feat(ai): Implement Gemini provider with streaming and tool support

- Added GeminiLLM provider implementation with GoogleGenerativeAI SDK
- Supports streaming with text/thinking content and completion signals
- Handles Gemini's parts-based content system (text, thought, functionCall)
- Implements tool/function calling with proper format conversion
- Maps between unified types and Gemini-specific formats (model vs assistant role)
- Added test example matching other provider patterns
- Fixed typo in AssistantMessage type (stopResaon -> stopReason) across all providers

package-lock.json

@@ -654,6 +654,15 @@
 				}
 			}
 		},
+		"node_modules/@google/generative-ai": {
+			"version": "0.24.1",
+			"resolved": "https://registry.npmjs.org/@google/generative-ai/-/generative-ai-0.24.1.tgz",
+			"integrity": "sha512-MqO+MLfM6kjxcKoy0p1wRzG3b4ZZXtPI+z2IE26UogS2Cm/XHO+7gGRBh6gcJsOiIVoH93UwKvW4HdgiOZCy9Q==",
+			"license": "Apache-2.0",
+			"engines": {
+				"node": ">=18.0.0"
+			}
+		},
 		"node_modules/@mariozechner/ai": {
 			"resolved": "packages/ai",
 			"link": true
@@ -1604,6 +1613,7 @@
 			"dependencies": {
 				"@anthropic-ai/sdk": "0.60.0",
 				"@google/genai": "1.14.0",
+				"@google/generative-ai": "^0.24.1",
 				"chalk": "^5.5.0",
 				"openai": "5.12.2"
 			},

packages/ai/package.json

@@ -5,7 +5,10 @@
 	"type": "module",
 	"main": "./dist/index.js",
 	"types": "./dist/index.d.ts",
-	"files": ["dist", "README.md"],
+	"files": [
+		"dist",
+		"README.md"
+	],
 	"scripts": {
 		"clean": "rm -rf dist",
 		"build": "tsc -p tsconfig.build.json",
@@ -13,13 +16,21 @@
 		"prepublishOnly": "npm run clean && npm run build"
 	},
 	"dependencies": {
-		"openai": "5.12.2",
 		"@anthropic-ai/sdk": "0.60.0",
 		"@google/genai": "1.14.0",
-		"chalk": "^5.5.0"
+		"@google/generative-ai": "^0.24.1",
+		"chalk": "^5.5.0",
+		"openai": "5.12.2"
 	},
-	"devDependencies": {},
-	"keywords": ["ai", "llm", "openai", "anthropic", "gemini", "unified", "api"],
+	"keywords": [
+		"ai",
+		"llm",
+		"openai",
+		"anthropic",
+		"gemini",
+		"unified",
+		"api"
+	],
 	"author": "Mario Zechner",
 	"license": "MIT",
 	"repository": {
@@ -30,4 +41,4 @@
 	"engines": {
 		"node": ">=20.0.0"
 	}
-}
+}

packages/ai/src/providers/anthropic.ts

@@ -186,7 +186,7 @@ export class AnthropicLLM implements LLM<AnthropicLLMOptions> {
 				toolCalls,
 				model: this.model,
 				usage,
-				stopResaon: this.mapStopReason(msg.stop_reason),
+				stopReason: this.mapStopReason(msg.stop_reason),
 			};
 		} catch (error) {
 			return {
@@ -198,7 +198,7 @@ export class AnthropicLLM implements LLM<AnthropicLLMOptions> {
 					cacheRead: 0,
 					cacheWrite: 0,
 				},
-				stopResaon: "error",
+				stopReason: "error",
 				error: error instanceof Error ? error.message : String(error),
 			};
 		}

