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from google import genai from google.genai import types import time  client = genai.Client()  # Create the File Search store with an optional display name file_search_store = client.file_search_stores.create(config={'display_name': 'your-fileSearchStore-name'})  # Upload and import a file into the File Search store, supply a file name which will be visible in citations operation = client.file_search_stores.upload_to_file_search_store(   file='sample.txt',   file_search_store_name=file_search_store.name,   config={       'display_name' : 'display-file-name',   } )  # Wait until import is complete while not operation.done:     time.sleep(5)     operation = client.operations.get(operation)  # Ask a question about the file response = client.models.generate_content(     model="gemini-2.5-flash",     contents="""Can you tell me about Robert Graves""",     config=types.GenerateContentConfig(         tools=[             file_search=(                   file_search_store_names=[file_search_store.name]             )         ]     ) )  print(response.text) 

const { GoogleGenAI } = require('@google/genai');  const ai = new GoogleGenAI({});  async function run() {   // Create the File Search store with an optional display name   const fileSearchStore = await ai.fileSearchStores.create({     config: { displayName: 'your-fileSearchStore-name' }   });    // Upload and import a file into the File Search store, supply a file name which will be visible in citations   let operation = await ai.fileSearchStores.uploadToFileSearchStore({     file: 'file.txt',     fileSearchStoreName: fileSearchStore.name,     config: {       displayName: 'file-name',     }   });    // Wait until import is complete   while (!operation.done) {     await new Promise(resolve => setTimeout(resolve, 5000));     operation = await ai.operations.get({ operation });   }    // Ask a question about the file   const response = await ai.models.generateContent({     model: "gemini-2.5-flash",     contents: "Can you tell me about Robert Graves",     config: {       tools: [         {           fileSearch: {             fileSearchStoreNames: [fileSearchStore.name]           }         }       ]     }   });    console.log(response.text); }  run(); 

FILE_PATH="path/to/sample.pdf" MIME_TYPE=$(file -b --mime-type "${FILE_PATH}") NUM_BYTES=$(wc -c < "${FILE_PATH}")  # Create a FileSearchStore STORE_RESPONSE=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/fileSearchStores?key=${GEMINI_API_KEY}" \     -H "Content-Type: application/json" \     -d '{ "displayName": "My Store" }')  # Extract the store name (format: fileSearchStores/xxxxxxx) STORE_NAME=$(echo $STORE_RESPONSE | jq -r '.name')  # Initiate Resumable Upload to the Store TMP_HEADER="upload-header.tmp"  curl -s -D "${TMP_HEADER}" \ "https://generativelanguage.googleapis.com/upload/v1beta/${STORE_NAME}:uploadToFileSearchStore?key=${GEMINI_API_KEY}" \   -H "X-Goog-Upload-Protocol: resumable" \   -H "X-Goog-Upload-Command: start" \   -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \   -H "Content-Type: application/json" > /dev/null  # Extract upload_url from headers UPLOAD_URL=$(grep -i "x-goog-upload-url: " "${TMP_HEADER}" | cut -d" " -f2 | tr -d "\r") rm "${TMP_HEADER}"  # --- Upload the actual bytes --- curl "${UPLOAD_URL}" \   -H "Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Offset: 0" \   -H "X-Goog-Upload-Command: upload, finalize" \   --data-binary "@${FILE_PATH}" 2> /dev/null  # Generate content using the FileSearchStore curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent" \     -H "x-goog-api-key: $GEMINI_API_KEY" \     -H 'Content-Type: application/json' \     -X POST \     -d '{             "contents": [{                 "parts":[{"text": "What does the research say about ..."}]                       }],             "tools": [{                 "file_search": { "file_search_store_names":["'$STORE_NAME'"] }             }]         }' 2> /dev/null > response.json  cat response.json 

