{"version":3,"sources":["../src/gpt.ts"],"sourcesContent":["/**\n * Copyright 2024 The Fire Company\n *\n * Licensed under the Apache License, Version 2.0 (the \"License\");\n * you may not use this file except in compliance with the License.\n * You may obtain a copy of the License at\n *\n * http://www.apache.org/licenses/LICENSE-2.0\n *\n * Unless required by applicable law or agreed to in writing, software\n * distributed under the License is distributed on an \"AS IS\" BASIS,\n * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n * See the License for the specific language governing permissions and\n * limitations under the License.\n */\n\nimport { GenerationCommonConfigSchema, Message, z } from 'genkit';\nimport type {\n GenerateRequest,\n Genkit,\n MessageData,\n Part,\n Role,\n ToolRequestPart,\n} from 'genkit';\nimport { CandidateData, modelRef, ToolDefinition } from 'genkit/model';\nimport { AzureOpenAI } from 'openai';\nimport {\n type ChatCompletion,\n type ChatCompletionChunk,\n type ChatCompletionContentPart,\n type ChatCompletionCreateParamsNonStreaming,\n type ChatCompletionMessageParam,\n type ChatCompletionMessageToolCall,\n type ChatCompletionRole,\n type ChatCompletionTool,\n type CompletionChoice,\n} from 'openai/resources/index.mjs';\n\ntype VisualDetailLevel = 'low' | 'auto' | 'high';\n\nconst MODELS_SUPPORTING_OPENAI_RESPONSE_FORMAT = [\n 'gpt-4',\n 'gpt-4-32k',\n 'gpt-4o',\n 'gpt-4o-mini',\n 'gpt-o1',\n 'gpt-o1-mini',\n 'gpt-o1-preview',\n 'gpt-3.5-turbo',\n 'gpt-3.5-turbo-instruct',\n 'gpt-3.5-turbo-26k',\n 'gpt-4.1-mini',\n 'gpt-4.1-nano',\n 'gpt-4.1',\n 'o3',\n 'o3-mini',\n 'o4-mini',\n 'o1',\n 'o1-mini',\n 'o1-preview',\n];\n\nexport const OpenAiConfigSchema = GenerationCommonConfigSchema.extend({\n frequencyPenalty: z.number().min(-2).max(2).optional(),\n logitBias: z.record(z.string(), z.number().min(-100).max(100)).optional(),\n logProbs: z.boolean().optional(),\n presencePenalty: z.number().min(-2).max(2).optional(),\n seed: z.number().int().optional(),\n topLogProbs: z.number().int().min(0).max(20).optional(),\n user: z.string().optional(),\n visualDetailLevel: z.enum(['auto', 'low', 'high']).optional(),\n});\n\nexport const gpt4o = modelRef({\n name: 'azure-openai/gpt-4o',\n info: {\n versions: ['gpt-4o'],\n label: 'OpenAI - GPT-4o',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt4oMini = modelRef({\n name: 'azure-openai/gpt-4o-mini',\n info: {\n versions: ['gpt-4o-mini'],\n label: 'OpenAI - GPT-4o Mini',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt4 = modelRef({\n name: 'azure-openai/gpt-4',\n info: {\n versions: ['gpt-4', 'gpt-4-32k'],\n label: 'OpenAI - GPT-4',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt45 = modelRef({\n name: 'azure-openai/gpt-4.5',\n info: {\n versions: ['gpt-4.5-preview'],\n label: 'OpenAI - GPT-4.5',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt41 = modelRef({\n name: 'azure-openai/gpt-4.1',\n info: {\n versions: ['gpt-4.1'],\n label: 'OpenAI - GPT-4.1',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt41Mini = modelRef({\n name: 'azure-openai/gpt-4.1-mini',\n info: {\n versions: ['gpt-4.1-mini'],\n label: 'OpenAI - GPT-4.1 Mini',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt41Nano = modelRef({\n name: 'azure-openai/gpt-4.1-nano',\n info: {\n versions: ['gpt-4.1-nano'],\n label: 'OpenAI - GPT-4.1 Nano',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text', 'json'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const o1 = modelRef({\n name: 