langchain - npm Package Compare versions

Comparing version 0.0.4 to 0.0.5

dist/cjs/agents/agent.d.ts

@@ -7,3 +7,12 @@ import { ChainValues } from "../chains";
 export interface StaticAgent {
+    /**
+     * Create a prompt for this class
+     *
+     * @param tools - List of tools the agent will have access to, used to format the prompt.
+     * @param fields - Additional fields used to format the prompt.
+     *
+     * @returns A PromptTemplate assembled from the given tools and fields.
+     * */
     createPrompt(tools: Tool[], fields?: Record<string, any>): BasePromptTemplate;
+    /** Construct an agent from an LLM and a list of tools */
     fromLLMAndTools(llm: BaseLLM, tools: Tool[], args?: Record<string, any>): Agent;
@@ -18,2 +27,9 @@ validateTools(_: Tool[]): void;
 }
+/**
+ * Class responsible for calling a language model and deciding an action.
+ *
+ * @remarks This is driven by an LLMChain. The prompt in the LLMChain *must*
+ * include a variable called "agent_scratchpad" where the agent can put its
+ * intermediary work.
+ */
 export declare abstract class Agent {
@@ -24,2 +40,5 @@ llmChain: LLMChain;
     constructor(input: AgentInput);
+    /**
+     * Extract tool and tool input from LLM output.
+     */
     abstract extractToolAndInput(input: string): {
@@ -29,13 +48,48 @@ tool: string;
     } | null;
+    /**
+     * Prefix to append the observation with.
+     */
     abstract observationPrefix(): string;
+    /**
+     * Prefix to append the LLM call with.
+     */
     abstract llmPrefix(): string;
+    /**
+     * Return the string type key uniquely identifying this class of agent.
+     */
     abstract _agentType(): string;
+    /**
+     * Prepare the agent for a new call, if needed
+     */
     prepareForNewCall(): void;
+    /**
+     * Validate that appropriate tools are passed in
+     */
     static validateTools(_: Tool[]): void;
     _stop(): string[];
+    /**
+     * Name of tool to use to terminate the chain.
+     */
     finishToolName(): string;
+    /**
+     * Construct a scratchpad to let the agent continue its thought process
+     */
     private constructScratchPad;
     private _plan;
+    /**
+     * Decide what to do given some input.
+     *
+     * @param steps - Steps the LLM has taken so far, along with observations from each.
+     * @param inputs - User inputs.
+     *
+     * @returns Action specifying what tool to use.
+     */
     plan(steps: AgentStep[], inputs: ChainValues): Promise<AgentAction | AgentFinish>;
+    /**
+     * Return response when agent has been stopped due to max iterations
+     */
     returnStoppedResponse(earlyStoppingMethod: StoppingMethod, steps: AgentStep[], inputs: ChainValues): Promise<AgentFinish>;
+    /**
+     * Load an agent from a json-like object describing it.
+     */
     static deserialize(data: SerializedAgent & {
@@ -42,0 +96,0 @@ llm?: BaseLLM;

dist/cjs/agents/agent.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -28,2 +19,9 @@ exports.Agent = exports.staticImplements = void 0;
 exports.staticImplements = staticImplements;
+/**
+ * Class responsible for calling a language model and deciding an action.
+ *
+ * @remarks This is driven by an LLMChain. The prompt in the LLMChain *must*
+ * include a variable called "agent_scratchpad" where the agent can put its
+ * intermediary work.
+ */
 class Agent {
@@ -52,3 +50,9 @@ constructor(input) {
     }
+    /**
+     * Prepare the agent for a new call, if needed
+     */
     prepareForNewCall() { }
+    /**
+     * Validate that appropriate tools are passed in
+     */
     // eslint-disable-next-line no-unused-vars
@@ -59,5 +63,11 @@ static validateTools(_) { }
     }
+    /**
+     * Name of tool to use to terminate the chain.
+     */
     finishToolName() {
         return "Final Answer";
     }
+    /**
+     * Construct a scratchpad to let the agent continue its thought process
+     */
     constructScratchPad(steps) {
@@ -71,60 +81,72 @@ return steps.reduce((thoughts, { action, observation }) => thoughts +
     }
-    _plan(steps, inputs, suffix) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const thoughts = this.constructScratchPad(steps);
-            const newInputs = Object.assign(Object.assign({}, inputs), { agent_scratchpad: suffix ? `${thoughts}${suffix}` : thoughts, stop: this._stop() });
-            const output = yield this.llmChain.predict(newInputs);
-            const parsed = this.extractToolAndInput(output);
-            if (!parsed) {
-                throw new ParseError(`Invalid output: ${output}`, output);
-            }
-            const action = {
-                tool: parsed.tool,
-                toolInput: parsed.input,
-                log: output,
-            };
-            if (action.tool === this.finishToolName()) {
-                return { returnValues: { output: action.toolInput }, log: action.log };
-            }
-            return action;
-        });
+    async _plan(steps, inputs, suffix) {
+        const thoughts = this.constructScratchPad(steps);
+        const newInputs = {
+            ...inputs,
+            agent_scratchpad: suffix ? `${thoughts}${suffix}` : thoughts,
+            stop: this._stop(),
+        };
+        const output = await this.llmChain.predict(newInputs);
+        const parsed = this.extractToolAndInput(output);
+        if (!parsed) {
+            throw new ParseError(`Invalid output: ${output}`, output);
+        }
+        const action = {
+            tool: parsed.tool,
+            toolInput: parsed.input,
+            log: output,
+        };
+        if (action.tool === this.finishToolName()) {
+            return { returnValues: { output: action.toolInput }, log: action.log };
+        }
+        return action;
     }
+    /**
+     * Decide what to do given some input.
+     *
+     * @param steps - Steps the LLM has taken so far, along with observations from each.
+     * @param inputs - User inputs.
+     *
+     * @returns Action specifying what tool to use.
+     */
     plan(steps, inputs) {
         return this._plan(steps, inputs);
     }
-    returnStoppedResponse(earlyStoppingMethod, steps, inputs) {
-        return __awaiter(this, void 0, void 0, function* () {
-            if (earlyStoppingMethod === "force") {
-                return {
-                    returnValues: { output: "Agent stopped due to max iterations." },
-                    log: "",
-                };
+    /**
+     * Return response when agent has been stopped due to max iterations
+     */
+    async returnStoppedResponse(earlyStoppingMethod, steps, inputs) {
+        if (earlyStoppingMethod === "force") {
+            return {
+                returnValues: { output: "Agent stopped due to max iterations." },
+                log: "",
+            };
+        }
+        if (earlyStoppingMethod === "generate") {
+            try {
+                const action = await this._plan(steps, inputs, "\n\nI now need to return a final answer based on the previous steps:");
+                if ("returnValues" in action) {
+                    return action;
+                }
+                return { returnValues: { output: action.log }, log: action.log };
             }
-            if (earlyStoppingMethod === "generate") {
-                try {
-                    const action = yield this._plan(steps, inputs, "\n\nI now need to return a final answer based on the previous steps:");
-                    if ("returnValues" in action) {
-                        return action;
-                    }
-                    return { returnValues: { output: action.log }, log: action.log };
+            catch (err) {
+                if (!(err instanceof ParseError)) {
+                    throw err;
                 }
-                catch (err) {
-                    if (!(err instanceof ParseError)) {
-                        throw err;
-                    }
-                    return { returnValues: { output: err.output }, log: err.output };
-                }
+                return { returnValues: { output: err.output }, log: err.output };
             }
-            throw new Error(`Invalid stopping method: ${earlyStoppingMethod}`);
-        });
+        }
+        throw new Error(`Invalid stopping method: ${earlyStoppingMethod}`);
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            switch (data._type) {
-                case "zero-shot-react-description":
-                    return index_1.ZeroShotAgent.deserialize(data);
-                default:
-                    throw new Error("Unknown agent type");
-            }
-        });
+    /**
+     * Load an agent from a json-like object describing it.
+     */
+    static async deserialize(data) {
+        switch (data._type) {
+            case "zero-shot-react-description":
+                return index_1.ZeroShotAgent.deserialize(data);
+            default:
+                throw new Error("Unknown agent type");
+        }
     }
@@ -131,0 +153,0 @@ }

dist/cjs/agents/executor.d.ts

@@ -11,2 +11,6 @@ import { ChainValues, BaseChain } from "../chains";
 };
+/**
+ * A chain managing an agent using tools.
+ * @augments BaseChain
+ */
 export declare class AgentExecutor extends BaseChain {
@@ -19,2 +23,3 @@ agent: Agent;
     constructor(input: AgentExecutorInput);
+    /** Create from agent and a list of tools. */
     static fromAgentAndTools(fields: {
@@ -21,0 +26,0 @@ agent: Agent;

dist/cjs/agents/executor.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
 exports.AgentExecutor = void 0;
 const chains_1 = require("../chains");
+/**
+ * A chain managing an agent using tools.
+ * @augments BaseChain
+ */
 class AgentExecutor extends chains_1.BaseChain {
@@ -56,2 +51,3 @@ constructor(input) {
     }
+    /** Create from agent and a list of tools. */
     static fromAgentAndTools(fields) {
@@ -63,36 +59,34 @@ return new AgentExecutor(fields);
     }
-    _call(inputs) {
-        return __awaiter(this, void 0, void 0, function* () {
-            this.agent.prepareForNewCall();
-            const toolsByName = Object.fromEntries(this.tools.map((t) => [t.name, t]));
-            const steps = [];
-            let iterations = 0;
-            const getOutput = (finishStep) => {
-                const { returnValues } = finishStep;
-                if (this.returnIntermediateSteps) {
-                    return Object.assign(Object.assign({}, returnValues), { intermediateSteps: steps });
-                }
-                return returnValues;
-            };
-            while (this.shouldContinue(iterations)) {
-                const action = yield this.agent.plan(steps, inputs);
-                if ("returnValues" in action) {
-                    return getOutput(action);
-                }
-                const tool = toolsByName[action.tool];
-                const observation = tool
-                    ? yield tool.call(action.toolInput)
-                    : `${action.tool} is not a valid tool, try another one.`;
-                steps.push({ action, observation });
-                if (tool === null || tool === void 0 ? void 0 : tool.returnDirect) {
-                    return getOutput({
-                        returnValues: { [this.agent.returnValues[0]]: observation },
-                        log: "",
-                    });
-                }
-                iterations += 1;
+    async _call(inputs) {
+        this.agent.prepareForNewCall();
+        const toolsByName = Object.fromEntries(this.tools.map((t) => [t.name.toLowerCase(), t]));
+        const steps = [];
+        let iterations = 0;
+        const getOutput = (finishStep) => {
+            const { returnValues } = finishStep;
+            if (this.returnIntermediateSteps) {
+                return { ...returnValues, intermediateSteps: steps };
             }
-            const finish = yield this.agent.returnStoppedResponse(this.earlyStoppingMethod, steps, inputs);
-            return getOutput(finish);
-        });
+            return returnValues;
+        };
+        while (this.shouldContinue(iterations)) {
+            const action = await this.agent.plan(steps, inputs);
+            if ("returnValues" in action) {
+                return getOutput(action);
+            }
+            const tool = toolsByName[action.tool.toLowerCase()];
+            const observation = tool
+                ? await tool.call(action.toolInput)
+                : `${action.tool} is not a valid tool, try another one.`;
+            steps.push({ action, observation });
+            if (tool === null || tool === void 0 ? void 0 : tool.returnDirect) {
+                return getOutput({
+                    returnValues: { [this.agent.returnValues[0]]: observation },
+                    log: "",
+                });
+            }
+            iterations += 1;
+        }
+        const finish = await this.agent.returnStoppedResponse(this.earlyStoppingMethod, steps, inputs);
+        return getOutput(finish);
     }
@@ -99,0 +93,0 @@ _chainType() {

dist/cjs/agents/helpers.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -15,3 +6,3 @@ exports.deserializeHelper = void 0;
 const util_1 = require("../util");
-const deserializeHelper = (llm, tools, data, fromLLMAndTools, fromConstructor) => __awaiter(void 0, void 0, void 0, function* () {
+const deserializeHelper = async (llm, tools, data, fromLLMAndTools, fromConstructor) => {
     if (data.load_from_llm_and_tools) {
@@ -27,6 +18,6 @@ if (!llm) {
     const serializedLLMChain = (0, util_1.resolveConfigFromFile)("llm_chain", data);
-    const llmChain = yield chains_1.LLMChain.deserialize(serializedLLMChain);
-    return fromConstructor(Object.assign(Object.assign({}, data), { llmChain }));
-});
+    const llmChain = await chains_1.LLMChain.deserialize(serializedLLMChain);
+    return fromConstructor({ ...data, llmChain });
+};
 exports.deserializeHelper = deserializeHelper;
 //# sourceMappingURL=helpers.js.map

dist/cjs/agents/index.d.ts

@@ -6,2 +6,3 @@ export { AgentAction, AgentFinish, AgentStep, StoppingMethod, SerializedAgentT, } from "./types";
 export { Tool } from "./tools";
+export { initializeAgentExecutor } from "./initialize";
 export { loadAgent } from "./load";

dist/cjs/agents/index.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.loadAgent = exports.ZeroShotAgent = exports.AgentExecutor = exports.staticImplements = exports.Agent = void 0;
+exports.loadAgent = exports.initializeAgentExecutor = exports.Tool = exports.ZeroShotAgent = exports.AgentExecutor = exports.staticImplements = exports.Agent = void 0;
 var agent_1 = require("./agent");
@@ -11,4 +11,8 @@ Object.defineProperty(exports, "Agent", { enumerable: true, get: function () { return agent_1.Agent; } });
 Object.defineProperty(exports, "ZeroShotAgent", { enumerable: true, get: function () { return mrkl_1.ZeroShotAgent; } });
+var tools_1 = require("./tools");
+Object.defineProperty(exports, "Tool", { enumerable: true, get: function () { return tools_1.Tool; } });
+var initialize_1 = require("./initialize");
+Object.defineProperty(exports, "initializeAgentExecutor", { enumerable: true, get: function () { return initialize_1.initializeAgentExecutor; } });
 var load_1 = require("./load");
 Object.defineProperty(exports, "loadAgent", { enumerable: true, get: function () { return load_1.loadAgent; } });
 //# sourceMappingURL=index.js.map

dist/cjs/agents/load.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -16,8 +7,8 @@ exports.loadAgent = void 0;
 const util_1 = require("../util");
-const loadAgentFromFile = (file, llmAndTools) => __awaiter(void 0, void 0, void 0, function* () {
+const loadAgentFromFile = async (file, llmAndTools) => {
     const serialized = (0, util_1.parseFileConfig)(file);
-    return _1.Agent.deserialize(Object.assign(Object.assign({}, serialized), llmAndTools));
-});
-const loadAgent = (uri, llmAndTools) => __awaiter(void 0, void 0, void 0, function* () {
-    const hubResult = yield (0, hub_1.loadFromHub)(uri, (u) => loadAgentFromFile(u, llmAndTools), "agents", new Set(["json", "yaml"]));
+    return _1.Agent.deserialize({ ...serialized, ...llmAndTools });
+};
+const loadAgent = async (uri, llmAndTools) => {
+    const hubResult = await (0, hub_1.loadFromHub)(uri, (u) => loadAgentFromFile(u, llmAndTools), "agents", new Set(["json", "yaml"]));
     if (hubResult) {
@@ -27,4 +18,4 @@ return hubResult;
     return loadAgentFromFile(uri, llmAndTools);
-});
+};
 exports.loadAgent = loadAgent;
 //# sourceMappingURL=load.js.map

