Merge branch 'main' into feat_short_based_memory_agent

Author: MRGuziX

.gitignore

@@ -1,3 +1,4 @@
+.env*
 .env
 .vscode
 .idea

agents/base/langgraph_react_agent/Dockerfile

@@ -8,16 +8,18 @@ WORKDIR /app
 # UID 1001 is commonly used in OpenShift deployments
 RUN groupadd -r appuser && useradd -r -u 1001 -g appuser appuser
 
-# Copy requirements file first for better layer caching
-COPY requirements.txt .
+# Install uv for fast dependency management
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
 
-# Install Python dependencies
-RUN pip install --no-cache-dir --upgrade pip && \
-    pip install --no-cache-dir -r requirements.txt
+# 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 code
+# Copy the application entrypoint
 COPY main.py .
-COPY src/ ./src/
 
 # Change ownership of the app directory to the non-privileged user
 RUN chown -R appuser:appuser /app
@@ -33,5 +35,4 @@ ENV PORT=8080
 ENV PYTHONPATH=/app:/app/src
 
 # Run the application
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8080"]
-
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8080"]

agents/base/langgraph_react_agent/README.md

@@ -1,28 +1,40 @@
 <div style="text-align: center;">
 
 ![LangGraph Logo](/images/langgraph_logo.svg)
+
 # ReACT Agent
 
 </div>
 
 ---
+
 ## What this agent does
-General-purpose agent using a ReAct loop: it reasons and calls tools (e.g. search, math) step by step. Built with LangGraph and LangChain.
+
+General-purpose agent using a ReAct loop: it reasons and calls tools (e.g. search, math) step by step. Built with
+LangGraph and LangChain.
 
 ---
+
 ### Preconditions:
-- You need to copy/paste .env file and change its values to yours
+
+- You need to change .env.template file to .env
 - Decide what way you want to go `local` or `RH OpenShift Cluster` and fill needed values
 - use `./init.sh` that will add those values from .env to environment variables
 
+Go to agent dir
 
+```bash
+cd agents/base/langgraph_react_agent
+```
+
+Change the name of .env file
 
-Copy .env file
 ```bash
-cp template.env agents/base/langgraph_react_agent/.env
+mv template.env .env
 ```
 
 #### Local
+
 Edit the `.env` file with your local configuration:
 
 ```
@@ -33,6 +45,7 @@ CONTAINER_IMAGE=not-needed
 ```
 
 #### OpenShift Cluster
+
 Edit the `.env` file and fill in all required values:
 
 ```
@@ -43,46 +56,47 @@ CONTAINER_IMAGE=quay.io/your-username/langgraph-react-agent:latest
 ```
 
 **Notes:**
+
 - `API_KEY` - contact your cluster administrator
 - `BASE_URL` - should end with `/v1`
 - `MODEL_ID` - contact your cluster administrator
 - `CONTAINER_IMAGE` - full image path where the agent container will be pushed and pulled from.
   The image is built locally, pushed to this registry, and then deployed to OpenShift.
 
   Format: `<registry>/<namespace>/<image-name>:<tag>`
-  
-  Examples:
-  - Quay.io: `quay.io/your-username/langgraph-react-agent:latest`
-  - Docker Hub: `docker.io/your-username/langgraph-react-agent:latest`
-  - GHCR: `ghcr.io/your-org/langgraph-react-agent:latest`
 
-Go to agent dir
-```bash
-cd agents/base/langgraph_react_agent
-```
+  Examples:
+    - Quay.io: `quay.io/your-username/langgraph-react-agent:latest`
+    - Docker Hub: `docker.io/your-username/langgraph-react-agent:latest`
+    - GHCR: `ghcr.io/your-org/langgraph-react-agent:latest`
 
 Create and activate a virtual environment (Python 3.12) in this directory using [uv](https://docs.astral.sh/uv/):
+
 ```bash
 uv venv --python 3.12
 source .venv/bin/activate
 ```
+
 (On Windows: `.venv\Scripts\activate`)
 
 Make scripts executable
+
 ```bash
 chmod +x init.sh
 ```
 
 Add to values from .env to environment variables
+
 ```bash
-./init.sh
+source ./init.sh
 ```
 