'azure-openai/o1',\n info: {\n versions: ['o1'],\n label: 'OpenAI - o1',\n supports: {\n multiturn: true,\n tools: false,\n media: true,\n systemRole: true,\n output: ['text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const o1Mini = modelRef({\n name: 'azure-openai/o1-mini',\n info: {\n versions: ['o1-mini'],\n label: 'OpenAI - o1 Mini',\n supports: {\n multiturn: true,\n tools: true,\n media: false,\n systemRole: true,\n output: ['text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const o1Preview = modelRef({\n name: 'azure-openai/o1-preview',\n info: {\n versions: ['o1-preview'],\n label: 'OpenAI - o1 Preview',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const o3 = modelRef({\n name: 'azure-openai/o3',\n info: {\n versions: ['o3'],\n label: 'OpenAI - o3',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const o4Mini = modelRef({\n name: 'azure-openai/o4-mini',\n info: {\n versions: ['o4-mini'],\n label: 'OpenAI - o4 Mini',\n supports: {\n multiturn: true,\n tools: true,\n media: true,\n systemRole: true,\n output: ['text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const o3Mini = modelRef({\n name: 'azure-openai/o3-mini',\n info: {\n versions: ['o3-mini'],\n label: 'OpenAI - o3 Mini',\n supports: {\n multiturn: true,\n tools: true,\n media: false,\n systemRole: true,\n output: ['text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const gpt35Turbo = modelRef({\n name: 'azure-openai/gpt-3.5-turbo',\n info: {\n versions: ['gpt-3.5-turbo', 'gpt-35-turbo-instruct', 'gpt-35-turbo-16k'],\n label: 'OpenAI - GPT-3.5 Turbo',\n supports: {\n multiturn: true,\n tools: true,\n media: false,\n systemRole: true,\n output: ['json', 'text'],\n },\n },\n configSchema: OpenAiConfigSchema,\n});\n\nexport const SUPPORTED_GPT_MODELS = {\n 'o1-mini': o1Mini,\n 'o1-preview': o1Preview,\n o1: o1,\n o3: o3,\n 'o3-mini': o3Mini,\n 'o4-mini': o4Mini,\n gpt41: gpt41,\n 'gpt41-mini': gpt41Mini,\n 'gpt41-nano': gpt41Nano,\n 'gpt-4': gpt4,\n 'gpt-4o': gpt4o,\n 'gpt-4o-mini': gpt4oMini,\n 'gpt-4.5': gpt45,\n 'gpt-3.5-turbo': gpt35Turbo,\n};\n\nfunction toOpenAIRole(role: Role): ChatCompletionRole {\n switch (role) {\n case 'user':\n return 'user';\n case 'model':\n return 'assistant';\n case 'system':\n return 'system';\n case 'tool':\n return 'tool';\n default:\n throw new Error(`role ${role} doesn't map to an OpenAI role.`);\n }\n}\n\nfunction toOpenAiTool(tool: ToolDefinition): ChatCompletionTool {\n let parameters;\n if (tool.inputSchema !== null) {\n if (typeof tool.inputSchema === 'string') {\n try {\n parameters = JSON.parse(tool.inputSchema);\n } catch (error) {\n const errorMessage =\n error instanceof Error ? error.message : 'Unknown parsing error';\n throw new Error(\n `Invalid JSON schema for function '${tool.name}': ${errorMessage}`\n );\n }\n } else {\n parameters = tool.inputSchema;\n }\n\n parameters.type = 'object';\n parameters.properties = {\n ...tool.inputSchema!.properties,\n };\n }\n\n return {\n type: 'function',\n function: {\n name: tool.name,\n parameters: parameters,\n },\n };\n}\n\nexport function toOpenAiTextAndMedia(\n part: Part,\n visualDetailLevel: VisualDetailLevel\n): ChatCompletionContentPart {\n if (part.text) {\n return {\n type: 'text',\n text: part.text,\n };\n } else if (part.media) {\n return {\n type: 'image_url',\n image_url: {\n url: part.media.url,\n detail: visualDetailLevel,\n },\n };\n }\n throw Error(\n `Unsupported genkit part fields encountered for current message role: ${part}.