dist/cjs/agents/mrkl/index.d.ts

@@ -11,7 +11,15 @@ import { BaseLLM } from "../../llms";
 type CreatePromptArgs = {
+    /** String to put after the list of tools. */
     suffix?: string;
+    /** String to put before the list of tools. */
     prefix?: string;
+    /** List of input variables the final prompt will expect. */
     inputVariables?: string[];
 };
 type ZeroShotAgentInput = AgentInput;
+/**
+ * Agent for the MRKL chain.
+ * @augments Agent
+ * @augments StaticAgent
+ */
 export declare class ZeroShotAgent extends Agent {
@@ -23,2 +31,11 @@ constructor(input: ZeroShotAgentInput);
     static validateTools(tools: Tool[]): void;
+    /**
+     * Create prompt in the style of the zero shot agent.
+     *
+     * @param tools - List of tools the agent will have access to, used to format the prompt.
+     * @param args - Arguments to create the prompt with.
+     * @param args.suffix - String to put after the list of tools.
+     * @param args.prefix - String to put before the list of tools.
+     * @param args.inputVariables - List of input variables the final prompt will expect.
+     */
     static createPrompt(tools: Tool[], args?: CreatePromptArgs): PromptTemplate;
@@ -25,0 +42,0 @@ static fromLLMAndTools(llm: BaseLLM, tools: Tool[], args?: CreatePromptArgs): ZeroShotAgent;

dist/cjs/agents/mrkl/index.js

@@ -8,22 +8,2 @@ "use strict";
 };
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-var __rest = (this && this.__rest) || function (s, e) {
-    var t = {};
-    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
-        t[p] = s[p];
-    if (s != null && typeof Object.getOwnPropertySymbols === "function")
-        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
-            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
-                t[p[i]] = s[p[i]];
-        }
-    return t;
-};
 var ZeroShotAgent_1;
@@ -38,2 +18,7 @@ Object.defineProperty(exports, "__esModule", { value: true });
 const FINAL_ANSWER_ACTION = "Final Answer:";
+/**
+ * Agent for the MRKL chain.
+ * @augments Agent
+ * @augments StaticAgent
+ */
 let ZeroShotAgent = ZeroShotAgent_1 = class ZeroShotAgent extends index_1.Agent {
@@ -60,2 +45,11 @@ constructor(input) {
     }
+    /**
+     * Create prompt in the style of the zero shot agent.
+     *
+     * @param tools - List of tools the agent will have access to, used to format the prompt.
+     * @param args - Arguments to create the prompt with.
+     * @param args.suffix - String to put after the list of tools.
+     * @param args.prefix - String to put before the list of tools.
+     * @param args.inputVariables - List of input variables the final prompt will expect.
+     */
     static createPrompt(tools, args) {
@@ -97,11 +91,9 @@ const { prefix = prompt_2.PREFIX, suffix = prompt_2.SUFFIX, inputVariables = ["input", "agent_scratchpad"], } = args !== null && args !== void 0 ? args : {};
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const { llm, tools } = data, rest = __rest(data, ["llm", "tools"]);
-            return (0, helpers_1.deserializeHelper)(llm, tools, rest, (llm, tools, args) => ZeroShotAgent_1.fromLLMAndTools(llm, tools, {
-                prefix: args.prefix,
-                suffix: args.suffix,
-                inputVariables: args.input_variables,
-            }), (args) => new ZeroShotAgent_1(args));
-        });
+    static async deserialize(data) {
+        const { llm, tools, ...rest } = data;
+        return (0, helpers_1.deserializeHelper)(llm, tools, rest, (llm, tools, args) => ZeroShotAgent_1.fromLLMAndTools(llm, tools, {
+            prefix: args.prefix,
+            suffix: args.suffix,
+            inputVariables: args.input_variables,
+        }), (args) => new ZeroShotAgent_1(args));
     }
@@ -108,0 +100,0 @@ };

dist/cjs/agents/mrkl/prompt.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 exports.SUFFIX = exports.formatInstructions = exports.PREFIX = void 0;
-/* eslint-disable max-len */
 exports.PREFIX = `Answer the following questions as best you can. You have access to the following tools:`;
@@ -6,0 +5,0 @@ const formatInstructions = (toolNames) => `Use the following format:

dist/cjs/agents/tests/agent.test.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -17,6 +8,8 @@ const globals_1 = require("@jest/globals");
 const serpapi_1 = require("../tools/serpapi");
-(0, globals_1.test)("Run agent from hub", () => __awaiter(void 0, void 0, void 0, function* () {
-    const model = new openai_1.OpenAI({});
-    const tools = [(0, serpapi_1.SerpAPI)()];
-    const agent = yield (0, load_1.loadAgent)("lc://agents/zero-shot-react-description/agent.json", { llm: model, tools });
+const calculator_1 = require("../tools/calculator");
+const initialize_1 = require("../initialize");
+(0, globals_1.test)("Run agent from hub", async () => {
+    const model = new openai_1.OpenAI({ temperature: 0 });
+    const tools = [new serpapi_1.SerpAPI(), new calculator_1.Calculator()];
+    const agent = await (0, load_1.loadAgent)("lc://agents/zero-shot-react-description/agent.json", { llm: model, tools });
     const executor = index_1.AgentExecutor.fromAgentAndTools({
@@ -27,7 +20,18 @@ agent,
     });
-    const res = yield executor.call({
+    const res = await executor.call({
         input: "Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?",
     });
     console.log(res);
-}), 30000);
+}, 30000);
+(0, globals_1.test)("Run agent locally", async () => {
+    const model = new openai_1.OpenAI({ temperature: 0 });
+    const tools = [new serpapi_1.SerpAPI(), new calculator_1.Calculator()];
+    const executor = await (0, initialize_1.initializeAgentExecutor)(tools, model, "zero-shot-react-description");
+    console.log("Loaded agent.");
+    const input = "Who is Olivia Wilde's boyfriend?" +
+        " What is his current age raised to the 0.23 power?";
+    console.log(`Executing with input "${input}"...`);
+    const result = await executor.call({ input });
+    console.log(`Got output ${result.output}`);
+}, 30000);
 //# sourceMappingURL=agent.test.js.map

dist/cjs/agents/tools/index.d.ts

 export { SerpAPI } from "./serpapi";
-export interface Tool {
-    call: (arg: string) => Promise<string>;
-    name: string;
-    description: string;
-    returnDirect?: boolean;
-}
+export { Calculator } from "./calculator";
+export { Tool } from "./base";

dist/cjs/agents/tools/index.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.SerpAPI = void 0;
+exports.Tool = exports.Calculator = exports.SerpAPI = void 0;
 var serpapi_1 = require("./serpapi");
 Object.defineProperty(exports, "SerpAPI", { enumerable: true, get: function () { return serpapi_1.SerpAPI; } });
+var calculator_1 = require("./calculator");
+Object.defineProperty(exports, "Calculator", { enumerable: true, get: function () { return calculator_1.Calculator; } });
+var base_1 = require("./base");
+Object.defineProperty(exports, "Tool", { enumerable: true, get: function () { return base_1.Tool; } });
 //# sourceMappingURL=index.js.map

dist/cjs/agents/tools/serpapi.d.ts

@@ -1,3 +0,18 @@
-import { GoogleParameters } from "serpapi";
-import { Tool } from "./index";
-export declare const SerpAPI: (params?: Partial<GoogleParameters>, apiKey?: string) => Tool;
+import type { GoogleParameters } from "serpapi";
+import { Tool } from "./base";
+/**
+ * Wrapper around SerpAPI.
+ *
+ * To use, you should have the `serpapi` package installed and the SERPAPI_API_KEY environment variable set.
+ */
+export declare class SerpAPI extends Tool {
+    protected key: string;
+    protected params: Partial<GoogleParameters>;
+    constructor(apiKey?: string | undefined, params?: Partial<GoogleParameters>);
+    name: string;
+    /**
+     * Run query through SerpAPI and parse result
+     */
+    call(input: string): Promise<any>;
+    description: string;
+}

dist/cjs/agents/tools/serpapi.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
 exports.SerpAPI = void 0;
-const serpapi_1 = require("serpapi");
-const SerpAPI = (params, apiKey) => {
-    const key = apiKey !== null && apiKey !== void 0 ? apiKey : process.env.SERPAPI_API_KEY;
-    return {
-        name: "search",
-        call: (input) => __awaiter(void 0, void 0, void 0, function* () {
-            var _a, _b, _c, _d, _e, _f, _g;
-            const res = yield (0, serpapi_1.getJson)("google", Object.assign(Object.assign({}, params), { api_key: key, q: input }));
-            if (res.error) {
-                throw new Error(`Got error from serpAPI: ${res.error}`);
-            }
-            if ((_a = res.answer_box) === null || _a === void 0 ? void 0 : _a.answer) {
-                return res.answer_box.answer;
-            }
-            if ((_b = res.answer_box) === null || _b === void 0 ? void 0 : _b.snippet) {
-                return res.answer_box.snippet;
-            }
-            if ((_c = res.answer_box) === null || _c === void 0 ? void 0 : _c.snippet_highlighted_words) {
-                return res.answer_box.snippet_highlighted_words[0];
-            }
-            if ((_d = res.sports_results) === null || _d === void 0 ? void 0 : _d.game_spotlight) {
-                return res.sports_results.game_spotlight;
-            }
-            if ((_e = res.knowledge_graph) === null || _e === void 0 ? void 0 : _e.description) {
-                return res.knowledge_graph.description;
-            }
-            if ((_g = (_f = res.organic_results) === null || _f === void 0 ? void 0 : _f[0]) === null || _g === void 0 ? void 0 : _g.snippet) {
-                return res.organic_results[0].snippet;
-            }
-            return "No good search result found";
-        }),
-        description: 
-        // eslint-disable-next-line max-len
-        "a search engine. useful for when you need to answer questions about current events. input should be a search query.",
-    };
-};
+const base_1 = require("./base");
+let getJson = null;
+try {
+    // eslint-disable-next-line global-require,import/no-extraneous-dependencies
+    ({ getJson } = require("serpapi"));
+}
+catch (_a) {
+    // ignore error
+}
+/**
+ * Wrapper around SerpAPI.
+ *
+ * To use, you should have the `serpapi` package installed and the SERPAPI_API_KEY environment variable set.
+ */
+class SerpAPI extends base_1.Tool {
+    constructor(apiKey = process.env.SERPAPI_API_KEY, params = {}) {
+        super();
+        Object.defineProperty(this, "key", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: void 0
+        });
+        Object.defineProperty(this, "params", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: void 0
+        });
+        Object.defineProperty(this, "name", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: "search"
+        });
+        Object.defineProperty(this, "description", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: "a search engine. useful for when you need to answer questions about current events. input should be a search query."
+        });
+        // Throw error at construction time.
+        if (getJson === null) {
+            throw new Error("Please install serpapi as a dependency with, e.g. `npm i serpapi`");
+        }
+        if (!apiKey) {
+            throw new Error("SerpAPI API key not set. You can set it as SERPAPI_API_KEY in your .env file, or pass it to SerpAPI.");
+        }
+        this.key = apiKey;
+        this.params = params;
+    }
+    /**
+     * Run query through SerpAPI and parse result
+     */
+    async call(input) {
+        var _a, _b, _c, _d, _e, _f, _g;
+        if (getJson === null) {
+            throw new Error("Please install serpapi as a dependency with, e.g. `npm i serpapi`");
+        }
+        const res = await getJson("google", {
+            ...this.params,
+            api_key: this.key,
+            q: input,
+        });
+        if (res.error) {
+            throw new Error(`Got error from serpAPI: ${res.error}`);
+        }
+        if ((_a = res.answer_box) === null || _a === void 0 ? void 0 : _a.answer) {
+            return res.answer_box.answer;
+        }
+        if ((_b = res.answer_box) === null || _b === void 0 ? void 0 : _b.snippet) {
+            return res.answer_box.snippet;
+        }
+        if ((_c = res.answer_box) === null || _c === void 0 ? void 0 : _c.snippet_highlighted_words) {
+            return res.answer_box.snippet_highlighted_words[0];
+        }
+        if ((_d = res.sports_results) === null || _d === void 0 ? void 0 : _d.game_spotlight) {
+            return res.sports_results.game_spotlight;
+        }
+        if ((_e = res.knowledge_graph) === null || _e === void 0 ? void 0 : _e.description) {
+            return res.knowledge_graph.description;
+        }
+        if ((_g = (_f = res.organic_results) === null || _f === void 0 ? void 0 : _f[0]) === null || _g === void 0 ? void 0 : _g.snippet) {
+            return res.organic_results[0].snippet;
+        }
+        return "No good search result found";
+    }
+}
 exports.SerpAPI = SerpAPI;
 //# sourceMappingURL=serpapi.js.map

dist/cjs/chains/base.d.ts

@@ -1,12 +0,42 @@
-import { SerializedLLMChain } from "./index";
+import { LLMChain, StuffDocumentsChain, VectorDBQAChain, ChatVectorDBQAChain } from "./index";
+import { BaseMemory } from "../memory";
 export type ChainValues = Record<string, any>;
-type SerializedBaseChain = SerializedLLMChain;
-export declare abstract class BaseChain {
+export type LoadValues = Record<string, any>;
+declare const chainClasses: (typeof LLMChain | typeof StuffDocumentsChain | typeof VectorDBQAChain | typeof ChatVectorDBQAChain)[];
+export type SerializedBaseChain = ReturnType<InstanceType<(typeof chainClasses)[number]>["serialize"]>;
+export interface ChainInputs {
+    memory?: BaseMemory;
+}
+/**
+ * Base interface that all chains must implement.
+ */
+export declare abstract class BaseChain implements ChainInputs {
+    memory?: BaseMemory;
+    /**
+     * Run the core logic of this chain and return the output
+     */
     abstract _call(values: ChainValues): Promise<ChainValues>;
+    /**
+     * Return the string type key uniquely identifying this class of chain.
+     */
     abstract _chainType(): string;
+    /**
+     * Return a json-like object representing this chain.
+     */
     abstract serialize(): SerializedBaseChain;
+    /**
+     * Run the core logic of this chain and add to output if desired.
+     *
+     * Wraps {@link _call} and handles memory.
+     */
     call(values: ChainValues): Promise<ChainValues>;
+    /**
+     * Call the chain on all inputs in the list
+     */
     apply(inputs: ChainValues[]): ChainValues[];
-    static deserialize(data: SerializedBaseChain): Promise<BaseChain>;
+    /**
+     * Load a chain from a json-like object describing it.
+     */
+    static deserialize(data: SerializedBaseChain, values?: LoadValues): Promise<BaseChain>;
 }
 export {};

dist/cjs/chains/base.js

@@ -5,14 +5,52 @@ "use strict";
 const index_1 = require("./index");
+const chainClasses = [index_1.LLMChain, index_1.StuffDocumentsChain, index_1.VectorDBQAChain, index_1.ChatVectorDBQAChain];
+/**
+ * Base interface that all chains must implement.
+ */
 class BaseChain {
-    call(values) {
+    constructor() {
+        Object.defineProperty(this, "memory", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: void 0
+        });
+    }
+    /**
+     * Run the core logic of this chain and add to output if desired.
+     *
+     * Wraps {@link _call} and handles memory.
+     */
+    async call(values) {
+        const fullValues = structuredClone(values);
+        if (!(this.memory == null)) {
+            const newValues = await this.memory.loadMemoryVariables(values);
+            for (const [key, value] of Object.entries(newValues)) {
+                fullValues[key] = value;
+            }
+        }
         // TODO(sean) add callback support
-        return this._call(values);
+        const outputValues = this._call(fullValues);
+        if (!(this.memory == null)) {
+            this.memory.saveContext(values, outputValues);
+        }
+        return outputValues;
     }
+    /**
+     * Call the chain on all inputs in the list
+     */
     apply(inputs) {
         return inputs.map(this.call);
     }
-    static deserialize(data) {
+    /**
+     * Load a chain from a json-like object describing it.
+     */
+    static deserialize(data, values = {}) {
         switch (data._type) {
             case "llm_chain":
                 return index_1.LLMChain.deserialize(data);
+            case "stuff_documents_chain":
+                return index_1.StuffDocumentsChain.deserialize(data);
+            case "vector_db_qa":
+                return index_1.VectorDBQAChain.deserialize(data, values);
             default:
@@ -19,0 +57,0 @@ throw new Error(`Invalid prompt type in config: ${data._type}`);

dist/cjs/chains/index.d.ts

 export { BaseChain, ChainValues } from "./base";
-export { SerializedLLMChain, LLMChain } from "./llm_chain";
+export { SerializedLLMChain, LLMChain, ConversationChain } from "./llm_chain";
+export { SerializedStuffDocumentsChain, StuffDocumentsChain, } from "./combine_docs_chain";
+export { ChatVectorDBQAChain, SerializedChatVectorDBQAChain } from "./chat_vector_db_chain";
+export { VectorDBQAChain, SerializedVectorDBQAChain } from "./vector_db_qa";
 export { loadChain } from "./load";
+export { loadQAChain } from "./question_answering/load";

