New tutorial for agentic workflow

multi-agentic-travel-advisor/places_agent/DOCKER_TAG

+cicd.ai4eu-dev.eu:7444/tutorials/multi-agent-new/places-agent-s
\ No newline at end of file

multi-agentic-travel-advisor/places_agent/Dockerfile

+# Use a slim Python base image
+FROM python:3.10-slim
+
+ENV PYTHONUNBUFFERED=1
+
+RUN apt-get update -y && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        gcc \
+        libffi-dev \
+        libssl-dev \
+        git \
+        curl \
+        ca-certificates \
+        tzdata \
+        protobuf-compiler && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Set timezone
+ARG TIMEZONE=Europe/Berlin
+ENV TZ=$TIMEZONE
+RUN ln -snf /usr/share/zoneinfo/$TIMEZONE /etc/localtime && echo $TIMEZONE > /etc/timezone
+
+# Set working directory
+WORKDIR /places-agent
+
+# Copy requirements and install
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy project files
+COPY . .
+
+# Compile .proto file
+RUN python3 -m grpc_tools.protoc \
+    --proto_path=. \
+    --python_out=. \
+    --grpc_python_out=. \
+    agent.proto
+
+# Run the server
+CMD ["python3", "-u", "server.py"]
+

multi-agentic-travel-advisor/places_agent/agent.proto

+syntax = "proto3";
+
+message Empty {
+
+}
+
+message UserQuery {
+    string text = 1;
+}
+
+message AgentRequest {
+    string text = 1;
+    AgentType agent_type = 2;
+}
+
+enum AgentType {
+    UNKNOWN = 0;
+    WEATHER = 1;
+    PLACES = 2;
+    FOOD = 3;
+    MAP = 4;
+}
+
+message AgentResponse {
+    string text = 1;
+}
+
+service Agent {
+    rpc evaluateAgentRequestsFromPlanner(stream AgentRequest) returns (stream AgentResponse);
+}

multi-agentic-travel-advisor/places_agent/agent_pb2.py

+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# NO CHECKED-IN PROTOBUF GENCODE
+# source: agent.proto
+# Protobuf Python Version: 5.29.0
+"""Generated protocol buffer code."""
+
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pool as _descriptor_pool
+from google.protobuf import runtime_version as _runtime_version
+from google.protobuf import symbol_database as _symbol_database
+from google.protobuf.internal import builder as _builder
+
+_runtime_version.ValidateProtobufRuntimeVersion(
+    _runtime_version.Domain.PUBLIC, 5, 29, 0, "", "agent.proto"
+)
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(
+    b'\n\x0b\x61gent.proto"\x19\n\tUserQuery\x12\x0c\n\x04text\x18\x01 \x01(\t"<\n\x0c\x41gentRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\x1e\n\nagent_type\x18\x02 \x01(\x0e\x32\n.AgentType"&\n\rAgentResponse\x12\x15\n\rresponse_text\x18\x01 \x01(\t*E\n\tAgentType\x12\x0b\n\x07UNKNOWN\x10\x00\x12\x0b\n\x07WEATHER\x10\x01\x12\x07\n\x03MAP\x10\x02\x12\x08\n\x04NEWS\x10\x03\x12\x0b\n\x07\x46INANCE\x10\x04\x32:\n\x05\x41gent\x12\x31\n\x10GetAgentResponse\x12\r.AgentRequest\x1a\x0e.AgentResponseb\x06proto3'
+)
+
+_globals = globals()
+_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
+_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, "agent_pb2", _globals)
+if not _descriptor._USE_C_DESCRIPTORS:
+    DESCRIPTOR._loaded_options = None
+    _globals["_AGENTTYPE"]._serialized_start = 144
+    _globals["_AGENTTYPE"]._serialized_end = 213
+    _globals["_USERQUERY"]._serialized_start = 15
+    _globals["_USERQUERY"]._serialized_end = 40
+    _globals["_AGENTREQUEST"]._serialized_start = 42
+    _globals["_AGENTREQUEST"]._serialized_end = 102
+    _globals["_AGENTRESPONSE"]._serialized_start = 104
+    _globals["_AGENTRESPONSE"]._serialized_end = 142
+    _globals["_AGENT"]._serialized_start = 215
+    _globals["_AGENT"]._serialized_end = 273
+# @@protoc_insertion_point(module_scope)

