Merge pull request #88 from google-gemini/update-embeddings-samples

updating embedding model to latest model

Author: soosung80

go/embed.go

@@ -26,7 +26,7 @@ func EmbedContent() error {
 	contents := []*genai.Content{
 		genai.NewContentFromText(text, genai.RoleUser),
 	}
-	result, err := client.Models.EmbedContent(ctx, "text-embedding-004", 
+	result, err := client.Models.EmbedContent(ctx, "gemini-embedding-001", 
 		contents, &genai.EmbedContentConfig{
 			OutputDimensionality: &outputDim,
 	})
@@ -61,7 +61,7 @@ func BatchEmbedContents() error {
 	}
 
 	outputDim := int32(10)
-	result, err := client.Models.EmbedContent(ctx, "text-embedding-004", contents, &genai.EmbedContentConfig{
+	result, err := client.Models.EmbedContent(ctx, "gemini-embedding-001", contents, &genai.EmbedContentConfig{
 		OutputDimensionality: &outputDim,
 	})
 	if err != nil {

javascript/embed.js

@@ -24,7 +24,7 @@ export async function embedContent() {
   const ai = new GoogleGenAI({ apiKey: process.env.GEMINI_API_KEY });
   const text = "Hello World!";
   const result = await ai.models.embedContent({
-    model: "text-embedding-004",
+    model: "gemini-embedding-001",
     contents: text,
     config: { outputDimensionality: 10 },
   });
@@ -44,7 +44,7 @@ export async function batchEmbedContents() {
     "How does the brain work?",
   ];
   const result = await ai.models.embedContent({
-    model: "text-embedding-004",
+    model: "gemini-embedding-001",
     contents: texts,
     config: { outputDimensionality: 10 },
   });

python/embed.py

@@ -25,7 +25,7 @@ def test_embed_content(self):
         client = genai.Client()
         text = "Hello World!"
         result = client.models.embed_content(
-            model="text-embedding-004",
+            model="gemini-embedding-001",
             contents=text,
             config=types.EmbedContentConfig(output_dimensionality=10),
         )
@@ -44,7 +44,7 @@ def test_batch_embed_contents(self):
             "How does the brain work?",
         ]
         result = client.models.embed_content(
-            model="text-embedding-004",
+            model="gemini-embedding-001",
             contents=texts,
             config=types.EmbedContentConfig(output_dimensionality=10),
         )

rest/embed.sh

@@ -0,0 +1,35 @@
+set -eu
+
+echo "[START embed_content]"
+# [START embed_content]
+curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-001:embedContent" \
+-H "x-goog-api-key: $GEMINI_API_KEY" \
+-H 'Content-Type: application/json' \
+-d '{"model": "models/gemini-embedding-001",
+     "content": {
+     "parts":[{
+     "text": "What is the meaning of life?"}]}
+    }'
+# [END embed_content]
+
+echo "[START batch_embed_contents]"
+# [START batch_embed_contents]
+curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-embedding-001:batchEmbedContents" \
+-H "x-goog-api-key: $GEMINI_API_KEY" \
+-H 'Content-Type: application/json' \
+-d '{"requests": [{
+      "model": "models/gemini-embedding-001",
+      "content": {
+      "parts":[{
+        "text": "What is the meaning of life?"}]}, },
+      {
+      "model": "models/gemini-embedding-001",
+      "content": {
+      "parts":[{
+        "text": "How much wood would a woodchuck chuck?"}]}, },
+      {
+      "model": "models/gemini-embedding-001",
+      "content": {
+      "parts":[{
+        "text": "How does the brain work?"}]}, }, ]}' 2> /dev/null | grep -C 5 values
+# [END batch_embed_contents]