 ---
 
 ## Local usage (Ollama + LlamaStack Server)
 
 Create package with agent and install it to venv
+
 ```bash
 uv pip install -e .
 ```
@@ -92,75 +106,93 @@ uv pip install ollama
 ```
 
 Install app from Ollama site or via Brew
+
 ```bash
 #brew install ollama
 # or
 curl -fsSL https://ollama.com/install.sh | sh
 ```
 
 Pull Required Model
+
 ```bash
 ollama pull llama3.2:3b
 ```
 
 Start Ollama Service
+
 ```bash
 ollama serve
 ```
->**Keep this terminal open!**\
+
+> **Keep this terminal open!**\
 > Ollama needs to keep running.
 
 Start LlamaStack Server
+
 ```bash
 llama stack run ../../../run_llama_server.yaml
 ```
+
 > **Keep this terminal open** - the server needs to keep running.\
 > You should see output indicating the server started on `http://localhost:8321`.
 
- Run the example:
+Run the example:
+
 ```bash
 uv run examples/execute_ai_service_locally.py
 ```
 
 # Deployment on RedHat OpenShift Cluster
+
 Login to OC
+
 ```bash
 oc login -u "login" -p "password" https://super-link-to-cluster:111
 ```
-Login ex. Docker 
+
+Login ex. Docker
+
 ```bash
 docker login -u='login' -p='password' quay.io
 ```
 
 Make deploy file executable
+
 ```bash
 chmod +x deploy.sh
 ```
 
 Build image and deploy Agent
+
 ```bash
 ./deploy.sh
 ```
 
 This will:
+
 - Create Kubernetes secret for API key
 - Build and push the Docker image
 - Deploy the agent to OpenShift
 - Create Service and Route
 
 COPY the route URL and PASTE into the CURL below
+
 ```bash
 oc get route langgraph-react-agent -o jsonpath='{.spec.host}'
 ```
 
 Send a test request:
+
 ```bash
 curl -X POST https://<YOUR_ROUTE_URL>/chat \
   -H "Content-Type: application/json" \
   -d '{"message": "What is the best company? Answer with the first correct answer."}'
 ```
 
 ## Agent-Specific Documentation
+
 Each agent has detailed documentation for setup and deployment:
+
 - https://ollama.com/
 - https://formulae.brew.sh/formula/ollama#default

agents/base/langgraph_react_agent/examples/execute_ai_service_locally.py

@@ -1,6 +1,7 @@
+from os import getenv
+
 from _interactive_chat import InteractiveChat
 from ai_service import ai_stream_service
-from langgraph_react_agent_base.utils import get_env_var
 
 
 class SimpleContext:
@@ -19,8 +20,8 @@ def get_headers(self):
         return {}
 
 
-base_url = get_env_var("BASE_URL")
-model_id = get_env_var("MODEL_ID")
+base_url = getenv("BASE_URL")
+model_id = getenv("MODEL_ID")
 
 # Ensure base_url ends with /v1 if provided
 if base_url and not base_url.endswith("/v1"):

agents/base/langgraph_react_agent/init.sh

@@ -1,44 +1,64 @@
 #!/bin/bash
-# Usage:
-#   ./init.sh
 #
-# Prerequisites:
-#   - oc CLI installed and logged in to OpenShift cluster
-#   - docker installed
-#   - Access to container registry (e.g., Quay.io)
+# init.sh - Environment bootstrap for the LangGraph ReAct Agent
 #
+# Loads environment variables from the .env file located next to this script,
+# validates that all required variables (API_KEY, BASE_URL, MODEL_ID,
+# CONTAINER_IMAGE) are set, and ensures the shared milvus_data directory
+# exists at the repository root.
 
-set -e
-
-source .env && echo "Environment variables loaded from .env file"
-
-if [ -z "$API_KEY" ]; then
-    echo "API_KEY not set, check .env file"
-    exit 1
-fi
+#
+# Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
+#
 
-if [ -z "$BASE_URL" ]; then
-    echo "BASE_URL not set, check .env file"
-    exit 1
-fi
+# Resolve the directory containing this script (works when sourced or executed)
+# BASH_SOURCE works in bash; ${(%):-%x} is the zsh equivalent
+AGENT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]:-${(%):-%x}}")" && pwd)"
+REPO_ROOT="$AGENT_DIR/../../.."
+ENV_FILE="$AGENT_DIR/.env"
 
-if [ -z "$MODEL_ID" ]; then
-    echo "MODEL_ID not set, check .env file"
-    exit 1
-fi
+# 1. Load .env, export variables, and collect their names for validation
+ENV_VARS=()
 
-if [ -z "$CONTAINER_IMAGE" ]; then
-    echo "CONTAINER_IMAGE not set, check .env file"
-    exit 1
+if [ -f "$ENV_FILE" ]; then
+    while IFS= read -r line || [ -n "$line" ]; do
+        line="${line//$'\r'/}"
+        line="${line#"${line%%[![:space:]]*}"}"
+        [[ -z "$line" || "$line" == \#* ]] && continue
+        export "$line"
+        ENV_VARS+=("${line%%=*}")
+    done < "$ENV_FILE"
+    echo "Environment variables loaded from $ENV_FILE"
+else
+    echo "ERROR: .env file not found at $ENV_FILE"
+    return 1 2>/dev/null || exit 1
 fi
 
-# Get the directory where the script is located
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-
-# Get the root directory of the repository (3 levels up from script)
-ROOT_DIR="$(cd "$SCRIPT_DIR/../../.." && pwd)"
+# 2. Validate every variable found in .env
+for var_name in "${ENV_VARS[@]}"; do
+    var_value=$(eval echo "\$$var_name")
+    if [ -z "$var_value" ]; then
+        echo "  ERROR: $var_name is empty. Check your .env file."
+        return 1 2>/dev/null || exit 1
+    fi
+    local_lower=$(echo "$var_name" | tr '[:upper:]' '[:lower:]')
+    if [[ "$local_lower" == *password* || "$local_lower" == *apikey* || "$local_lower" == *api_key* || "$local_lower" == *secret* || "$local_lower" == *token* ]]; then
+        echo "  $var_name=****"
+    else
+        echo "  $var_name=$var_value"
+    fi
+done
 
-# Copy utils.py to the destination
-cp "$ROOT_DIR/utils.py" "$SCRIPT_DIR/src/langgraph_react_agent_base/" && echo "Utils.py copied to destination"
+# 3. Ensure milvus_data directory exists at repo root
+MILVUS_DIR="$REPO_ROOT/milvus_data"
 
-echo "Agent initialized successfully"
+if [ -d "$MILVUS_DIR" ]; then
+    echo "milvus_data directory exists in root folder"
+else
+    if mkdir -p "$MILVUS_DIR"; then
+        echo "Created milvus_data directory at: $MILVUS_DIR"
+    else
+        echo "ERROR: Failed to create $MILVUS_DIR"
+        return 1 2>/dev/null || exit 1
+    fi
+fi