Attempting to add support for anthropic

examples/abort-chat-completion.ts

@@ -1,6 +1,6 @@
 import 'dotenv/config';
 
-import { ChatModel, type Msg, MsgUtil } from '@dexaai/dexter';
+import { ChatModel, type Msg, MsgUtil } from '../src/index.js';
 
 /**
  * npx tsx examples/abort-chat-completion.ts

examples/ai-function.ts

@@ -1,8 +1,14 @@
 import 'dotenv/config';
 
-import { ChatModel, createAIFunction, type Msg, MsgUtil } from '@dexaai/dexter';
 import { z } from 'zod';
 
+import {
+  ChatModel,
+  createAIFunction,
+  type Msg,
+  MsgUtil,
+} from '../src/index.js';
+
 /**
  * npx tsx examples/ai-function.ts
  */

examples/ai-runner-with-error.ts

@@ -1,12 +1,18 @@
 import 'dotenv/config';
 
+import { z } from 'zod';
+
 import {
   ChatModel,
   createAIFunction,
   createAIRunner,
   MsgUtil,
+<<<<<<< HEAD
+} from '../src/index.js';
+=======
 } from '@dexaai/dexter';
 import { z } from 'zod';
+>>>>>>> origin/master
 
 /** Get the weather for a given location. */
 const getWeather = createAIFunction(

examples/ai-runner.ts

@@ -1,12 +1,18 @@
 import 'dotenv/config';
 
+import { z } from 'zod';
+
 import {
   ChatModel,
   createAIFunction,
   createAIRunner,
   MsgUtil,
+<<<<<<< HEAD
+} from '../src/index.js';
+=======
 } from '@dexaai/dexter';
 import { z } from 'zod';
+>>>>>>> origin/master
 
 /** Get the weather for a given location. */
 const getWeather = createAIFunction(

examples/anthropic-ai-function.ts

@@ -0,0 +1,108 @@
+import 'dotenv/config';
+
+import { z } from 'zod';
+
+import {
+  ChatModel,
+  createAIFunction,
+  createAnthropicClient,
+  type Msg,
+  MsgUtil,
+} from '../src/index.js';
+
+/**
+ * npx tsx examples/ai-function.ts
+ */
+async function main() {
+  const getWeather = createAIFunction(
+    {
+      name: 'get_weather',
+      description: 'Gets the weather for a given location',
+      argsSchema: z.object({
+        location: z
+          .string()
+          .describe('The city and state e.g. San Francisco, CA'),
+        unit: z
+          .enum(['c', 'f'])
+          .optional()
+          .default('f')
+          .describe('The unit of temperature to use'),
+      }),
+    },
+    // Fake weather API implementation which returns a random temperature
+    // after a short delay
+    async (args: { location: string; unit?: string }) => {
+      await new Promise((resolve) => setTimeout(resolve, 500));
+
+      return {
+        location: args.location,
+        unit: args.unit,
+        temperature: (30 + Math.random() * 70) | 0,
+      };
+    }
+  );
+
+  const chatModel = new ChatModel({
+    debug: true,
+    client: createAnthropicClient(),
+    params: {
+      model: 'claude-2.0',
+      temperature: 0.5,
+      max_tokens: 500,
+      tools: [
+        {
+          type: 'function',
+          function: getWeather.spec,
+        },
+      ],
+    },
+  });
+
+  const messages: Msg[] = [
+    MsgUtil.user('What is the weather in San Francisco?'),
+  ];
+
+  {
+    // Invoke the chat model and have it create the args for the `get_weather` function
+    const { message } = await chatModel.run({
+      messages,
+      model: 'claude-2.0',
+      tool_choice: {
+        type: 'function',
+        function: {
+          name: 'get_weather',
+        },
+      },
+    });
+
+    if (!MsgUtil.isToolCall(message)) {
+      throw new Error('Expected tool call');
+    }
+    messages.push(message);
+
+    for (const toolCall of message.tool_calls) {
+      if (toolCall.function.name !== 'get_weather') {
+        throw new Error(`Invalid function name: ${toolCall.function.name}`);
+      }
+
+      const result = await getWeather(toolCall.function.arguments);
+      const toolResult = MsgUtil.toolResult(result, toolCall.id);
+      messages.push(toolResult);
+    }
+  }
+
+  {
+    // Invoke the chat model with the result
+    const { message } = await chatModel.run({
+      messages,
+      tool_choice: 'none',
+    });
+    if (!MsgUtil.isAssistant(message)) {
+      throw new Error('Expected assistant message');
+    }
+
+    console.log(message.content);
+  }
+}
+
+main();

