mirror of
https://github.com/getcompanion-ai/co-mono.git
synced 2026-04-21 17:00:45 +00:00
Massive refactor of API
- Switch to function based API - Anthropic SDK style async generator - Fully typed with escape hatches for custom models
This commit is contained in:
Mario Zechner
parent
004de3c9d0
commit
66cefb236e
29 changed files with 5835 additions and 6225 deletions
|
|
@ -1,19 +1,21 @@
|
|||
import {
|
||||
type Content,
|
||||
type FinishReason,
|
||||
FinishReason,
|
||||
FunctionCallingConfigMode,
|
||||
type GenerateContentConfig,
|
||||
type GenerateContentParameters,
|
||||
GoogleGenAI,
|
||||
type Part,
|
||||
} from "@google/genai";
|
||||
import { QueuedGenerateStream } from "../generate.js";
|
||||
import { calculateCost } from "../models.js";
|
||||
import type {
|
||||
Api,
|
||||
AssistantMessage,
|
||||
Context,
|
||||
LLM,
|
||||
LLMOptions,
|
||||
Message,
|
||||
GenerateFunction,
|
||||
GenerateOptions,
|
||||
GenerateStream,
|
||||
Model,
|
||||
StopReason,
|
||||
TextContent,
|
||||
|
|
@ -23,7 +25,7 @@ import type {
|
|||
} from "../types.js";
|
||||
import { transformMessages } from "./utils.js";
|
||||
|
||||
export interface GoogleLLMOptions extends LLMOptions {
|
||||
export interface GoogleOptions extends GenerateOptions {
|
||||
toolChoice?: "auto" | "none" | "any";
|
||||
thinking?: {
|
||||
enabled: boolean;
|
||||
|
|
@ -31,38 +33,20 @@ export interface GoogleLLMOptions extends LLMOptions {
|
|||
};
|
||||
}
|
||||
|
||||
export class GoogleLLM implements LLM<GoogleLLMOptions> {
|
||||
private client: GoogleGenAI;
|
||||
private modelInfo: Model;
|
||||
export const streamGoogle: GenerateFunction<"google-generative-ai"> = (
|
||||
model: Model<"google-generative-ai">,
|
||||
context: Context,
|
||||
options?: GoogleOptions,
|
||||
): GenerateStream => {
|
||||
const stream = new QueuedGenerateStream();
|
||||
|
||||
constructor(model: Model, apiKey?: string) {
|
||||
if (!apiKey) {
|
||||
if (!process.env.GEMINI_API_KEY) {
|
||||
throw new Error(
|
||||
"Gemini API key is required. Set GEMINI_API_KEY environment variable or pass it as an argument.",
|
||||
);
|
||||
}
|
||||
apiKey = process.env.GEMINI_API_KEY;
|
||||
}
|
||||
this.client = new GoogleGenAI({ apiKey });
|
||||
this.modelInfo = model;
|
||||
}
|
||||
|
||||
getModel(): Model {
|
||||
return this.modelInfo;
|
||||
}
|
||||
|
||||
getApi(): string {
|
||||
return "google-generative-ai";
|
||||
}
|
||||
|
||||
async generate(context: Context, options?: GoogleLLMOptions): Promise<AssistantMessage> {
|
||||
(async () => {
|
||||
const output: AssistantMessage = {
|
||||
role: "assistant",
|
||||
content: [],
|
||||
api: this.getApi(),
|
||||
provider: this.modelInfo.provider,
|
||||
model: this.modelInfo.id,
|
||||
api: "google-generative-ai" as Api,
|
||||
provider: model.provider,
|
||||
model: model.id,
|
||||
usage: {
|
||||
input: 0,
|
||||
output: 0,
|
||||
|
|
@ -72,70 +56,20 @@ export class GoogleLLM implements LLM<GoogleLLMOptions> {
|
|||
},
|
||||
stopReason: "stop",
|
||||
};
|
||||
|
||||
try {
|
||||
const contents = this.convertMessages(context.messages);
|
||||
const client = createClient(options?.apiKey);
|
||||
const params = buildParams(model, context, options);
|
||||
const googleStream = await client.models.generateContentStream(params);
|
||||
|
||||
// Build generation config
|
||||
const generationConfig: GenerateContentConfig = {};
|
||||
if (options?.temperature !== undefined) {
|
||||
generationConfig.temperature = options.temperature;
|
||||
}
|
||||
if (options?.maxTokens !== undefined) {
|
||||
generationConfig.maxOutputTokens = options.maxTokens;
|
||||
}
|
||||
|
||||
// Build the config object
|
||||
const config: GenerateContentConfig = {
|
||||
...(Object.keys(generationConfig).length > 0 && generationConfig),
|
||||
...(context.systemPrompt && { systemInstruction: context.systemPrompt }),
