diff --git a/apps/gui/src/lib/simulation/provider-resolver.ts b/apps/gui/src/lib/simulation/provider-resolver.ts index bdb22fb..47a2993 100644 --- a/apps/gui/src/lib/simulation/provider-resolver.ts +++ b/apps/gui/src/lib/simulation/provider-resolver.ts @@ -6,6 +6,8 @@ import { ProviderManager, OpenRouterProvider, AnthropicProvider, + OpenAIProvider, + OpenAIEmbeddingProvider, GeminiEmbeddingProvider, MockEmbeddingProvider, } from "@omnia/llm"; @@ -75,6 +77,13 @@ function buildLLMProvider(inst: ModelProviderInstance): ILLMProvider { inst.name, inst.maxContext, ); + } else if (inst.providerName === "openai") { + return new OpenAIProvider( + inst.apiKey, + inst.modelName, + inst.name, + inst.maxContext, + ); } return new MockLLMProvider([]); } @@ -86,6 +95,8 @@ function buildEmbeddingProvider( return new GeminiEmbeddingProvider(inst.apiKey, inst.modelName); } else if (inst.providerName === "ollama") { return new OllamaEmbeddingProvider(inst.endpointUrl, inst.modelName); + } else if (inst.providerName === "openai") { + return new OpenAIEmbeddingProvider(inst.apiKey, inst.modelName); } return new MockEmbeddingProvider(inst.modelName); } diff --git a/package.json b/package.json index f4d1a3d..9989e42 100644 --- a/package.json +++ b/package.json @@ -50,6 +50,7 @@ "@langchain/anthropic": "^0.3.11", "@langchain/google-genai": "^2.2.0", "@langchain/ollama": "^0.2.3", + "@langchain/openai": "^0.3.17", "@langchain/openrouter": "^0.4.3", "@types/node": "^20.19.43", "dotenv": "^17.4.2" diff --git a/packages/llm/README.md b/packages/llm/README.md index 4f0fea8..5d71278 100644 --- a/packages/llm/README.md +++ b/packages/llm/README.md @@ -279,6 +279,29 @@ Also exports `GeminiEmbeddingProvider` (implements `IEmbeddingProvider`) using t 4. None found → throw Error ``` +### OpenAI — `OpenAIProvider` + +| Property | Value | +| --------------------------- | ------------------------------------------------------ | +| **File** | [`providers/openai.ts`](src/providers/openai.ts) | +| **Provider ID** | `openai` | +| **SDK** | `@langchain/openai` (`ChatOpenAI`, `OpenAIEmbeddings`) | +| **Default Model** | `gpt-4o-mini` | +| **Default Embedding Model** | `text-embedding-3-small` | +| **Default Max Context** | `128000` | +| **Type** | Generative + Embedding | + +**Key resolution** in the constructor follows this cascade: + +``` +1. Explicit apiKey argument → use it +2. ProviderManager.getActive() → if providerName matches "openai" +3. OPENAI_API_KEY env var → final fallback +4. None found → throw Error +``` + +Also exports `OpenAIEmbeddingProvider` (implements `IEmbeddingProvider`) using the same key resolution pattern against the `"embedding"` type instance. The default embedding model is `text-embedding-3-small`. + ### OpenRouter — `OpenRouterProvider` | Property | Value | @@ -377,6 +400,7 @@ The `buildLLMProvider()` and `buildEmbeddingProvider()` functions perform the fi | `providerName` | Generative Class | Embedding Class | | ----------------- | -------------------- | ------------------------- | | `"google-genai"` | `GeminiProvider` | `GeminiEmbeddingProvider` | +| `"openai"` | `OpenAIProvider` | `OpenAIEmbeddingProvider` | | `"openrouter"` | `OpenRouterProvider` | _(falls through to mock)_ | | `"ollama"` | `OllamaProvider` | `OllamaEmbeddingProvider` | | `"anthropic"` | `AnthropicProvider` | _(falls through to mock)_ | @@ -405,6 +429,7 @@ This sends the Zod schema to the model as a structured output constraint. The re | Variable | Required | Description | | -------------------- | -------- | ------------------------ | | `GOOGLE_API_KEY` | No | Google Gemini API key | +| `OPENAI_API_KEY` | No | OpenAI API key | | `OPENROUTER_API_KEY` | No | OpenRouter API key | | `ANTHROPIC_API_KEY` | No | Anthropic Claude API key | @@ -424,6 +449,7 @@ packages/llm/ │ ├── ollama.ts # OllamaProvider + OllamaEmbeddingProvider │ ├── openrouter.ts # OpenRouterProvider │ ├── anthropic.ts # AnthropicProvider +│ ├── openai.ts # OpenAIProvider + OpenAIEmbeddingProvider │ └── mock.ts # MockLLMProvider + MockEmbeddingProvider ├── tests/ │ ├── mock.test.ts diff --git a/packages/llm/chat-openai.md b/packages/llm/chat-openai.md new file mode 100644 index 0000000..ac1c5ba --- /dev/null +++ b/packages/llm/chat-openai.md @@ -0,0 +1,225 @@ +> ## Documentation Index +> +> Fetch the complete documentation index at: https://docs.langchain.com/llms.txt +> Use this file to discover all available pages before exploring further. + +# OpenAI integrations + +> Integrate with OpenAI using LangChain JavaScript. + +LangChain integrates with OpenAI and Azure OpenAI through the `@langchain/openai` package. + +> [OpenAI](https://en.wikipedia.org/wiki/OpenAI) is American artificial intelligence (AI) research laboratory +> consisting of the non-profit `OpenAI Incorporated` +> and its for-profit subsidiary corporation `OpenAI Limited Partnership`. +> OpenAI conducts AI research with the declared intention of promoting and developing a friendly AI. +> OpenAI systems run on an `Azure`-based supercomputing platform from `Microsoft`. + +> The [OpenAI API](https://platform.openai.com/docs/models) is powered by a diverse set of models with different capabilities and price points. +> +> [ChatGPT](https://chat.openai.com) is the Artificial Intelligence (AI) chatbot developed by `OpenAI`. + +## Installation and setup + +- Get an OpenAI api key and set it as an environment variable (`OPENAI_API_KEY`) + +## Chat model + +See a [usage example](/oss/javascript/integrations/chat/openai). + +```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +import { ChatOpenAI } from "@langchain/openai"; +``` + +## LLM + +See a [usage example](/oss/javascript/integrations/llms/openai). + + + See [this section for general instructions on installing LangChain packages](/oss/javascript/langchain/install). + + +```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +npm install @langchain/openai @langchain/core +``` + +```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +import { OpenAI } from "@langchain/openai"; +``` + +## Text embedding model + +See a [usage example](/oss/javascript/integrations/embeddings/openai) + +```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +import { OpenAIEmbeddings } from "@langchain/openai"; +``` + +## Chain + +```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +import { OpenAIModerationChain } from "@langchain/classic/chains"; +``` + +## Middleware + +Middleware specifically designed for OpenAI models. Learn more about [middleware](/oss/javascript/langchain/middleware/overview). + +| Middleware | Description | +| ----------------------------------------- | --------------------------------------------------------- | +| [Content moderation](#content-moderation) | Moderate agent traffic using OpenAI's moderation endpoint | + +### Content moderation + +Moderate agent traffic (user input, model output, and tool results) using OpenAI's moderation endpoint to detect and handle unsafe content. Content moderation is useful for the following: + +- Applications requiring content safety and compliance +- Filtering harmful, hateful, or inappropriate content +- Customer-facing agents that need safety guardrails +- Meeting platform moderation requirements + + + Learn more about [OpenAI's moderation models](https://platform.openai.com/docs/guides/moderation) and categories. + + +**API