multi-agentic-travel-advisor/places_agent/agent_pb2_grpc.py

+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+
+import grpc
+import warnings
+
+import agent_pb2 as agent__pb2
+
+GRPC_GENERATED_VERSION = "1.70.0"
+GRPC_VERSION = grpc.__version__
+_version_not_supported = False
+
+try:
+    from grpc._utilities import first_version_is_lower
+
+    _version_not_supported = first_version_is_lower(
+        GRPC_VERSION, GRPC_GENERATED_VERSION
+    )
+except ImportError:
+    _version_not_supported = True
+
+if _version_not_supported:
+    raise RuntimeError(
+        f"The grpc package installed is at version {GRPC_VERSION},"
+        + f" but the generated code in agent_pb2_grpc.py depends on"
+        + f" grpcio>={GRPC_GENERATED_VERSION}."
+        + f" Please upgrade your grpc module to grpcio>={GRPC_GENERATED_VERSION}"
+        + f" or downgrade your generated code using grpcio-tools<={GRPC_VERSION}."
+    )
+
+
+class AgentStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.GetAgentResponse = channel.unary_unary(
+            "/Agent/GetAgentResponse",
+            request_serializer=agent__pb2.AgentRequest.SerializeToString,
+            response_deserializer=agent__pb2.AgentResponse.FromString,
+            _registered_method=True,
+        )
+
+
+class AgentServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def GetAgentResponse(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details("Method not implemented!")
+        raise NotImplementedError("Method not implemented!")
+
+
+def add_AgentServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+        "GetAgentResponse": grpc.unary_unary_rpc_method_handler(
+            servicer.GetAgentResponse,
+            request_deserializer=agent__pb2.AgentRequest.FromString,
+            response_serializer=agent__pb2.AgentResponse.SerializeToString,
+        ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler("Agent", rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+    server.add_registered_method_handlers("Agent", rpc_method_handlers)
+
+
+# This class is part of an EXPERIMENTAL API.
+class Agent(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def GetAgentResponse(
+        request,
+        target,
+        options=(),
+        channel_credentials=None,
+        call_credentials=None,
+        insecure=False,
+        compression=None,
+        wait_for_ready=None,
+        timeout=None,
+        metadata=None,
+    ):
+        return grpc.experimental.unary_unary(
+            request,
+            target,
+            "/Agent/GetAgentResponse",
+            agent__pb2.AgentRequest.SerializeToString,
+            agent__pb2.AgentResponse.FromString,
+            options,
+            channel_credentials,
+            insecure,
+            call_credentials,
+            compression,
+            wait_for_ready,
+            timeout,
+            metadata,
+            _registered_method=True,
+        )

multi-agentic-travel-advisor/places_agent/build_and_deploy.sh

+#!/bin/bash
+
+# Variables
+IMAGE_NAME="places-agent-s"
+REGISTRY_URL="cicd.ai4eu-dev.eu:7444"
+REPO_PATH="tutorials/multi-agent-new"
+TAG="latest"  
+
+# Step 1: Build the Docker image
+echo "Building Docker image..."
+docker build -t $IMAGE_NAME .
+
+# Step 2: Tag the Docker image
+echo "Tagging Docker image..."
+docker tag $IMAGE_NAME $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG
+
+# Step 3: Push the Docker image to the registry
+echo "Pushing Docker image to registry..."
+docker push $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG
+
+# Check if the image was pushed successfully
+if [ $? -eq 0 ]; then
+  echo "Docker image successfully pushed to $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG"
+else
+  echo "Error: Docker push failed!"
+  exit 1
+fi
\ No newline at end of file