|
||||
...(context.tools && { tools: this.convertTools(context.tools) }),
|
||||
};
|
||||
|
||||
// Add tool config if needed
|
||||
if (context.tools && options?.toolChoice) {
|
||||
config.toolConfig = {
|
||||
functionCallingConfig: {
|
||||
mode: this.mapToolChoice(options.toolChoice),
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
// Add thinking config if enabled and model supports it
|
||||
if (options?.thinking?.enabled && this.modelInfo.reasoning) {
|
||||
config.thinkingConfig = {
|
||||
includeThoughts: true,
|
||||
...(options.thinking.budgetTokens !== undefined && { thinkingBudget: options.thinking.budgetTokens }),
|
||||
};
|
||||
}
|
||||
|
||||
// Abort signal
|
||||
if (options?.signal) {
|
||||
if (options.signal.aborted) {
|
||||
throw new Error("Request aborted");
|
||||
}
|
||||
config.abortSignal = options.signal;
|
||||
}
|
||||
|
||||
// Build the request parameters
|
||||
const params: GenerateContentParameters = {
|
||||
model: this.modelInfo.id,
|
||||
contents,
|
||||
config,
|
||||
};
|
||||
|
||||
const stream = await this.client.models.generateContentStream(params);
|
||||
|
||||
options?.onEvent?.({ type: "start", model: this.modelInfo.id, provider: this.modelInfo.provider });
|
||||
stream.push({ type: "start", partial: output });
|
||||
let currentBlock: TextContent | ThinkingContent | null = null;
|
||||
for await (const chunk of stream) {
|
||||
// Extract parts from the chunk
|
||||
for await (const chunk of googleStream) {
|
||||
const candidate = chunk.candidates?.[0];
|
||||
if (candidate?.content?.parts) {
|
||||
for (const part of candidate.content.parts) {
|
||||
if (part.text !== undefined) {
|
||||
const isThinking = part.thought === true;
|
||||
|
||||
// Check if we need to switch blocks
|
||||
if (
|
||||
!currentBlock ||
|
||||
(isThinking && currentBlock.type !== "thinking") ||
|
||||
|
|
@ -143,50 +77,60 @@ export class GoogleLLM implements LLM<GoogleLLMOptions> {
|
|||
) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
options?.onEvent?.({ type: "text_end", content: currentBlock.text });
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
options?.onEvent?.({ type: "thinking_end", content: currentBlock.thinking });
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
// Start new block
|
||||
if (isThinking) {
|
||||
currentBlock = { type: "thinking", thinking: "", thinkingSignature: undefined };
|
||||
options?.onEvent?.({ type: "thinking_start" });
|
||||
stream.push({ type: "thinking_start", partial: output });
|
||||
} else {
|
||||
currentBlock = { type: "text", text: "" };
|
||||
options?.onEvent?.({ type: "text_start" });
|
||||
stream.push({ type: "text_start", partial: output });
|
||||
}
|
||||
output.content.push(currentBlock);
|
||||
}
|
||||
|
||||
// Append content to current block
|
||||
if (currentBlock.type === "thinking") {
|
||||
currentBlock.thinking += part.text;
|
||||
currentBlock.thinkingSignature = part.thoughtSignature;
|
||||
options?.onEvent?.({
|
||||
stream.push({
|
||||
type: "thinking_delta",
|
||||
content: currentBlock.thinking,
|
||||
delta: part.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
currentBlock.text += part.text;
|
||||
options?.onEvent?.({ type: "text_delta", content: currentBlock.text, delta: part.text });
|
||||
stream.push({ type: "text_delta", delta: part.text, partial: output });
|
||||
}
|
||||
}
|
||||
|
||||
// Handle function calls
|
||||
if (part.functionCall) {
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
options?.onEvent?.({ type: "text_end", content: currentBlock.text });
|
||||
stream.push({
|
||||
type: "text_end",
|
||||
content: currentBlock.text,
|
||||
partial: output,
|
||||
});
|
||||
} else {
|
||||
options?.onEvent?.({ type: "thinking_end", content: currentBlock.thinking });
|
||||
stream.push({
|
||||
type: "thinking_end",
|
||||