dist/cjs/chains/index.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.loadChain = exports.LLMChain = exports.BaseChain = void 0;
+exports.loadQAChain = exports.loadChain = exports.VectorDBQAChain = exports.ChatVectorDBQAChain = exports.StuffDocumentsChain = exports.ConversationChain = exports.LLMChain = exports.BaseChain = void 0;
 var base_1 = require("./base");
@@ -8,4 +8,13 @@ Object.defineProperty(exports, "BaseChain", { enumerable: true, get: function () { return base_1.BaseChain; } });
 Object.defineProperty(exports, "LLMChain", { enumerable: true, get: function () { return llm_chain_1.LLMChain; } });
+Object.defineProperty(exports, "ConversationChain", { enumerable: true, get: function () { return llm_chain_1.ConversationChain; } });
+var combine_docs_chain_1 = require("./combine_docs_chain");
+Object.defineProperty(exports, "StuffDocumentsChain", { enumerable: true, get: function () { return combine_docs_chain_1.StuffDocumentsChain; } });
+var chat_vector_db_chain_1 = require("./chat_vector_db_chain");
+Object.defineProperty(exports, "ChatVectorDBQAChain", { enumerable: true, get: function () { return chat_vector_db_chain_1.ChatVectorDBQAChain; } });
+var vector_db_qa_1 = require("./vector_db_qa");
+Object.defineProperty(exports, "VectorDBQAChain", { enumerable: true, get: function () { return vector_db_qa_1.VectorDBQAChain; } });
 var load_1 = require("./load");
 Object.defineProperty(exports, "loadChain", { enumerable: true, get: function () { return load_1.loadChain; } });
+var load_2 = require("./question_answering/load");
+Object.defineProperty(exports, "loadQAChain", { enumerable: true, get: function () { return load_2.loadQAChain; } });
 //# sourceMappingURL=index.js.map

dist/cjs/chains/llm_chain.d.ts

 import { BaseChain, ChainValues } from "./index";
 import { BaseLLM, SerializedLLM } from "../llms";
+import { BaseMemory } from "../memory";
 import { BasePromptTemplate, SerializedBasePromptTemplate } from "../prompt";
 export interface LLMChainInput {
+    /** Prompt object to use */
     prompt: BasePromptTemplate;
+    /** LLM Wrapper to use */
     llm: BaseLLM;
+    /** @ignore */
     outputKey: string;
@@ -16,2 +20,14 @@ }
 };
+/**
+ * Chain to run queries against LLMs.
+ * @augments BaseChain
+ * @augments LLMChainInput
+ *
+ * @example
+ * ```ts
+ * import { LLMChain, OpenAI, PromptTemplate } from "langchain";
+ * const prompt = PromptTemplate.fromTemplate("Tell me a {adjective} joke");
+ * const llm = LLMChain({ llm: new OpenAI(), prompt });
+ * ```
+ */
 export declare class LLMChain extends BaseChain implements LLMChainInput {
@@ -27,2 +43,13 @@ prompt: BasePromptTemplate;
     _call(values: ChainValues): Promise<ChainValues>;
+    /**
+     * Format prompt with values and pass to LLM
+     *
+     * @param values - keys to pass to prompt template
+     * @returns Completion from LLM.
+     *
+     * @example
+     * ```ts
+     * llm.predict({ adjective: "funny" })
+     * ```
+     */
     predict(values: ChainValues): Promise<string>;
@@ -33,1 +60,9 @@ _chainType(): "llm_chain";
 }
+export declare class ConversationChain extends LLMChain {
+    constructor(fields: {
+        llm: BaseLLM;
+        prompt?: BasePromptTemplate;
+        outputKey?: string;
+        memory?: BaseMemory;
+    });
+}

dist/cjs/chains/llm_chain.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.LLMChain = void 0;
+exports.ConversationChain = exports.LLMChain = void 0;
 const index_1 = require("./index");
 const llms_1 = require("../llms");
+const memory_1 = require("../memory");
 const prompt_1 = require("../prompt");
 const util_1 = require("../util");
+/**
+ * Chain to run queries against LLMs.
+ * @augments BaseChain
+ * @augments LLMChainInput
+ *
+ * @example
+ * ```ts
+ * import { LLMChain, OpenAI, PromptTemplate } from "langchain";
+ * const prompt = PromptTemplate.fromTemplate("Tell me a {adjective} joke");
+ * const llm = LLMChain({ llm: new OpenAI(), prompt });
+ * ```
+ */
 class LLMChain extends index_1.BaseChain {
@@ -43,19 +47,26 @@ constructor(fields) {
     }
-    _call(values) {
-        return __awaiter(this, void 0, void 0, function* () {
-            let stop;
-            if ("stop" in values && Array.isArray(values.stop)) {
-                stop = values.stop;
-            }
-            const formattedString = this.prompt.format(values);
-            const llmResult = yield this.llm.call(formattedString, stop);
-            const result = { [this.outputKey]: llmResult };
-            return result;
-        });
+    async _call(values) {
+        let stop;
+        if ("stop" in values && Array.isArray(values.stop)) {
+            stop = values.stop;
+        }
+        const formattedString = this.prompt.format(values);
+        const llmResult = await this.llm.call(formattedString, stop);
+        const result = { [this.outputKey]: llmResult };
+        return result;
     }
-    predict(values) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const output = yield this.call(values);
-            return output[this.outputKey];
-        });
+    /**
+     * Format prompt with values and pass to LLM
+     *
+     * @param values - keys to pass to prompt template
+     * @returns Completion from LLM.
+     *
+     * @example
+     * ```ts
+     * llm.predict({ adjective: "funny" })
+     * ```
+     */
+    async predict(values) {
+        const output = await this.call(values);
+        return output[this.outputKey];
     }
@@ -65,10 +76,8 @@ _chainType() {
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const serializedLLM = (0, util_1.resolveConfigFromFile)("llm", data);
-            const serializedPrompt = (0, util_1.resolveConfigFromFile)("prompt", data);
-            return new LLMChain({
-                llm: yield llms_1.BaseLLM.deserialize(serializedLLM),
-                prompt: yield prompt_1.BasePromptTemplate.deserialize(serializedPrompt),
-            });
+    static async deserialize(data) {
+        const serializedLLM = (0, util_1.resolveConfigFromFile)("llm", data);
+        const serializedPrompt = (0, util_1.resolveConfigFromFile)("prompt", data);
+        return new LLMChain({
+            llm: await llms_1.BaseLLM.deserialize(serializedLLM),
+            prompt: await prompt_1.BasePromptTemplate.deserialize(serializedPrompt),
         });
@@ -85,2 +94,25 @@ }
 exports.LLMChain = LLMChain;
+// eslint-disable-next-line max-len
+const defaultTemplate = `The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
+
+Current conversation:
+{history}
+Human: {input}
+AI:`;
+const defaultPrompt = new prompt_1.PromptTemplate({
+    template: defaultTemplate,
+    inputVariables: ["history", "input"],
+});
+class ConversationChain extends LLMChain {
+    constructor(fields) {
+        var _a, _b, _c;
+        super({
+            prompt: (_a = fields.prompt) !== null && _a !== void 0 ? _a : defaultPrompt,
+            llm: fields.llm,
+            outputKey: (_b = fields.outputKey) !== null && _b !== void 0 ? _b : "response",
+        });
+        this.memory = (_c = fields.memory) !== null && _c !== void 0 ? _c : new memory_1.BufferMemory();
+    }
+}
+exports.ConversationChain = ConversationChain;
 //# sourceMappingURL=llm_chain.js.map

dist/cjs/chains/load.d.ts

 import { BaseChain } from ".";
-export declare const loadChain: (uri: string) => Promise<BaseChain>;
+export type LoadValues = Record<string, any>;
+/**
+ * Load a chain from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("lc://chains/hello-world/chain.json");
+ * const res = await chain.call({ topic: "my favorite color" });
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("/path/to/chain.json");
+ * ```
+ */
+export declare const loadChain: (uri: string, values?: LoadValues) => Promise<BaseChain>;

dist/cjs/chains/load.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -16,15 +7,32 @@ exports.loadChain = void 0;
 const util_1 = require("../util");
-const loadChainFromFile = (file) => __awaiter(void 0, void 0, void 0, function* () {
+const loadChainFromFile = async (file, values = {}) => {
     const serialized = (0, util_1.parseFileConfig)(file);
-    console.log({ serialized });
-    return _1.BaseChain.deserialize(serialized);
-});
-const loadChain = (uri) => __awaiter(void 0, void 0, void 0, function* () {
-    const hubResult = yield (0, hub_1.loadFromHub)(uri, loadChainFromFile, "chains", new Set(["json", "yaml"]));
+    return _1.BaseChain.deserialize(serialized, values);
+};
+/**
+ * Load a chain from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("lc://chains/hello-world/chain.json");
+ * const res = await chain.call({ topic: "my favorite color" });
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("/path/to/chain.json");
+ * ```
+ */
+const loadChain = async (uri, values = {}) => {
+    const hubResult = await (0, hub_1.loadFromHub)(uri, (uri) => loadChainFromFile(uri, values), "chains", new Set(["json", "yaml"]), values);
     if (hubResult) {
         return hubResult;
     }
-    return loadChainFromFile(uri);
-});
+    return loadChainFromFile(uri, values);
+};
 exports.loadChain = loadChain;
 //# sourceMappingURL=load.js.map

dist/cjs/chains/tests/llm_chain.test.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -17,3 +8,3 @@ const globals_1 = require("@jest/globals");
 const load_1 = require("../load");
-(0, globals_1.test)("Test OpenAI", () => __awaiter(void 0, void 0, void 0, function* () {
+(0, globals_1.test)("Test OpenAI", async () => {
     const model = new openai_1.OpenAI({});
@@ -25,10 +16,16 @@ const prompt = new prompt_1.PromptTemplate({
     const chain = new llm_chain_1.LLMChain({ prompt, llm: model });
-    const res = yield chain.call({ foo: "my favorite color" });
+    const res = await chain.call({ foo: "my favorite color" });
     console.log({ res });
-}));
-(0, globals_1.test)("Load chain from hub", () => __awaiter(void 0, void 0, void 0, function* () {
-    const chain = yield (0, load_1.loadChain)("lc://chains/hello-world/chain.json");
-    const res = yield chain.call({ topic: "my favorite color" });
+});
+(0, globals_1.test)("Load chain from hub", async () => {
+    const chain = await (0, load_1.loadChain)("lc://chains/hello-world/chain.json");
+    const res = await chain.call({ topic: "my favorite color" });
     console.log({ res });
-}));
+});
+(0, globals_1.test)("Test ConversationChain", async () => {
+    const model = new openai_1.OpenAI({});
+    const chain = new llm_chain_1.ConversationChain({ llm: model });
+    const res = await chain.call({ input: "my favorite color" });
+    console.log({ res });
+});
 //# sourceMappingURL=llm_chain.test.js.map

dist/cjs/llms/base.d.ts

@@ -5,20 +5,61 @@ import { LLMCallbackManager, LLMResult } from "./index";
 } & Record<string, any>;
+/**
+ * LLM Wrapper. Provides an {@link call} (an {@link generate}) function that takes in a prompt (or prompts) and returns a string.
+ */
 export declare abstract class BaseLLM {
+    /**
+     * The name of the LLM class
+     */
     name: string;
     cache?: boolean;
     callbackManager: LLMCallbackManager;
+    /**
+     * Whether to print out response text.
+     */
     verbose?: boolean;
     constructor(callbackManager?: LLMCallbackManager, verbose?: boolean);
+    /**
+     * Run the LLM on the given prompts and input.
+     */
     abstract _generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /** @ignore */
     _generateUncached(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /**
+     * Run the LLM on the given propmts an input, handling caching.
+     */
     generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /**
+     * Convenience wrapper for {@link generate} that takes in a single string prompt and returns a single string output.
+     */
     call(prompt: string, stop?: string[]): Promise<string>;
+    /**
+     * Get the identifying parameters of the LLM.
+     */
     _identifyingParams(): Record<string, any>;
+    /**
+     * Return the string type key uniquely identifying this class of LLM.
+     */
     abstract _llmType(): string;
+    /**
+     * Return a json-like object representing this LLM.
+     */
     serialize(): SerializedLLM;
+    /**
+     * Load an LLM from a json-like object describing it.
+     */
     static deserialize(data: SerializedLLM): Promise<BaseLLM>;
 }
+/**
+ * LLM class that provides a simpler interface to subclass than {@link BaseLLM}.
+ *
+ * Requires only implementing a simpler {@link _call} method instead of {@link _generate}.
+ *
+ * @augments BaseLLM
+ */
 export declare abstract class LLM extends BaseLLM {
+    /**
+     * Run the LLM on the given prompt and input.
+     */
     abstract _call(prompt: string, stop?: string[]): Promise<string>;
     _generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
 }