`\n );\n}\n\nexport function toOpenAiMessages(\n messages: MessageData[],\n visualDetailLevel: VisualDetailLevel = 'auto'\n): ChatCompletionMessageParam[] {\n const openAiMsgs: ChatCompletionMessageParam[] = [];\n for (const message of messages) {\n const msg = new Message(message);\n const role = toOpenAIRole(message.role);\n switch (role) {\n case 'user':\n openAiMsgs.push({\n role: role,\n content: msg.content.map((part) =>\n toOpenAiTextAndMedia(part, visualDetailLevel)\n ),\n });\n break;\n case 'system':\n openAiMsgs.push({\n role: role,\n content: msg.text,\n });\n break;\n case 'assistant':\n const toolCalls: ChatCompletionMessageToolCall[] = msg.content\n .filter((part) => part.toolRequest)\n .map((part) => {\n if (!part.toolRequest) {\n throw Error(\n 'Mapping genkit message to openai tool call content part but message.toolRequest not provided.'\n );\n }\n return {\n id: part.toolRequest.ref || '',\n type: 'function',\n function: {\n name: part.toolRequest.name,\n arguments: JSON.stringify(part.toolRequest.input),\n },\n };\n });\n if (toolCalls?.length > 0) {\n openAiMsgs.push({\n role: role,\n tool_calls: toolCalls,\n });\n } else {\n openAiMsgs.push({\n role: role,\n content: msg.text,\n });\n }\n break;\n case 'tool':\n const toolResponseParts = msg.toolResponseParts();\n toolResponseParts.map((part) => {\n openAiMsgs.push({\n role: role,\n tool_call_id: part.toolResponse.ref || '',\n content:\n typeof part.toolResponse.output === 'string'\n ? part.toolResponse.output\n : JSON.stringify(part.toolResponse.output),\n });\n });\n break;\n default:\n throw new Error('unrecognized role');\n }\n }\n return openAiMsgs;\n}\n\nconst finishReasonMap: Record<\n // OpenAI Node SDK doesn't support tool_call in the enum, but it is returned from the API\n CompletionChoice['finish_reason'] | 'tool_calls',\n CandidateData['finishReason']\n> = {\n length: 'length',\n stop: 'stop',\n tool_calls: 'stop',\n content_filter: 'blocked',\n};\n\nfunction fromOpenAiToolCall(\n toolCall:\n | ChatCompletionMessageToolCall\n | ChatCompletionChunk.Choice.Delta.ToolCall,\n choice: ChatCompletion.Choice | ChatCompletionChunk.Choice\n) {\n if (!toolCall.function) {\n throw Error(\n `Unexpected openAI chunk choice. tool_calls was provided but one or more tool_calls is missing.`\n );\n }\n const f = toolCall.function;\n if (choice.finish_reason === 'tool_calls') {\n return {\n toolRequest: {\n name: f.name,\n ref: toolCall.id,\n input: f.arguments ? JSON.parse(f.arguments) : f.arguments,\n },\n };\n } else {\n return {\n toolRequest: {\n name: f.name,\n ref: toolCall.id,\n input: '',\n },\n };\n }\n}\n\nfunction fromOpenAiChoice(\n choice: ChatCompletion['choices'][0],\n jsonMode = false\n): CandidateData {\n const toolRequestParts = choice.message.tool_calls?.map((toolCall) =>\n fromOpenAiToolCall(toolCall, choice)\n );\n return {\n index: choice.index,\n finishReason: finishReasonMap[choice.finish_reason] || 'other',\n message: {\n role: 'model',\n content: toolRequestParts\n ? // Note: Not sure why I have to cast here exactly.\n // Otherwise it thinks toolRequest must be 'undefined' if provided\n (toolRequestParts as ToolRequestPart[])\n : [\n jsonMode\n ? { data: JSON.parse(choice.message.content!) }\n : { text: choice.message.content! },\n ],\n },\n custom: {},\n };\n}\n\nfunction fromOpenAiChunkChoice(\n choice: ChatCompletionChunk['choices'][0],\n jsonMode = false\n): CandidateData {\n const toolRequestParts = choice.delta.tool_calls?.map((toolCall) =>\n fromOpenAiToolCall(toolCall, choice)\n );\n return {\n index: choice.index,\n finishReason: choice.finish_reason\n ? finishReasonMap[choice.finish_reason] || 'other'\n : 'unknown',\n message: {\n role: 'model',\n content: toolRequestParts\n ? // Note: Not sure why I have to cast here exactly.