content: currentBlock.thinking,
|
||||
partial: output,
|
||||
});
|
||||
}
|
||||
currentBlock = null;
|
||||
}
|
||||
|
||||
// Add tool call
|
||||
const toolCallId = part.functionCall.id || `${part.functionCall.name}_${Date.now()}`;
|
||||
const toolCall: ToolCall = {
|
||||
type: "toolCall",
|
||||
|
|
@ -195,21 +139,18 @@ export class GoogleLLM implements LLM<GoogleLLMOptions> {
|
|||
arguments: part.functionCall.args as Record<string, any>,
|
||||
};
|
||||
output.content.push(toolCall);
|
||||
options?.onEvent?.({ type: "toolCall", toolCall });
|
||||
stream.push({ type: "toolCall", toolCall, partial: output });
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Map finish reason
|
||||
if (candidate?.finishReason) {
|
||||
output.stopReason = this.mapStopReason(candidate.finishReason);
|
||||
// Check if we have tool calls in blocks
|
||||
output.stopReason = mapStopReason(candidate.finishReason);
|
||||
if (output.content.some((b) => b.type === "toolCall")) {
|
||||
output.stopReason = "toolUse";
|
||||
}
|
||||
}
|
||||
|
||||
// Capture usage metadata if available
|
||||
if (chunk.usageMetadata) {
|
||||
output.usage = {
|
||||
input: chunk.usageMetadata.promptTokenCount || 0,
|
||||
|
|
@ -225,166 +166,223 @@ export class GoogleLLM implements LLM<GoogleLLMOptions> {
|
|||
total: 0,
|
||||
},
|
||||
};
|
||||
calculateCost(this.modelInfo, output.usage);
|
||||
calculateCost(model, output.usage);
|
||||
}
|
||||
}
|
||||
|
||||
// Finalize last block
|
||||
if (currentBlock) {
|
||||
if (currentBlock.type === "text") {
|
||||
options?.onEvent?.({ type: "text_end", content: currentBlock.text });
|
||||
stream.push({ type: "text_end", content: currentBlock.text, partial: output });
|
||||
} else {
|
||||
options?.onEvent?.({ type: "thinking_end", content: currentBlock.thinking });
|
||||
stream.push({ type: "thinking_end", content: currentBlock.thinking, partial: output });
|
||||
}
|
||||
}
|
||||
|
||||
options?.onEvent?.({ type: "done", reason: output.stopReason, message: output });
|
||||
return output;
|
||||
stream.push({ type: "done", reason: output.stopReason, message: output });
|
||||
stream.end();
|
||||
} catch (error) {
|
||||
output.stopReason = "error";
|
||||
output.error = error instanceof Error ? error.message : JSON.stringify(error);
|
||||
options?.onEvent?.({ type: "error", error: output.error });
|
||||
return output;
|
||||
stream.push({ type: "error", error: output.error, partial: output });
|
||||
stream.end();
|
||||
}
|
||||
})();
|
||||
|
||||
return stream;
|
||||
};
|
||||
|
||||
function createClient(apiKey?: string): GoogleGenAI {
|
||||
if (!apiKey) {
|
||||
if (!process.env.GEMINI_API_KEY) {
|
||||
throw new Error(
|
||||
"Gemini API key is required. Set GEMINI_API_KEY environment variable or pass it as an argument.",
|
||||
);
|
||||
}
|
||||
apiKey = process.env.GEMINI_API_KEY;
|
||||
}
|
||||
return new GoogleGenAI({ apiKey });
|
||||
}
|
||||
|
||||
function buildParams(
|
||||
model: Model<"google-generative-ai">,
|
||||
context: Context,
|
||||
options: GoogleOptions = {},
|
||||
): GenerateContentParameters {
|
||||
const contents = convertMessages(model, context);
|
||||
|
||||
const generationConfig: GenerateContentConfig = {};
|
||||
if (options.temperature !== undefined) {
|
||||
generationConfig.temperature = options.temperature;
|
||||
}
|
||||
if (options.maxTokens !== undefined) {
|
||||
generationConfig.maxOutputTokens = options.maxTokens;
|
||||
}
|
||||
|
||||
private convertMessages(messages: Message[]): Content[] {
|
||||
const contents: Content[] = [];
|
||||
const config: GenerateContentConfig = {
|
||||
...(Object.keys(generationConfig).length > 0 && generationConfig),
|
||||
...(context.systemPrompt && { systemInstruction: context.systemPrompt }),
|
||||
...(context.tools && { tools: convertTools(context.tools) }),
|
||||
};
|
||||
|
||||