packages/ai/src/providers/gemini.ts

@@ -0,0 +1,264 @@
+import { FunctionCallingMode, GoogleGenerativeAI } from "@google/generative-ai";
+import type {
+	AssistantMessage,
+	Context,
+	LLM,
+	LLMOptions,
+	Message,
+	StopReason,
+	TokenUsage,
+	Tool,
+	ToolCall,
+} from "../types.js";
+
+export interface GeminiLLMOptions extends LLMOptions {
+	toolChoice?: "auto" | "none" | "any";
+}
+
+export class GeminiLLM implements LLM<GeminiLLMOptions> {
+	private client: GoogleGenerativeAI;
+	private model: string;
+
+	constructor(model: string, 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 GoogleGenerativeAI(apiKey);
+		this.model = model;
+	}
+
+	async complete(context: Context, options?: GeminiLLMOptions): Promise<AssistantMessage> {
+		try {
+			const model = this.client.getGenerativeModel({
+				model: this.model,
+				systemInstruction: context.systemPrompt,
+				tools: context.tools ? this.convertTools(context.tools) : undefined,
+				toolConfig: options?.toolChoice
+					? {
+							functionCallingConfig: {
+								mode: this.mapToolChoice(options.toolChoice),
+							},
+						}
+					: undefined,
+			});
+
+			const contents = this.convertMessages(context.messages);
+
+			const stream = await model.generateContentStream({
+				contents,
+				generationConfig: {
+					temperature: options?.temperature,
+					maxOutputTokens: options?.maxTokens,
+				},
+			});
+
+			let content = "";
+			let thinking = "";
+			const toolCalls: ToolCall[] = [];
+			let usage: TokenUsage = {
+				input: 0,
+				output: 0,
+				cacheRead: 0,
+				cacheWrite: 0,
+			};
+			let stopReason: StopReason = "stop";
+			let inTextBlock = false;
+			let inThinkingBlock = false;
+
+			// Process the stream
+			for await (const chunk of stream.stream) {
+				// Extract parts from the chunk
+				const candidate = chunk.candidates?.[0];
+				if (candidate?.content?.parts) {
+					for (const part of candidate.content.parts) {
+						if (part.text) {
+							// Check if it's thinking content
+							if ((part as any).thought) {
+								thinking += part.text;
+								options?.onThinking?.(part.text, false);
+								inThinkingBlock = true;
+								if (inTextBlock) {
+									options?.onText?.("", true);
+									inTextBlock = false;
+								}
+							} else {
+								content += part.text;
+								options?.onText?.(part.text, false);
+								inTextBlock = true;
+								if (inThinkingBlock) {
+									options?.onThinking?.("", true);
+									inThinkingBlock = false;
+								}
+							}
+						}
+
+						// Handle function calls
+						if (part.functionCall) {
+							if (inTextBlock) {
+								options?.onText?.("", true);
+								inTextBlock = false;
+							}
+							if (inThinkingBlock) {
+								options?.onThinking?.("", true);
+								inThinkingBlock = false;
+							}
+
+							toolCalls.push({
+								id: `call_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`,
+								name: part.functionCall.name,
+								arguments: part.functionCall.args as Record<string, any>,
+							});
+						}
+					}
+				}
+
+				// Map finish reason
+				if (candidate?.finishReason) {
+					stopReason = this.mapStopReason(candidate.finishReason);
+				}
+			}
+
+			// Signal end of blocks
+			if (inTextBlock) {
+				options?.onText?.("", true);
+			}
+			if (inThinkingBlock) {
+				options?.onThinking?.("", true);
+			}
+
+			// Get final response for usage metadata
+			const response = await stream.response;
+			if (response.usageMetadata) {
+				usage = {
+					input: response.usageMetadata.promptTokenCount || 0,
+					output: response.usageMetadata.candidatesTokenCount || 0,
+					cacheRead: response.usageMetadata.cachedContentTokenCount || 0,
+					cacheWrite: 0,
+				};
+			}
+
+			return {
+				role: "assistant",
+				content: content || undefined,
+				thinking: thinking || undefined,
+				toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
+				model: this.model,
+				usage,
+				stopReason,
+			};
+		} catch (error) {
+			return {
+				role: "assistant",
+				model: this.model,
+				usage: {
+					input: 0,
+					output: 0,
+					cacheRead: 0,
+					cacheWrite: 0,
+				},
+				stopReason: "error",
+				error: error instanceof Error ? error.message : String(error),
+			};
+		}
+	}
+
+	private convertMessages(messages: Message[]): any[] {
+		const contents: any[] = [];
+
+		for (const msg of messages) {
+			if (msg.role === "user") {
+				contents.push({
+					role: "user",
+					parts: [{ text: msg.content }],
+				});
+			} else if (msg.role === "assistant") {
+				const parts: any[] = [];
+
+				if (msg.content) {
+					parts.push({ text: msg.content });
+				}
+
+				if (msg.toolCalls) {
+					for (const toolCall of msg.toolCalls) {
+						parts.push({
+							functionCall: {
+								name: toolCall.name,
+								args: toolCall.arguments,
+							},
+						});
+					}
+				}
+
+				if (parts.length > 0) {
+					contents.push({
+						role: "model",
+						parts,
+					});
+				}
+			} else if (msg.role === "toolResult") {
+				// Tool results are sent as function responses
+				contents.push({
+					role: "user",
+					parts: [
+						{
+							functionResponse: {
+								name: msg.toolCallId.split("_")[1], // Extract function name from our ID format
+								response: {
+									result: msg.content,
+									isError: msg.isError || false,
+								},
+							},
+						},
+					],
+				});
+			}
+		}
+
+		return contents;
+	}
+
+	private convertTools(tools: Tool[]): any[] {
+		return [
+			{
+				functionDeclarations: tools.map((tool) => ({
+					name: tool.name,
+					description: tool.description,
+					parameters: tool.parameters,
+				})),
+			},
+		];
+	}
+
+	private mapToolChoice(choice: string): FunctionCallingMode {
+		switch (choice) {
+			case "auto":
+				return FunctionCallingMode.AUTO;
+			case "none":
+				return FunctionCallingMode.NONE;
+			case "any":
+				return FunctionCallingMode.ANY;
+			default:
+				return FunctionCallingMode.AUTO;
+		}
+	}
+
+	private mapStopReason(reason: string): StopReason {
+		switch (reason) {
+			case "STOP":
+				return "stop";
+			case "MAX_TOKENS":
+				return "length";
+			case "SAFETY":
+				return "safety";
+			case "RECITATION":
+				return "safety";
+			default:
+				return "stop";
+		}
+	}
+}

