@langchain/community
Version:
Third-party integrations for LangChain.js
138 lines (137 loc) • 5.46 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
exports.OllamaFunctions = void 0;
const messages_1 = require("@langchain/core/messages");
const chat_models_1 = require("@langchain/core/language_models/chat_models");
const prompts_1 = require("@langchain/core/prompts");
const ollama_js_1 = require("../../chat_models/ollama.cjs");
const DEFAULT_TOOL_SYSTEM_TEMPLATE = `You have access to the following tools:
{tools}
You must always select one of the above tools and respond with only a JSON object matching the following schema:
{{
"tool": <name of the selected tool>,
"tool_input": <parameters for the selected tool, matching the tool's JSON schema>
}}`;
class OllamaFunctions extends chat_models_1.BaseChatModel {
static lc_name() {
return "OllamaFunctions";
}
constructor(fields) {
super(fields ?? {});
Object.defineProperty(this, "llm", {
enumerable: true,
configurable: true,
writable: true,
value: void 0
});
Object.defineProperty(this, "toolSystemPromptTemplate", {
enumerable: true,
configurable: true,
writable: true,
value: DEFAULT_TOOL_SYSTEM_TEMPLATE
});
Object.defineProperty(this, "defaultResponseFunction", {
enumerable: true,
configurable: true,
writable: true,
value: {
name: "__conversational_response",
description: "Respond conversationally if no other tools should be called for a given query.",
parameters: {
type: "object",
properties: {
response: {
type: "string",
description: "Conversational response to the user.",
},
},
required: ["response"],
},
}
});
Object.defineProperty(this, "lc_namespace", {
enumerable: true,
configurable: true,
writable: true,
value: ["langchain", "experimental", "chat_models"]
});
this.llm = fields?.llm ?? new ollama_js_1.ChatOllama({ ...fields, format: "json" });
this.toolSystemPromptTemplate =
fields?.toolSystemPromptTemplate ?? this.toolSystemPromptTemplate;
}
invocationParams() {
return this.llm.invocationParams();
}
/** @ignore */
_identifyingParams() {
return this.llm._identifyingParams();
}
async _generate(messages, options, runManager) {
let functions = options.functions ?? [];
if (options.function_call !== undefined) {
functions = functions.filter((fn) => fn.name === options.function_call?.name);
if (!functions.length) {
throw new Error(`If "function_call" is specified, you must also pass a matching function in "functions".`);
}
}
else if (functions.length === 0) {
functions.push(this.defaultResponseFunction);
}
const systemPromptTemplate = prompts_1.SystemMessagePromptTemplate.fromTemplate(this.toolSystemPromptTemplate);
const systemMessage = await systemPromptTemplate.format({
tools: JSON.stringify(functions, null, 2),
});
const chatResult = await this.llm._generate([systemMessage, ...messages], options, runManager);
const chatGenerationContent = chatResult.generations[0].message.content;
if (typeof chatGenerationContent !== "string") {
throw new Error("OllamaFunctions does not support non-string output.");
}
let parsedChatResult;
try {
parsedChatResult = JSON.parse(chatGenerationContent);
}
catch (e) {
throw new Error(`"${this.llm.model}" did not respond with valid JSON. Please try again.`);
}
const calledToolName = parsedChatResult.tool;
const calledToolArguments = parsedChatResult.tool_input;
const calledTool = functions.find((fn) => fn.name === calledToolName);
if (calledTool === undefined) {
throw new Error(`Failed to parse a function call from ${this.llm.model} output: ${chatGenerationContent}`);
}
if (calledTool.name === this.defaultResponseFunction.name) {
return {
generations: [
{
message: new messages_1.AIMessage({
content: calledToolArguments.response,
}),
text: calledToolArguments.response,
},
],
};
}
const responseMessageWithFunctions = new messages_1.AIMessage({
content: "",
additional_kwargs: {
function_call: {
name: calledToolName,
arguments: calledToolArguments
? JSON.stringify(calledToolArguments)
: "",
},
},
});
return {
generations: [{ message: responseMessageWithFunctions, text: "" }],
};
}
_llmType() {
return "ollama_functions";
}
/** @ignore */
_combineLLMOutput() {
return [];
}
}
exports.OllamaFunctions = OllamaFunctions;