multi-agentic-travel-advisor/places_agent/client.py

+import grpc
+import agent_pb2
+import agent_pb2_grpc
+
+
+def run():
+    channel = grpc.insecure_channel("localhost:8061")
+    stub = agent_pb2_grpc.AgentStub(channel)
+    user_query = input("Please enter your query (e.g., 'Is it sunny in Rome?'): ")
+    request = agent_pb2.UserQuery(text=user_query)
+    response = stub.ProcessUserQuery(request)
+    print("Response from agent:", response.text)
+    channel.close()
+
+
+if __name__ == "__main__":
+    run()

multi-agentic-travel-advisor/places_agent/requirements.txt

+grpcio==1.38.0
+grpcio-tools==1.38.0
+grpc-interceptor
+protobuf==3.16.0
+multithreading
+openai
+requests
+geopy
\ No newline at end of file

multi-agentic-travel-advisor/places_agent/server.py

+import grpc
+import json
+from concurrent import futures
+
+import agent_pb2
+import agent_pb2_grpc
+
+from tool_calling.tools import get_attractions, get_wiki, tools
+from tool_calling.llm_client import client, deployment_name
+
+
+def run_conversation(prompt: str) -> str:
+    messages = [{"role": "user", "content": prompt}]
+
+    # First API call: Ask model for response or tool invocation
+    response = client.chat.completions.create(
+        model=deployment_name, messages=messages, tools=tools, tool_choice="required"
+    )
+
+    response_message = response.choices[0].message
+    messages.append(response_message)
+
+    print("\nModel's Response:")
+    print(response_message)
+
+    # If the model requests tool execution, handle it
+    if response_message.tool_calls:
+        for tool_call in response_message.tool_calls:
+            function_name = tool_call.function.name
+            function_args = json.loads(tool_call.function.arguments)
+
+            print(f"\nFunction Call: {function_name}")
+            print(f"Arguments: {function_args}")
+
+            if function_name == "get_attractions":
+                function_response = get_attractions(
+                    location=function_args.get("location")
+                )
+            elif function_name == "get_wiki":
+                function_response = get_wiki(topic=function_args.get("topic"))
+            else:
+                function_response = json.dumps({"error": "Unknown function"})
+
+            messages.append(
+                {
+                    "tool_call_id": tool_call.id,
+                    "role": "tool",
+                    "name": function_name,
+                    "content": function_response,
+                }
+            )
+
+    else:
+        print("No tool calls were made by the model.")
+
+    # Second API call: Get final response
+    final_response = client.chat.completions.create(
+        model=deployment_name,
+        messages=messages,
+    )
+
+    return final_response.choices[0].message.content
+
+
+class PlacesAgent(agent_pb2_grpc.AgentServicer):
+    def __init__(self):
+        self.latest_places_info = None
+
+    def evaluateAgentRequestsFromPlanner(self, request_iterator, context):
+        for request in request_iterator:
+            if request.agent_type == agent_pb2.PLACES:
+                print(f"\nReceived query: {request.text}")
+                places_info = run_conversation(request.text)
+
+                if places_info is None:
+                    places_info = "No weather info available."
+
+                self.latest_places_info = places_info
+                print(f"Weather info set to: {self.latest_places_info}")
+
+                response = agent_pb2.AgentResponse(text=places_info)
+                yield response
+
+
+def serve():
+    server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
+    agent_pb2_grpc.add_AgentServicer_to_server(PlacesAgent(), server)
+    port = 8061
+    server.add_insecure_port(f"[::]:{port}")
+    print(f"\Places agent server started on port {port}...")
+    server.start()
+    server.wait_for_termination()
+
+
+if __name__ == "__main__":
+    serve()

multi-agentic-travel-advisor/places_agent/tool_calling/llm_client.py

+from openai import OpenAI
+import os
+from base64 import b64encode
+
+platform = "OpenAI"
+# "Llama-3.3-70B-Instruct"
+# "gpt-4o-mini"
+deployment_name = "gpt-4o-mini"
+
+
+if platform == "GenAI":
+    # Initialize OpenAI client
+    genai_username = os.getenv("IAIS_GENAI_USERNAME")
+    genai_password = os.getenv("IAIS_GENAI_PASSWORD")
+    token_string = f"{genai_username}:{genai_password}"
+    token_bytes = b64encode(token_string.encode())
+
+    client = OpenAI(
+        api_key="xxxx",
+        default_headers={"Authorization": f"Basic {token_bytes.decode()}"},
+        base_url="https://genai.iais.fraunhofer.de/api/v2",
+    )
+
+elif platform == "OpenAI":
+    os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
+    # os.environ["OPENAI_ORG_ID"] = os.getenv("OPENAI_ORG_ID")
+
+    client = OpenAI()