from google import genai from google.genai import types import time  client = genai.Client()  # Upload the file using the Files API, supply a file name which will be visible in citations sample_file = client.files.upload(file='sample.txt', config={'name': 'display_file_name'})  # Create the File Search store with an optional display name file_search_store = client.file_search_stores.create(config={'display_name': 'your-fileSearchStore-name'})  # Import the file into the File Search store operation = client.file_search_stores.import_file(     file_search_store_name=file_search_store.name,     file_name=sample_file.name )  # Wait until import is complete while not operation.done:     time.sleep(5)     operation = client.operations.get(operation)  # Ask a question about the file response = client.models.generate_content(     model="gemini-2.5-flash",     contents="""Can you tell me about Robert Graves""",     config=types.GenerateContentConfig(         tools=[             file_search=(                   file_search_store_names=[file_search_store.name]             )         ]     ) )  print(response.text) 

const { GoogleGenAI } = require('@google/genai');  const ai = new GoogleGenAI({});  async function run() {   // Upload the file using the Files API, supply a file name which will be visible in citations   const sampleFile = await ai.files.upload({     file: 'sample.txt',     config: { name: 'file-name' }   });    // Create the File Search store with an optional display name   const fileSearchStore = await ai.fileSearchStores.create({     config: { displayName: 'your-fileSearchStore-name' }   });    // Import the file into the File Search store   let operation = await ai.fileSearchStores.importFile({     fileSearchStoreName: fileSearchStore.name,     fileName: sampleFile.name   });    // Wait until import is complete   while (!operation.done) {     await new Promise(resolve => setTimeout(resolve, 5000));     operation = await ai.operations.get({ operation: operation });   }    // Ask a question about the file   const response = await ai.models.generateContent({     model: "gemini-2.5-flash",     contents: "Can you tell me about Robert Graves",     config: {       tools: [         {           fileSearch: {             fileSearchStoreNames: [fileSearchStore.name]           }         }       ]     }   });    console.log(response.text); }  run(); 

FILE_PATH="path/to/sample.pdf" MIME_TYPE=$(file -b --mime-type "${FILE_PATH}") NUM_BYTES=$(wc -c < "${FILE_PATH}")  # Create a FileSearchStore STORE_RESPONSE=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/fileSearchStores?key=${GEMINI_API_KEY}" \     -H "Content-Type: application/json" \     -d '{ "displayName": "My Store" }')  STORE_NAME=$(echo $STORE_RESPONSE | jq -r '.name')  # Initiate Resumable Upload to the Store TMP_HEADER="upload-header.tmp"  curl -s -X POST "https://generativelanguage.googleapis.com/upload/v1beta/files?key=${GEMINI_API_KEY}" \   -D "${TMP_HEADER}" \   -H "X-Goog-Upload-Protocol: resumable" \   -H "X-Goog-Upload-Command: start" \   -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \   -H "Content-Type: application/json" 2> /dev/null  UPLOAD_URL=$(grep -i "x-goog-upload-url: " "${TMP_HEADER}" | cut -d" " -f2 | tr -d "\r") rm "${TMP_HEADER}"  # Upload the actual bytes. curl -s -X POST "${UPLOAD_URL}" \   -H "Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Offset: 0" \   -H "X-Goog-Upload-Command: upload, finalize" \   --data-binary "@${FILE_PATH}" 2> /dev/null > file_info.json  file_uri=$(jq ".file.name" file_info.json)  # Import files into the file search store operation_name=$(curl "https://generativelanguage.googleapis.com/v1beta/${STORE_NAME}:importFile?key=${GEMINI_API_KEY}" \   -H "Content-Type: application/json" \   -X POST \   -d '{         "file_name":'$file_uri'     }' | jq -r .name)  # Wait for long running operation to complete while true; do   # Get the full JSON status and store it in a variable.   status_response=$(curl -s -H "x-goog-api-key: $GEMINI_API_KEY" "https://generativelanguage.googleapis.com/v1beta/${operation_name}")    # Check the "done" field from the JSON stored in the variable.   is_done=$(echo "${status_response}" | jq .done)    if [ "${is_done}" = "true" ]; then     break   fi   # Wait for 10 seconds before checking again.   sleep 10 done  # Generate content using the FileSearchStore curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=${GEMINI_API_KEY}" \     -H 'Content-Type: application/json' \     -X POST \     -d '{             "contents": [{                 "parts":[{"text": "What does the research say about ..."}]                       }],             "tools": [{                 "file_search": { "file_search_store_names":["'$STORE_NAME'"] }             }]         }' 2> /dev/null > response.json  cat response.json 

