feat: add initial support for OpenAI functions w/ chat completion

examples/basic.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

examples/facts.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

examples/functions.ts

@@ -0,0 +1,19 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
+import 'dotenv/config'
+import { z } from 'zod'
+
+import { Agentic, CalculatorTool } from '@/index'
+
+async function main() {
+  const openai = new OpenAIClient({ apiKey: process.env.OPENAI_API_KEY! })
+  const agentic = new Agentic({ openai })
+
+  const example = await agentic
+    .gpt4('What is 5 * 50?')
+    .tools([new CalculatorTool({ agentic })])
+    .output(z.object({ answer: z.number() }))
+    .call()
+  console.log(example)
+}
+
+main()

examples/llm-with-search.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic, MetaphorSearchTool } from '@/index'

examples/sentiment.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

package.json

@@ -38,11 +38,13 @@
     "test:eslint": "eslint \"**/*.ts\""
   },
   "dependencies": {
+    "@agentic/openai-fetch": "^1.5.3",
     "@anthropic-ai/sdk": "^0.4.4",
     "@inquirer/checkbox": "^1.3.1",
     "@inquirer/editor": "^1.2.0",
     "@inquirer/input": "^1.2.1",
     "@inquirer/select": "^1.2.1",
+    "@types/json-schema": "^7.0.12",
     "debug": "^4.3.4",
     "expr-eval": "^2.0.2",
     "handlebars": "^4.7.7",
@@ -52,7 +54,6 @@
     "ky": "^0.33.3",
     "nanoid": "^4.0.2",
     "normalize-url": "^8.0.0",
-    "openai-fetch": "^1.5.1",
     "p-map": "^6.0.0",
     "p-retry": "^5.1.2",
     "p-timeout": "^6.1.2",
@@ -60,6 +61,7 @@
     "ts-dedent": "^2.2.0",
     "uuid": "^9.0.0",
     "zod": "^3.21.4",
+    "zod-to-json-schema": "^3.21.1",
     "zod-to-ts": "^1.1.4",
     "zod-validation-error": "^1.3.0"
   },

pnpm-lock.yaml

@@ -1,10 +1,13 @@
-lockfileVersion: '6.1'
+lockfileVersion: '6.0'
 
 settings:
   autoInstallPeers: true
   excludeLinksFromLockfile: false
 
 dependencies:
+  '@agentic/openai-fetch':
+    specifier: ^1.5.3
+    version: 1.5.3
   '@anthropic-ai/sdk':
     specifier: ^0.4.4
     version: 0.4.4
@@ -20,6 +23,9 @@ dependencies:
   '@inquirer/select':
     specifier: ^1.2.1
     version: 1.2.1
+  '@types/json-schema':
+    specifier: ^7.0.12
+    version: 7.0.12
   debug:
     specifier: ^4.3.4
     version: 4.3.4
@@ -47,9 +53,6 @@ dependencies:
   normalize-url:
     specifier: ^8.0.0
     version: 8.0.0
-  openai-fetch:
-    specifier: ^1.5.1
-    version: 1.5.1
   p-map:
     specifier: ^6.0.0
     version: 6.0.0
@@ -71,6 +74,9 @@ dependencies:
   zod:
     specifier: ^3.21.4
     version: 3.21.4
+  zod-to-json-schema:
+    specifier: ^3.21.1
+    version: 3.21.1(zod@3.21.4)
   zod-to-ts:
     specifier: ^1.1.4
     version: 1.1.4(typescript@5.1.3)(zod@3.21.4)
@@ -163,6 +169,13 @@ devDependencies:
 
 packages:
 
+  /@agentic/openai-fetch@1.5.3:
+    resolution: {integrity: sha512-4c5YWz6jQdGxxM+SVhf0XW3mKYnFr56hntPep+y7wRfkjUl6lgZiuU3J61esQ8bj8vSFkgSfwjf3DeZIi/IEsg==}
+    dependencies:
+      ky: 0.33.3
+      zod: 3.21.4
+    dev: false
+
   /@anthropic-ai/sdk@0.4.4:
     resolution: {integrity: sha512-Z/39nQi1sSUCeLII3lsAbL1u+0JF6cR2XmUEX9sLH0VtxmIjY6cjOUYjCkYh4oapTxOkhAFnVSAFJ6cxml2qXg==}
     dependencies:
@@ -756,7 +769,6 @@ packages:
 