// Transform messages for cross-provider compatibility
|
||||
const transformedMessages = transformMessages(messages, this.modelInfo, this.getApi());
|
||||
if (context.tools && options.toolChoice) {
|
||||
config.toolConfig = {
|
||||
functionCallingConfig: {
|
||||
mode: mapToolChoice(options.toolChoice),
|
||||
},
|
||||
};
|
||||
}
|
||||
|
||||
for (const msg of transformedMessages) {
|
||||
if (msg.role === "user") {
|
||||
// Handle both string and array content
|
||||
if (typeof msg.content === "string") {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [{ text: msg.content }],
|
||||
});
|
||||
} else {
|
||||
// Convert array content to Google format
|
||||
const parts: Part[] = msg.content.map((item) => {
|
||||
if (item.type === "text") {
|
||||
return { text: item.text };
|
||||
} else {
|
||||
// Image content - Google uses inlineData
|
||||
return {
|
||||
inlineData: {
|
||||
mimeType: item.mimeType,
|
||||
data: item.data,
|
||||
},
|
||||
};
|
||||
}
|
||||
});
|
||||
const filteredParts = !this.modelInfo?.input.includes("image")
|
||||
? parts.filter((p) => p.text !== undefined)
|
||||
: parts;
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: filteredParts,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const parts: Part[] = [];
|
||||
if (options.thinking?.enabled && model.reasoning) {
|
||||
config.thinkingConfig = {
|
||||
includeThoughts: true,
|
||||
...(options.thinking.budgetTokens !== undefined && { thinkingBudget: options.thinking.budgetTokens }),
|
||||
};
|
||||
}
|
||||
|
||||
// Process content blocks
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "text") {
|
||||
parts.push({ text: block.text });
|
||||
} else if (block.type === "thinking") {
|
||||
const thinkingPart: Part = {
|
||||
thought: true,
|
||||
thoughtSignature: block.thinkingSignature,
|
||||
text: block.thinking,
|
||||
};
|
||||
parts.push(thinkingPart);
|
||||
} else if (block.type === "toolCall") {
|
||||
parts.push({
|
||||
functionCall: {
|
||||
id: block.id,
|
||||
name: block.name,
|
||||
args: block.arguments,
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
if (options.signal) {
|
||||
if (options.signal.aborted) {
|
||||
throw new Error("Request aborted");
|
||||
}
|
||||
config.abortSignal = options.signal;
|
||||
}
|
||||
|
||||
if (parts.length > 0) {
|
||||
contents.push({
|
||||
role: "model",
|
||||
parts,
|
||||
});
|
||||
}
|
||||
} else if (msg.role === "toolResult") {
|
||||
const params: GenerateContentParameters = {
|
||||
model: model.id,
|
||||
contents,
|
||||
config,
|
||||
};
|
||||
|
||||
return params;
|
||||
}
|
||||
function convertMessages(model: Model<"google-generative-ai">, context: Context): Content[] {
|
||||
const contents: Content[] = [];
|
||||
const transformedMessages = transformMessages(context.messages, model);
|
||||
|
||||
for (const msg of transformedMessages) {
|
||||
if (msg.role === "user") {
|
||||
if (typeof msg.content === "string") {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [
|
||||
{
|
||||
functionResponse: {
|
||||
id: msg.toolCallId,
|
||||
name: msg.toolName,
|
||||
response: {
|
||||
result: msg.content,
|
||||
isError: msg.isError,
|
||||
},
|
||||
parts: [{ text: msg.content }],
|
||||
});
|
||||
} else {
|
||||
const parts: Part[] = msg.content.map((item) => {
|
||||
if (item.type === "text") {
|
||||
return { text: item.text };
|
||||
} else {
|
||||
return {
|
||||
inlineData: {
|
||||
mimeType: item.mimeType,
|
||||
data: item.data,
|
||||
},
|
||||
},
|
||||
],
|
||||
};
|
||||
}
|
||||
});
|
||||
const filteredParts = !model.input.includes("image") ? parts.filter((p) => p.text !== undefined) : parts;
|
||||
if (filteredParts.length === 0) continue;
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: filteredParts,
|
||||
});
|
||||
}
|
||||
}
|
||||
} else if (msg.role === "assistant") {
|
||||
const parts: Part[] = [];
