Suggested updates

8_BeeAIRequirement.ipynb

@@ -142,7 +142,7 @@
     "from beeai_framework.adapters.gemini import GeminiChatModel\n",
     "\n",
     "# If using Vertex AI\n",
-    "# from beeai_framework.adapters.vertexai import VertexAIChatModel\n",
+    "from beeai_framework.adapters.vertexai import VertexAIChatModel  # noqa: F401\n",
     "from beeai_framework.agents.requirement import RequirementAgent\n",
     "from beeai_framework.agents.requirement.requirements.conditional import (\n",
     "    ConditionalRequirement,\n",
@@ -244,11 +244,11 @@
     "        allow_parallel_tool_calls=True,\n",
     "    ),\n",
     "    # If using Vertex AI\n",
-    "    # llm=VertexAIChatModel(\n",
-    "    #     model_id=\"gemini-3-flash-preview\",\n",
-    "    #     project=project_id,\n",
-    "    #     location=\"global\",\n",
-    "    #     allow_parallel_tool_calls=True,\n",
+    "    # llm = VertexAIChatModel(\n",
+    "    #    model_id=\"gemini-3-flash-preview\",\n",
+    "    #    project= os.environ.get(\"GOOGLE_CLOUD_PROJECT\"),\n",
+    "    #    location=\"global\",\n",
+    "    #    allow_parallel_tool_calls=True,\n",
     "    # ),\n",
     "    tools=[\n",
     "        thinktool := ThinkTool(),\n",

README.md

@@ -79,7 +79,7 @@ Follow these steps to set up your environment and run the example agents. Each n
 
 Before running the examples, complete the following setup steps:
 
-1. **Create a [Gemini API Key](https://ai.google.dev/gemini-api/docs/api-key) or [configure your environment for Vertex AI](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/start/quickstart?usertype=adc).**
+1. **Create a [Gemini API Key](https://ai.google.dev/gemini-api/docs/api-key) or [configure your environment for Vertex AI](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/start/quickstart?usertype=adc).** If you choose to use Vertex AI, make sure to uncomment the corresponding code in the notebooks and Python files.
 
 2. **Configure Environment Variables:**
     - In the project root, make a copy of `example.env` and rename it to `.env`.
@@ -97,15 +97,15 @@ Before running the examples, complete the following setup steps:
       uv sync
       ```
 
-    - **Notebooks / Google Colab:** If running in a notebook environment, you can install the dependencies by running the following in a cell:
+    - **Notebooks / Google Colab:** If running in a notebook environment, you can install the dependencies by running the following in a cell (or in the terminal):
 
       ```python
       %pip install .
       ```
 
 ## Running the Agents
 
-You can run the agent servers using `uv run`. Ensure you are in the project root.
+You can run each agent server in a separate terminal using `uv run`. Ensure you are in the project root.
 
 - **Policy Agent (Lesson 2):**
 
@@ -130,3 +130,11 @@ You can run the agent servers using `uv run`. Ensure you are in the project root
   ```sh
   uv run a2a_healthcare_agent.py
   ```
+
+To interact with these A2A agent servers, you can run the A2A clients defined in the provided notebooks or create Python files defining A2A clients to run in a terminal. For example, run:
+
+```sh
+uv run a2a_healthcare_client.py
+```
+
+to interact with the Healthcare Concierge Agent.

a2a_healthcare_agent.py

@@ -5,6 +5,7 @@
 from beeai_framework.adapters.a2a.agents import A2AAgent
 from beeai_framework.adapters.a2a.serve.server import A2AServer, A2AServerConfig
 from beeai_framework.adapters.gemini import GeminiChatModel
+from beeai_framework.adapters.vertexai import VertexAIChatModel  # noqa: F401
 from beeai_framework.agents.requirement import RequirementAgent
 from beeai_framework.agents.requirement.requirements.conditional import (
     ConditionalRequirement,
@@ -66,10 +67,15 @@ def main() -> None:
         description="A personal concierge for Healthcare Information, customized to your policy.",
         llm=GeminiChatModel(
             "gemini-3-flash-preview",
-            # For Vertex AI:
-            # "vertex_ai/gemini-3-flash-preview",
             allow_parallel_tool_calls=True,
         ),
+        # If using Vertex AI
+        # llm = VertexAIChatModel(
+        #    model_id="gemini-3-flash-preview",
+        #    project= os.environ.get("GOOGLE_CLOUD_PROJECT"),
+        #    location="global",
+        #    allow_parallel_tool_calls=True,
+        # ),
         tools=[
             thinktool := ThinkTool(),
             policy_tool := HandoffTool(

a2a_healthcare_client.py

@@ -0,0 +1,37 @@
+import asyncio
+import os
+from typing import Any
+
+from beeai_framework.adapters.a2a.agents import A2AAgent
+from beeai_framework.memory import UnconstrainedMemory
+from beeai_framework.middleware.trajectory import EventMeta, GlobalTrajectoryMiddleware
+
+from helpers import setup_env
+
+
+class ConciseGlobalTrajectoryMiddleware(GlobalTrajectoryMiddleware):
+    def _format_prefix(self, meta: EventMeta) -> str:
+        prefix = super()._format_prefix(meta)
+        return prefix.rstrip(": ")
+
+    def _format_payload(self, value: Any) -> str:
+        return ""
+
+
+async def main() -> None:
+    setup_env()
+
+    host = os.getenv("AGENT_HOST")
+    healthcare_agent_port = int(os.getenv("HEALTHCARE_AGENT_PORT"))
+
+    agent = A2AAgent(
+        url=f"http://{host}:{healthcare_agent_port}", memory=UnconstrainedMemory()
+    )
+    response = await agent.run(
+        "I'm based in Austin, TX. How do I get mental health therapy near me and what does my insurance cover?"
+    ).middleware(ConciseGlobalTrajectoryMiddleware())
+    print(response.last_message.text)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

example.env

@@ -6,6 +6,9 @@ GEMINI_API_KEY="YOUR_GEMINI_API_KEY"
 # GOOGLE_CLOUD_LOCATION="global"
 # GOOGLE_GENAI_USE_VERTEXAI=True
 # GOOGLE_APPLICATION_CREDENTIALS="credentials.json"
+# LiteLLM Vertex AI settings 
+# VERTEXAI_PROJECT="YOUR_GOOGLE_CLOUD_PROJECT"
+# VERTEXAI_LOCATION="global"
 
 # Agent Network Configuration
 AGENT_HOST="localhost"

helpers.py

@@ -1,4 +1,3 @@
-import logging
 import warnings
 
 import nest_asyncio
@@ -12,7 +11,6 @@ def setup_env() -> None:
     load_dotenv(override=True)
     nest_asyncio.apply()
 
-    logging.disable(level=logging.WARNING)
     warnings.filterwarnings("ignore", category=UserWarning)
     warnings.filterwarnings("ignore", category=FutureWarning)
 

pyproject.toml

@@ -12,13 +12,14 @@ dependencies = [
     "agent-framework==1.0.0b251120",
     "agent-framework-a2a==1.0.0b251120",
     "langchain-mcp-adapters==0.1.11",
-    "langchain-litellm",
     "langgraph==1.0.2",
     "langchain==1.0.2",
-    "beeai-framework[a2a]==0.1.75",
+    "langchain_litellm",
+    "beeai-framework[a2a]==0.1.70",
     "nest_asyncio",
     "ipython",
-    "langgraph-a2a-server>=0.1.6",
+    "python-dotenv",
+    "langgraph-a2a-server==0.1.6",
 ]
 
 [tool.ruff]