dist/cjs/llms/base.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-var __rest = (this && this.__rest) || function (s, e) {
-    var t = {};
-    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
-        t[p] = s[p];
-    if (s != null && typeof Object.getOwnPropertySymbols === "function")
-        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
-            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
-                t[p[i]] = s[p[i]];
-        }
-    return t;
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -39,4 +19,10 @@ exports.LLM = exports.BaseLLM = void 0;
 const cache = new cache_1.InMemoryCache();
+/**
+ * LLM Wrapper. Provides an {@link call} (an {@link generate}) function that takes in a prompt (or prompts) and returns a string.
+ */
 class BaseLLM {
     constructor(callbackManager, verbose) {
+        /**
+         * The name of the LLM class
+         */
         Object.defineProperty(this, "name", {
@@ -60,2 +46,5 @@ enumerable: true,
         });
+        /**
+         * Whether to print out response text.
+         */
         Object.defineProperty(this, "verbose", {
@@ -70,59 +59,63 @@ enumerable: true,
     }
-    _generateUncached(prompts, stop) {
-        return __awaiter(this, void 0, void 0, function* () {
-            this.callbackManager.handleStart({ name: this.name }, prompts, this.verbose);
-            let output;
-            try {
-                output = yield this._generate(prompts, stop);
-            }
-            catch (err) {
-                this.callbackManager.handleError(`${err}`, this.verbose);
-                throw err;
-            }
-            this.callbackManager.handleEnd(output, this.verbose);
-            return output;
-        });
+    /** @ignore */
+    async _generateUncached(prompts, stop) {
+        this.callbackManager.handleStart({ name: this.name }, prompts, this.verbose);
+        let output;
+        try {
+            output = await this._generate(prompts, stop);
+        }
+        catch (err) {
+            this.callbackManager.handleError(`${err}`, this.verbose);
+            throw err;
+        }
+        this.callbackManager.handleEnd(output, this.verbose);
+        return output;
     }
-    generate(prompts, stop) {
+    /**
+     * Run the LLM on the given propmts an input, handling caching.
+     */
+    async generate(prompts, stop) {
         var _a;
-        return __awaiter(this, void 0, void 0, function* () {
-            if (!Array.isArray(prompts)) {
-                throw new Error("Argument 'prompts' is expected to be a string[]");
+        if (!Array.isArray(prompts)) {
+            throw new Error("Argument 'prompts' is expected to be a string[]");
+        }
+        if (this.cache === true && cache === null) {
+            throw new Error("Requested cache, but no cache found");
+        }
+        if (cache === null || this.cache === false) {
+            return this._generateUncached(prompts, stop);
+        }
+        const params = this.serialize();
+        params.stop = stop;
+        const llmStringKey = `${Object.entries(params).sort()}`;
+        const missingPromptIndices = [];
+        const generations = prompts.map((prompt, index) => {
+            const result = cache.lookup(prompt, llmStringKey);
+            if (!result) {
+                missingPromptIndices.push(index);
             }
-            if (this.cache === true && cache === null) {
-                throw new Error("Requested cache, but no cache found");
-            }
-            if (cache === null || this.cache === false) {
-                return this._generateUncached(prompts, stop);
-            }
-            const params = this.serialize();
-            params.stop = stop;
-            const llmStringKey = `${Object.entries(params).sort()}`;
-            const missingPromptIndices = [];
-            const generations = prompts.map((prompt, index) => {
-                const result = cache.lookup(prompt, llmStringKey);
-                if (!result) {
-                    missingPromptIndices.push(index);
-                }
-                return result;
+            return result;
+        });
+        let llmOutput = {};
+        if (missingPromptIndices.length > 0) {
+            const results = await this._generateUncached(missingPromptIndices.map((i) => prompts[i]), stop);
+            results.generations.forEach((generation, index) => {
+                const promptIndex = missingPromptIndices[index];
+                generations[promptIndex] = generation;
+                cache.update(prompts[promptIndex], llmStringKey, generation);
             });
-            let llmOutput = {};
-            if (missingPromptIndices.length > 0) {
-                const results = yield this._generateUncached(missingPromptIndices.map((i) => prompts[i]), stop);
-                results.generations.forEach((generation, index) => {
-                    const promptIndex = missingPromptIndices[index];
-                    generations[promptIndex] = generation;
-                    cache.update(prompts[promptIndex], llmStringKey, generation);
-                });
-                llmOutput = (_a = results.llmOutput) !== null && _a !== void 0 ? _a : {};
-            }
-            return { generations, llmOutput };
-        });
+            llmOutput = (_a = results.llmOutput) !== null && _a !== void 0 ? _a : {};
+        }
+        return { generations, llmOutput };
     }
-    call(prompt, stop) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const { generations } = yield this.generate([prompt], stop);
-            return generations[0][0].text;
-        });
+    /**
+     * Convenience wrapper for {@link generate} that takes in a single string prompt and returns a single string output.
+     */
+    async call(prompt, stop) {
+        const { generations } = await this.generate([prompt], stop);
+        return generations[0][0].text;
     }
+    /**
+     * Get the identifying parameters of the LLM.
+     */
     // eslint-disable-next-line @typescript-eslint/no-explicit-any
@@ -132,29 +125,41 @@ _identifyingParams() {
     }
+    /**
+     * Return a json-like object representing this LLM.
+     */
     serialize() {
-        return Object.assign(Object.assign({}, this._identifyingParams()), { _type: this._llmType() });
+        return {
+            ...this._identifyingParams(),
+            _type: this._llmType(),
+        };
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const { _type } = data, rest = __rest(data, ["_type"]);
-            const Cls = {
-                openai: index_1.OpenAI,
-            }[_type];
-            if (Cls === undefined) {
-                throw new Error(`Cannot load  LLM with type ${_type}`);
-            }
-            return new Cls(rest);
-        });
+    /**
+     * Load an LLM from a json-like object describing it.
+     */
+    static async deserialize(data) {
+        const { _type, ...rest } = data;
+        const Cls = {
+            openai: index_1.OpenAI,
+        }[_type];
+        if (Cls === undefined) {
+            throw new Error(`Cannot load  LLM with type ${_type}`);
+        }
+        return new Cls(rest);
     }
 }
 exports.BaseLLM = BaseLLM;
+/**
+ * LLM class that provides a simpler interface to subclass than {@link BaseLLM}.
+ *
+ * Requires only implementing a simpler {@link _call} method instead of {@link _generate}.
+ *
+ * @augments BaseLLM
+ */
 class LLM extends BaseLLM {
-    _generate(prompts, stop) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const generations = [];
-            for (let i = 0; i < prompts.length; i += 1) {
-                const text = yield this._call(prompts[i], stop);
-                generations.push([{ text }]);
-            }
-            return { generations };
-        });
+    async _generate(prompts, stop) {
+        const generations = [];
+        for (let i = 0; i < prompts.length; i += 1) {
+            const text = await this._call(prompts[i], stop);
+            generations.push([{ text }]);
+        }
+        return { generations };
     }
@@ -161,0 +166,0 @@ }

dist/cjs/llms/index.d.ts

@@ -11,9 +11,28 @@ export { BaseLLM, LLM, SerializedLLM } from "./base";
 };
+/**
+ * Output of a single generation.
+ */
 export type Generation = {
+    /**
+     * Generated text output
+     */
     text: string;
+    /**
+     * Raw generation info response from the provider.
+     * May include things like reason for finishing (e.g. in {@link OpenAI})
+     */
     generationInfo?: Record<string, any>;
 };
+/**
+ * Contains all relevant information returned by an LLM.
+ */
 export type LLMResult = {
+    /**
+     * List of the things generated. Each input could have multiple {@link Generation | generations}, hence this is a list of lists.
+     */
     generations: Generation[][];
+    /**
+     * Dictionary of arbitrary LLM-provider specific output.
+     */
     llmOutput?: Record<string, any>;
 };

dist/cjs/llms/load.d.ts

 import { BaseLLM } from "./base";
-export declare const loadLLM: typeof BaseLLM.deserialize;
-export declare const loadLLMFromFile: (file: string) => Promise<BaseLLM>;
+/**
+ * Load an LLM from a local file.
+ *
+ * @example
+ * ```ts
+ * import { loadLLM } from "langchain/llms";
+ * const model = await loadLLM("/path/to/llm.json");
+ * ```
+ */
+export declare const loadLLM: (file: string) => Promise<BaseLLM>;

dist/cjs/llms/load.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.loadLLMFromFile = exports.loadLLM = void 0;
+exports.loadLLM = void 0;
 const base_1 = require("./base");
 const util_1 = require("../util");
-exports.loadLLM = base_1.BaseLLM.deserialize;
-const loadLLMFromFile = (file) => (0, exports.loadLLM)((0, util_1.parseFileConfig)(file));
-exports.loadLLMFromFile = loadLLMFromFile;
+/**
+ * Load an LLM from a local file.
+ *
+ * @example
+ * ```ts
+ * import { loadLLM } from "langchain/llms";
+ * const model = await loadLLM("/path/to/llm.json");
+ * ```
+ */
+const loadLLM = (file) => base_1.BaseLLM.deserialize((0, util_1.parseFileConfig)(file));
+exports.loadLLM = loadLLM;
 //# sourceMappingURL=load.js.map

dist/cjs/llms/openai.d.ts

 import type { CreateCompletionRequest } from "openai";
 import { BaseLLM, LLMResult, LLMCallbackManager } from ".";
 interface ModelParams {
+    /** Sampling temperature to use */
     temperature: number;
+    /**
+     * Maximum number of tokens to generate in the completion. -1 returns as many
+     * tokens as possible given the prompt and the model's maximum context size.
+     */
     maxTokens: number;
+    /** Total probability mass of tokens to consider at each step */
     topP: number;
+    /** Penalizes repeated tokens according to frequency */
     frequencyPenalty: number;
+    /** Penalizes repeated tokens */
     presencePenalty: number;
+    /** Number of completions to generate for each prompt */
     n: number;
+    /** Generates `bestOf` completions server side and returns the "best" */
     bestOf: number;
+    /** Dictionary used to adjust the probability of specific tokens being generated */
     logitBias?: Record<string, number>;
 }
+/**
+ * Input to OpenAI class.
+ * @augments ModelParams
+ */
+interface OpenAIInput extends ModelParams {
+    /** Model name to use */
+    modelName: string;
+    /** Holds any additional parameters that are valid to pass to {@link
+     * https://platform.openai.com/docs/api-reference/completions/create |
+     * `openai.createCompletion`} that are not explicitly specified on this class.
+     */
+    modelKwargs?: Kwargs;
+    /** Batch size to use when passing multiple documents to generate */
+    batchSize: number;
+    /** Maximum number of retries to make when generating */
+    maxRetries: number;
+    /** List of stop words to use when generating */
+    stop?: string[];
+}
 type Kwargs = Record<string, any>;
-export declare class OpenAI extends BaseLLM implements ModelParams {
+/**
+ * Wrapper around OpenAI large language models.
+ *
+ * To use you should have the `openai` package installed, with the
+ * `OPENAI_API_KEY` environment variable set.
+ *
+ * @remarks
+ * Any parameters that are valid to be passed to {@link
+ * https://platform.openai.com/docs/api-reference/completions/create |
+ * `openai.createCompletion`} can be passed through {@link modelKwargs}, even
+ * if not explicitly available on this class.
+ *
+ * @augments BaseLLM
+ * @augments OpenAIInput
+ */
+export declare class OpenAI extends BaseLLM implements OpenAIInput {
     temperature: number;
@@ -29,13 +74,14 @@ maxTokens: number;
     private client;
-    constructor(fields?: Partial<ModelParams> & {
+    constructor(fields?: Partial<OpenAIInput> & {
         callbackManager?: LLMCallbackManager;
         verbose?: boolean;
-        modelName?: string;
-        modelKwargs?: Kwargs;
         openAIApiKey?: string;
-        batchSize?: number;
-        maxRetries?: number;
-        stop?: string[];
     });
+    /**
+     * Get the parameters used to invoke the model
+     */
     invocationParams(): CreateCompletionRequest & Kwargs;
+    /**
+     * Get the identifyin parameters for the model
+     */
     identifyingParams(): {
@@ -60,3 +106,19 @@ model: string;
     };
+    /**
+     * Call out to OpenAI's endpoint with k unique prompts
+     *
+     * @param prompts - The prompts to pass into the model.
+     * @param [stop] - Optional list of stop words to use when generating.
+     *
+     * @returns The full LLM output.
+     *
+     * @example
+     * ```ts
+     * import { OpenAI } from "langchain/llms";
+     * const openai = new OpenAI();
+     * const response = await openai.generate(["Tell me a joke."]);
+     * ```
+     */
     _generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /** @ignore */
     completionWithRetry(request: CreateCompletionRequest): Promise<import("axios").AxiosResponse<import("openai").CreateCompletionResponse, any>>;
@@ -63,0 +125,0 @@ _llmType(): string;

dist/cjs/llms/openai.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
 exports.OpenAI = void 0;
 const exponential_backoff_1 = require("exponential-backoff");
+const util_1 = require("../util");
 const _1 = require(".");
@@ -18,3 +10,3 @@ let Configuration = null;
 try {
-    // eslint-disable-next-line global-require
+    // eslint-disable-next-line global-require,import/no-extraneous-dependencies
     ({ Configuration, OpenAIApi } = require("openai"));
@@ -25,9 +17,17 @@ }
 }
-const chunkArray = (arr, chunkSize) => arr.reduce((chunks, elem, index) => {
-    const chunkIndex = Math.floor(index / chunkSize);
-    const chunk = chunks[chunkIndex] || [];
-    // eslint-disable-next-line no-param-reassign
-    chunks[chunkIndex] = chunk.concat([elem]);
-    return chunks;
-}, []);
+/**
+ * Wrapper around OpenAI large language models.
+ *
+ * To use you should have the `openai` package installed, with the
+ * `OPENAI_API_KEY` environment variable set.
+ *
+ * @remarks
+ * Any parameters that are valid to be passed to {@link
+ * https://platform.openai.com/docs/api-reference/completions/create |
+ * `openai.createCompletion`} can be passed through {@link modelKwargs}, even
+ * if not explicitly available on this class.
+ *
+ * @augments BaseLLM
+ * @augments OpenAIInput
+ */
 class OpenAI extends _1.BaseLLM {
@@ -122,3 +122,3 @@ constructor(fields) {
         if (Configuration === null || OpenAIApi === null) {
-            throw new Error("Please install openai as a dependency with, e.g. `npm install -S openai`");
+            throw new Error("Please install openai as a dependency with, e.g. `npm i openai`");
         }
@@ -143,50 +143,88 @@ this.modelName = (_a = fields === null || fields === void 0 ? void 0 : fields.modelName) !== null && _a !== void 0 ? _a : this.modelName;
     }
+    /**
+     * Get the parameters used to invoke the model
+     */
     invocationParams() {
-        return Object.assign({ model: this.modelName, temperature: this.temperature, max_tokens: this.maxTokens, top_p: this.topP, frequency_penalty: this.frequencyPenalty, presence_penalty: this.presencePenalty, n: this.n, best_of: this.bestOf, logit_bias: this.logitBias, stop: this.stop }, this.modelKwargs);
+        return {
+            model: this.modelName,
+            temperature: this.temperature,
+            max_tokens: this.maxTokens,
+            top_p: this.topP,
+            frequency_penalty: this.frequencyPenalty,
+            presence_penalty: this.presencePenalty,
+            n: this.n,
+            best_of: this.bestOf,
+            logit_bias: this.logitBias,
+            stop: this.stop,
+            ...this.modelKwargs,
+        };
     }
+    /**
+     * Get the identifyin parameters for the model
+     */
     identifyingParams() {
-        return Object.assign({ model_name: this.modelName }, this.invocationParams());
+        return {
+            model_name: this.modelName,
+            ...this.invocationParams(),
+        };
     }
-    _generate(prompts, stop) {
+    /**
+     * Call out to OpenAI's endpoint with k unique prompts
+     *
+     * @param prompts - The prompts to pass into the model.
+     * @param [stop] - Optional list of stop words to use when generating.
+     *
+     * @returns The full LLM output.
+     *
+     * @example
+     * ```ts
+     * import { OpenAI } from "langchain/llms";
+     * const openai = new OpenAI();
+     * const response = await openai.generate(["Tell me a joke."]);
+     * ```
+     */
+    async _generate(prompts, stop) {
         var _a, _b, _c, _d;
-        return __awaiter(this, void 0, void 0, function* () {
-            const subPrompts = chunkArray(prompts, this.batchSize);
-            const choices = [];
-            const tokenUsage = {};
-            if (this.stop && stop) {
-                throw new Error("Stop found in input and default params");
+        const subPrompts = (0, util_1.chunkArray)(prompts, this.batchSize);
+        const choices = [];
+        const tokenUsage = {};
+        if (this.stop && stop) {
+            throw new Error("Stop found in input and default params");
+        }
+        const params = this.invocationParams();
+        params.stop = stop !== null && stop !== void 0 ? stop : params.stop;
+        for (let i = 0; i < subPrompts.length; i += 1) {
+            const { data } = await this.completionWithRetry({
+                ...params,
+                prompt: subPrompts[i],
+            });
+            choices.push(...data.choices);
+            const { completion_tokens: completionTokens, prompt_tokens: promptTokens, total_tokens: totalTokens, } = (_a = data.usage) !== null && _a !== void 0 ? _a : {};
+            if (completionTokens) {
+                tokenUsage.completionTokens =
+                    ((_b = tokenUsage.completionTokens) !== null && _b !== void 0 ? _b : 0) + completionTokens;
             }
-            const params = this.invocationParams();
-            params.stop = stop !== null && stop !== void 0 ? stop : params.stop;
-            for (let i = 0; i < subPrompts.length; i += 1) {
-                const { data } = yield this.completionWithRetry(Object.assign(Object.assign({}, params), { prompt: subPrompts[i] }));
-                choices.push(...data.choices);
-                const { completion_tokens: completionTokens, prompt_tokens: promptTokens, total_tokens: totalTokens, } = (_a = data.usage) !== null && _a !== void 0 ? _a : {};
-                if (completionTokens) {
-                    tokenUsage.completionTokens =
-                        ((_b = tokenUsage.completionTokens) !== null && _b !== void 0 ? _b : 0) + completionTokens;
-                }
-                if (promptTokens) {
-                    tokenUsage.promptTokens = ((_c = tokenUsage.promptTokens) !== null && _c !== void 0 ? _c : 0) + promptTokens;
-                }
-                if (totalTokens) {
-                    tokenUsage.totalTokens = ((_d = tokenUsage.totalTokens) !== null && _d !== void 0 ? _d : 0) + totalTokens;
-                }
+            if (promptTokens) {
+                tokenUsage.promptTokens = ((_c = tokenUsage.promptTokens) !== null && _c !== void 0 ? _c : 0) + promptTokens;
             }
-            const generations = chunkArray(choices, this.n).map((promptChoices) => promptChoices.map((choice) => {
-                var _a;
-                return ({
-                    text: (_a = choice.text) !== null && _a !== void 0 ? _a : "",
-                    generationInfo: {
-                        finishReason: choice.finish_reason,
-                        logprobs: choice.logprobs,
-                    },
-                });
-            }));
-            return {
-                generations,
-                llmOutput: { tokenUsage },
-            };
-        });
+            if (totalTokens) {
+                tokenUsage.totalTokens = ((_d = tokenUsage.totalTokens) !== null && _d !== void 0 ? _d : 0) + totalTokens;
+            }
+        }
+        const generations = (0, util_1.chunkArray)(choices, this.n).map((promptChoices) => promptChoices.map((choice) => {
+            var _a;
+            return ({
+                text: (_a = choice.text) !== null && _a !== void 0 ? _a : "",
+                generationInfo: {
+                    finishReason: choice.finish_reason,
+                    logprobs: choice.logprobs,
+                },
+            });
+        }));
+        return {
+            generations,
+            llmOutput: { tokenUsage },
+        };
     }
+    /** @ignore */
     completionWithRetry(request) {
@@ -193,0 +231,0 @@ const makeCompletionRequest = () => this.client.createCompletion(request);

