langchain/qdrant";
+import { OpenAIEmbeddings } from "@langchain/openai";
+import { createRetrieverTool } from "langchain/tools/retriever";
+
+const vectorStore = await QdrantVectorStore.fromTexts(
+    ["<SOME_KNOWLEDGE_TEXT>", "<SOME_OTHER_TEXT>"],
+    new OpenAIEmbeddings(),
+    {
+        url: "http://localhost:6333/",
+        collectionName: "goldel_escher_bach",
+    }
+);
+
+const retriever = vectorStore.asRetriever();
+
+const tool = createRetrieverTool(
+  retriever,
+  {
+    name: "retrieve_my_texts",
+    description:
+      "Retrieve texts stored in the Qdrant collection",
+  },
+);
+```
+
+- Add the retriever tool as a node in LangGraph
+
+```python
+from langgraph.graph import StateGraph
+from langgraph.prebuilt import ToolNode
+
+workflow = StateGraph()
+
+# Define other the nodes which we'll cycle between.
+workflow.add_node("retrieve_qdrant", ToolNode([retriever_tool]))
+
+graph = workflow.compile()
+```
+
+```typescript
+import { StateGraph } from "@langchain/langgraph";
+import { ToolNode } from "@langchain/langgraph/prebuilt";
+
+// Define the graph
+const workflow = new StateGraph(GraphState)
+  // Define the nodes which we'll cycle between.
+  .addNode("retrieve", new ToolNode([tool]));
+
+const graph = workflow.compile();
+```
+
+## Further Reading
+
+- [LangGraph Documentation](https://langchain-ai.github.io/langgraph/)
+- [LangGraph End-to-End Guides](https://langchain-ai.github.io/langgraph/tutorials/)

qdrant-landing/content/documentation/frameworks/testcontainers.md

@@ -1,6 +1,6 @@
 ---
 title: Testcontainers
-aliases: [ ../frameworks/testcontainers/ ]
+aliases: [ ../infrastructure/testcontainers/ ]
 ---
 
 # Testcontainers

qdrant-landing/content/documentation/infrastructure/_index.md

@@ -1,11 +0,0 @@
----
-title: Infrastructure
-weight: 21
-partition: build
----
-
-## Infrastructure Integrations
-
-| Integration                         | Description                                                                                 |
-| ----------------------------------- | ------------------------------------------------------------------------------------------- |
-| [Testcontainers](/documentation/infrastructure/testcontainers/) | Open source framework for providing throwaway, lightweight instances of systems for testing |