genkitx-azure-openai/lib/gpt.mjs.map

Firebase Genkit AI framework plugin for Azure OpenAI APIs.

{"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];\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', 'gpt-4o-mini'],\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 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 gptO1 = modelRef({\n  name: 'azure-openai/gpt-o1',\n  info: {\n    versions: ['gpt-o1'],\n    label: 'OpenAI - GPT-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 gptO1Mini = modelRef({\n  name: 'azure-openai/gpt-o1-mini',\n  info: {\n    versions: ['o1-mini'],\n    label: 'OpenAI - GPT-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 gptO1Preview = modelRef({\n  name: 'azure-openai/gpt-o1-preview',\n  info: {\n    versions: ['o1-preview'],\n    label: 'OpenAI - GPT-o1 Preview',\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 gptO3Mini = modelRef({\n  name: 'azure-openai/gpt-o3-mini',\n  info: {\n    versions: ['o3-mini'],\n    label: 'OpenAI - GPT-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  'gpt-o1-mini': gptO1Mini,\n  'gpt-o1-preview': gptO1Preview,\n  'gpt-o1': gptO1,\n  'gpt-o3-mini': gptO3Mini,\n  'gpt-4': gpt4,\n  'gpt-4o': gpt4o,\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  return {\n    type: 'function',\n    function: {\n      name: tool.name,\n      parameters: tool.inputSchema !== null ? tool.inputSchema : undefined,\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) {\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  return {\n    toolRequest: {\n      name: f.name,\n      ref: toolCall.id,\n      input: f.arguments ? JSON.parse(f.arguments) : f.arguments,\n    },\n  };\n}\n\nfunction fromOpenAiChoice(\n  choice: ChatCompletion['choices'][0],\n  jsonMode = false\n): CandidateData {\n  const toolRequestParts = choice.message.tool_calls?.map(fromOpenAiToolCall);\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(fromOpenAiToolCall);\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 = <T extends Record<string, any>>(\n    obj: T\n  ): Record<string, any> => {\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     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