Initial commit

.gitignore

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+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv
+
+# uv lock files
+uv.lock
+
+# config
+.env
+
+# database
+sessions.db

.python-version

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+3.13

README.md

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+### ADK Sample Project
+
+Public example using Google ADK with a simple email pipeline.
+
+### Requirements
+- Python 3.13, `uv` (`pip install uv` or see `https://astral.sh/uv`)
+
+### Setup
+1) Install deps:
+```
+uv sync
+```
+2) Create `.env` in project root:
+```
+GEMINI_API_KEY=your_key
+GENAI_MODEL=gemini-2.5-flash
+```
+
+### Run
+```
+uv run uvicorn main:app --reload
+```
+Web UI at `http://localhost:8000`.
+
+### API
+POST `http://localhost:8000/process_data`
+```
+curl -s -X POST http://localhost:8000/process_data \
+  -H 'Content-Type: application/json' \
+  -d '{"message":"Draft an email about Friday meeting at 2pm"}'
+```
+Returns `{ "emails": "..." }`.
+
+

agents/__init__.py

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+from agents.pipeline import agent as agent

agents/pipeline/__init__.py

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+from agents.pipeline import agent as agent

agents/pipeline/agent.py

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+import os
+
+from google.adk.agents.llm_agent import LlmAgent
+from google.adk.agents.sequential_agent import SequentialAgent
+
+MODEL_ID = os.getenv("GENAI_MODEL", "gemini-2.5-flash")
+
+intake_agent = LlmAgent(
+    name="intake",
+    description="Receives the user's message and produces a cleaned version.",
+    model=MODEL_ID,
+    instruction=(
+        "You are the first step in a pipeline. Read the user's message and "
+        "briefly restate it clearly without changing meaning. Return only the restated text."
+    ),
+)
+
+transform_agent = LlmAgent(
+    name="transform",
+    description="Transforms the intake text into a concise bullet list summary.",
+    model=MODEL_ID,
+    instruction=(
+        "Convert the previous step's text into 3-6 concise bullet points. "
+        "No preamble, output only bullet points prefixed with '- '."
+    ),
+)
+
+email_agent = LlmAgent(
+    name="email_generator",
+    description="Generates a professional email draft from the bullet points.",
+    model=MODEL_ID,
+    instruction=(
+        "You are an assistant that writes concise, friendly emails. Given bullet points, "
+        "compose a short email with: subject line, greeting, 1-2 paragraphs, and sign-off. "
+        "Return in plain text with 'Subject:' on the first line."
+    ),
+)
+
+root_agent = SequentialAgent(
+    name="root_pipeline",
+    description="Runs intake -> transform -> email_generator sequentially.",
+    sub_agents=[intake_agent, transform_agent, email_agent],
+)

main.py

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+import os
+
+import uvicorn
+from dotenv import load_dotenv
+from fastapi import Body, FastAPI
+from google.adk.cli.fast_api import get_fast_api_app
+from google.adk.runners import InMemoryRunner
+from google.genai import types as genai_types
+
+from agents.pipeline.agent import root_agent as pipeline_root_agent
+
+
+def build_pipeline_root(_: str):
+    # Agents now live under ./agents and are auto-loaded by ADK FastAPI app.
+    # Kept for compatibility with run_sample(); unused in API path.
+    from agents.pipeline.agent import root_agent as ra
+    return ra
+
+
+def run_sample():
+    load_dotenv()
+
+    # Allow GEMINI_API_KEY provided in .env to be used by google-genai client
+    api_key = os.getenv("GEMINI_API_KEY", "")
+    if api_key and not os.getenv("GOOGLE_GENAI_API_KEY"):
+        os.environ["GOOGLE_GENAI_API_KEY"] = api_key
+
+    # Sample disabled: use the FastAPI server instead.
+    print("Sample disabled: start the FastAPI app.")
+
+
+"""FastAPI application configured via ADK's get_fast_api_app, auto-loading agents from ./agents."""
+DEFAULT_ENV = os.path.abspath(os.path.join(os.path.dirname(__file__), ".env"))
+ENV_FILE = os.getenv("ENV_FILE", DEFAULT_ENV)
+load_dotenv(dotenv_path=ENV_FILE)
+if os.getenv("GEMINI_API_KEY") and not os.getenv("GOOGLE_GENAI_API_KEY"):
+    os.environ["GOOGLE_GENAI_API_KEY"] = os.getenv("GEMINI_API_KEY")
+
+AGENTS_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "agents")
+SESSION_SERVICE_URI = "sqlite:///./sessions.db"
+ALLOWED_ORIGINS = ["*"]
+SERVE_WEB_INTERFACE = True
+
+app: FastAPI = get_fast_api_app(
+    agents_dir=AGENTS_DIR,
+    session_service_uri=SESSION_SERVICE_URI,
+    allow_origins=ALLOWED_ORIGINS,
+    web=SERVE_WEB_INTERFACE,
+)
+
+_api_runner = InMemoryRunner(agent=pipeline_root_agent)
+
+
+@app.post("/process_data")
+def process_data(data: dict = Body(...)):
+    message = data.get("message") or data.get("text") or data.get("input") or ""
+    content = genai_types.Content(parts=[genai_types.Part.from_text(text=message)], role="user")
+
+    session = _api_runner.session_service.create_session_sync(
+        app_name=_api_runner.app_name,
+        user_id="api-user",
+    )
+
+    final_text = None
+    for event in _api_runner.run(user_id="api-user", session_id=session.id, new_message=content):
+        if getattr(event, "content", None):
+            for part in event.content.parts or []:
+                text = getattr(part, "text", None)
+                if text:
+                    final_text = text
+
+    return {"emails": final_text or ""}
+
+
+if __name__ == "__main__":
+    # Run API from this directory: `uv run uvicorn main:app --reload`
+    uvicorn.run(app, host="0.0.0.0", port=int(os.environ.get("PORT", 8000)))

pyproject.toml

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+[project]
+name = "test-project"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.13"
+dependencies = [
+    "google-adk>=1.10.0",
+    "ruff>=0.12.8",
+]
+
+[tool.ruff]
+line-length = 100
+[tool.ruff.lint]
+select = ["E", "F", "I", "TID"]
+[tool.ruff.lint.isort]
+combine-as-imports = true
+known-first-party = ["agents"]
+[tool.ruff.lint.flake8-tidy-imports]
+ban-relative-imports = "all"