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more intuitive and consistent interface on top of existing chatbot APIs.","maintainers":[{"name":"lackita","email":"lackita@gmail.com"}],"readme":"# Colloquy\n\nA more intuitive and consistent interface on top of existing chatbot APIs.\n\n## Installation\n\n```bash\n# Using npm\nnpm install colloquy_chatbot\n\n# Using Bun\nbun add colloquy_chatbot\n\n# Using yarn\nyarn add colloquy_chatbot\n```\n\n## Quick Start\n\n```typescript\nimport { OpenAIBot, ClaudeBot, PromptFunction } from \"colloquy_chatbot\";\n\n// Create a basic OpenAI chatbot\nconst openaiBot = new OpenAIBot({\n  instructions: \"You are a helpful assistant.\",\n});\n\n// Or use Claude\nconst claudeBot = new ClaudeBot({\n  instructions: \"You are a helpful assistant.\",\n});\n\n// Send a message and get a response\nconst response = await openaiBot.prompt(\"Hello, can you help me?\");\nconsole.log(response); // Bot's response\n\n// Create a chatbot with function calling\nfunction getWeather(location = \"New York\") {\n  return `It's sunny in ${location}`;\n}\n\nconst weatherBot = new OpenAIBot({\n  instructions: \"You can check the weather.\",\n  functions: [\n    new PromptFunction(getWeather, {\n      description: \"Get the current weather for a location\",\n    }),\n  ],\n});\n\nconst weatherResponse = await weatherBot.prompt(\n  \"What's the weather like in Tokyo?\",\n);\nconsole.log(weatherResponse);\n```\n\n## Chatbot Types\n\n### OpenAIBot\n\nThe main chatbot implementation that uses OpenAI's API:\n\n```typescript\nimport { OpenAIBot } from \"colloquy_chatbot\";\n\nconst bot = new OpenAIBot({\n  instructions: \"You are a helpful assistant.\", // Optional system message\n});\n\nconst response = await bot.prompt(\"Hello!\");\nconsole.log(response);\n\n// Access conversation history\nconsole.log(bot.history);\n```\n\n### ClaudeBot\n\nThe chatbot implementation that uses Anthropic's Claude API:\n\n```typescript\nimport { ClaudeBot } from \"colloquy_chatbot\";\n\nconst bot = new ClaudeBot({\n  instructions: \"You are a helpful assistant.\", // Optional system message\n});\n\nconst response = await bot.prompt(\"Hello!\");\nconsole.log(response);\n\n// Access conversation history\nconsole.log(bot.history);\n```\n\n### EchoBot\n\nA simple bot for testing that echoes back the input:\n\n```typescript\nimport { EchoBot } from \"colloquy_chatbot\";\n\nconst bot = new EchoBot();\nconst response = await bot.prompt(\"Hello!\");\nconsole.log(response); // \"Hello!\"\n```\n\n### Custom Bots\n\nCreate your own bot by extending the ChatBot class:\n\n```typescript\nimport { ChatBot, BotMessage } from \"colloquy_chatbot\";\n\nclass ReverseBot extends ChatBot {\n  async send_prompt(): Promise<BotMessage> {\n    const lastMessage = this.history.at(-1);\n    const reversed = lastMessage.text.split(\"\").reverse().join(\"\");\n    return new BotMessage(reversed);\n  }\n}\n\nconst bot = new ReverseBot();\nconsole.log(await bot.prompt(\"Hello\")); // \"olleH\"\n```\n\n## Function Calling\n\nColloquy makes it easy to enable function calling with both OpenAI and Claude:\n\n### With OpenAI\n\n```typescript\nimport { OpenAIBot, PromptFunction } from \"colloquy_chatbot\";\n\n// Define a function\nfunction calculateArea(length = 1, width = 1) {\n  return length * width;\n}\n\n// Create a bot with the function\nconst bot = new OpenAIBot({\n  functions: [\n    new PromptFunction(calculateArea, {\n      description: \"Calculate the area of a rectangle\",\n      parameters: {\n        length: { description: \"The length of the rectangle\" },\n        width: { description: \"The width of the rectangle\" },\n      },\n    }),\n  ],\n});\n\n// The AI can now use the function when appropriate\nconst response = await bot.prompt(\"What's the area of a 5x3 rectangle?\");\nconsole.log(response);\n```\n\n### With Claude\n\n```typescript\nimport { ClaudeBot, PromptFunction } from \"colloquy_chatbot\";\n\n// Define a function\nfunction calculateArea(length = 1, width = 1) {\n  return length * width;\n}\n\n// Create a bot with the function\nconst bot = new ClaudeBot({\n  functions: [\n    new PromptFunction(calculateArea, {\n      description: \"Calculate the area of a rectangle\",\n      parameters: {\n        length: { description: \"The length of the rectangle\" },\n        width: { description: \"The width of the rectangle\" },\n      },\n    }),\n  ],\n});\n\n// Claude can now use the function when appropriate\nconst response = await bot.prompt(\"What's the area of a 5x3 rectangle?\");\nconsole.log(response);\n```\n\nIt can infer a lot from the function definition itself:\n\n- It can determine the name from the name of the function\n  - It understands both `() => \"foo\"` and `function test() { return \"foo\" }`, but only the latter has a name attached\n- Default parameters are used to infer the type when they are specified\n  - Typescript annotations are stripped at runtime, but default parameters are always there\n\nThese inferences are there to make your life easier, but you can always override everything but parameter names like this:\n\n```typescript\nnew PromptFunction(calculateArea, {\n  name: \"some-other-name\",\n  description: \"Calculate the area of a rectangle\",\n  parameters: {\n    length: {\n      type: \"string\",\n      description: \"The length of the rectangle\",\n    },\n    width: {\n      type: \"number\",\n      description: \"The width of the rectangle\",\n    },\n  },\n});\n```\n\nPositional arguments get translated into an object before being sent to OpenAI, so feel free to use them in your functions. The goal is to allow you to define functions in a way that is intuitive, while still translating into a form supported by the API.\n\n### Environment Variables\n\n- `OPENAI_API_KEY`: Required for using OpenAIBot\n- `ANTHROPIC_API_KEY`: Required for using ClaudeBot\n\n## License\n\nMIT\n","readmeFilename":"README.md"}