   /@types/json-schema@7.0.12:
     resolution: {integrity: sha512-Hr5Jfhc9eYOQNPYO5WLDq/n4jqijdHNlDXjuAQkkt+mWdQR+XJToOHrsD4cPaMXpn6KO7y2+wM8AZEs8VpBLVA==}
-    dev: true
 
   /@types/minimist@1.2.2:
     resolution: {integrity: sha512-jhuKLIRrhvCPLqwPcx6INqmKeiA5EWrsCOPhrlFSrbrmU4ZMPjj5Ul/oLCMDO98XRUIwVm78xICz4EPCektzeQ==}
@@ -2989,13 +3001,6 @@ packages:
       mimic-fn: 4.0.0
     dev: true
 
-  /openai-fetch@1.5.1:
-    resolution: {integrity: sha512-LDSsXTFa2ssjYTZY51+B/69wXg8/UteqKyPtuFa+bMFRav7ACQXi3AJl+gieh3BF8La95NHCE0FS8t0F8fRHwA==}
-    dependencies:
-      ky: 0.33.3
-      zod: 3.21.4
-    dev: false
-
   /optionator@0.9.1:
     resolution: {integrity: sha512-74RlY5FCnhq4jRxVUPKDaRwrVNXMqsGsiW6AJw4XK8hmtm10wC0ypZBLw5IIp85NZMr91+qd1RvvENwg7jjRFw==}
     engines: {node: '>= 0.8.0'}
@@ -4147,6 +4152,14 @@ packages:
     engines: {node: '>=12.20'}
     dev: true
 
+  /zod-to-json-schema@3.21.1(zod@3.21.4):
+    resolution: {integrity: sha512-y5g0MPxDq+YG/T+cHGPYH4PcBpyCqwK6wxeJ76MR563y0gk/14HKfebq8xHiItY7lkc9GDFygCnkvNDTvAhYAg==}
+    peerDependencies:
+      zod: ^3.21.4
+    dependencies:
+      zod: 3.21.4
+    dev: false
+
   /zod-to-ts@1.1.4(typescript@5.1.3)(zod@3.21.4):
     resolution: {integrity: sha512-jsCg+pTNxLAdJOfW4ul+SpechdGYEJPPnssSbqWdR2LSIkotT22k+UvqPb1nEHwe/YbEcbUOlZUfGM0npgR+Jg==}
     peerDependencies:

scratch/examples/calc-eval.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

scratch/examples/equation-producer.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

scratch/examples/food-expert.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

scratch/examples/human-feedback-select.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic, HumanFeedbackSelect } from '@/index'

scratch/examples/human-feedback.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic, HumanFeedbackSingle } from '@/index'

scratch/examples/json-summary.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

scratch/examples/misc.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic } from '@/agentic'

scratch/examples/tools.ts

@@ -1,5 +1,5 @@
+import { OpenAIClient } from '@agentic/openai-fetch'
 import 'dotenv/config'
-import { OpenAIClient } from 'openai-fetch'
 import { z } from 'zod'
 
 import { Agentic, MetaphorSearchTool } from '@/index'

scratch/scratch-types.ts

@@ -0,0 +1,74 @@
+import { z } from 'zod'
+
+// export type ChatMessageRole = 'user' | 'system' | 'assistant'
+export const ChatMessageRoleSchema = z.union([
+  z.literal('user'),
+  z.literal('system'),
+  z.literal('assistant'),
+  z.literal('function')
+])
+export type ChatMessageRole = z.infer<typeof ChatMessageRoleSchema>
+
+export interface ChatMessageBase {
+  role: ChatMessageRole
+  content: string
+  name?: string
+}
+
+export interface ChatMessageUser extends ChatMessageBase {
+  role: 'user'
+}
+
+export interface ChatMessageSystem extends ChatMessageBase {
+  role: 'system'
+}
+
+export interface ChatMessageAssistant extends ChatMessageBase {
+  role: 'assistant'
+}
+
+export interface ChatMessageFunctionCall extends ChatMessageBase {
+  role: 'assistant'
+  function_call: FunctionCall
+}
+
+export interface FunctionCall {
+  name: string
+  arguments: string
+}
+
+export interface ChatMessageFunction extends ChatMessageBase {
+  role: 'function'
+  name: string
+}
+
+export type ChatMessage =
+  | ChatMessageUser
+  | ChatMessageSystem
+  | ChatMessageAssistant
+  | ChatMessageFunctionCall
+  | ChatMessageFunction
+
+export interface FunctionDefinition {
+  /**
+   * The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
+   */
+  name: string
+
+  /**
+   * The description of what the function does.
+   */
+  description?: string
+
+  /**
+   * The parameters the functions accepts, described as a JSON Schema object. See the [guide](/docs/guides/gpt/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format.
+   */
+  parameters?: { [key: string]: any }
+}
+
+export type FunctionCallOptions =
+  | 'none'
+  | 'auto'
+  | {
+      name: string
+    }