|
||||
|
||||
return contents;
|
||||
}
|
||||
for (const block of msg.content) {
|
||||
if (block.type === "text") {
|
||||
parts.push({ text: block.text });
|
||||
} else if (block.type === "thinking") {
|
||||
const thinkingPart: Part = {
|
||||
thought: true,
|
||||
thoughtSignature: block.thinkingSignature,
|
||||
text: block.thinking,
|
||||
};
|
||||
parts.push(thinkingPart);
|
||||
} else if (block.type === "toolCall") {
|
||||
parts.push({
|
||||
functionCall: {
|
||||
id: block.id,
|
||||
name: block.name,
|
||||
args: block.arguments,
|
||||
},
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private convertTools(tools: Tool[]): any[] {
|
||||
return [
|
||||
{
|
||||
functionDeclarations: tools.map((tool) => ({
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters,
|
||||
})),
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
private mapToolChoice(choice: string): FunctionCallingConfigMode {
|
||||
switch (choice) {
|
||||
case "auto":
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
case "none":
|
||||
return FunctionCallingConfigMode.NONE;
|
||||
case "any":
|
||||
return FunctionCallingConfigMode.ANY;
|
||||
default:
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
if (parts.length === 0) continue;
|
||||
contents.push({
|
||||
role: "model",
|
||||
parts,
|
||||
});
|
||||
} else if (msg.role === "toolResult") {
|
||||
contents.push({
|
||||
role: "user",
|
||||
parts: [
|
||||
{
|
||||
functionResponse: {
|
||||
id: msg.toolCallId,
|
||||
name: msg.toolName,
|
||||
response: {
|
||||
result: msg.content,
|
||||
isError: msg.isError,
|
||||
},
|
||||
},
|
||||
},
|
||||
],
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
private mapStopReason(reason: FinishReason): StopReason {
|
||||
switch (reason) {
|
||||
case "STOP":
|
||||
return "stop";
|
||||
case "MAX_TOKENS":
|
||||
return "length";
|
||||
case "BLOCKLIST":
|
||||
case "PROHIBITED_CONTENT":
|
||||
case "SPII":
|
||||
case "SAFETY":
|
||||
case "IMAGE_SAFETY":
|
||||
return "safety";
|
||||
case "RECITATION":
|
||||
return "safety";
|
||||
case "FINISH_REASON_UNSPECIFIED":
|
||||
case "OTHER":
|
||||
case "LANGUAGE":
|
||||
case "MALFORMED_FUNCTION_CALL":
|
||||
case "UNEXPECTED_TOOL_CALL":
|
||||
return "error";
|
||||
default:
|
||||
return "stop";
|
||||
return contents;
|
||||
}
|
||||
|
||||
function convertTools(tools: Tool[]): any[] {
|
||||
return [
|
||||
{
|
||||
functionDeclarations: tools.map((tool) => ({
|
||||
name: tool.name,
|
||||
description: tool.description,
|
||||
parameters: tool.parameters,
|
||||
})),
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
function mapToolChoice(choice: string): FunctionCallingConfigMode {
|
||||
switch (choice) {
|
||||
case "auto":
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
case "none":
|
||||
return FunctionCallingConfigMode.NONE;
|
||||
case "any":
|
||||
return FunctionCallingConfigMode.ANY;
|
||||
default:
|
||||
return FunctionCallingConfigMode.AUTO;
|
||||
}
|
||||
}
|
||||
|
||||
function mapStopReason(reason: FinishReason): StopReason {
|
||||
switch (reason) {
|
||||
case FinishReason.STOP:
|
||||
return "stop";
|
||||
case FinishReason.MAX_TOKENS:
|
||||
return "length";
|
||||
case FinishReason.BLOCKLIST:
|
||||
case FinishReason.PROHIBITED_CONTENT:
|
||||
case FinishReason.SPII:
|
||||
case FinishReason.SAFETY:
|
||||
case FinishReason.IMAGE_SAFETY:
|
||||
case FinishReason.RECITATION:
|
||||
return "safety";
|
||||
case FinishReason.FINISH_REASON_UNSPECIFIED:
|
||||
case FinishReason.OTHER:
|
||||
case FinishReason.LANGUAGE:
|
||||
case FinishReason.MALFORMED_FUNCTION_CALL:
|
||||
case FinishReason.UNEXPECTED_TOOL_CALL:
|
||||
return "error";
|
||||
default: {
|
||||
const _exhaustive: never = reason;
|
||||
throw new Error(`Unhandled stop reason: ${_exhaustive}`);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue