الاستناد إلى "خرائط Google"

from google import genai
from google.genai import types

client = genai.Client()

prompt = "What are the best Italian restaurants within a 15-minute walk from here?"

response = client.models.generate_content(
    model='gemini-2.5-flash-lite',
    contents=prompt,
    config=types.GenerateContentConfig(
        # Turn on grounding with Google Maps
        tools=[types.Tool(google_maps=types.GoogleMaps())],
        # Optionally provide the relevant location context (this is in Los Angeles)
        tool_config=types.ToolConfig(retrieval_config=types.RetrievalConfig(
            lat_lng=types.LatLng(
                latitude=34.050481, longitude=-118.248526))),
    ),
)

print("Generated Response:")
print(response.text)

if grounding := response.candidates[0].grounding_metadata:
  if grounding.grounding_chunks:
    print('-' * 40)
    print("Sources:")
    for chunk in grounding.grounding_chunks:
      print(f'- [{chunk.maps.title}]({chunk.maps.uri})')

import { GoogleGenAI } from "@google/gnai";

const ai = new GoogleGenAI({});

async function generateContentWithMapsGrounding() {
  const response = await ai.models.generateContent({
    model: "gemini-2.5-flash",
    contents: "What are the best Italian restaurants within a 15-minute walk from here?",
    config: {
      // Turn on grounding with Google Maps
      tools: [{ googleMaps: {} }],
      toolConfig: {
        retrievalConfig: {
          // Optionally provide the relevant location context (this is in Los Angeles)
          latLng: {
            latitude: 34.050481,
            longitude: -118.248526,
          },
        },
      },
    },
  });

  console.log("Generated Response:");
  console.log(response.text);

  const grounding = response.candidates[0]?.groundingMetadata;
  if (grounding?.groundingChunks) {
    console.log("-".repeat(40));
    console.log("Sources:");
    for (const chunk of grounding.groundingChunks) {
      if (chunk.maps) {
        console.log(`- [${chunk.maps.title}](${chunk.maps.uri})`);
      }
    }
  }
}

generateContentWithMapsGrounding();

curl -X POST 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent' \
  -H 'Content-Type: application/json' \
  -H "x-goog-api-key: ${GEMINI_API_KEY}" \
  -d '{
  "contents": [{
    "role": "user",
    "parts": [{
      "text": "What are the best Italian restaurants within a 15-minute walk from here?"
    }]
  }],
  "tools": [{"googleMaps": {}}],
  "toolConfig": {
    "retrievalConfig": {
      "latLng": {"latitude": 34.050481, "longitude": -118.248526}
    }
  }
}'

{
  "contents": [{
    "parts": [
      {"text": "Restaurants near Times Square."}
    ]
  }],
  "tools":  { "googleMaps": {} }
}

{
"contents": [{
    "parts": [
      {"text": "Restaurants near Times Square."}
    ]
  }],
  "tools":  { "googleMaps": { "enableWidget": true } }
}

{
  "contents": [{
    "parts": [
      {"text": "Restaurants near here."}
    ]
  }],
  "tools":  { "googleMaps": {} },
  "toolConfig":  {
    "retrievalConfig": {
      "latLng": {
        "latitude": 40.758896,
        "longitude": -73.985130
      }
    }
  }
}

{
  "candidates": [
    {
      "content": {
        "parts": [
          {
            "text": "CanteenM is an American restaurant with..."
          }
        ],
        "role": "model"
      },
      "groundingMetadata": {
        "groundingChunks": [
          {
            "maps": {
              "uri": "https://maps.google.com/?cid=13100894621228039586",
              "title": "Heaven on 7th Marketplace",
              "placeId": "places/ChIJ0-zA1vBZwokRon0fGj-6z7U"
            },
            // repeated ...
          }
        ],
        "groundingSupports": [
          {
            "segment": {
              "startIndex": 0,
              "endIndex": 79,
              "text": "CanteenM is an American restaurant with a 4.6-star rating and is open 24 hours."
            },
            "groundingChunkIndices": [0]
          },
          // repeated ...
        ],
        "webSearchQueries": [
          "restaurants near me"
        ],
        "googleMapsWidgetContextToken": "widgetcontent/..."
      }
    }
  ]
}

from google import genai
from google.genai import types

client = genai.Client()

prompt = "Is there a cafe near the corner of 1st and Main that has outdoor seating?"

response = client.models.generate_content(
    model='gemini-2.5-flash-lite',
    contents=prompt,
    config=types.GenerateContentConfig(
        # Turn on the Maps tool
        tools=[types.Tool(google_maps=types.GoogleMaps())],

        # Provide the relevant location context (this is in Los Angeles)
        tool_config=types.ToolConfig(retrieval_config=types.RetrievalConfig(
            lat_lng=types.LatLng(
                latitude=34.050481, longitude=-118.248526))),
    ),
)

print("Generated Response:")
print(response.text)

if grounding := response.candidates[0].grounding_metadata:
  if chunks := grounding.grounding_chunks:
    print('-' * 40)
    print("Sources:")
    for chunk in chunks:
      print(f'- [{chunk.maps.title}]({chunk.maps.uri})')
  ```

import { GoogleGenAI } from '@google/genai';

const ai = new GoogleGenAI({});

async function run() {
  const prompt = "Is there a cafe near the corner of 1st and Main that has outdoor seating?";

  const response = await ai.models.generateContent({
    model: 'gemini-2.5-flash',
    contents: prompt,
    config: {
      // Turn on the Maps tool
      tools: [{googleMaps: {}}],
      // Provide the relevant location context (this is in Los Angeles)
      toolConfig: {
        retrievalConfig: {
          latLng: {
            latitude: 34.050481,
            longitude: -118.248526
          }
        }
      }
    },
  });

  console.log("Generated Response:");
  console.log(response.text);

  const chunks = response.candidates[0].groundingMetadata?.groundingChunks;
  if (chunks) {
    console.log('-'.repeat(40));
    console.log("Sources:");
    for (const chunk of chunks) {
      if (chunk.maps) {
        console.log(`- [${chunk.maps.title}](${chunk.maps.uri})`);
      }
    }
  }
}

run();

curl -X POST 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent' \
  -H 'Content-Type: application/json' \
  -H "x-goog-api-key: ${GEMINI_API_KEY}" \
  -d '{
  "contents": [{
    "role": "user",
    "parts": [{
      "text": "Is there a cafe near the corner of 1st and Main that has outdoor seating?"
    }]
  }],
  "tools": [{"googleMaps": {}}],
  "toolConfig": {
    "retrievalConfig": {
      "latLng": {"latitude": 34.050481, "longitude": -118.248526}
    }
  }
}'

from google import genai
from google.genai import types

client = genai.Client()

prompt = "Which family-friendly restaurants near here have the best playground reviews?"

response = client.models.generate_content(
    model='gemini-2.5-flash',
    contents=prompt,
    config=types.GenerateContentConfig(
      tools=[types.Tool(google_maps=types.GoogleMaps())],
      tool_config=types.ToolConfig(retrieval_config=types.RetrievalConfig(
          # Provide the location as context; this is Austin, TX.
          lat_lng=types.LatLng(
              latitude=30.2672, longitude=-97.7431))),
    ),
)

print("Generated Response:")
print(response.text)

if grounding := response.candidates[0].grounding_metadata:
  if chunks := grounding.grounding_chunks:
    print('-' * 40)
    print("Sources:")
    for chunk in chunks:
      print(f'- [{chunk.maps.title}]({chunk.maps.uri})')

import { GoogleGenAI } from '@google/genai';

const ai = new GoogleGenAI({});

async function run() {
  const prompt = "Which family-friendly restaurants near here have the best playground reviews?";

  const response = await ai.models.generateContent({
    model: 'gemini-2.5-flash',
    contents: prompt,
    config: {
      tools: [{googleMaps: {}}],
      toolConfig: {
        retrievalConfig: {
          // Provide the location as context; this is Austin, TX.
          latLng: {
            latitude: 30.2672,
            longitude: -97.7431
          }
        }
      }
    },
  });

  console.log("Generated Response:");
  console.log(response.text);

  const chunks = response.candidates[0].groundingMetadata?.groundingChunks;
  if (chunks) {
    console.log('-'.repeat(40));
    console.log("Sources:");
    for (const chunk of chunks) {
      if (chunk.maps) {
        console.log(`- [${chunk.maps.title}](${chunk.maps.uri})`);
      }
    }
  }
}

run();

curl -X POST 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent' \
  -H 'Content-Type: application/json' \
  -H "x-goog-api-key: ${GEMINI_API_KEY}" \
  -d '{
  "contents": [{
    "role": "user",
    "parts": [{
      "text": "Which family-friendly restaurants near here have the best playground reviews?"
    }],
  }],
  "tools": [{"googleMaps": {}}],
  "toolConfig": {
    "retrievalConfig": {
      "latLng": {"latitude": 30.2672, "longitude": -97.7431}
    }
  }
}'

from google import genai
from google.genai import types

client = genai.Client()

prompt = "Plan a day in San Francisco for me. I want to see the Golden Gate Bridge, visit a museum, and have a nice dinner."

response = client.models.generate_content(
    model='gemini-2.5-flash',
    contents=prompt,
    config=types.GenerateContentConfig(
      tools=[types.Tool(google_maps=types.GoogleMaps(enable_widget=True))],
      tool_config=types.ToolConfig(retrieval_config=types.RetrievalConfig(
          # Provide the location as context, this is in San Francisco.
          lat_lng=types.LatLng(
              latitude=37.78193, longitude=-122.40476))),
    ),
)

print("Generated Response:")
print(response.text)

if grounding := response.candidates[0].grounding_metadata:
  if grounding.grounding_chunks:
    print('-' * 40)
    print("Sources:")
    for chunk in grounding.grounding_chunks:
      print(f'- [{chunk.maps.title}]({chunk.maps.uri})')

  if widget_token := grounding.google_maps_widget_context_token:
    print('-' * 40)
    print(f'<gmp-place-contextual context-token="{widget_token}"></gmp-place-contextual>')

import { GoogleGenAI } from '@google/genai';

const ai = new GoogleGenAI({});

async function run() {
  const prompt = "Plan a day in San Francisco for me. I want to see the Golden Gate Bridge, visit a museum, and have a nice dinner.";

  const response = await ai.models.generateContent({
    model: 'gemini-2.5-flash',
    contents: prompt,
    config: {
      tools: [{googleMaps: {enableWidget: true}}],
      toolConfig: {
        retrievalConfig: {
          // Provide the location as context, this is in San Francisco.
          latLng: {
            latitude: 37.78193,
            longitude: -122.40476
          }
        }
      }
    },
  });

  console.log("Generated Response:");
  console.log(response.text);

  const groundingMetadata = response.candidates[0]?.groundingMetadata;
  if (groundingMetadata) {
    if (groundingMetadata.groundingChunks) {
      console.log('-'.repeat(40));
      console.log("Sources:");
      for (const chunk of groundingMetadata.groundingChunks) {
        if (chunk.maps) {
          console.log(`- [${chunk.maps.title}](${chunk.maps.uri})`);
        }
      }
    }

    if (groundingMetadata.googleMapsWidgetContextToken) {
      console.log('-'.repeat(40));
      document.body.insertAdjacentHTML('beforeend', `<gmp-place-contextual context-token="${groundingMetadata.googleMapsWidgetContextToken}`"></gmp-place-contextual>`);
    }
  }
}

run();

curl -X POST 'https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash-lite:generateContent' \
  -H 'Content-Type: application/json' \
  -H "x-goog-api-key: ${GEMINI_API_KEY}" \
  -d '{
  "contents": [{
    "role": "user",
    "parts": [{
      "text": "Plan a day in San Francisco for me. I want to see the Golden Gate Bridge, visit a museum, and have a nice dinner."
    }]
  }],
  "tools": [{"googleMaps": {"enableWidget":"true"}}],
  "toolConfig": {
    "retrievalConfig": {
    "latLng": {"latitude": 37.78193, "longitude": -122.40476}
  }
  }
}'

@import url('https://fonts.googleapis.com/css2?family=Roboto&display=swap');

.GMP-attribution {

font-family: Roboto, Sans-Serif;
font-style: normal;
font-weight: 400;
font-size: 1rem;
letter-spacing: normal;
white-space: nowrap;
color: #5e5e5e;
}