src/llms/anthropic.ts

@@ -47,6 +47,14 @@ export class AnthropicChatModel<
     }
   }
 
+  public override get nameForModel(): string {
+    return 'anthropic_chat'
+  }
+
+  public override get nameForHuman(): string {
+    return 'AnthropicChatModel'
+  }
+
   protected override async _createChatCompletion(
     messages: types.ChatMessage[]
   ): Promise<types.BaseChatCompletionResponse<anthropic.CompletionResponse>> {
@@ -62,6 +70,7 @@ export class AnthropicChatModel<
               return message.content
           }
         })
+        .filter(Boolean)
         .join('') + anthropic.AI_PROMPT
 
     // TODO: support streaming

src/llms/chat.ts

@@ -3,6 +3,7 @@ import pMap from 'p-map'
 import { dedent } from 'ts-dedent'
 import { type SetRequired } from 'type-fest'
 import { ZodType, z } from 'zod'
+import { zodToJsonSchema } from 'zod-to-json-schema'
 import { printNode, zodToTs } from 'zod-to-ts'
 
 import * as errors from '@/errors'
@@ -14,6 +15,7 @@ import {
   extractJSONObjectFromString
 } from '@/utils'
 
+import { BaseTask } from '../task'
 import { BaseLLM } from './llm'
 
 export abstract class BaseChatModel<
@@ -22,7 +24,8 @@ export abstract class BaseChatModel<
   TModelParams extends Record<string, any> = Record<string, any>,
   TChatCompletionResponse extends Record<string, any> = Record<string, any>
 > extends BaseLLM<TInput, TOutput, TModelParams> {
-  _messages: types.ChatMessage[]
+  protected _messages: types.ChatMessage[]
+  protected _tools?: BaseTask<any, any>[]
 
   constructor(
     options: SetRequired<
@@ -33,6 +36,7 @@ export abstract class BaseChatModel<
     super(options)
 
     this._messages = options.messages
+    this._tools = options.tools
   }
 
   // TODO: use polymorphic `this` type to return correct BaseLLM subclass type
@@ -57,6 +61,11 @@ export abstract class BaseChatModel<
     return refinedInstance
   }
 
+  tools(tools: BaseTask<any, any>[]): this {
+    this._tools = tools
+    return this
+  }
+
   protected abstract _createChatCompletion(
     messages: types.ChatMessage[]
   ): Promise<types.BaseChatCompletionResponse<TChatCompletionResponse>>
@@ -70,9 +79,6 @@ export abstract class BaseChatModel<
       input = this.inputSchema.parse(input)
     }
 
-    // TODO: validate input message variables against input schema
-    console.log({ input })
-
     const messages = this._messages
       .map((message) => {
         return {
@@ -263,9 +269,15 @@ export abstract class BaseChatModel<
     const numTokensPerMessage = await pMap(
       messages,
       async (message) => {
+        let content = message.content || ''
+        if (message.function_call) {
+          // TODO: this case needs testing
+          content = message.function_call.arguments
+        }
+
         const [numTokensContent, numTokensRole, numTokensName] =
           await Promise.all([
-            this.getNumTokens(message.content),
+            this.getNumTokens(content),
             this.getNumTokens(message.role),
             message.name
               ? this.getNumTokens(message.name).then((n) => n + tokensPerName)

src/llms/llm.ts

@@ -69,7 +69,11 @@ export abstract class BaseLLM<
     }
   }
 
-  public override get name(): string {
+  public override get nameForModel(): string {
+    return `${this._provider}_chat`
+  }
+
+  public override get nameForHuman(): string {
     return `${this._provider}:chat:${this._model}`
   }
 