dist/cjs/llms/tests/openai.test.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
 const globals_1 = require("@jest/globals");
 const openai_1 = require("../openai");
-(0, globals_1.test)("Test OpenAI", () => __awaiter(void 0, void 0, void 0, function* () {
+(0, globals_1.test)("Test OpenAI", async () => {
     const model = new openai_1.OpenAI({ maxTokens: 5 });
-    const res = yield model.call("Print hello world");
+    const res = await model.call("Print hello world");
     console.log({ res });
-}));
+});
 //# sourceMappingURL=openai.test.js.map

dist/cjs/prompt/base.d.ts

@@ -6,6 +6,20 @@ import { BaseOutputParser } from "./parser";
 export type InputValues = Record<string, any>;
+/**
+ * Input common to all prompt templates.
+ */
 export interface BasePromptTemplateInput {
+    /**
+     * A list of variable names the prompt template expects
+     */
     inputVariables: string[];
+    /**
+     * How to parse the output of calling an LLM on this formatted prompt
+     */
     outputParser?: BaseOutputParser;
 }
+/**
+ * Base class for prompt templates. Exposes a format method that returns a
+ * string prompt given a set of input values.
+ * @augments BasePromptTemplateInput
+ */
 export declare abstract class BasePromptTemplate implements BasePromptTemplateInput {
@@ -15,7 +29,32 @@ inputVariables: string[];
     constructor(input: BasePromptTemplateInput);
+    /**
+     * Format the prompt given the input values.
+     *
+     * @param inputValues - A dictionary of arguments to be passed to the prompt template.
+     * @returns A formatted prompt string.
+     *
+     * @example
+     * ```ts
+     * prompt.format({ foo: "bar" });
+     * ```
+     */
     abstract format(values: InputValues): string;
+    /**
+     * Return the string type key uniquely identifying this class of prompt template.
+     */
     abstract _getPromptType(): string;
+    /**
+     * Return a json-like object representing this prompt template.
+     */
     abstract serialize(): SerializedBasePromptTemplate;
+    /**
+     * Load a prompt template from a json-like object describing it.
+     *
+     * @remarks
+     * Deserializing needs to be async because templates (e.g. {@link FewShotPromptTemplate}) can
+     * reference remote resources that we read asynchronously with a web
+     * request.
+     */
     static deserialize(data: SerializedBasePromptTemplate): Promise<BasePromptTemplate>;
 }
 export {};

dist/cjs/prompt/base.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -15,2 +6,7 @@ exports.BasePromptTemplate = void 0;
 const templateClasses = [index_1.PromptTemplate, index_1.FewShotPromptTemplate];
+/**
+ * Base class for prompt templates. Exposes a format method that returns a
+ * string prompt given a set of input values.
+ * @augments BasePromptTemplateInput
+ */
 class BasePromptTemplate {
@@ -36,18 +32,21 @@ constructor(input) {
     }
-    // Deserializing needs to be async because templates (e.g. few_shot) can
-    // reference remote resources that we read asynchronously with a web
-    // request.
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            switch (data._type) {
-                case "prompt":
-                    return index_1.PromptTemplate.deserialize(data);
-                case undefined:
-                    return index_1.PromptTemplate.deserialize(Object.assign(Object.assign({}, data), { _type: "prompt" }));
-                case "few_shot":
-                    return index_1.FewShotPromptTemplate.deserialize(data);
-                default:
-                    throw new Error(`Invalid prompt type in config: ${data._type}`);
-            }
-        });
+    /**
+     * Load a prompt template from a json-like object describing it.
+     *
+     * @remarks
+     * Deserializing needs to be async because templates (e.g. {@link FewShotPromptTemplate}) can
+     * reference remote resources that we read asynchronously with a web
+     * request.
+     */
+    static async deserialize(data) {
+        switch (data._type) {
+            case "prompt":
+                return index_1.PromptTemplate.deserialize(data);
+            case undefined:
+                return index_1.PromptTemplate.deserialize({ ...data, _type: "prompt" });
+            case "few_shot":
+                return index_1.FewShotPromptTemplate.deserialize(data);
+            default:
+                throw new Error(`Invalid prompt type in config: ${data._type}`);
+        }
     }
@@ -54,0 +53,0 @@ }

dist/cjs/prompt/few_shot.d.ts

@@ -22,11 +22,46 @@ import { BasePromptTemplate, InputValues, BasePromptTemplateInput } from "./index";
 export interface FewShotPromptTemplateInput extends BasePromptTemplateInput {
+    /**
+     * Examples to format into the prompt. Exactly one of this or
+     * {@link exampleSelector} must be
+     * provided.
+     */
     examples?: Example[];
+    /**
+     * An {@link ExampleSelector} Examples to format into the prompt. Exactly one of this or
+     * {@link examples} must be
+     * provided.
+     */
+    exampleSelector?: ExampleSelector;
+    /**
+     * An {@link PromptTemplate} used to format a single example.
+     */
     examplePrompt: PromptTemplate;
-    exampleSelector?: ExampleSelector;
+    /**
+     * String separator used to join the prefix, the examples, and suffix.
+     */
     exampleSeparator: string;
+    /**
+     * A prompt template string to put before the examples.
+     *
+     * @defaultValue `""`
+     */
     prefix: string;
+    /**
+     * A prompt template string to put after the examples.
+     */
     suffix: string;
+    /**
+     * The format of the prompt template. Options are: 'f-string', 'jinja-2'
+     */
     templateFormat: TemplateFormat;
+    /**
+     * Whether or not to try validating the template on initialization.
+     */
     validateTemplate?: boolean;
 }
+/**
+ * Prompt template that contains few-shot examples.
+ * @augments BasePromptTemplate
+ * @augments FewShotPromptTemplateInput
+ */
 export declare class FewShotPromptTemplate extends BasePromptTemplate implements FewShotPromptTemplateInput {
@@ -33,0 +68,0 @@ examples?: InputValues[];

dist/cjs/prompt/few_shot.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -18,2 +9,7 @@ exports.FewShotPromptTemplate = void 0;
 const parser_1 = require("./parser");
+/**
+ * Prompt template that contains few-shot examples.
+ * @augments BasePromptTemplate
+ * @augments FewShotPromptTemplateInput
+ */
 class FewShotPromptTemplate extends index_1.BasePromptTemplate {
@@ -116,26 +112,24 @@ constructor(input) {
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const serializedPrompt = (0, util_1.resolveConfigFromFile)("example_prompt", data);
-            const examplePrompt = yield prompt_1.PromptTemplate.deserialize(serializedPrompt);
-            let examples;
-            if (typeof data.examples === "string") {
-                examples = (0, util_1.parseFileConfig)(data.examples, [".json", ".yml", ".yaml"]);
-            }
-            else if (Array.isArray(data.examples)) {
-                examples = data.examples;
-            }
-            else {
-                throw new Error("Invalid examples format. Only list or string are supported.");
-            }
-            return new FewShotPromptTemplate({
-                inputVariables: data.input_variables,
-                outputParser: data.output_parser && parser_1.BaseOutputParser.deserialize(data.output_parser),
-                examplePrompt,
-                examples,
-                exampleSeparator: data.example_separator,
-                prefix: (0, util_1.resolveTemplateFromFile)("prefix", data),
-                suffix: (0, util_1.resolveTemplateFromFile)("suffix", data),
-                templateFormat: data.template_format,
-            });
+    static async deserialize(data) {
+        const serializedPrompt = (0, util_1.resolveConfigFromFile)("example_prompt", data);
+        const examplePrompt = await prompt_1.PromptTemplate.deserialize(serializedPrompt);
+        let examples;
+        if (typeof data.examples === "string") {
+            examples = (0, util_1.parseFileConfig)(data.examples, [".json", ".yml", ".yaml"]);
+        }
+        else if (Array.isArray(data.examples)) {
+            examples = data.examples;
+        }
+        else {
+            throw new Error("Invalid examples format. Only list or string are supported.");
+        }
+        return new FewShotPromptTemplate({
+            inputVariables: data.input_variables,
+            outputParser: data.output_parser && parser_1.BaseOutputParser.deserialize(data.output_parser),
+            examplePrompt,
+            examples,
+            exampleSeparator: data.example_separator,
+            prefix: (0, util_1.resolveTemplateFromFile)("prefix", data),
+            suffix: (0, util_1.resolveTemplateFromFile)("suffix", data),
+            templateFormat: data.template_format,
         });
@@ -142,0 +136,0 @@ }

dist/cjs/prompt/index.d.ts

 export { BasePromptTemplate, BasePromptTemplateInput, SerializedBasePromptTemplate, InputValues, } from "./base";
 export { PromptTemplate, PromptTemplateInput, SerializedPromptTemplate, } from "./prompt";
 export { FewShotPromptTemplate, FewShotPromptTemplateInput, SerializedFewShotTemplate, } from "./few_shot";
+export { loadPrompt } from "./load";

dist/cjs/prompt/index.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.FewShotPromptTemplate = exports.PromptTemplate = exports.BasePromptTemplate = void 0;
+exports.loadPrompt = exports.FewShotPromptTemplate = exports.PromptTemplate = exports.BasePromptTemplate = void 0;
 var base_1 = require("./base");
@@ -10,2 +10,4 @@ Object.defineProperty(exports, "BasePromptTemplate", { enumerable: true, get: function () { return base_1.BasePromptTemplate; } });
 Object.defineProperty(exports, "FewShotPromptTemplate", { enumerable: true, get: function () { return few_shot_1.FewShotPromptTemplate; } });
+var load_1 = require("./load");
+Object.defineProperty(exports, "loadPrompt", { enumerable: true, get: function () { return load_1.loadPrompt; } });
 //# sourceMappingURL=index.js.map

dist/cjs/prompt/load.d.ts

 import { BasePromptTemplate } from ".";
+/**
+ * Load a prompt from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("lc://prompts/hello-world/prompt.yaml");
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("/path/to/prompt.json");
+ * ```
+ */
 export declare const loadPrompt: (uri: string) => Promise<BasePromptTemplate>;

dist/cjs/prompt/load.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -16,5 +7,22 @@ exports.loadPrompt = void 0;
 const util_1 = require("../util");
-const loadPromptFromFile = (file) => __awaiter(void 0, void 0, void 0, function* () { return _1.BasePromptTemplate.deserialize((0, util_1.parseFileConfig)(file)); });
-const loadPrompt = (uri) => __awaiter(void 0, void 0, void 0, function* () {
-    const hubResult = yield (0, hub_1.loadFromHub)(uri, loadPromptFromFile, "prompts", new Set(["py", "json", "yaml"]));
+const loadPromptFromFile = async (file) => _1.BasePromptTemplate.deserialize((0, util_1.parseFileConfig)(file));
+/**
+ * Load a prompt from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("lc://prompts/hello-world/prompt.yaml");
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("/path/to/prompt.json");
+ * ```
+ */
+const loadPrompt = async (uri) => {
+    const hubResult = await (0, hub_1.loadFromHub)(uri, loadPromptFromFile, "prompts", new Set(["py", "json", "yaml"]));
     if (hubResult) {
@@ -24,4 +32,4 @@ return hubResult;
     return loadPromptFromFile(uri);
-});
+};
 exports.loadPrompt = loadPrompt;
 //# sourceMappingURL=load.js.map

dist/cjs/prompt/parser.d.ts

 export type SerializedOutputParser = SerializedRegexParser | SerializedCommaSeparatedListOutputParser;
+/**
+ * Class to parse the output of an LLM call.
+ */
 export declare abstract class BaseOutputParser {
+    /**
+     * Parse the output of an LLM call.
+     *
+     * @param text - LLM output to parse.
+     * @returns Parsed output.
+     */
     abstract parse(text: string): string | string[] | Record<string, string>;
+    /**
+     * Return the string type key uniquely identifying this class of parser
+     */
     _type(): string;
+    /**
+     * Return a json-like object representing this output parser.
+     */
     abstract serialize(): SerializedOutputParser;
+    /**
+     * Load an output parser from a json-like object describing the parser.
+     */
     static deserialize(data: SerializedOutputParser): BaseOutputParser;
 }
+/**
+ * Class to parse the output of an LLM call to a list.
+ * @augments BaseOutputParser
+ */
 export declare abstract class ListOutputParser extends BaseOutputParser {
@@ -14,2 +36,6 @@ abstract parse(text: string): string[];
 };
+/**
+ * Class to parse the output of an LLM call as a comma-separated list.
+ * @augments ListOutputParser
+ */
 export declare class CommaSeparatedListOutputParser extends ListOutputParser {
@@ -26,2 +52,6 @@ parse(text: string): string[];
 };
+/**
+ * Class to parse the output of an LLM call into a dictionary.
+ * @augments BaseOutputParser
+ */
 export declare class RegexParser extends BaseOutputParser {
@@ -28,0 +58,0 @@ regex: string | RegExp;

dist/cjs/prompt/parser.js

 "use strict";
 Object.defineProperty(exports, "__esModule", { value: true });
 exports.RegexParser = exports.CommaSeparatedListOutputParser = exports.ListOutputParser = exports.BaseOutputParser = void 0;
+/**
+ * Class to parse the output of an LLM call.
+ */
 class BaseOutputParser {
+    /**
+     * Return the string type key uniquely identifying this class of parser
+     */
     _type() {
         throw new Error("_type not implemented");
     }
+    /**
+     * Load an output parser from a json-like object describing the parser.
+     */
     static deserialize(data) {
@@ -19,5 +28,13 @@ switch (data._type) {
 exports.BaseOutputParser = BaseOutputParser;
+/**
+ * Class to parse the output of an LLM call to a list.
+ * @augments BaseOutputParser
+ */
 class ListOutputParser extends BaseOutputParser {
 }
 exports.ListOutputParser = ListOutputParser;
+/**
+ * Class to parse the output of an LLM call as a comma-separated list.
+ * @augments ListOutputParser
+ */
 class CommaSeparatedListOutputParser extends ListOutputParser {
@@ -37,2 +54,6 @@ parse(text) {
 exports.CommaSeparatedListOutputParser = CommaSeparatedListOutputParser;
+/**
+ * Class to parse the output of an LLM call into a dictionary.
+ * @augments BaseOutputParser
+ */
 class RegexParser extends BaseOutputParser {
@@ -39,0 +60,0 @@ constructor(regex, outputKeys, defaultOutputKey) {

dist/cjs/prompt/prompt.d.ts

@@ -12,7 +12,39 @@ import { BasePromptTemplate, BasePromptTemplateInput, InputValues } from "./index";
 };
+/**
+ * Inputs to create a {@link PromptTemplate}
+ * @augments BasePromptTemplateInput
+ */
 export interface PromptTemplateInput extends BasePromptTemplateInput {
+    /**
+     * The propmt template
+     */
     template: string;
+    /**
+     * The format of the prompt template. Options are 'f-string', 'jinja-2'
+     *
+     * @defaultValue 'f-string'
+     */
     templateFormat?: TemplateFormat;
+    /**
+     * Whether or not to try validating the template on initialization
+     *
+     * @defaultValue `true`
+     */
     validateTemplate?: boolean;
 }
+/**
+ * Schema to represent a basic prompt for an LLM.
+ * @augments BasePromptTemplate
+ * @augments PromptTemplateInput
+ *
+ * @example
+ * ```ts
+ * import { PromptTemplate } from "@langchain/prompt";
+ *
+ * const prompt = new PromptTemplate({
+ *   inputVariables: ["foo"],
+ *   template: "Say {foo}",
+ * });
+ * ```
+ */
 export declare class PromptTemplate extends BasePromptTemplate implements PromptTemplateInput {
@@ -25,3 +57,19 @@ template: string;
     format(values: InputValues): string;
+    /**
+     * Take examples in list format with prefix and suffix to create a prompt.
+     *
+     * Intendend to be used a a way to dynamically create a prompt from examples.
+     *
+     * @param examples - List of examples to use in the prompt.
+     * @param suffix - String to go after the list of examples. Should generally set up the user's input.
+     * @param inputVariables - A list of variable names the final prompt template will expect
+     * @param exampleSeparator - The separator to use in between examples
+     * @param prefix - String that should go before any examples. Generally includes examples.
+     *
+     * @returns The final prompt template generated.
+     */
     static fromExamples(examples: string[], suffix: string, inputVariables: string[], exampleSeparator?: string, prefix?: string): PromptTemplate;
+    /**
+     * Load prompt template from a template f-string
+     */
     static fromTemplate(template: string): PromptTemplate;
@@ -28,0 +76,0 @@ serialize(): SerializedPromptTemplate;