\n // Otherwise it thinks toolRequest must be 'undefined' if provided\n (toolRequestParts as ToolRequestPart[])\n : [\n jsonMode\n ? { data: JSON.parse(choice.delta.content!) }\n : { text: choice.delta.content! },\n ],\n },\n custom: {},\n };\n}\n\nexport function toOpenAiRequestBody(\n modelName: string,\n request: GenerateRequest\n) {\n const mapToSnakeCase = >(\n obj: T\n ): Record => {\n return Object.entries(obj).reduce((acc, [key, value]) => {\n const snakeCaseKey = key.replace(\n /[A-Z]/g,\n (letter) => `_${letter.toLowerCase()}`\n );\n acc[snakeCaseKey] = value;\n return acc;\n }, {});\n };\n const model = SUPPORTED_GPT_MODELS[modelName];\n if (!model) throw new Error(`Unsupported model: ${modelName}`);\n const openAiMessages = toOpenAiMessages(\n request.messages,\n request.config?.visualDetailLevel\n );\n const mappedModelName = request.config?.version || modelName;\n const body = {\n messages: openAiMessages,\n tools: request.tools?.map(toOpenAiTool),\n model: mappedModelName,\n max_tokens: request.config?.maxOutputTokens,\n temperature: request.config?.temperature,\n top_p: request.config?.topP,\n n: request.candidates,\n stop: request.config?.stopSequences,\n ...mapToSnakeCase(request.config?.custom || {}),\n } as ChatCompletionCreateParamsNonStreaming;\n\n const response_format = request.output?.format;\n if (\n response_format &&\n MODELS_SUPPORTING_OPENAI_RESPONSE_FORMAT.includes(mappedModelName)\n ) {\n if (\n response_format === 'json' &&\n model.info.supports?.output?.includes('json')\n ) {\n body.response_format = {\n type: 'json_object',\n };\n } else if (\n response_format === 'text' &&\n model.info.supports?.output?.includes('text')\n ) {\n body.response_format = {\n type: 'text',\n };\n } else {\n throw new Error(\n `${response_format} format is not supported for GPT models currently`\n );\n }\n }\n for (const key in body) {\n if (!body[key] || (Array.isArray(body[key]) && !body[key].length))\n delete body[key];\n }\n return body;\n}\n\n/**\n *\n */\nexport function gptModel(ai: Genkit, name: string, client: AzureOpenAI) {\n const modelId = `azure-openai/${name}`;\n const model = SUPPORTED_GPT_MODELS[name];\n if (!model) throw new Error(`Unsupported model: ${name}`);\n\n return ai.defineModel(\n {\n name: modelId,\n ...model.info,\n configSchema: SUPPORTED_GPT_MODELS[name].configSchema,\n },\n async (request, streamingCallback) => {\n let response: ChatCompletion;\n const body = toOpenAiRequestBody(name, request);\n if (streamingCallback) {\n const stream = client.beta.chat.completions.stream({\n ...body,\n stream: true,\n });\n for await (const chunk of stream) {\n chunk.choices?.forEach((chunk) => {\n const c = fromOpenAiChunkChoice(chunk);\n streamingCallback({\n index: c.index,\n content: c.message.content,\n });\n });\n }\n response = await stream.finalChatCompletion();\n } else {\n response = await client.chat.completions.create(body);\n }\n return {\n candidates: response.choices.map((c) =>\n fromOpenAiChoice(c, request.output?.format === 'json')\n ),\n usage: {\n inputTokens: response.usage?.prompt_tokens,\n outputTokens: response.usage?.completion_tokens,\n totalTokens: response.usage?.total_tokens,\n },\n custom: response,\n };\n }\n 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