multi-agentic-travel-advisor/places_agent/tool_calling/tools.py

+import requests
+import json
+from geopy.geocoders import Nominatim
+
+
+tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "get_attractions",
+            "description": "Get nearby tourist attractions for a given location.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "location": {
+                        "type": "string",
+                        "description": "Search for nearby attractions.",
+                    }
+                },
+                "required": ["location"],
+                "additionalProperties": False,
+            },
+        },
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "get_wiki",
+            "description": "Fetches a summary and metadata for a given Wikipedia topic.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "topic": {
+                        "type": "string",
+                        "description": "The topic to search for on Wikipedia.",
+                    }
+                },
+                "required": ["topic"],
+                "additionalProperties": False,
+            },
+        },
+    },
+]
+
+
+def get_attractions(location: str, radius: int = 500):
+    # Initialize geolocator
+    geolocator = Nominatim(user_agent="your_travel_app")
+
+    # Get latitude and longitude of the location
+    location_data = geolocator.geocode(location)
+    if not location_data:
+        return json.dumps({"error": f"Location '{location}' not found"}, indent=4)
+
+    lat, lon = location_data.latitude, location_data.longitude
+
+    # Construct the Overpass API query for tourism data
+    overpass_url = "http://overpass-api.de/api/interpreter"
+    query = f"""
+    [out:json];
+    (
+        node["tourism"](around:{radius},{lat},{lon});
+        way["tourism"](around:{radius},{lat},{lon});
+        relation["tourism"](around:{radius},{lat},{lon});
+    );
+    out center;
+    """
+
+    # Fetch data from Overpass API
+    try:
+        response = requests.get(overpass_url, params={"data": query})
+        response.raise_for_status()  # Raises an error for bad responses (4xx or 5xx)
+        data = response.json()
+    except requests.exceptions.RequestException as e:
+        return json.dumps({"error": f"Error fetching attractions: {str(e)}"}, indent=4)
+
+    # Process the attraction data
+    attractions = []
+    for element in data.get("elements", []):
+        tags = element.get("tags", {})
+
+        name = (
+            tags.get("name")
+            or tags.get("official_name")
+            or tags.get("brand")
+            or tags.get("operator")
+        )
+        tourism_type = tags.get("tourism", "Unknown Type")
+        latitude = element.get("lat") or element.get("center", {}).get("lat")
+        longitude = element.get("lon") or element.get("center", {}).get("lon")
+
+        if name and latitude and longitude:
+            attraction_info = {
+                "name": name,
+                "type": tourism_type,
+                "latitude": latitude,
+                "longitude": longitude,
+            }
+            attractions.append(attraction_info)
+
+    return json.dumps({"attractions": attractions}, indent=4)
+
+
+def get_wiki(topic: str):
+    topic_for_url = topic.replace(" ", "_")
+    wiki_url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{topic_for_url}"
+
+    # Fetch data from Wikipedia API
+    try:
+        response = requests.get(wiki_url)
+        response.raise_for_status()  # Raises an error for bad responses (4xx or 5xx)
+        data = response.json()
+    except requests.exceptions.RequestException as e:
+        return json.dumps(
+            {"error": f"Wikipedia page for '{topic}' not found: {str(e)}"}, indent=4
+        )
+
+    # Extract useful information from the response
+    title = data.get("title", topic)
+    summary = data.get("extract", "No summary available")
+    page_url = data.get("content_urls", {}).get("desktop", {}).get("page", "")
+    thumbnail = data.get("thumbnail", {}).get("source", "")
+
+    wiki_info = {
+        "title": title,
+        "summary": summary,
+        "page_url": page_url,
+        "thumbnail": thumbnail,
+    }
+
+    return json.dumps(wiki_info, indent=4)