dist/cjs/prompt/prompt.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 Object.defineProperty(exports, "__esModule", { value: true });
@@ -17,2 +8,17 @@ exports.PromptTemplate = void 0;
 const parser_1 = require("./parser");
+/**
+ * Schema to represent a basic prompt for an LLM.
+ * @augments BasePromptTemplate
+ * @augments PromptTemplateInput
+ *
+ * @example
+ * ```ts
+ * import { PromptTemplate } from "@langchain/prompt";
+ *
+ * const prompt = new PromptTemplate({
+ *   inputVariables: ["foo"],
+ *   template: "Say {foo}",
+ * });
+ * ```
+ */
 class PromptTemplate extends index_1.BasePromptTemplate {
@@ -50,2 +56,15 @@ constructor(input) {
     }
+    /**
+     * Take examples in list format with prefix and suffix to create a prompt.
+     *
+     * Intendend to be used a a way to dynamically create a prompt from examples.
+     *
+     * @param examples - List of examples to use in the prompt.
+     * @param suffix - String to go after the list of examples. Should generally set up the user's input.
+     * @param inputVariables - A list of variable names the final prompt template will expect
+     * @param exampleSeparator - The separator to use in between examples
+     * @param prefix - String that should go before any examples. Generally includes examples.
+     *
+     * @returns The final prompt template generated.
+     */
     static fromExamples(examples, suffix, inputVariables, exampleSeparator = "\n\n", prefix = "") {
@@ -58,2 +77,5 @@ const template = [prefix, ...examples, suffix].join(exampleSeparator);
     }
+    /**
+     * Load prompt template from a template f-string
+     */
     static fromTemplate(template) {
@@ -81,12 +103,10 @@ const names = new Set();
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const res = new PromptTemplate({
-                inputVariables: data.input_variables,
-                outputParser: data.output_parser && parser_1.BaseOutputParser.deserialize(data.output_parser),
-                template: (0, util_1.resolveTemplateFromFile)("template", data),
-                templateFormat: data.template_format,
-            });
-            return res;
+    static async deserialize(data) {
+        const res = new PromptTemplate({
+            inputVariables: data.input_variables,
+            outputParser: data.output_parser && parser_1.BaseOutputParser.deserialize(data.output_parser),
+            template: (0, util_1.resolveTemplateFromFile)("template", data),
+            templateFormat: data.template_format,
         });
+        return res;
     }
@@ -93,0 +113,0 @@ }

dist/cjs/prompt/tests/load.test.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 var __importDefault = (this && this.__importDefault) || function (mod) {
@@ -19,13 +10,13 @@ return (mod && mod.__esModule) ? mod : { "default": mod };
 const PROMPTS_DIR = path_1.default.join(__dirname, "prompts");
-(0, globals_1.test)("Load Hello World Prompt", () => __awaiter(void 0, void 0, void 0, function* () {
+(0, globals_1.test)("Load Hello World Prompt", async () => {
     const helloWorld = path_1.default.join(PROMPTS_DIR, "hello_world.yaml");
-    const prompt = yield (0, load_1.loadPrompt)(helloWorld);
+    const prompt = await (0, load_1.loadPrompt)(helloWorld);
     (0, globals_1.expect)(prompt._getPromptType()).toBe("prompt");
     (0, globals_1.expect)(prompt.format({})).toBe("Say hello world.");
-}));
-(0, globals_1.test)("Load hub prompt", () => __awaiter(void 0, void 0, void 0, function* () {
-    const prompt = yield (0, load_1.loadPrompt)("lc@abb92d8://prompts/hello-world/prompt.yaml");
+});
+(0, globals_1.test)("Load hub prompt", async () => {
+    const prompt = await (0, load_1.loadPrompt)("lc@abb92d8://prompts/hello-world/prompt.yaml");
     (0, globals_1.expect)(prompt._getPromptType()).toBe("prompt");
     (0, globals_1.expect)(prompt.format({})).toBe("Say hello world.");
-}));
+});
 //# sourceMappingURL=load.test.js.map

dist/cjs/util/hub.d.ts

@@ -1,1 +0,2 @@
-export declare const loadFromHub: <T>(uri: string, loader: (a: string) => T, validPrefix: string, validSuffixes: Set<string>) => Promise<T | undefined>;
+export type LoadValues = Record<string, any>;
+export declare const loadFromHub: <T>(uri: string, loader: (a: string, values: LoadValues) => T, validPrefix: string, validSuffixes: Set<string>, values?: LoadValues) => Promise<T | undefined>;

dist/cjs/util/hub.js

 "use strict";
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 var __importDefault = (this && this.__importDefault) || function (mod) {
@@ -24,3 +15,3 @@ return (mod && mod.__esModule) ? mod : { "default": mod };
 const URL_BASE = (_b = process.env.LANGCHAIN_HUB_URL_BASE) !== null && _b !== void 0 ? _b : "https://raw.githubusercontent.com/hwchase17/langchain-hub/";
-const loadFromHub = (uri, loader, validPrefix, validSuffixes) => __awaiter(void 0, void 0, void 0, function* () {
+const loadFromHub = async (uri, loader, validPrefix, validSuffixes, values = {}) => {
     const match = uri.match(HUB_PATH_REGEX);
@@ -40,13 +31,13 @@ if (!match) {
     const url = [URL_BASE, ref, remotePath].join("/");
-    const res = yield (0, index_1.fetchWithTimeout)(url, { timeout: 5000 });
+    const res = await (0, index_1.fetchWithTimeout)(url, { timeout: 5000 });
     if (res.status !== 200) {
         throw new Error(`Could not find file at ${url}`);
     }
-    const text = yield res.text();
+    const text = await res.text();
     const tmpdir = fs_1.default.mkdtempSync(path_1.default.join(os_1.default.tmpdir(), "langchain"));
     const file = path_1.default.join(tmpdir, path_1.default.basename(remotePath));
     fs_1.default.writeFileSync(file, text);
-    return loader(file);
-});
+    return loader(file, values);
+};
 exports.loadFromHub = loadFromHub;
 //# sourceMappingURL=hub.js.map

dist/cjs/util/index.d.ts

@@ -13,1 +13,2 @@ import { RequestInit } from "node-fetch";
 export declare const parseFileConfig: (file: string, supportedTypes?: string[]) => any;
+export declare const chunkArray: <T>(arr: T[], chunkSize: number) => T[][];

dist/cjs/util/index.js

@@ -25,22 +25,2 @@ "use strict";
 };
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-var __rest = (this && this.__rest) || function (s, e) {
-    var t = {};
-    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
-        t[p] = s[p];
-    if (s != null && typeof Object.getOwnPropertySymbols === "function")
-        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
-            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
-                t[p[i]] = s[p[i]];
-        }
-    return t;
-};
 var __importDefault = (this && this.__importDefault) || function (mod) {
@@ -50,3 +30,3 @@ return (mod && mod.__esModule) ? mod : { "default": mod };
 Object.defineProperty(exports, "__esModule", { value: true });
-exports.parseFileConfig = exports.resolveConfigFromFile = exports.resolveTemplateFromFile = exports.fetchWithTimeout = void 0;
+exports.chunkArray = exports.parseFileConfig = exports.resolveConfigFromFile = exports.resolveTemplateFromFile = exports.fetchWithTimeout = void 0;
 const path_1 = __importDefault(require("path"));
@@ -56,11 +36,11 @@ const node_fetch_1 = __importDefault(require("node-fetch"));
 const yaml = __importStar(require("yaml"));
-const fetchWithTimeout = (url, init) => __awaiter(void 0, void 0, void 0, function* () {
-    const { timeout } = init, rest = __rest(init, ["timeout"]);
+const fetchWithTimeout = async (url, init) => {
+    const { timeout, ...rest } = init;
     const controller = new AbortController();
     const timeoutId = setTimeout(() => controller.abort(), timeout);
     // eslint-disable-next-line @typescript-eslint/no-explicit-any
-    const res = yield (0, node_fetch_1.default)(url, Object.assign(Object.assign({}, rest), { signal: controller.signal }));
+    const res = await (0, node_fetch_1.default)(url, { ...rest, signal: controller.signal });
     clearTimeout(timeoutId);
     return res;
-});
+};
 exports.fetchWithTimeout = fetchWithTimeout;
@@ -110,2 +90,10 @@ const loadFileContents = (contents, format) => {
 exports.parseFileConfig = parseFileConfig;
+const chunkArray = (arr, chunkSize) => arr.reduce((chunks, elem, index) => {
+    const chunkIndex = Math.floor(index / chunkSize);
+    const chunk = chunks[chunkIndex] || [];
+    // eslint-disable-next-line no-param-reassign
+    chunks[chunkIndex] = chunk.concat([elem]);
+    return chunks;
+}, []);
+exports.chunkArray = chunkArray;
 //# sourceMappingURL=index.js.map

dist/esm/agents/agent.d.ts

@@ -7,3 +7,12 @@ import { ChainValues } from "../chains";
 export interface StaticAgent {
+    /**
+     * Create a prompt for this class
+     *
+     * @param tools - List of tools the agent will have access to, used to format the prompt.
+     * @param fields - Additional fields used to format the prompt.
+     *
+     * @returns A PromptTemplate assembled from the given tools and fields.
+     * */
     createPrompt(tools: Tool[], fields?: Record<string, any>): BasePromptTemplate;
+    /** Construct an agent from an LLM and a list of tools */
     fromLLMAndTools(llm: BaseLLM, tools: Tool[], args?: Record<string, any>): Agent;
@@ -18,2 +27,9 @@ validateTools(_: Tool[]): void;
 }
+/**
+ * Class responsible for calling a language model and deciding an action.
+ *
+ * @remarks This is driven by an LLMChain. The prompt in the LLMChain *must*
+ * include a variable called "agent_scratchpad" where the agent can put its
+ * intermediary work.
+ */
 export declare abstract class Agent {
@@ -24,2 +40,5 @@ llmChain: LLMChain;
     constructor(input: AgentInput);
+    /**
+     * Extract tool and tool input from LLM output.
+     */
     abstract extractToolAndInput(input: string): {
@@ -29,13 +48,48 @@ tool: string;
     } | null;
+    /**
+     * Prefix to append the observation with.
+     */
     abstract observationPrefix(): string;
+    /**
+     * Prefix to append the LLM call with.
+     */
     abstract llmPrefix(): string;
+    /**
+     * Return the string type key uniquely identifying this class of agent.
+     */
     abstract _agentType(): string;
+    /**
+     * Prepare the agent for a new call, if needed
+     */
     prepareForNewCall(): void;
+    /**
+     * Validate that appropriate tools are passed in
+     */
     static validateTools(_: Tool[]): void;
     _stop(): string[];
+    /**
+     * Name of tool to use to terminate the chain.
+     */
     finishToolName(): string;
+    /**
+     * Construct a scratchpad to let the agent continue its thought process
+     */
     private constructScratchPad;
     private _plan;
+    /**
+     * Decide what to do given some input.
+     *
+     * @param steps - Steps the LLM has taken so far, along with observations from each.
+     * @param inputs - User inputs.
+     *
+     * @returns Action specifying what tool to use.
+     */
     plan(steps: AgentStep[], inputs: ChainValues): Promise<AgentAction | AgentFinish>;
+    /**
+     * Return response when agent has been stopped due to max iterations
+     */
     returnStoppedResponse(earlyStoppingMethod: StoppingMethod, steps: AgentStep[], inputs: ChainValues): Promise<AgentFinish>;
+    /**
+     * Load an agent from a json-like object describing it.
+     */
     static deserialize(data: SerializedAgent & {
@@ -42,0 +96,0 @@ llm?: BaseLLM;

dist/esm/agents/agent.js

@@ -1,10 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { ZeroShotAgent, } from "./index";
@@ -24,2 +15,9 @@ class ParseError extends Error {
 export const staticImplements = (_) => { };
+/**
+ * Class responsible for calling a language model and deciding an action.
+ *
+ * @remarks This is driven by an LLMChain. The prompt in the LLMChain *must*
+ * include a variable called "agent_scratchpad" where the agent can put its
+ * intermediary work.
+ */
 export class Agent {
@@ -48,3 +46,9 @@ constructor(input) {
     }
+    /**
+     * Prepare the agent for a new call, if needed
+     */
     prepareForNewCall() { }
+    /**
+     * Validate that appropriate tools are passed in
+     */
     // eslint-disable-next-line no-unused-vars
@@ -55,5 +59,11 @@ static validateTools(_) { }
     }
+    /**
+     * Name of tool to use to terminate the chain.
+     */
     finishToolName() {
         return "Final Answer";
     }
+    /**
+     * Construct a scratchpad to let the agent continue its thought process
+     */
     constructScratchPad(steps) {
@@ -67,62 +77,74 @@ return steps.reduce((thoughts, { action, observation }) => thoughts +
     }
-    _plan(steps, inputs, suffix) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const thoughts = this.constructScratchPad(steps);
-            const newInputs = Object.assign(Object.assign({}, inputs), { agent_scratchpad: suffix ? `${thoughts}${suffix}` : thoughts, stop: this._stop() });
-            const output = yield this.llmChain.predict(newInputs);
-            const parsed = this.extractToolAndInput(output);
-            if (!parsed) {
-                throw new ParseError(`Invalid output: ${output}`, output);
-            }
-            const action = {
-                tool: parsed.tool,
-                toolInput: parsed.input,
-                log: output,
-            };
-            if (action.tool === this.finishToolName()) {
-                return { returnValues: { output: action.toolInput }, log: action.log };
-            }
-            return action;
-        });
+    async _plan(steps, inputs, suffix) {
+        const thoughts = this.constructScratchPad(steps);
+        const newInputs = {
+            ...inputs,
+            agent_scratchpad: suffix ? `${thoughts}${suffix}` : thoughts,
+            stop: this._stop(),
+        };
+        const output = await this.llmChain.predict(newInputs);
+        const parsed = this.extractToolAndInput(output);
+        if (!parsed) {
+            throw new ParseError(`Invalid output: ${output}`, output);
+        }
+        const action = {
+            tool: parsed.tool,
+            toolInput: parsed.input,
+            log: output,
+        };
+        if (action.tool === this.finishToolName()) {
+            return { returnValues: { output: action.toolInput }, log: action.log };
+        }
+        return action;
     }
+    /**
+     * Decide what to do given some input.
+     *
+     * @param steps - Steps the LLM has taken so far, along with observations from each.
+     * @param inputs - User inputs.
+     *
+     * @returns Action specifying what tool to use.
+     */
     plan(steps, inputs) {
         return this._plan(steps, inputs);
     }
-    returnStoppedResponse(earlyStoppingMethod, steps, inputs) {
-        return __awaiter(this, void 0, void 0, function* () {
-            if (earlyStoppingMethod === "force") {
-                return {
-                    returnValues: { output: "Agent stopped due to max iterations." },
-                    log: "",
-                };
+    /**
+     * Return response when agent has been stopped due to max iterations
+     */
+    async returnStoppedResponse(earlyStoppingMethod, steps, inputs) {
+        if (earlyStoppingMethod === "force") {
+            return {
+                returnValues: { output: "Agent stopped due to max iterations." },
+                log: "",
+            };
+        }
+        if (earlyStoppingMethod === "generate") {
+            try {
+                const action = await this._plan(steps, inputs, "\n\nI now need to return a final answer based on the previous steps:");
+                if ("returnValues" in action) {
+                    return action;
+                }
+                return { returnValues: { output: action.log }, log: action.log };
             }
-            if (earlyStoppingMethod === "generate") {
-                try {
-                    const action = yield this._plan(steps, inputs, "\n\nI now need to return a final answer based on the previous steps:");
-                    if ("returnValues" in action) {
-                        return action;
-                    }
-                    return { returnValues: { output: action.log }, log: action.log };
+            catch (err) {
+                if (!(err instanceof ParseError)) {
+                    throw err;
                 }
-                catch (err) {
-                    if (!(err instanceof ParseError)) {
-                        throw err;
-                    }
-                    return { returnValues: { output: err.output }, log: err.output };
-                }
+                return { returnValues: { output: err.output }, log: err.output };
             }
-            throw new Error(`Invalid stopping method: ${earlyStoppingMethod}`);
-        });
+        }
+        throw new Error(`Invalid stopping method: ${earlyStoppingMethod}`);
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            switch (data._type) {
-                case "zero-shot-react-description":
-                    return ZeroShotAgent.deserialize(data);
-                default:
-                    throw new Error("Unknown agent type");
-            }
-        });
+    /**
+     * Load an agent from a json-like object describing it.
+     */
+    static async deserialize(data) {
+        switch (data._type) {
+            case "zero-shot-react-description":
+                return ZeroShotAgent.deserialize(data);
+            default:
+                throw new Error("Unknown agent type");
+        }
     }
 }
 //# sourceMappingURL=agent.js.map

dist/esm/agents/executor.d.ts

@@ -11,2 +11,6 @@ import { ChainValues, BaseChain } from "../chains";
 };
+/**
+ * A chain managing an agent using tools.
+ * @augments BaseChain
+ */
 export declare class AgentExecutor extends BaseChain {
@@ -19,2 +23,3 @@ agent: Agent;
     constructor(input: AgentExecutorInput);
+    /** Create from agent and a list of tools. */
     static fromAgentAndTools(fields: {
@@ -21,0 +26,0 @@ agent: Agent;

dist/esm/agents/executor.js

@@ -1,11 +0,6 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { BaseChain } from "../chains";
+/**
+ * A chain managing an agent using tools.
+ * @augments BaseChain
+ */
 export class AgentExecutor extends BaseChain {
@@ -53,2 +48,3 @@ constructor(input) {
     }
+    /** Create from agent and a list of tools. */
     static fromAgentAndTools(fields) {
@@ -60,36 +56,34 @@ return new AgentExecutor(fields);
     }
-    _call(inputs) {
-        return __awaiter(this, void 0, void 0, function* () {
-            this.agent.prepareForNewCall();
-            const toolsByName = Object.fromEntries(this.tools.map((t) => [t.name, t]));
-            const steps = [];
-            let iterations = 0;
-            const getOutput = (finishStep) => {
-                const { returnValues } = finishStep;
-                if (this.returnIntermediateSteps) {
-                    return Object.assign(Object.assign({}, returnValues), { intermediateSteps: steps });
-                }
-                return returnValues;
-            };
-            while (this.shouldContinue(iterations)) {
-                const action = yield this.agent.plan(steps, inputs);
-                if ("returnValues" in action) {
-                    return getOutput(action);
-                }
-                const tool = toolsByName[action.tool];
-                const observation = tool
-                    ? yield tool.call(action.toolInput)
-                    : `${action.tool} is not a valid tool, try another one.`;
-                steps.push({ action, observation });
-                if (tool === null || tool === void 0 ? void 0 : tool.returnDirect) {
-                    return getOutput({
-                        returnValues: { [this.agent.returnValues[0]]: observation },
-                        log: "",
-                    });
-                }
-                iterations += 1;
+    async _call(inputs) {
+        this.agent.prepareForNewCall();
+        const toolsByName = Object.fromEntries(this.tools.map((t) => [t.name.toLowerCase(), t]));
+        const steps = [];
+        let iterations = 0;
+        const getOutput = (finishStep) => {
+            const { returnValues } = finishStep;
+            if (this.returnIntermediateSteps) {
+                return { ...returnValues, intermediateSteps: steps };
             }
-            const finish = yield this.agent.returnStoppedResponse(this.earlyStoppingMethod, steps, inputs);
-            return getOutput(finish);
-        });
+            return returnValues;
+        };
+        while (this.shouldContinue(iterations)) {
+            const action = await this.agent.plan(steps, inputs);
+            if ("returnValues" in action) {
+                return getOutput(action);
+            }
+            const tool = toolsByName[action.tool.toLowerCase()];
+            const observation = tool
+                ? await tool.call(action.toolInput)
+                : `${action.tool} is not a valid tool, try another one.`;
+            steps.push({ action, observation });
+            if (tool === null || tool === void 0 ? void 0 : tool.returnDirect) {
+                return getOutput({
+                    returnValues: { [this.agent.returnValues[0]]: observation },
+                    log: "",
+                });
+            }
+            iterations += 1;
+        }
+        const finish = await this.agent.returnStoppedResponse(this.earlyStoppingMethod, steps, inputs);
+        return getOutput(finish);
     }
@@ -96,0 +90,0 @@ _chainType() {

dist/esm/agents/helpers.js

@@ -1,13 +0,4 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { LLMChain } from "../chains";
 import { resolveConfigFromFile } from "../util";
-export const deserializeHelper = (llm, tools, data, fromLLMAndTools, fromConstructor) => __awaiter(void 0, void 0, void 0, function* () {
+export const deserializeHelper = async (llm, tools, data, fromLLMAndTools, fromConstructor) => {
     if (data.load_from_llm_and_tools) {
@@ -23,5 +14,5 @@ if (!llm) {
     const serializedLLMChain = resolveConfigFromFile("llm_chain", data);
-    const llmChain = yield LLMChain.deserialize(serializedLLMChain);
-    return fromConstructor(Object.assign(Object.assign({}, data), { llmChain }));
-});
+    const llmChain = await LLMChain.deserialize(serializedLLMChain);
+    return fromConstructor({ ...data, llmChain });
+};
 //# sourceMappingURL=helpers.js.map

dist/esm/agents/index.d.ts

@@ -6,2 +6,3 @@ export { AgentAction, AgentFinish, AgentStep, StoppingMethod, SerializedAgentT, } from "./types";
 export { Tool } from "./tools";
+export { initializeAgentExecutor } from "./initialize";
 export { loadAgent } from "./load";

dist/esm/agents/index.js

 export { Agent, staticImplements } from "./agent";
 export { AgentExecutor } from "./executor";
 export { ZeroShotAgent } from "./mrkl";
+export { Tool } from "./tools";
+export { initializeAgentExecutor } from "./initialize";
 export { loadAgent } from "./load";
 //# sourceMappingURL=index.js.map

dist/esm/agents/load.js

@@ -1,19 +0,10 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { Agent } from ".";
 import { loadFromHub } from "../util/hub";
 import { parseFileConfig } from "../util";
-const loadAgentFromFile = (file, llmAndTools) => __awaiter(void 0, void 0, void 0, function* () {
+const loadAgentFromFile = async (file, llmAndTools) => {
     const serialized = parseFileConfig(file);
-    return Agent.deserialize(Object.assign(Object.assign({}, serialized), llmAndTools));
-});
-export const loadAgent = (uri, llmAndTools) => __awaiter(void 0, void 0, void 0, function* () {
-    const hubResult = yield loadFromHub(uri, (u) => loadAgentFromFile(u, llmAndTools), "agents", new Set(["json", "yaml"]));
+    return Agent.deserialize({ ...serialized, ...llmAndTools });
+};
+export const loadAgent = async (uri, llmAndTools) => {
+    const hubResult = await loadFromHub(uri, (u) => loadAgentFromFile(u, llmAndTools), "agents", new Set(["json", "yaml"]));
     if (hubResult) {
@@ -23,3 +14,3 @@ return hubResult;
     return loadAgentFromFile(uri, llmAndTools);
-});
+};
 //# sourceMappingURL=load.js.map

dist/esm/agents/mrkl/index.d.ts

@@ -11,7 +11,15 @@ import { BaseLLM } from "../../llms";
 type CreatePromptArgs = {
+    /** String to put after the list of tools. */
     suffix?: string;
+    /** String to put before the list of tools. */
     prefix?: string;
+    /** List of input variables the final prompt will expect. */
     inputVariables?: string[];
 };
 type ZeroShotAgentInput = AgentInput;
+/**
+ * Agent for the MRKL chain.
+ * @augments Agent
+ * @augments StaticAgent
+ */
 export declare class ZeroShotAgent extends Agent {
@@ -23,2 +31,11 @@ constructor(input: ZeroShotAgentInput);
     static validateTools(tools: Tool[]): void;
+    /**
+     * Create prompt in the style of the zero shot agent.
+     *
+     * @param tools - List of tools the agent will have access to, used to format the prompt.
+     * @param args - Arguments to create the prompt with.
+     * @param args.suffix - String to put after the list of tools.
+     * @param args.prefix - String to put before the list of tools.
+     * @param args.inputVariables - List of input variables the final prompt will expect.
+     */
     static createPrompt(tools: Tool[], args?: CreatePromptArgs): PromptTemplate;
@@ -25,0 +42,0 @@ static fromLLMAndTools(llm: BaseLLM, tools: Tool[], args?: CreatePromptArgs): ZeroShotAgent;

dist/esm/agents/mrkl/index.js

@@ -7,22 +7,2 @@ var __decorate = (this && this.__decorate) || function (decorators, target, key, desc) {
 };
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-var __rest = (this && this.__rest) || function (s, e) {
-    var t = {};
-    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
-        t[p] = s[p];
-    if (s != null && typeof Object.getOwnPropertySymbols === "function")
-        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
-            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
-                t[p[i]] = s[p[i]];
-        }
-    return t;
-};
 var ZeroShotAgent_1;
@@ -35,2 +15,7 @@ import { LLMChain } from "../../chains";
 const FINAL_ANSWER_ACTION = "Final Answer:";
+/**
+ * Agent for the MRKL chain.
+ * @augments Agent
+ * @augments StaticAgent
+ */
 let ZeroShotAgent = ZeroShotAgent_1 = class ZeroShotAgent extends Agent {
@@ -57,2 +42,11 @@ constructor(input) {
     }
+    /**
+     * Create prompt in the style of the zero shot agent.
+     *
+     * @param tools - List of tools the agent will have access to, used to format the prompt.
+     * @param args - Arguments to create the prompt with.
+     * @param args.suffix - String to put after the list of tools.
+     * @param args.prefix - String to put before the list of tools.
+     * @param args.inputVariables - List of input variables the final prompt will expect.
+     */
     static createPrompt(tools, args) {
@@ -94,11 +88,9 @@ const { prefix = PREFIX, suffix = SUFFIX, inputVariables = ["input", "agent_scratchpad"], } = args !== null && args !== void 0 ? args : {};
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const { llm, tools } = data, rest = __rest(data, ["llm", "tools"]);
-            return deserializeHelper(llm, tools, rest, (llm, tools, args) => ZeroShotAgent_1.fromLLMAndTools(llm, tools, {
-                prefix: args.prefix,
-                suffix: args.suffix,
-                inputVariables: args.input_variables,
-            }), (args) => new ZeroShotAgent_1(args));
-        });
+    static async deserialize(data) {
+        const { llm, tools, ...rest } = data;
+        return deserializeHelper(llm, tools, rest, (llm, tools, args) => ZeroShotAgent_1.fromLLMAndTools(llm, tools, {
+            prefix: args.prefix,
+            suffix: args.suffix,
+            inputVariables: args.input_variables,
+        }), (args) => new ZeroShotAgent_1(args));
     }
@@ -105,0 +97,0 @@ };

dist/esm/agents/mrkl/prompt.js

@@ -1,2 +0,1 @@
-/* eslint-disable max-len */
 export const PREFIX = `Answer the following questions as best you can. You have access to the following tools:`;
@@ -3,0 +2,0 @@ export const formatInstructions = (toolNames) => `Use the following format:

dist/esm/agents/tests/agent.test.js

@@ -1,10 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { test } from "@jest/globals";
@@ -15,6 +6,8 @@ import { OpenAI } from "../../llms/openai";
 import { SerpAPI } from "../tools/serpapi";
-test("Run agent from hub", () => __awaiter(void 0, void 0, void 0, function* () {
-    const model = new OpenAI({});
-    const tools = [SerpAPI()];
-    const agent = yield loadAgent("lc://agents/zero-shot-react-description/agent.json", { llm: model, tools });
+import { Calculator } from "../tools/calculator";
+import { initializeAgentExecutor } from "../initialize";
+test("Run agent from hub", async () => {
+    const model = new OpenAI({ temperature: 0 });
+    const tools = [new SerpAPI(), new Calculator()];
+    const agent = await loadAgent("lc://agents/zero-shot-react-description/agent.json", { llm: model, tools });
     const executor = AgentExecutor.fromAgentAndTools({
@@ -25,7 +18,18 @@ agent,
     });
-    const res = yield executor.call({
+    const res = await executor.call({
         input: "Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?",
     });
     console.log(res);
-}), 30000);
+}, 30000);
+test("Run agent locally", async () => {
+    const model = new OpenAI({ temperature: 0 });
+    const tools = [new SerpAPI(), new Calculator()];
+    const executor = await initializeAgentExecutor(tools, model, "zero-shot-react-description");
+    console.log("Loaded agent.");
+    const input = "Who is Olivia Wilde's boyfriend?" +
+        " What is his current age raised to the 0.23 power?";
+    console.log(`Executing with input "${input}"...`);
+    const result = await executor.call({ input });
+    console.log(`Got output ${result.output}`);
+}, 30000);
 //# sourceMappingURL=agent.test.js.map

dist/esm/agents/tools/index.d.ts

 export { SerpAPI } from "./serpapi";
-export interface Tool {
-    call: (arg: string) => Promise<string>;
-    name: string;
-    description: string;
-    returnDirect?: boolean;
-}
+export { Calculator } from "./calculator";
+export { Tool } from "./base";

dist/esm/agents/tools/index.js

 export { SerpAPI } from "./serpapi";
+export { Calculator } from "./calculator";
+export { Tool } from "./base";
 //# sourceMappingURL=index.js.map

dist/esm/agents/tools/serpapi.d.ts

@@ -1,3 +0,18 @@
-import { GoogleParameters } from "serpapi";
-import { Tool } from "./index";
-export declare const SerpAPI: (params?: Partial<GoogleParameters>, apiKey?: string) => Tool;
+import type { GoogleParameters } from "serpapi";
+import { Tool } from "./base";
+/**
+ * Wrapper around SerpAPI.
+ *
+ * To use, you should have the `serpapi` package installed and the SERPAPI_API_KEY environment variable set.
+ */
+export declare class SerpAPI extends Tool {
+    protected key: string;
+    protected params: Partial<GoogleParameters>;
+    constructor(apiKey?: string | undefined, params?: Partial<GoogleParameters>);
+    name: string;
+    /**
+     * Run query through SerpAPI and parse result
+     */
+    call(input: string): Promise<any>;
+    description: string;
+}