src/llms/openai.ts

@@ -38,16 +38,26 @@ export class OpenAIChatModel<
     }
   }
 
+  public override get nameForModel(): string {
+    return 'openai_chat'
+  }
+
+  public override get nameForHuman(): string {
+    return 'OpenAIChatModel'
+  }
+
   protected override async _createChatCompletion(
     messages: types.ChatMessage[]
   ): Promise<
     types.BaseChatCompletionResponse<types.openai.ChatCompletionResponse>
   > {
-    return this._client.createChatCompletion({
+    const res = await this._client.createChatCompletion({
       ...this._modelParams,
       model: this._model,
       messages
     })
+
+    return res
   }
 
   public override clone(): OpenAIChatModel<TInput, TOutput> {
@@ -61,6 +71,7 @@ export class OpenAIChatModel<
       model: this._model,
       examples: this._examples,
       messages: this._messages,
+      tools: this._tools,
       ...this._modelParams
     })
   }

src/task.ts

@@ -46,12 +46,20 @@ export abstract class BaseTask<TInput = void, TOutput = string> {
   public abstract get inputSchema(): ZodType<TInput>
   public abstract get outputSchema(): ZodType<TOutput>
 
-  public abstract get name(): string
+  public abstract get nameForModel(): string
+
+  public get nameForHuman(): string {
+    return this.nameForModel
+  }
+
+  public get descForModel(): string {
+    return ''
+  }
 
   // TODO: is this really necessary?
   public clone(): BaseTask<TInput, TOutput> {
     // TODO: override in subclass if needed
-    throw new Error(`clone not implemented for task "${this.name}"`)
+    throw new Error(`clone not implemented for task "${this.nameForModel}"`)
   }
 
   public retryConfig(retryConfig: types.RetryConfig): this {
@@ -81,7 +89,7 @@ export abstract class BaseTask<TInput = void, TOutput = string> {
       input,
       attemptNumber: 0,
       metadata: {
-        taskName: this.name,
+        taskName: this.nameForModel,
         taskId: this.id,
         callId: this._agentic.idGeneratorFn()
       }

src/tokenizer.ts

@@ -91,6 +91,11 @@ export async function getTokenizerForModel(
 }
 
 export function getModelNameForTiktoken(modelName: string): TiktokenModel {
+  if (modelName.startsWith('gpt-3.5-turbo-16k-')) {
+    // TODO: remove this once the model is added to tiktoken
+    return 'gpt-3.5-turbo-16k' as TiktokenModel
+  }
+
   if (modelName.startsWith('gpt-3.5-turbo-')) {
     return 'gpt-3.5-turbo'
   }
@@ -119,6 +124,9 @@ export function getContextSizeForModel(model: string): number {
   const modelName = getModelNameForTiktoken(model)
 
   switch (modelName) {
+    case 'gpt-3.5-turbo-16k' as TiktokenModel:
+      return 16384
+
     case 'gpt-3.5-turbo':
       return 4096
 

src/tools/calculator.ts

@@ -29,11 +29,15 @@ export class CalculatorTool extends BaseTask<
     return CalculatorOutputSchema
   }
 
-  public override get name(): string {
+  public override get nameForModel(): string {
     return 'calculator'
   }
 
-  public get descriptionForModel(): string {
+  public override get nameForHuman(): string {
+    return 'Calculator'
+  }
+
+  public override get descForModel(): string {
     return 'Useful for getting the result of a math expression. The input to this tool should be a valid mathematical expression that could be executed by a simple calculator.'
   }
 

src/tools/metaphor.ts

@@ -33,8 +33,8 @@ export class MetaphorSearchTool extends BaseTask<
     return metaphor.MetaphorSearchOutputSchema
   }
 
-  public override get name(): string {
-    return 'metaphor-search'
+  public override get nameForModel(): string {
+    return 'metaphor_web_search'
   }
 
   protected override async _call(

src/tools/novu.ts

@@ -63,8 +63,8 @@ export class NovuNotificationTool extends BaseTask<
     return NovuNotificationToolOutputSchema
   }
 
