Pythongemini_demo.py
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import os
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import json
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import google.generativeai as genai
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genai.configure(api_key=os.environ["GOOGLE_API_KEY"])
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# ── 1. Basic text inference ─────────────────────────────────────────
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model = genai.GenerativeModel("gemini-1.5-flash")
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response = model.generate_content("Explain transformer architecture in 3 bullet points.")
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print("=== Text ===")
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print(response.text)
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# ── 2. Structured JSON output ───────────────────────────────────────
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import typing_extensions as typing
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class Movie(typing.TypedDict):
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    title: str
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    year: int
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    genre: str
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    rating: float
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model_structured = genai.GenerativeModel(
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    "gemini-1.5-flash",
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    generation_config=genai.GenerationConfig(
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        response_mime_type="application/json",
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        response_schema=list[Movie],
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    ),
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)
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result = model_structured.generate_content(
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    "List 3 classic sci-fi movies with their year, genre, and IMDB rating."
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)
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movies = json.loads(result.text)
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print("\n=== Structured Output ===")
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for movie in movies:
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    print(f"  {movie['title']} ({movie['year']}) — {movie['rating']}/10")
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# ── 3. Function calling ─────────────────────────────────────────────
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def search_products(query: str, max_price: float = 100.0) -> dict:
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    """Simulate a product search."""
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    return {
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        "results": [
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            {"name": f"Product for {query}", "price": max_price * 0.8},
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        ]
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    }
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search_tool = genai.protos.Tool(
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    function_declarations=[
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        genai.protos.FunctionDeclaration(
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            name="search_products",
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            description="Search for products by query and max price",
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            parameters=genai.protos.Schema(
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                type=genai.protos.Type.OBJECT,
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                properties={
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                    "query": genai.protos.Schema(type=genai.protos.Type.STRING),
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                    "max_price": genai.protos.Schema(type=genai.protos.Type.NUMBER),
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                },
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                required=["query"],
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            ),
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        )
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    ]
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)
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chat = model.start_chat()
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response = chat.send_message(
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    "Find me laptops under $800",
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    tools=[search_tool],
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)
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print("\n=== Function Call ===")
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for part in response.candidates[0].content.parts:
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    if fn := part.function_call:
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        print(f"Function: {fn.name}, Args: {dict(fn.args)}")
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        # Execute and send result back
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        result = search_products(**fn.args)
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        response2 = chat.send_message(
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            genai.protos.Content(parts=[
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                genai.protos.Part(function_response=genai.protos.FunctionResponse(
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                    name=fn.name, response=result
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                ))
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            ])
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        )
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        print(f"Final: {response2.text}")
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