reference:** [`openAIModerationMiddleware`](https://reference.langchain.com/javascript/langchain/index/openAIModerationMiddleware) + +```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +import { createAgent, openAIModerationMiddleware } from "langchain"; + +const agent = createAgent({ + model: "openai:gpt-5.5", + tools: [searchTool, databaseTool], + middleware: [ + openAIModerationMiddleware({ + model: "openai:gpt-5.5", + moderationModel: "omni-moderation-latest", + checkInput: true, + checkOutput: true, + exitBehavior: "end", + }), + ], +}); +``` + + + + OpenAI model to use for moderation. Can be either a model name string (e.g., `"openai:gpt-5.5"`) or a `BaseChatModel` instance. The middleware will use this model's client to access the moderation endpoint. + + + + OpenAI moderation model to use. Options: `'omni-moderation-latest'`, `'omni-moderation-2024-09-26'`, `'text-moderation-latest'`, `'text-moderation-stable'` + + + + Whether to check user input messages before the model is called + + + + Whether to check model output messages after the model is called + + + + Whether to check tool result messages before the model is called + + + + How to handle violations when content is flagged. Options: + + * `'end'` - End agent execution immediately with a violation message + * `'error'` - Throw `OpenAIModerationError` exception + * `'replace'` - Replace the flagged content with the violation message and continue + + + + + Custom template for violation messages. Supports template variables: + + * `{categories}` - Comma-separated list of flagged categories + * `{category_scores}` - JSON string of category scores + * `{original_content}` - The original flagged content + + Default: `"I'm sorry, but I can't comply with that request. It was flagged for {categories}."` + + + + + + The middleware integrates OpenAI's moderation endpoint to check content at different stages: + +**Moderation stages:** + +- `checkInput` - User messages before model call +- `checkOutput` - AI messages after model call +- `checkToolResults` - Tool outputs before model call + +**Exit behaviors:** + +- `'end'` (default) - Stop execution with violation message +- `'error'` - Throw exception for application handling +- `'replace'` - Replace flagged content and continue + +```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}} +import { createAgent, openAIModerationMiddleware } from "langchain"; + +// Basic moderation +const agent = createAgent({ + model: "openai:gpt-5.5", + tools: [searchTool, customerDataTool], + middleware: [ + openAIModerationMiddleware({ + model: "openai:gpt-5.5", + moderationModel: "omni-moderation-latest", + checkInput: true, + checkOutput: true, + }), + ], +}); + +// Strict moderation with custom message +const agentStrict = createAgent({ + model: "openai:gpt-5.5", + tools: [searchTool, customerDataTool], + middleware: [ + openAIModerationMiddleware({ + model: "openai:gpt-5.5", + moderationModel: "omni-moderation-latest", + checkInput: true, + checkOutput: true, + checkToolResults: true, + exitBehavior: "error", + violationMessage: + "Content policy violation detected: {categories}. " + + "Please rephrase your request.", + }), + ], +}); + +// Moderation with replacement behavior +const agentReplace = createAgent({ + model: "openai:gpt-5.5", + tools: [searchTool], + middleware: [ + openAIModerationMiddleware({ + model: "openai:gpt-5.5", + checkInput: true, + exitBehavior: "replace", + violationMessage: "[Content removed due to safety policies]", + }), + ], +}); +``` + + + +--- + +
+ + [Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers. + + + + [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/oss/javascript/integrations/providers/openai.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose). + +