multi-agentic-travel-advisor/planner/DOCKER_TAG

+cicd.ai4eu-dev.eu:7444/tutorials/multi-agent-new/planner-stream
\ No newline at end of file

multi-agentic-travel-advisor/planner/Dockerfile

+# Use a slim Python base image
+FROM python:3.10-slim
+
+ENV PYTHONUNBUFFERED=1
+
+RUN apt-get update -y && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        gcc \
+        libffi-dev \
+        libssl-dev \
+        git \
+        curl \
+        ca-certificates \
+        tzdata \
+        protobuf-compiler && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Set timezone
+ARG TIMEZONE=Europe/Berlin
+ENV TZ=$TIMEZONE
+RUN ln -snf /usr/share/zoneinfo/$TIMEZONE /etc/localtime && echo $TIMEZONE > /etc/timezone
+
+# Set working directory
+WORKDIR /chatbot
+
+# Copy requirements and install
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy project files
+COPY . .
+
+# Compile .proto file
+RUN python3 -m grpc_tools.protoc \
+    --proto_path=. \
+    --python_out=. \
+    --grpc_python_out=. \
+    planner.proto
+
+# Run the server
+CMD ["python3", "-u", "server.py"]
\ No newline at end of file

multi-agentic-travel-advisor/planner/build_and_deploy.sh

+#!/bin/bash
+
+# Variables
+IMAGE_NAME="planner-stream"
+REGISTRY_URL="cicd.ai4eu-dev.eu:7444"
+REPO_PATH="tutorials/multi-agent-new"
+TAG="latest"  
+
+# Step 1: Build the Docker image
+echo "Building Docker image..."
+docker build -t $IMAGE_NAME .
+
+# Step 2: Tag the Docker image
+echo "Tagging Docker image..."
+docker tag $IMAGE_NAME $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG
+
+# Step 3: Push the Docker image to the registry
+echo "Pushing Docker image to registry..."
+docker push $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG
+
+# Check if the image was pushed successfully
+if [ $? -eq 0 ]; then
+  echo "Docker image successfully pushed to $REGISTRY_URL/$REPO_PATH/$IMAGE_NAME:$TAG"
+else
+  echo "Error: Docker push failed!"
+  exit 1
+fi
\ No newline at end of file

multi-agentic-travel-advisor/planner/client.py

+import grpc
+import planner_pb2
+import planner_pb2_grpc
+
+
+def run():
+    # Connect to the gRPC server
+    with grpc.insecure_channel("localhost:8061") as channel:
+        stub = planner_pb2_grpc.PlannerStub(channel)
+
+        # Example user query
+        query = "What's the weather like today?"
+        request = planner_pb2.UserQuery(text=query)
+
+        # Send request and get response
+        response = stub.ProcessUserQuery(request)
+
+        # Print the response
+        print(f"Response: {response.text}")
+        print(f"Agent Type: {response.agent_type}")
+
+
+if __name__ == "__main__":
+    run()

multi-agentic-travel-advisor/planner/planner.proto

+syntax = "proto3";
+
+message Empty {
+
+}
+
+message UserQuery {
+    string text = 1;
+}
+
+message AgentRequest {
+    string text = 1;
+    AgentType agent_type = 2;
+}
+
+enum AgentType {
+    UNKNOWN = 0;
+    WEATHER = 1;
+    PLACES = 2;
+    FOOD = 3;
+    MAP = 4;
+}
+
+message AgentResponse {
+    string text = 1;
+}
+
+service Planner {
+    rpc evaluateUserQueriesFromChatbot(stream UserQuery) returns (stream AgentRequest);
+    rpc processAgentResponsesFromAgent(stream AgentResponse) returns (stream AgentResponse);
+}

multi-agentic-travel-advisor/planner/requirements.txt

+grpcio==1.38.0
+grpcio-tools==1.38.0
+grpc-interceptor
+protobuf==3.16.0
+multithreading
+Flask
+
+torch
+transformers
\ No newline at end of file

