Mulai 29 April 2025, model Gemini 1.5 Pro dan Gemini 1.5 Flash tidak tersedia di project yang belum pernah menggunakan model ini, termasuk project baru. Untuk mengetahui detailnya, lihat
Versi dan siklus proses model.
Membuat Konten menggunakan Panggilan Fungsi Pydantic
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Contoh ini menunjukkan cara menggunakan Deklarasi Fungsi Pydantic untuk memengaruhi konten yang dihasilkan oleh Gemini MultiModal
Mempelajari lebih lanjut
Untuk dokumentasi mendetail yang menyertakan contoh kode ini, lihat artikel berikut:
Contoh kode
Kecuali dinyatakan lain, konten di halaman ini dilisensikan berdasarkan Lisensi Creative Commons Attribution 4.0, sedangkan contoh kode dilisensikan berdasarkan Lisensi Apache 2.0. Untuk mengetahui informasi selengkapnya, lihat Kebijakan Situs Google Developers. Java adalah merek dagang terdaftar dari Oracle dan/atau afiliasinya.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],[],[],[],null,["# Generate Content using Pydantic Function Calling\n\nThis sample demonstrates how to use Pydantic Function declaration to influence the content generated by Gemini MultiModal\n\nExplore further\n---------------\n\n\nFor detailed documentation that includes this code sample, see the following:\n\n- [Function calling reference](/vertex-ai/generative-ai/docs/model-reference/function-calling)\n\nCode sample\n-----------\n\n### Python\n\n\nBefore trying this sample, follow the Python setup instructions in the\n[Vertex AI quickstart using\nclient libraries](/vertex-ai/docs/start/client-libraries).\n\n\nFor more information, see the\n[Vertex AI Python API\nreference documentation](/python/docs/reference/aiplatform/latest).\n\n\nTo authenticate to Vertex AI, set up Application Default Credentials.\nFor more information, see\n\n[Set up authentication for a local development environment](/docs/authentication/set-up-adc-local-dev-environment).\n\n from google import genai\n from google.genai.types import GenerateContentConfig, HttpOptions\n\n def get_current_weather(location: str) -\u003e str:\n \"\"\"Example method. Returns the current weather.\n\n Args:\n location: The city and state, e.g. San Francisco, CA\n \"\"\"\n weather_map: dict[str, str] = {\n \"Boston, MA\": \"snowing\",\n \"San Francisco, CA\": \"foggy\",\n \"Seattle, WA\": \"raining\",\n \"Austin, TX\": \"hot\",\n \"Chicago, IL\": \"windy\",\n }\n return weather_map.get(location, \"unknown\")\n\n client = genai.Client(http_options=HttpOptions(api_version=\"v1\"))\n model_id = \"gemini-2.5-flash\"\n\n response = client.models.generate_content(\n model=model_id,\n contents=\"What is the weather like in Boston?\",\n config=GenerateContentConfig(\n tools=[get_current_weather],\n temperature=0,\n ),\n )\n\n print(response.text)\n # Example response:\n # The weather in Boston is sunny.\n\nWhat's next\n-----------\n\n\nTo search and filter code samples for other Google Cloud products, see the\n[Google Cloud sample browser](/docs/samples?product=googlegenaisdk)."]]