examples/anthropic-ai-runner.ts

@@ -0,0 +1,98 @@
+import 'dotenv/config';
+
+import { z } from 'zod';
+
+import {
+  ChatModel,
+  createAIFunction,
+  createAIRunner,
+  createAnthropicClient,
+  MsgUtil,
+} from '../src/index.js';
+
+/** Get the weather for a given location. */
+const getWeather = createAIFunction(
+  {
+    name: 'get_weather',
+    description: 'Gets the weather for a given location',
+    argsSchema: z.object({
+      location: z
+        .string()
+        .describe('The city and state e.g. San Francisco, CA'),
+      unit: z
+        .enum(['c', 'f'])
+        .optional()
+        .default('f')
+        .describe('The unit of temperature to use'),
+    }),
+  },
+  async ({ location, unit }) => {
+    await new Promise((resolve) => setTimeout(resolve, 500));
+    const temperature = (30 + Math.random() * 70) | 0;
+    return { location, unit, temperature };
+  }
+);
+
+/** Get the capital city for a given state. */
+const getCapitalCity = createAIFunction(
+  {
+    name: 'get_capital_city',
+    description: 'Use this to get the the capital city for a given state',
+    argsSchema: z.object({
+      state: z
+        .string()
+        .length(2)
+        .describe(
+          'The state to get the capital city for, using the two letter abbreviation e.g. CA'
+        ),
+    }),
+  },
+  async ({ state }) => {
+    await new Promise((resolve) => setTimeout(resolve, 500));
+    let capitalCity = '';
+    switch (state) {
+      case 'CA':
+        capitalCity = 'Sacramento';
+        break;
+      case 'NY':
+        capitalCity = 'Albany';
+        break;
+      default:
+        capitalCity = 'Unknown';
+    }
+    return { capitalCity };
+  }
+);
+
+/** A runner that uses the weather and capital city functions. */
+const weatherCapitalRunner = createAIRunner({
+  chatModel: new ChatModel({
+    client: createAnthropicClient(),
+    params: { model: 'claude-2.0' },
+  }),
+  functions: [getWeather, getCapitalCity],
+  systemMessage: `You use functions to answer questions about the weather and capital cities.`,
+});
+
+/**
+ * npx tsx examples/ai-runner.ts
+ */
+async function main() {
+  // Run with a string input
+  const rString = await weatherCapitalRunner(
+    `Whats the capital of California and NY and the weather for both`
+  );
+  console.log('rString', rString);
+
+  // Run with a message input
+  const rMessage = await weatherCapitalRunner({
+    messages: [
+      MsgUtil.user(
+        `Whats the capital of California and NY and the weather for both`
+      ),
+    ],
+  });
+  console.log('rMessage', rMessage);
+}
+
+main().catch(console.error);

examples/caching-redis.ts

@@ -1,9 +1,14 @@
 import 'dotenv/config';
 
+<<<<<<< HEAD
+=======
 import { EmbeddingModel } from '@dexaai/dexter';
+>>>>>>> origin/master
 import KeyvRedis from '@keyv/redis';
 import Keyv from 'keyv';
 
+import { EmbeddingModel } from '../src/index.js';
+
 /**
  * npx tsx examples/caching-redis.ts
  */

examples/embeddings.ts

@@ -0,0 +1,25 @@
+import 'dotenv/config';
+
+import { createOpenAIClient, EmbeddingModel } from '../src/index.js';
+
+/**
+ * npx tsx examples/ai-function.ts
+ */
+async function main() {
+  const embeddingModel = new EmbeddingModel({
+    client: createOpenAIClient(),
+    params: { model: 'text-embedding-3-small' },
+  });
+
+  {
+    // Invoke the chat model and have it create the args for the `get_weather` function
+    const response = await embeddingModel.run({
+      input: ['What is the weather in San Francisco?'],
+      model: 'text-embedding-3-small',
+    });
+
+    console.log(response);
+  }
+}
+
+main();

examples/extract-people-names.ts

@@ -1,8 +1,13 @@
 import 'dotenv/config';
 
+<<<<<<< HEAD
+=======
 import { ChatModel, createExtractFunction } from '@dexaai/dexter';
+>>>>>>> origin/master
 import { z } from 'zod';
 
+import { ChatModel, createExtractFunction } from '../src/index.js';
+
 /** A function to extract people names from text. */
 const extractPeopleNamesRunner = createExtractFunction({
   chatModel: new ChatModel({ params: { model: 'gpt-4o-mini' } }),

examples/with-telemetry.ts

@@ -1,9 +1,10 @@
 import './instrument.js';
 import 'dotenv/config';
 
-import { ChatModel } from '@dexaai/dexter';
 import * as Sentry from '@sentry/node';
 
+import { ChatModel } from '../src/index.js';
+
 const chatModel = new ChatModel({
   // Send tracing data to Sentry
   telemetry: Sentry,

package.json

@@ -49,7 +49,8 @@
     "hash-object": "^5.0.1",
     "jsonrepair": "^3.8.1",
     "ky": "^1.7.2",
-    "openai-fetch": "3.3.1",
+    "ai-fetch": "../ai-fetch",
+    "openai-fetch": "../openai-fetch",
     "openai-zod-to-json-schema": "^1.0.3",
     "p-map": "^7.0.2",
     "p-throttle": "^6.2.0",
@@ -58,7 +59,8 @@
     "tslib": "^2.7.0",
     "zod": "^3.23.8",
     "zod-to-json-schema": "^3.23.3",
-    "zod-validation-error": "^3.4.0"
+    "zod-validation-error": "^3.4.0",
+    "anthropic-fetch": "../anthropic-fetch"
   },
   "devDependencies": {
     "@dexaai/eslint-config": "^1.3.6",