# Upload and import and upload the file into the File Search store with a custom chunking configuration operation = client.file_search_stores.upload_to_file_search_store(     file_search_store_name=file_search_store.name,     file_name=sample_file.name,     config={         'chunking_config': {           'white_space_config': {             'max_tokens_per_chunk': 200,             'max_overlap_tokens': 20           }         }     } ) 

// Upload and import and upload the file into the File Search store with a custom chunking configuration let operation = await ai.fileSearchStores.uploadToFileSearchStore({   file: 'file.txt',   fileSearchStoreName: fileSearchStore.name,   config: {     displayName: 'file-name',     chunkingConfig: {       whiteSpaceConfig: {         maxTokensPerChunk: 200,         maxOverlapTokens: 20       }     }   } }); 

FILE_PATH="path/to/sample.pdf" MIME_TYPE=$(file -b --mime-type "${FILE_PATH}") NUM_BYTES=$(wc -c < "${FILE_PATH}")  # Create a FileSearchStore STORE_RESPONSE=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/fileSearchStores?key=${GEMINI_API_KEY}" \     -H "Content-Type: application/json" \     -d '{ "displayName": "My Store" }')  # Extract the store name (format: fileSearchStores/xxxxxxx) STORE_NAME=$(echo $STORE_RESPONSE | jq -r '.name')  # Initiate Resumable Upload to the Store TMP_HEADER="upload-header.tmp"  curl -s -D "${TMP_HEADER}" \ "https://generativelanguage.googleapis.com/upload/v1beta/${STORE_NAME}:uploadToFileSearchStore?key=${GEMINI_API_KEY}" \   -H "X-Goog-Upload-Protocol: resumable" \   -H "X-Goog-Upload-Command: start" \   -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \   -H "Content-Type: application/json" > /dev/null   -d '{         "chunking_config": {           "white_space_config": {             "max_tokens_per_chunk": 200,             "max_overlap_tokens": 20           }         }     }'  # Extract upload_url from headers UPLOAD_URL=$(grep -i "x-goog-upload-url: " "${TMP_HEADER}" | cut -d" " -f2 | tr -d "\r") rm "${TMP_HEADER}"  # --- Upload the actual bytes --- curl "${UPLOAD_URL}" \   -H "Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Offset: 0" \   -H "X-Goog-Upload-Command: upload, finalize" \   --data-binary "@${FILE_PATH}" 2> /dev/null 

# Create a File Search store (including optional display_name for easier reference) file_search_store = client.file_search_stores.create(config={'display_name': 'my-file_search-store-123'})  # List all your File Search stores for file_search_store in client.file_search_stores.list():     print(file_search_store)  # Get a specific File Search store by name my_file_search_store = client.file_search_stores.get(name='fileSearchStores/my-file_search-store-123')  # Delete a File Search store client.file_search_stores.delete(name='fileSearchStores/my-file_search-store-123', config={'force': True}) 

// Create a File Search store (including optional display_name for easier reference) const fileSearchStore = await ai.fileSearchStores.create({   config: { displayName: 'my-file_search-store-123' } });  // List all your File Search stores const fileSearchStores = await ai.fileSearchStores.list(); for await (const store of fileSearchStores) {   console.log(store); }  // Get a specific File Search store by name const myFileSearchStore = await ai.fileSearchStores.get({   name: 'fileSearchStores/my-file_search-store-123' });  // Delete a File Search store await ai.fileSearchStores.delete({   name: 'fileSearchStores/my-file_search-store-123',   config: { force: true } }); 

# Create a File Search store (including optional display_name for easier reference) curl -X POST "https://generativelanguage.googleapis.com/v1beta/fileSearchStores?key=${GEMINI_API_KEY}" \     -H "Content-Type: application/json"      -d '{ "displayName": "My Store" }'  # List all your File Search stores curl "https://generativelanguage.googleapis.com/v1beta/fileSearchStores?key=${GEMINI_API_KEY}" \  # Get a specific File Search store by name curl "https://generativelanguage.googleapis.com/v1beta/fileSearchStores/my-file_search-store-123?key=${GEMINI_API_KEY}"  # Delete a File Search store curl -X DELETE "https://generativelanguage.googleapis.com/v1beta/fileSearchStores/my-file_search-store-123?key=${GEMINI_API_KEY}" 

# Import the file into the File Search store with custom metadata op = client.file_search_stores.import_file(     file_search_store_name=file_search_store.name,     file_name=sample_file.name,     custom_metadata=[         {"key": "author", "string_value": "Robert Graves"},         {"key": "year", "numeric_value": 1934}     ] ) 

// Import the file into the File Search store with custom metadata let operation = await ai.fileSearchStores.importFile({   fileSearchStoreName: fileSearchStore.name,   fileName: sampleFile.name,   config: {     customMetadata: [       { key: "author", stringValue: "Robert Graves" },       { key: "year", numericValue: 1934 }     ]   } }); 

FILE_PATH="path/to/sample.pdf" MIME_TYPE=$(file -b --mime-type "${FILE_PATH}") NUM_BYTES=$(wc -c < "${FILE_PATH}")  # Create a FileSearchStore STORE_RESPONSE=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/fileSearchStores?key=${GEMINI_API_KEY}" \     -H "Content-Type: application/json" \     -d '{ "displayName": "My Store" }')  # Extract the store name (format: fileSearchStores/xxxxxxx) STORE_NAME=$(echo $STORE_RESPONSE | jq -r '.name')  # Initiate Resumable Upload to the Store TMP_HEADER="upload-header.tmp"  curl -s -D "${TMP_HEADER}" \   "https://generativelanguage.googleapis.com/upload/v1beta/${STORE_NAME}:uploadToFileSearchStore?key=${GEMINI_API_KEY}" \   -H "X-Goog-Upload-Protocol: resumable" \   -H "X-Goog-Upload-Command: start" \   -H "X-Goog-Upload-Header-Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Header-Content-Type: ${MIME_TYPE}" \   -H "Content-Type: application/json" \   -d '{         "custom_metadata": [           {"key": "author", "string_value": "Robert Graves"},           {"key": "year", "numeric_value": 1934}         ]     }' > /dev/null  # Extract upload_url from headers UPLOAD_URL=$(grep -i "x-goog-upload-url: " "${TMP_HEADER}" | cut -d" " -f2 | tr -d "\r") rm "${TMP_HEADER}"  # --- Upload the actual bytes --- curl "${UPLOAD_URL}" \   -H "Content-Length: ${NUM_BYTES}" \   -H "X-Goog-Upload-Offset: 0" \   -H "X-Goog-Upload-Command: upload, finalize" \   --data-binary "@${FILE_PATH}" 2> /dev/null 

# Use the metadata filter to search within a subset of documents response = client.models.generate_content(     model="gemini-2.5-flash",     contents="Tell me about the book 'I, Claudius'",     config=types.GenerateContentConfig(         tools=[             types.Tool(                 file_search=types.FileSearch(                     file_search_store_names=[file_search_store.name],                     metadata_filter="author=Robert Graves",                 )             )         ]     ) )  print(response.text) 

// Use the metadata filter to search within a subset of documents const response = await ai.models.generateContent({   model: "gemini-2.5-flash",   contents: "Tell me about the book 'I, Claudius'",   config: {     tools: [       {         fileSearch: {           fileSearchStoreNames: [fileSearchStore.name],           metadataFilter: 'author="Robert Graves"',         }       }     ]   } });  console.log(response.text); 

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-flash:generateContent?key=${GEMINI_API_KEY}" \     -H 'Content-Type: application/json' \     -X POST \     -d '{             "contents": [{                 "parts":[{"text": "Tell me about the book I, Claudius"}]                       }],             "tools": [{                 "file_search": {                      "file_search_store_names":["'$STORE_NAME'"],                     "metadata_filter": "author = \"Robert Graves\""                 }             }]         }' 2> /dev/null > response.json  cat response.json 

print(response.candidates[0].grounding_metadata) 

console.log(JSON.stringify(response.candidates?.[0]?.groundingMetadata, null, 2));