diff --git a/packages/llm/src/config.ts b/packages/llm/src/config.ts index dad9d7b..f3b3b7f 100644 --- a/packages/llm/src/config.ts +++ b/packages/llm/src/config.ts @@ -4,6 +4,7 @@ const LLMConfigSchema = z.object({ GOOGLE_API_KEY: z.string().optional(), OPENROUTER_API_KEY: z.string().optional(), ANTHROPIC_API_KEY: z.string().optional(), + OPENAI_API_KEY: z.string().optional(), }); export const llmConfig = LLMConfigSchema.parse(process.env); diff --git a/packages/llm/src/index.ts b/packages/llm/src/index.ts index bb0aee7..b6452b0 100644 --- a/packages/llm/src/index.ts +++ b/packages/llm/src/index.ts @@ -5,4 +5,5 @@ export * from "./providers/mock.js"; export * from "./providers/ollama.js"; export * from "./providers/openrouter.js"; export * from "./providers/anthropic.js"; +export * from "./providers/openai.js"; export * from "./provider-manager.js"; diff --git a/packages/llm/src/llm.ts b/packages/llm/src/llm.ts index ea850c9..98f7614 100644 --- a/packages/llm/src/llm.ts +++ b/packages/llm/src/llm.ts @@ -76,6 +76,13 @@ export const AVAILABLE_PROVIDERS: ModelProviderMeta[] = [ defaultModel: "gemini-2.5-flash", defaultEmbeddingModel: "gemini-embedding-001", }, + { + id: "openai", + displayName: "OpenAI", + description: "Official OpenAI integration using @langchain/openai SDK", + defaultModel: "gpt-4o-mini", + defaultEmbeddingModel: "text-embedding-3-small", + }, { id: "anthropic", displayName: "Anthropic Claude", diff --git a/packages/llm/src/provider-manager.ts b/packages/llm/src/provider-manager.ts index 4fc572d..e8b5693 100644 --- a/packages/llm/src/provider-manager.ts +++ b/packages/llm/src/provider-manager.ts @@ -100,7 +100,9 @@ function getSettingsDb() { const googleKey = process.env.GOOGLE_API_KEY; const openRouterKey = process.env.OPENROUTER_API_KEY; const anthropicKey = process.env.ANTHROPIC_API_KEY; + const openaiKey = process.env.OPENAI_API_KEY; let hasInsertedGenerative = false; + let hasInsertedEmbedding = false; if (googleKey && googleKey.trim()) { const id = "provider-default-google"; @@ -137,6 +139,7 @@ function getSettingsDb() { "embedding", 0, ); + hasInsertedEmbedding = true; } if (anthropicKey && anthropicKey.trim()) { @@ -162,6 +165,50 @@ function getSettingsDb() { } } + if (openaiKey && openaiKey.trim()) { + const id = "provider-default-openai"; + const isActive = hasInsertedGenerative ? 0 : 1; + db.prepare( + ` + INSERT INTO provider_instances (id, name, providerName, apiKey, isActive, modelName, type, maxContext) + VALUES (?, ?, ?, ?, ?, ?, ?, ?) + `, + ).run( + id, + "OpenAI (Env)", + "openai", + openaiKey.trim(), + isActive, + "gpt-4o-mini", + "generative", + 128000, + ); + if (isActive === 1) { + hasInsertedGenerative = true; + } + + const embedId = "provider-default-openai-embed"; + const isEmbedActive = hasInsertedEmbedding ? 0 : 1; + db.prepare( + ` + INSERT INTO provider_instances (id, name, providerName, apiKey, isActive, modelName, type, maxContext) + VALUES (?, ?, ?, ?, ?, ?, ?, ?) + `, + ).run( + embedId, + "OpenAI Embed (Env)", + "openai", + openaiKey.trim(), + isEmbedActive, + "text-embedding-3-small", + "embedding", + 0, + ); + if (isEmbedActive === 1) { + hasInsertedEmbedding = true; + } + } + if (openRouterKey && openRouterKey.trim()) { const id = "provider-default-openrouter"; const isActive = hasInsertedGenerative ? 