-  public override get name(): string {
-    return 'novu'
+  public override get nameForModel(): string {
+    return 'novu_send_notification'
   }
 
   protected override async _call(

src/types.ts

@@ -1,10 +1,11 @@
+import * as openai from '@agentic/openai-fetch'
 import * as anthropic from '@anthropic-ai/sdk'
-import * as openai from 'openai-fetch'
 import type { Options as RetryOptions } from 'p-retry'
 import type { JsonObject } from 'type-fest'
 import { SafeParseReturnType, ZodType, ZodTypeAny, output, z } from 'zod'
 
 import type { Agentic } from './agentic'
+import type { BaseTask } from './task'
 
 export { openai }
 export { anthropic }
@@ -54,19 +55,8 @@ export interface LLMOptions<
   promptSuffix?: string
 }
 
-// export type ChatMessageRole = 'user' | 'system' | 'assistant'
-export const ChatMessageRoleSchema = z.union([
-  z.literal('user'),
-  z.literal('system'),
-  z.literal('assistant')
-])
-export type ChatMessageRole = z.infer<typeof ChatMessageRoleSchema>
-
-export interface ChatMessage {
-  role: ChatMessageRole
-  content: string
-  name?: string
-}
+export type ChatMessage = openai.ChatMessage
+export type ChatMessageRole = openai.ChatMessageRole
 
 export interface ChatModelOptions<
   TInput = void,
@@ -74,6 +64,7 @@ export interface ChatModelOptions<
   TModelParams extends Record<string, any> = Record<string, any>
 > extends BaseLLMOptions<TInput, TOutput, TModelParams> {
   messages: ChatMessage[]
+  tools?: BaseTask<any, any>[]
 }
 
 export interface BaseChatCompletionResponse<

test/_utils.ts

@@ -1,11 +1,11 @@
 import * as anthropic from '@anthropic-ai/sdk'
+import { OpenAIClient } from '@agentic/openai-fetch'
 import KeyvRedis from '@keyv/redis'
 import 'dotenv/config'
 import hashObject from 'hash-obj'
 import Redis from 'ioredis'
 import Keyv from 'keyv'
 import defaultKy from 'ky'
-import { OpenAIClient } from 'openai-fetch'
 import pMemoize from 'p-memoize'
 
 import { Agentic } from '@/agentic'

test/services/openai.test.ts

@@ -0,0 +1,72 @@
+import test from 'ava'
+
+import * as types from '@/types'
+
+import { createOpenAITestClient } from '../_utils'
+
+test('OpenAIClient - createChatCompletion - functions', async (t) => {
+  const openai = createOpenAITestClient()
+
+  const model = 'gpt-3.5-turbo-0613'
+  const messages: types.ChatMessage[] = [
+    {
+      role: 'user',
+      content: 'What’s the weather like in Boston right now?'
+    }
+  ]
+  const functions = [
+    {
+      name: 'get_current_weather',
+      description: 'Get the current weather in a given location',
+      parameters: {
+        type: 'object',
+        properties: {
+          location: {
+            type: 'string',
+            description: 'The city and state, e.g. San Francisco, CA'
+          },
+          unit: {
+            type: 'string',
+            enum: ['celsius', 'fahrenheit']
+          }
+        },
+        required: ['location']
+      }
+    }
+  ]
+
+  const res0 = await openai.createChatCompletion({
+    model,
+    messages,
+    functions
+  })
+
+  // console.log(JSON.stringify(res0, null, 2))
+  t.is(res0.message.role, 'assistant')
+  t.is(res0.message.content as any, null)
+  t.is(res0.message.function_call!.name, 'get_current_weather')
+
+  const args = JSON.parse(res0.message.function_call!.arguments)
+  t.deepEqual(args, { location: 'Boston' })
+
+  const weatherMock = { temperature: 22, unit: 'celsius', description: 'Sunny' }
+
+  const res1 = await openai.createChatCompletion({
+    model,
+    messages: [
+      ...messages,
+      res0.message,
+      {
+        role: 'function',
+        name: 'get_current_weather',
+        content: JSON.stringify(weatherMock)
+      }
+    ],
+    functions
+  })
+
+  // console.log(JSON.stringify(res1, null, 2))
+  t.is(res1.message.role, 'assistant')
+  t.true(res1.message.content.length > 0)
+  t.is(res1.message.function_call, undefined)
+})

test/tokenizer.test.ts

@@ -7,6 +7,7 @@ import './_utils'
 const models = [
   'gpt-3.5-turbo',
   'gpt-4',
+  'gpt-4-0613',
   'text-davinci-003',
   'code-davinci-002'
 ]