feat: langgraph short-term memory agent

Author: MRGuziX

README.md

@@ -1,31 +1,45 @@
 <div style="text-align: center;">
 
 ![Agentic Starter Kits](/images/ask_logo.png)
+
 # Agentic Starter Kits
 
 </div>
 
 ## Purpose
-Production-ready agent templates to build and deploy LLM-powered agents. Run locally (e.g. with Ollama/Llama Stack) or deploy to Red Hat OpenShift. Each agent has step-by-step docs.
+
+Production-ready agent templates to build and deploy LLM-powered agents. Run locally (e.g. with Ollama/Llama Stack) or
+deploy to Red Hat OpenShift. Each agent has step-by-step docs.
 
 ## Agents
+
 Choose an agent and follow its README for setup and deployment:
 
-- **[LangGraph ReAct](./agents/base/langgraph_react_agent/README.md)** – General-purpose agent using a ReAct loop: it reasons and calls tools (e.g. search, math) step by step. Built with LangGraph and LangChain.
-- **[LlamaIndex WebSearch](./agents/base/llamaindex_websearch_agent/README.md)** – Agent built on LlamaIndex that uses a web search tool to query the internet and use the results in its answers.
-- **[OpenAI Responses](./agents/base/openai_responses_agent/README.md)** – Minimal agent with no framework: only the OpenAI Python client and an Action/Observation loop with tools. Use with OpenAI or any compatible API.
-- **[LangGraph Agentic RAG](./agents/community/langgraph_agentic_rag/README.md)** – RAG agent that indexes documents in a vector store (Milvus) and retrieves relevant chunks to augment the LLM’s answers with your own data.
+- **[LangGraph ReAct](./agents/base/langgraph_react_agent/README.md)** – General-purpose agent using a ReAct loop: it
+  reasons and calls tools (e.g. search, math) step by step. Built with LangGraph and LangChain.
+- **[LlamaIndex WebSearch](./agents/base/llamaindex_websearch_agent/README.md)** – Agent built on LlamaIndex that uses a
+  web search tool to query the internet and use the results in its answers.
+- **[OpenAI Responses](./agents/base/openai_responses_agent/README.md)** – Minimal agent with no framework: only the
+  OpenAI Python client and an Action/Observation loop with tools. Use with OpenAI or any compatible API.
+- **[LangGraph Agentic RAG](./agents/community/langgraph_agentic_rag/README.md)** – RAG agent that indexes documents in
+  a vector store (Milvus) and retrieves relevant chunks to augment the LLM’s answers with your own data.
+- **[LangGraph ReAct with Database Memory](./agents/community/langgraph_react_with_database_memory/README.md)** – ReAct
+  agent with PostgreSQL-backed conversation memory. Full chat history is persisted in the database while a FIFO sliding
+  window keeps only the last N messages in the LLM context. Built with LangGraph and `create_agent` middleware.
 
 ## Deployment Options
+
 Agents in this repository can support two deployment modes:
 
 ### 🖥️ Local Development
+
 - Run agents on your local machine
 - Use Llama Stack server with Ollama for model serving
 - Ideal for development, testing, and experimentation
 - No cloud infrastructure required
 
 ### ☁️ Production Deployment
+
 - Deploy agents to Red Hat OpenShift Cluster
 - Containerized deployment with Kubernetes
 - Production-grade scaling and monitoring
@@ -41,7 +55,8 @@ Agentic-Starter-Kits/
 │   │   └── llamaindex_websearch_agent/  # LlamaIndex web search agent
 │   │   └── openai_responses_agent/      # OpenAI Responses API (no framework)
 │   └── community/
-│       └── langgraph_agentic_rag/       # RAG agent with Milvus vector store
+│       ├── langgraph_agentic_rag/       # RAG agent with Milvus vector store
+│       └── langgraph_react_with_database_memory/  # ReAct agent with PostgreSQL memory (FIFO)
 ├── run_llama_server.yaml                # Llama Stack server configuration
 ├── utils.py                             # Shared utilities
 └── README.md                            # This file
@@ -50,41 +65,52 @@ Agentic-Starter-Kits/
 ---
 
 ## How to Use This Repository
+
 1. **Start Here**: Read this README to understand the overall structure and install core dependencies
 2. **Choose an Agent**: Select an agent from the `agents/` directory based on your use case
 3. **Follow Agent README**: Navigate to the agent's directory and follow its specific README for:
-   - Agent-specific dependencies installation
-   - Configuration and setup
-   - Local development or OpenShift deployment
-   - Usage examples and API endpoints
-
+    - Agent-specific dependencies installation
+    - Configuration and setup
+    - Local development or OpenShift deployment
+    - Usage examples and API endpoints
 
 ### Pre-requisitions to run that repo
+
 Run this script to set up repo stuff with a use of [UV](https://docs.astral.sh/uv/) and python 3.12
 
 Download repo
+
 ```bash
 git clone https://github.com/red-hat-data-services/agentic-starter-kits
 ```
+
 Get into root dir
+
 ```bash
 cd agentic-starter-kits
 ```
+
 Install UV
+
 ```bash
 curl -LsSf https://astral.sh/uv/install.sh | sh
 ```
+
 ---
 
 ## Additional Resources
+
 - **Llama Stack Documentation**: https://llama-stack.readthedocs.io/
 - **Ollama Documentation**: https://docs.ollama.com/
 - **OpenShift Documentation**: https://docs.openshift.com/
 - **Kubernetes**: https://kubernetes.io/docs/
 
-
 ## Contributing
+
 Contributions are welcome! Please see individual agent READMEs for specific guidelines.
 
 ## License
-MIT License
+
+MIT License
+
+Copyright (c) 2026

agents/base/langgraph_react_agent/LICENSE

@@ -1 +1,3 @@
 MIT License
+
+Copyright (c) 2026

agents/base/llamaindex_websearch_agent/LICENSE

@@ -1 +1,3 @@
 MIT License
+
+Copyright (c) 2026

agents/base/openai_responses_agent/LICENSE

@@ -1 +1,3 @@
 MIT License
+
+Copyright (c) 2026

agents/community/__init__.py

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2024
+Copyright (c) 2026
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

agents/community/langgraph_agentic_rag/LICENSE

@@ -0,0 +1,8 @@
+.env
+.vscode
+__pycache__
+.pytest_cache
+.venv
+dist
+config.toml
+inference_engine_cache/

agents/community/langgraph_react_with_database_memory/.gitignore

@@ -0,0 +1,39 @@
+# Use Python 3.12 slim image as base
+FROM python:3.12-slim
+
+# Set working directory
+WORKDIR /app
+
+# Create a non-privileged user for OpenShift
+# UID 1001 is commonly used in OpenShift deployments
+RUN groupadd -r appuser && useradd -r -u 1001 -g appuser appuser
+
+# Install uv for fast dependency management
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
+
+# Copy project files for dependency installation
+COPY pyproject.toml .
+COPY src/ ./src/
+
+# Install the project and its dependencies using uv
+RUN uv pip install --system --no-cache .
+
+# Copy the application entrypoint
+COPY main.py .
+
+# Create data directory for vector store
+RUN mkdir -p /app/data && \
+    chown -R appuser:appuser /app
+
+# Switch to non-privileged user
+USER appuser
+
+# Expose port 8080 (OpenShift standard)
+EXPOSE 8080
+
+# Set environment variables
+ENV PORT=8080
+ENV PYTHONPATH=/app:/app/src
+
+# Run the application
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8080"]

agents/community/langgraph_react_with_database_memory/Dockerfile

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.