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@ai-sdk/google - npm Package Compare versions

Comparing version 0.0.16 to 0.0.17

96

./dist/index.js

@@ -178,3 +178,2 @@ "use strict";

}) {
var _a;
const type = mode.type;

@@ -211,10 +210,2 @@ const warnings = [];

case "regular": {
const functionDeclarations = (_a = mode.tools) == null ? void 0 : _a.map((tool) => {
var _a2;
return {
name: tool.name,
description: (_a2 = tool.description) != null ? _a2 : "",
parameters: prepareJsonSchema(tool.parameters)
};
});
return {

@@ -224,3 +215,3 @@ args: {

contents,
tools: functionDeclarations == null ? void 0 : { functionDeclarations }
...prepareToolsAndToolConfig(mode)
},

@@ -380,18 +371,2 @@ warnings

};
function prepareJsonSchema(jsonSchema) {
if (typeof jsonSchema !== "object") {
return jsonSchema;
}
if (Array.isArray(jsonSchema)) {
return jsonSchema.map(prepareJsonSchema);
}
const result = {};
for (const [key, value] of Object.entries(jsonSchema)) {
if (key === "additionalProperties" || key === "$schema") {
continue;
}
result[key] = prepareJsonSchema(value);
}
return result;
}
function getToolCallsFromParts({

@@ -457,2 +432,71 @@ parts,

});
function prepareToolsAndToolConfig(mode) {
var _a;
const tools = ((_a = mode.tools) == null ? void 0 : _a.length) ? mode.tools : void 0;
if (tools == null) {
return { tools: void 0, toolConfig: void 0 };
}
const mappedTools = {
functionDeclarations: tools.map((tool) => {
var _a2;
return {
name: tool.name,
description: (_a2 = tool.description) != null ? _a2 : "",
parameters: prepareJsonSchema(tool.parameters)
};
})
};
const toolChoice = mode.toolChoice;
if (toolChoice == null) {
return { tools: mappedTools, toolConfig: void 0 };
}
const type = toolChoice.type;
switch (type) {
case "auto":
return {
tools: mappedTools,
toolConfig: { functionCallingConfig: { mode: "AUTO" } }
};
case "none":
return {
tools: mappedTools,
toolConfig: { functionCallingConfig: { mode: "NONE" } }
};
case "required":
return {
tools: mappedTools,
toolConfig: { functionCallingConfig: { mode: "ANY" } }
};
case "tool":
return {
tools: mappedTools,
toolConfig: {
functionCallingConfig: {
mode: "ANY",
allowedFunctionNames: [toolChoice.toolName]
}
}
};
default: {
const _exhaustiveCheck = type;
throw new Error(`Unsupported tool choice type: ${_exhaustiveCheck}`);
}
}
}
function prepareJsonSchema(jsonSchema) {
if (typeof jsonSchema !== "object") {
return jsonSchema;
}
if (Array.isArray(jsonSchema)) {
return jsonSchema.map(prepareJsonSchema);
}
const result = {};
for (const [key, value] of Object.entries(jsonSchema)) {
if (key === "additionalProperties" || key === "$schema") {
continue;
}
result[key] = prepareJsonSchema(value);
}
return result;
}

@@ -459,0 +503,0 @@ // src/google-facade.ts

@@ -178,3 +178,2 @@ "use strict";

}) {
var _a;
const type = mode.type;

@@ -211,10 +210,2 @@ const warnings = [];

case "regular": {
const functionDeclarations = (_a = mode.tools) == null ? void 0 : _a.map((tool) => {
var _a2;
return {
name: tool.name,
description: (_a2 = tool.description) != null ? _a2 : "",
parameters: prepareJsonSchema(tool.parameters)
};
});
return {

@@ -224,3 +215,3 @@ args: {

contents,
tools: functionDeclarations == null ? void 0 : { functionDeclarations }
...prepareToolsAndToolConfig(mode)
},

@@ -380,18 +371,2 @@ warnings

};
function prepareJsonSchema(jsonSchema) {
if (typeof jsonSchema !== "object") {
return jsonSchema;
}
if (Array.isArray(jsonSchema)) {
return jsonSchema.map(prepareJsonSchema);
}
const result = {};
for (const [key, value] of Object.entries(jsonSchema)) {
if (key === "additionalProperties" || key === "$schema") {
continue;
}
result[key] = prepareJsonSchema(value);
}
return result;
}
function getToolCallsFromParts({