0 : 1; @@ -416,7 +463,9 @@ export class ProviderManager { const googleKey = process.env.GOOGLE_API_KEY; const openRouterKey = process.env.OPENROUTER_API_KEY; const anthropicKey = process.env.ANTHROPIC_API_KEY; + const openaiKey = process.env.OPENAI_API_KEY; let hasInsertedGenerative = false; + let hasInsertedEmbedding = false; if (googleKey && googleKey.trim()) { const id = "provider-default-google"; @@ -453,6 +502,7 @@ export class ProviderManager { "embedding", 0, ); + hasInsertedEmbedding = true; } if (anthropicKey && anthropicKey.trim()) { @@ -478,6 +528,50 @@ export class ProviderManager { } } + if (openaiKey && openaiKey.trim()) { + const id = "provider-default-openai"; + const isActive = hasInsertedGenerative ? 0 : 1; + db.prepare( + ` + INSERT INTO provider_instances (id, name, providerName, apiKey, isActive, modelName, type, maxContext) + VALUES (?, ?, ?, ?, ?, ?, ?, ?) + `, + ).run( + id, + "OpenAI (Env)", + "openai", + openaiKey.trim(), + isActive, + "gpt-4o-mini", + "generative", + 128000, + ); + if (isActive === 1) { + hasInsertedGenerative = true; + } + + const embedId = "provider-default-openai-embed"; + const isEmbedActive = hasInsertedEmbedding ? 0 : 1; + db.prepare( + ` + INSERT INTO provider_instances (id, name, providerName, apiKey, isActive, modelName, type, maxContext) + VALUES (?, ?, ?, ?, ?, ?, ?, ?) + `, + ).run( + embedId, + "OpenAI Embed (Env)", + "openai", + openaiKey.trim(), + isEmbedActive, + "text-embedding-3-small", + "embedding", + 0, + ); + if (isEmbedActive === 1) { + hasInsertedEmbedding = true; + } + } + if (openRouterKey && openRouterKey.trim()) { const id = "provider-default-openrouter"; const isActive = hasInsertedGenerative ? 0 : 1; @@ -608,6 +702,19 @@ export class ProviderManager { maxContext: 0, }; } + const openaiKey = process.env.OPENAI_API_KEY; + if (openaiKey && openaiKey.trim()) { + return { + id: "provider-default-env-embed-fallback", + name: "OpenAI Embed (Env Fallback)", + providerName: "openai", + apiKey: openaiKey.trim(), + isActive: true, + modelName: "text-embedding-3-small", + type: "embedding", + maxContext: 0, + }; + } return null; } @@ -624,6 +731,19 @@ export class ProviderManager { maxContext: 32768, }; } + const openaiKey = process.env.OPENAI_API_KEY; + if (openaiKey && openaiKey.trim()) { + return { + id: "provider-default-env-fallback", + name: "OpenAI (Env Fallback)", + providerName: "openai", + apiKey: openaiKey.trim(), + isActive: true, + modelName: "gpt-4o-mini", + type: "generative", + maxContext: 128000, + }; + } const anthropicKey = process.env.ANTHROPIC_API_KEY; if (anthropicKey && anthropicKey.trim()) { return { diff --git a/packages/llm/src/providers/openai.ts b/packages/llm/src/providers/openai.ts new file mode 100644 index 0000000..0565504 --- /dev/null +++ b/packages/llm/src/providers/openai.ts @@ -0,0 +1,160 @@ +import { z } from "zod"; +import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai"; +import { + ILLMProvider, + LLMRequest, + LLMResponse, + LLMCallRecord, + IEmbeddingProvider, +} from "../llm.js"; +import { llmConfig } from "../config.js"; +import { ProviderManager } from "../provider-manager.js"; + +export class OpenAIProvider implements ILLMProvider { + static readonly providerId = "openai"; + static readonly displayName = "OpenAI"; + static readonly description = + "Official OpenAI integration using @langchain/openai SDK"; + static readonly defaultModel = "gpt-4o-mini"; + + providerName = "OpenAI"; + private model: ChatOpenAI; + private modelNameUsed: string; + private providerInstanceName?: string; + private maxContextUsed?: number; + lastCalls: LLMCallRecord[] = []; + + constructor( + apiKey?: string, + modelName?: string, + providerInstanceName?: string, + maxContext?: number, + ) { + let key = apiKey; + let model = modelName; + this.providerInstanceName = providerInstanceName; + this.maxContextUsed = maxContext; + + if (!key) { + const active = ProviderManager.getActive("generative"); + if (active && active.providerName === OpenAIProvider.providerId) { + key = active.apiKey; + if (!model) { + model = active.modelName; + } + if (!this.providerInstanceName) { + this.providerInstanceName = active.name; + } + if (this.maxContextUsed === undefined) { + this.maxContextUsed = active.maxContext; + } + } + } + + if (!key) { + key = llmConfig.OPENAI_API_KEY; + if (!this.providerInstanceName && key) { + this.providerInstanceName = "Environment Variable"; + } + } + + if (!key) { + throw new Error( + "OPENAI_API_KEY is required to initialize OpenAIProvider", + ); + } + + this.modelNameUsed = model || OpenAIProvider.defaultModel; + this.model = new ChatOpenAI({ + apiKey: key, + model: this.modelNameUsed, + }); + } + + async generateStructuredResponse( + request: LLMRequest, + ): Promise>> { + const structuredModel = this.model.withStructuredOutput(request.schema, { + includeRaw: true, + }); + const result = (await structuredModel.invoke([ + { role: "system", content: request.systemPrompt }, + { role: "user", content: request.userContext }, + ])) as unknown as { + parsed?: z.infer; + raw?: { + usage_metadata?: { + input_tokens?: number; + output_tokens?: number; + total_tokens?: number; + }; + }; + }; + + const parsed = result?.parsed; + const raw = result?.raw; + + const usage = { + inputTokens: raw?.usage_metadata?.input_tokens || 0, + outputTokens: raw?.usage_metadata?.output_tokens || 0, + totalTokens: raw?.usage_metadata?.total_tokens || 0, + modelName: this.modelNameUsed, + providerInstanceName: this.providerInstanceName || "Default", + maxContext: + this.maxContextUsed !== undefined ? this.maxContextUsed : 128000, + }; + + this.lastCalls.push({ + systemPrompt: request.systemPrompt, + userContext: request.userContext, + usage, + }); + + return { success: true, data: parsed, usage }; + } +} + +export class OpenAIEmbeddingProvider implements IEmbeddingProvider { + static readonly providerId = "openai"; + static readonly displayName = "OpenAI Embeddings"; + + providerName = "OpenAI"; + private model: OpenAIEmbeddings; + + constructor(apiKey?: string, modelName?: string) { + let key = apiKey; + let model = modelName; + + if (!key) { + const active = ProviderManager.getActive("embedding"); + if ( + active && + active.providerName === OpenAIEmbeddingProvider.providerId + ) { + key = active.apiKey; + if (!model) { + model = active.modelName; + } + } + } + + if (!key) { + key = llmConfig.OPENAI_API_KEY; + } + + if (!key) { + throw new Error( + "OPENAI_API_KEY is required to initialize OpenAIEmbeddingProvider", + ); + } + + this.model = new OpenAIEmbeddings({ + apiKey: key, + model: model || "text-embedding-3-small", + }); + } + + async embed(text: string): Promise { + return this.model.embedQuery(text); + } +} diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml index 63145f6..13ed722 100644 --- a/pnpm-lock.yaml +++ b/pnpm-lock.yaml @@ -269,6 +269,9 @@ importers: "@langchain/ollama": specifier: ^0.2.3 version: 0.2.4 + "@langchain/openai": + specifier: ^0.3.17 + version: 0.3.17(ws@8.21.0) "@langchain/openrouter": specifier: ^0.4.3 version: 0.4.3(ws@8.21.0)(zod@4.4.3) @@ -2101,6 +2104,15 @@ packages: peerDependencies: "@langchain/core": ">=0.3.58 <0.4.0" + "@langchain/openai@0.3.17": + resolution: + { + integrity: sha512-uw4po32OKptVjq+CYHrumgbfh4NuD7LqyE+ZgqY9I/LrLc6bHLMc+sisHmI17vgek0K/yqtarI0alPJbzrwyag==, + } + engines: { node: ">=18" } + peerDependencies: + "@langchain/core": ">=0.3.29 <0.4.0" + "@langchain/openai@1.5.3": resolution: { @@ -3894,6 +3906,18 @@ packages: integrity: sha512-vSYNSDe6Ix3q+6Z7ri9lyWqgGhJTmzRjZRqyq15N0Z/1/UnVsno9G/N40NBijoYx2seFDIl0+B2mgAb9mezUCA==, } 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