packages/ai/src/providers/openai-completions.ts

@@ -163,7 +163,7 @@ export class OpenAICompletionsLLM implements LLM<OpenAICompletionsLLMOptions> {
 				toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
 				model: this.model,
 				usage,
-				stopResaon: this.mapStopReason(finishReason),
+				stopReason: this.mapStopReason(finishReason),
 			};
 		} catch (error) {
 			return {
@@ -175,7 +175,7 @@ export class OpenAICompletionsLLM implements LLM<OpenAICompletionsLLMOptions> {
 					cacheRead: 0,
 					cacheWrite: 0,
 				},
-				stopResaon: "error",
+				stopReason: "error",
 				error: error instanceof Error ? error.message : String(error),
 			};
 		}

packages/ai/src/providers/openai-responses.ts

@@ -144,7 +144,7 @@ export class OpenAIResponsesLLM implements LLM<OpenAIResponsesLLMOptions> {
 						role: "assistant",
 						model: this.model,
 						usage,
-						stopResaon: "error",
+						stopReason: "error",
 						error: `Code ${event.code}: ${event.message}` || "Unknown error",
 					};
 				}
@@ -158,7 +158,7 @@ export class OpenAIResponsesLLM implements LLM<OpenAIResponsesLLMOptions> {
 				toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
 				model: this.model,
 				usage,
-				stopResaon: stopReason,
+				stopReason,
 			};
 		} catch (error) {
 			return {
@@ -170,7 +170,7 @@ export class OpenAIResponsesLLM implements LLM<OpenAIResponsesLLMOptions> {
 					cacheRead: 0,
 					cacheWrite: 0,
 				},
-				stopResaon: "error",
+				stopReason: "error",
 				error: error instanceof Error ? error.message : String(error),
 			};
 		}

packages/ai/src/types.ts

@@ -51,7 +51,7 @@ export interface AssistantMessage {
 	model: string;
 	usage: TokenUsage;
 
-	stopResaon: StopReason;
+	stopReason: StopReason;
 	error?: string | Error;
 }
 

packages/ai/test/examples/gemini.ts

@@ -0,0 +1,61 @@
+import chalk from "chalk";
+import { GeminiLLM, GeminiLLMOptions } from "../../src/providers/gemini.js";
+import { Context, Tool } from "../../src/types.js";
+
+// Define a simple calculator tool
+const tools: Tool[] = [
+    {
+        name: "calculate",
+        description: "Perform a mathematical calculation",
+        parameters: {
+            type: "object" as const,
+            properties: {
+                expression: {
+                    type: "string",
+                    description: "The mathematical expression to evaluate"
+                }
+            },
+            required: ["expression"]
+        }
+    }
+];
+
+const options: GeminiLLMOptions = {
+    onText: (t, complete) => process.stdout.write(t + (complete ? "\n" : "")),
+    onThinking: (t, complete) => process.stdout.write(chalk.dim(t + (complete ? "\n" : ""))),
+    toolChoice: "auto"
+};
+
+const ai = new GeminiLLM("gemini-2.0-flash-exp", process.env.GEMINI_API_KEY || "fake-api-key-for-testing");
+const context: Context = {
+    systemPrompt: "You are a helpful assistant that can use tools to answer questions.",
+    messages: [
+        {
+            role: "user",
+            content: "Think about birds briefly. Then give me a list of 10 birds. Finally, calculate 42 * 17 + 123 and 453 + 434 in parallel using the calculator tool.",
+        }
+    ],
+    tools
+}
+
+let msg = await ai.complete(context, options)
+context.messages.push(msg);
+console.log();
+console.log(chalk.yellow(JSON.stringify(msg, null, 2)));
+
+for (const toolCall of msg.toolCalls || []) {
+    if (toolCall.name === "calculate") {
+        const expression = toolCall.arguments.expression;
+        const result = eval(expression);
+        context.messages.push({
+            role: "toolResult",
+            content: `The result of ${expression} is ${result}.`,
+            toolCallId: toolCall.id,
+            isError: false
+        });
+    }
+}
+
+msg = await ai.complete(context, options);
+console.log();
+console.log(chalk.yellow(JSON.stringify(msg, null, 2)));