@@ -457,2 +432,71 @@ parts,

});
function prepareToolsAndToolConfig(mode) {
var _a;
const tools = ((_a = mode.tools) == null ? void 0 : _a.length) ? mode.tools : void 0;
if (tools == null) {
return { tools: void 0, toolConfig: void 0 };
}
const mappedTools = {
functionDeclarations: tools.map((tool) => {
var _a2;
return {
name: tool.name,
description: (_a2 = tool.description) != null ? _a2 : "",
parameters: prepareJsonSchema(tool.parameters)
};
})
};
const toolChoice = mode.toolChoice;
if (toolChoice == null) {
return { tools: mappedTools, toolConfig: void 0 };
}
const type = toolChoice.type;
switch (type) {
case "auto":
return {
tools: mappedTools,
toolConfig: { functionCallingConfig: { mode: "AUTO" } }
};
case "none":
return {
tools: mappedTools,
toolConfig: { functionCallingConfig: { mode: "NONE" } }
};
case "required":
return {
tools: mappedTools,
toolConfig: { functionCallingConfig: { mode: "ANY" } }
};
case "tool":
return {
tools: mappedTools,
toolConfig: {
functionCallingConfig: {
mode: "ANY",
allowedFunctionNames: [toolChoice.toolName]
}
}
};
default: {
const _exhaustiveCheck = type;
throw new Error(`Unsupported tool choice type: ${_exhaustiveCheck}`);
}
}
}
function prepareJsonSchema(jsonSchema) {
if (typeof jsonSchema !== "object") {
return jsonSchema;
}
if (Array.isArray(jsonSchema)) {
return jsonSchema.map(prepareJsonSchema);
}
const result = {};
for (const [key, value] of Object.entries(jsonSchema)) {
if (key === "additionalProperties" || key === "$schema") {
continue;
}
result[key] = prepareJsonSchema(value);
}
return result;
}

@@ -459,0 +503,0 @@ // src/google-facade.ts

{
"name": "@ai-sdk/google",
"version": "0.0.16",
"version": "0.0.17",
"license": "Apache-2.0",

@@ -21,4 +21,4 @@ "sideEffects": false,

"dependencies": {
"@ai-sdk/provider": "0.0.7",
"@ai-sdk/provider-utils": "0.0.10"
"@ai-sdk/provider": "0.0.8",
"@ai-sdk/provider-utils": "0.0.11"
},

@@ -25,0 +25,0 @@ "devDependencies": {

# Vercel AI SDK - Google Generative AI Provider
The Google provider for the [Vercel AI SDK](https://sdk.vercel.ai/docs) contains language model support for the [Google Generative AI](https://ai.google/discover/generativeai/) APIs.
It creates language model objects that can be used with the `generateText`, `streamText`, `generateObject`, and `streamObject` AI functions.
The **[Google Generative AI provider](https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai)** for the [Vercel AI SDK](https://sdk.vercel.ai/docs) contains language model support for the [Google Generative AI](https://ai.google/discover/generativeai/) APIs.
## Setup
The Google provider is available in the `@ai-sdk/google` module. You can install it with
The Google Generative AI provider is available in the `@ai-sdk/google` module. You can install it with

@@ -22,55 +21,16 @@ ```bash

If you need a customized setup, you can import `createGoogleGenerativeAI` from `@ai-sdk/google` and create a provider instance with your settings:
## Example
```ts
import { createGoogleGenerativeAI } from '@ai-sdk/google';
import { google } from '@ai-sdk/google';
import { generateText } from 'ai';
const google = createGoogleGenerativeAI({
// custom settings
const { text } = await generateText({
model: google('models/gemini-pro'),
prompt: 'Write a vegetarian lasagna recipe for 4 people.',
});
```
You can use the following optional settings to customize the Google Generative AI provider instance:
## Documentation
- **baseURL** _string_
Use a different URL prefix for API calls, e.g. to use proxy servers.
The default prefix is `https://generativelanguage.googleapis.com/v1beta`.
- **apiKey** _string_
API key that is being send using the `x-goog-api-key` header.
It defaults to the `GOOGLE_GENERATIVE_AI_API_KEY` environment variable.
- **headers** _Record<string,string>_
Custom headers to include in the requests.
## Models
You can create models that call the [Google Generative AI API](https://ai.google.dev/api/rest) using the provider instance.
The first argument is the model id, e.g. `models/gemini-pro`.
The models support tool calls and some have multi-modal capabilities.
```ts
const model = google('models/gemini-pro');
```
Google Generative AI models support also some model specific settings that are not part of the [standard call settings](/docs/ai-core/settings).
You can pass them as an options argument:
```ts
const model = google('models/gemini-pro', {
topK: 0.2,
});
```
The following optional settings are available for Google Generative AI models:
- **topK** _number_
Optional. The maximum number of tokens to consider when sampling.
Models use nucleus sampling or combined Top-k and nucleus sampling.
Top-k sampling considers the set of topK most probable tokens.
Models running with nucleus sampling don't allow topK setting.
Please check out the **[Google Generative AI provider documentation](https://sdk.vercel.ai/providers/ai-sdk-providers/google-generative-ai)** for more information.

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