multi-agentic-travel-advisor/planner/server.py

+import grpc
+from concurrent import futures
+import planner_pb2
+import planner_pb2_grpc
+from transformers import pipeline
+import logging
+import time
+
+logger = logging.getLogger(__name__)
+logging.basicConfig(level=logging.INFO)
+
+# Zero-shot classifier
+classifier = pipeline("zero-shot-classification")
+
+
+def match_agent(text):
+    candidate_labels = ["weather", "places", "food", "map"]
+    result = classifier(text, candidate_labels)
+    label = result["labels"][0]
+
+    if label == "weather":
+        return planner_pb2.WEATHER
+    elif label == "places":
+        return planner_pb2.PLACES
+    elif label == "food":
+        return planner_pb2.FOOD
+    elif label == "map":
+        return planner_pb2.MAP
+    else:
+        return planner_pb2.UNKNOWN
+
+
+class PlannerService(planner_pb2_grpc.PlannerServicer):
+    def __init__(self):
+        logger.info("PlannerService initialized.")
+
+    def evaluateUserQueriesFromChatbot(self, request_iterator, context):
+        print("evaluateUserQueriesFromChatbot..............................")
+        for user_query in request_iterator:
+            logger.info(f"Received user query: {user_query.text}")
+            agent_type = match_agent(user_query.text)
+            logger.info(f"Matched agent type: {agent_type}")
+
+            agent_response = planner_pb2.AgentRequest()
+            agent_response.text = user_query.text
+            agent_response.agent_type = agent_type
+
+            if agent_type == planner_pb2.AgentType.WEATHER:
+                logger.info("Handling WEATHER agent.")
+            elif agent_type == planner_pb2.AgentType.PLACES:
+                logger.info("Handling PLACES agent.")
+            elif agent_type == planner_pb2.AgentType.FOOD:
+                logger.info("Handling FOOD agent.")
+            elif agent_type == planner_pb2.AgentType.MAP:
+                logger.info("Handling MAP agent.")
+            else:
+                agent_response.text = "Sorry, I couldn't understand the query."
+
+            yield agent_response
+
+    def processAgentResponsesFromAgent(self, request_iterator, context):
+        logger.info("Receiving AgentResponses from agent...")
+
+        for response in request_iterator:
+            logger.info(f"Received AgentResponse: {response.text}")
+            res = planner_pb2.AgentResponse()
+            res.text = response.text
+            print(res)
+            yield res
+
+        logger.info("Finished processing AgentResponses.")
+
+
+def serve():
+    server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
+    planner_pb2_grpc.add_PlannerServicer_to_server(PlannerService(), server)
+    server.add_insecure_port("[::]:8061")
+    server.start()
+    logger.info("Planner Service running on port 8061")
+    server.wait_for_termination()
+
+
+if __name__ == "__main__":
+    serve()

multi-agentic-travel-advisor/weather_agent/DOCKER_TAG

+cicd.ai4eu-dev.eu:7444/tutorials/multi-agent-new/weather-agent-s
\ No newline at end of file

multi-agentic-travel-advisor/weather_agent/Dockerfile

+# Use a slim Python base image
+FROM python:3.10-slim
+
+ENV PYTHONUNBUFFERED=1
+
+RUN apt-get update -y && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        gcc \
+        libffi-dev \
+        libssl-dev \
+        git \
+        curl \
+        ca-certificates \
+        tzdata \
+        protobuf-compiler && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Set timezone
+ARG TIMEZONE=Europe/Berlin
+ENV TZ=$TIMEZONE
+RUN ln -snf /usr/share/zoneinfo/$TIMEZONE /etc/localtime && echo $TIMEZONE > /etc/timezone
+
+# Set working directory
+WORKDIR /weather-agent
+
+# Copy requirements and install
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy project files
+COPY . .
+
+# Compile .proto file
+RUN python3 -m grpc_tools.protoc \
+    --proto_path=. \
+    --python_out=. \
+    --grpc_python_out=. \
+    agent.proto
+
+# Run the server
+CMD ["python3", "-u", "server.py"]
+