dist/esm/agents/tools/serpapi.js

@@ -1,46 +0,89 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-import { getJson } from "serpapi";
-export const SerpAPI = (params, apiKey) => {
-    const key = apiKey !== null && apiKey !== void 0 ? apiKey : process.env.SERPAPI_API_KEY;
-    return {
-        name: "search",
-        call: (input) => __awaiter(void 0, void 0, void 0, function* () {
-            var _a, _b, _c, _d, _e, _f, _g;
-            const res = yield getJson("google", Object.assign(Object.assign({}, params), { api_key: key, q: input }));
-            if (res.error) {
-                throw new Error(`Got error from serpAPI: ${res.error}`);
-            }
-            if ((_a = res.answer_box) === null || _a === void 0 ? void 0 : _a.answer) {
-                return res.answer_box.answer;
-            }
-            if ((_b = res.answer_box) === null || _b === void 0 ? void 0 : _b.snippet) {
-                return res.answer_box.snippet;
-            }
-            if ((_c = res.answer_box) === null || _c === void 0 ? void 0 : _c.snippet_highlighted_words) {
-                return res.answer_box.snippet_highlighted_words[0];
-            }
-            if ((_d = res.sports_results) === null || _d === void 0 ? void 0 : _d.game_spotlight) {
-                return res.sports_results.game_spotlight;
-            }
-            if ((_e = res.knowledge_graph) === null || _e === void 0 ? void 0 : _e.description) {
-                return res.knowledge_graph.description;
-            }
-            if ((_g = (_f = res.organic_results) === null || _f === void 0 ? void 0 : _f[0]) === null || _g === void 0 ? void 0 : _g.snippet) {
-                return res.organic_results[0].snippet;
-            }
-            return "No good search result found";
-        }),
-        description: 
-        // eslint-disable-next-line max-len
-        "a search engine. useful for when you need to answer questions about current events. input should be a search query.",
-    };
-};
+import { Tool } from "./base";
+let getJson = null;
+try {
+    // eslint-disable-next-line global-require,import/no-extraneous-dependencies
+    ({ getJson } = require("serpapi"));
+}
+catch (_a) {
+    // ignore error
+}
+/**
+ * Wrapper around SerpAPI.
+ *
+ * To use, you should have the `serpapi` package installed and the SERPAPI_API_KEY environment variable set.
+ */
+export class SerpAPI extends Tool {
+    constructor(apiKey = process.env.SERPAPI_API_KEY, params = {}) {
+        super();
+        Object.defineProperty(this, "key", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: void 0
+        });
+        Object.defineProperty(this, "params", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: void 0
+        });
+        Object.defineProperty(this, "name", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: "search"
+        });
+        Object.defineProperty(this, "description", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: "a search engine. useful for when you need to answer questions about current events. input should be a search query."
+        });
+        // Throw error at construction time.
+        if (getJson === null) {
+            throw new Error("Please install serpapi as a dependency with, e.g. `npm i serpapi`");
+        }
+        if (!apiKey) {
+            throw new Error("SerpAPI API key not set. You can set it as SERPAPI_API_KEY in your .env file, or pass it to SerpAPI.");
+        }
+        this.key = apiKey;
+        this.params = params;
+    }
+    /**
+     * Run query through SerpAPI and parse result
+     */
+    async call(input) {
+        var _a, _b, _c, _d, _e, _f, _g;
+        if (getJson === null) {
+            throw new Error("Please install serpapi as a dependency with, e.g. `npm i serpapi`");
+        }
+        const res = await getJson("google", {
+            ...this.params,
+            api_key: this.key,
+            q: input,
+        });
+        if (res.error) {
+            throw new Error(`Got error from serpAPI: ${res.error}`);
+        }
+        if ((_a = res.answer_box) === null || _a === void 0 ? void 0 : _a.answer) {
+            return res.answer_box.answer;
+        }
+        if ((_b = res.answer_box) === null || _b === void 0 ? void 0 : _b.snippet) {
+            return res.answer_box.snippet;
+        }
+        if ((_c = res.answer_box) === null || _c === void 0 ? void 0 : _c.snippet_highlighted_words) {
+            return res.answer_box.snippet_highlighted_words[0];
+        }
+        if ((_d = res.sports_results) === null || _d === void 0 ? void 0 : _d.game_spotlight) {
+            return res.sports_results.game_spotlight;
+        }
+        if ((_e = res.knowledge_graph) === null || _e === void 0 ? void 0 : _e.description) {
+            return res.knowledge_graph.description;
+        }
+        if ((_g = (_f = res.organic_results) === null || _f === void 0 ? void 0 : _f[0]) === null || _g === void 0 ? void 0 : _g.snippet) {
+            return res.organic_results[0].snippet;
+        }
+        return "No good search result found";
+    }
+}
 //# sourceMappingURL=serpapi.js.map

dist/esm/chains/base.d.ts

@@ -1,12 +0,42 @@
-import { SerializedLLMChain } from "./index";
+import { LLMChain, StuffDocumentsChain, VectorDBQAChain, ChatVectorDBQAChain } from "./index";
+import { BaseMemory } from "../memory";
 export type ChainValues = Record<string, any>;
-type SerializedBaseChain = SerializedLLMChain;
-export declare abstract class BaseChain {
+export type LoadValues = Record<string, any>;
+declare const chainClasses: (typeof LLMChain | typeof StuffDocumentsChain | typeof VectorDBQAChain | typeof ChatVectorDBQAChain)[];
+export type SerializedBaseChain = ReturnType<InstanceType<(typeof chainClasses)[number]>["serialize"]>;
+export interface ChainInputs {
+    memory?: BaseMemory;
+}
+/**
+ * Base interface that all chains must implement.
+ */
+export declare abstract class BaseChain implements ChainInputs {
+    memory?: BaseMemory;
+    /**
+     * Run the core logic of this chain and return the output
+     */
     abstract _call(values: ChainValues): Promise<ChainValues>;
+    /**
+     * Return the string type key uniquely identifying this class of chain.
+     */
     abstract _chainType(): string;
+    /**
+     * Return a json-like object representing this chain.
+     */
     abstract serialize(): SerializedBaseChain;
+    /**
+     * Run the core logic of this chain and add to output if desired.
+     *
+     * Wraps {@link _call} and handles memory.
+     */
     call(values: ChainValues): Promise<ChainValues>;
+    /**
+     * Call the chain on all inputs in the list
+     */
     apply(inputs: ChainValues[]): ChainValues[];
-    static deserialize(data: SerializedBaseChain): Promise<BaseChain>;
+    /**
+     * Load a chain from a json-like object describing it.
+     */
+    static deserialize(data: SerializedBaseChain, values?: LoadValues): Promise<BaseChain>;
 }
 export {};

dist/esm/chains/base.js

@@ -1,14 +0,52 @@
-import { LLMChain } from "./index";
+import { LLMChain, StuffDocumentsChain, VectorDBQAChain, ChatVectorDBQAChain } from "./index";
+const chainClasses = [LLMChain, StuffDocumentsChain, VectorDBQAChain, ChatVectorDBQAChain];
+/**
+ * Base interface that all chains must implement.
+ */
 export class BaseChain {
-    call(values) {
+    constructor() {
+        Object.defineProperty(this, "memory", {
+            enumerable: true,
+            configurable: true,
+            writable: true,
+            value: void 0
+        });
+    }
+    /**
+     * Run the core logic of this chain and add to output if desired.
+     *
+     * Wraps {@link _call} and handles memory.
+     */
+    async call(values) {
+        const fullValues = structuredClone(values);
+        if (!(this.memory == null)) {
+            const newValues = await this.memory.loadMemoryVariables(values);
+            for (const [key, value] of Object.entries(newValues)) {
+                fullValues[key] = value;
+            }
+        }
         // TODO(sean) add callback support
-        return this._call(values);
+        const outputValues = this._call(fullValues);
+        if (!(this.memory == null)) {
+            this.memory.saveContext(values, outputValues);
+        }
+        return outputValues;
     }
+    /**
+     * Call the chain on all inputs in the list
+     */
     apply(inputs) {
         return inputs.map(this.call);
     }
-    static deserialize(data) {
+    /**
+     * Load a chain from a json-like object describing it.
+     */
+    static deserialize(data, values = {}) {
         switch (data._type) {
             case "llm_chain":
                 return LLMChain.deserialize(data);
+            case "stuff_documents_chain":
+                return StuffDocumentsChain.deserialize(data);
+            case "vector_db_qa":
+                return VectorDBQAChain.deserialize(data, values);
             default:
@@ -15,0 +53,0 @@ throw new Error(`Invalid prompt type in config: ${data._type}`);

dist/esm/chains/index.d.ts

 export { BaseChain, ChainValues } from "./base";
-export { SerializedLLMChain, LLMChain } from "./llm_chain";
+export { SerializedLLMChain, LLMChain, ConversationChain } from "./llm_chain";
+export { SerializedStuffDocumentsChain, StuffDocumentsChain, } from "./combine_docs_chain";
+export { ChatVectorDBQAChain, SerializedChatVectorDBQAChain } from "./chat_vector_db_chain";
+export { VectorDBQAChain, SerializedVectorDBQAChain } from "./vector_db_qa";
 export { loadChain } from "./load";
+export { loadQAChain } from "./question_answering/load";

dist/esm/chains/index.js

 export { BaseChain } from "./base";
-export { LLMChain } from "./llm_chain";
+export { LLMChain, ConversationChain } from "./llm_chain";
+export { StuffDocumentsChain, } from "./combine_docs_chain";
+export { ChatVectorDBQAChain } from "./chat_vector_db_chain";
+export { VectorDBQAChain } from "./vector_db_qa";
 export { loadChain } from "./load";
+export { loadQAChain } from "./question_answering/load";
 //# sourceMappingURL=index.js.map

dist/esm/chains/llm_chain.d.ts

 import { BaseChain, ChainValues } from "./index";
 import { BaseLLM, SerializedLLM } from "../llms";
+import { BaseMemory } from "../memory";
 import { BasePromptTemplate, SerializedBasePromptTemplate } from "../prompt";
 export interface LLMChainInput {
+    /** Prompt object to use */
     prompt: BasePromptTemplate;
+    /** LLM Wrapper to use */
     llm: BaseLLM;
+    /** @ignore */
     outputKey: string;
@@ -16,2 +20,14 @@ }
 };
+/**
+ * Chain to run queries against LLMs.
+ * @augments BaseChain
+ * @augments LLMChainInput
+ *
+ * @example
+ * ```ts
+ * import { LLMChain, OpenAI, PromptTemplate } from "langchain";
+ * const prompt = PromptTemplate.fromTemplate("Tell me a {adjective} joke");
+ * const llm = LLMChain({ llm: new OpenAI(), prompt });
+ * ```
+ */
 export declare class LLMChain extends BaseChain implements LLMChainInput {
@@ -27,2 +43,13 @@ prompt: BasePromptTemplate;
     _call(values: ChainValues): Promise<ChainValues>;
+    /**
+     * Format prompt with values and pass to LLM
+     *
+     * @param values - keys to pass to prompt template
+     * @returns Completion from LLM.
+     *
+     * @example
+     * ```ts
+     * llm.predict({ adjective: "funny" })
+     * ```
+     */
     predict(values: ChainValues): Promise<string>;
@@ -33,1 +60,9 @@ _chainType(): "llm_chain";
 }
+export declare class ConversationChain extends LLMChain {
+    constructor(fields: {
+        llm: BaseLLM;
+        prompt?: BasePromptTemplate;
+        outputKey?: string;
+        memory?: BaseMemory;
+    });
+}

dist/esm/chains/llm_chain.js

@@ -1,14 +0,18 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { BaseChain } from "./index";
 import { BaseLLM } from "../llms";
-import { BasePromptTemplate } from "../prompt";
+import { BufferMemory } from "../memory";
+import { BasePromptTemplate, PromptTemplate } from "../prompt";
 import { resolveConfigFromFile } from "../util";
+/**
+ * Chain to run queries against LLMs.
+ * @augments BaseChain
+ * @augments LLMChainInput
+ *
+ * @example
+ * ```ts
+ * import { LLMChain, OpenAI, PromptTemplate } from "langchain";
+ * const prompt = PromptTemplate.fromTemplate("Tell me a {adjective} joke");
+ * const llm = LLMChain({ llm: new OpenAI(), prompt });
+ * ```
+ */
 export class LLMChain extends BaseChain {
@@ -40,19 +44,26 @@ constructor(fields) {
     }
-    _call(values) {
-        return __awaiter(this, void 0, void 0, function* () {
-            let stop;
-            if ("stop" in values && Array.isArray(values.stop)) {
-                stop = values.stop;
-            }
-            const formattedString = this.prompt.format(values);
-            const llmResult = yield this.llm.call(formattedString, stop);
-            const result = { [this.outputKey]: llmResult };
-            return result;
-        });
+    async _call(values) {
+        let stop;
+        if ("stop" in values && Array.isArray(values.stop)) {
+            stop = values.stop;
+        }
+        const formattedString = this.prompt.format(values);
+        const llmResult = await this.llm.call(formattedString, stop);
+        const result = { [this.outputKey]: llmResult };
+        return result;
     }
-    predict(values) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const output = yield this.call(values);
-            return output[this.outputKey];
-        });
+    /**
+     * Format prompt with values and pass to LLM
+     *
+     * @param values - keys to pass to prompt template
+     * @returns Completion from LLM.
+     *
+     * @example
+     * ```ts
+     * llm.predict({ adjective: "funny" })
+     * ```
+     */
+    async predict(values) {
+        const output = await this.call(values);
+        return output[this.outputKey];
     }
@@ -62,10 +73,8 @@ _chainType() {
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const serializedLLM = resolveConfigFromFile("llm", data);
-            const serializedPrompt = resolveConfigFromFile("prompt", data);
-            return new LLMChain({
-                llm: yield BaseLLM.deserialize(serializedLLM),
-                prompt: yield BasePromptTemplate.deserialize(serializedPrompt),
-            });
+    static async deserialize(data) {
+        const serializedLLM = resolveConfigFromFile("llm", data);
+        const serializedPrompt = resolveConfigFromFile("prompt", data);
+        return new LLMChain({
+            llm: await BaseLLM.deserialize(serializedLLM),
+            prompt: await BasePromptTemplate.deserialize(serializedPrompt),
         });
@@ -81,2 +90,24 @@ }
 }
+// eslint-disable-next-line max-len
+const defaultTemplate = `The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
+
+Current conversation:
+{history}
+Human: {input}
+AI:`;
+const defaultPrompt = new PromptTemplate({
+    template: defaultTemplate,
+    inputVariables: ["history", "input"],
+});
+export class ConversationChain extends LLMChain {
+    constructor(fields) {
+        var _a, _b, _c;
+        super({
+            prompt: (_a = fields.prompt) !== null && _a !== void 0 ? _a : defaultPrompt,
+            llm: fields.llm,
+            outputKey: (_b = fields.outputKey) !== null && _b !== void 0 ? _b : "response",
+        });
+        this.memory = (_c = fields.memory) !== null && _c !== void 0 ? _c : new BufferMemory();
+    }
+}
 //# sourceMappingURL=llm_chain.js.map

dist/esm/chains/load.d.ts

 import { BaseChain } from ".";
-export declare const loadChain: (uri: string) => Promise<BaseChain>;
+export type LoadValues = Record<string, any>;
+/**
+ * Load a chain from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("lc://chains/hello-world/chain.json");
+ * const res = await chain.call({ topic: "my favorite color" });
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("/path/to/chain.json");
+ * ```
+ */
+export declare const loadChain: (uri: string, values?: LoadValues) => Promise<BaseChain>;

dist/esm/chains/load.js

@@ -1,25 +0,33 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { BaseChain } from ".";
 import { loadFromHub } from "../util/hub";
 import { parseFileConfig } from "../util";
-const loadChainFromFile = (file) => __awaiter(void 0, void 0, void 0, function* () {
+const loadChainFromFile = async (file, values = {}) => {
     const serialized = parseFileConfig(file);
-    console.log({ serialized });
-    return BaseChain.deserialize(serialized);
-});
-export const loadChain = (uri) => __awaiter(void 0, void 0, void 0, function* () {
-    const hubResult = yield loadFromHub(uri, loadChainFromFile, "chains", new Set(["json", "yaml"]));
+    return BaseChain.deserialize(serialized, values);
+};
+/**
+ * Load a chain from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("lc://chains/hello-world/chain.json");
+ * const res = await chain.call({ topic: "my favorite color" });
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadChain } from "langchain/chains";
+ * const chain = await loadChain("/path/to/chain.json");
+ * ```
+ */
+export const loadChain = async (uri, values = {}) => {
+    const hubResult = await loadFromHub(uri, (uri) => loadChainFromFile(uri, values), "chains", new Set(["json", "yaml"]), values);
     if (hubResult) {
         return hubResult;
     }
-    return loadChainFromFile(uri);
-});
+    return loadChainFromFile(uri, values);
+};
 //# sourceMappingURL=load.js.map

dist/esm/chains/tests/llm_chain.test.js

@@ -1,16 +0,7 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { test } from "@jest/globals";
 import { OpenAI } from "../../llms/openai";
 import { PromptTemplate } from "../../prompt";
-import { LLMChain } from "../llm_chain";
+import { LLMChain, ConversationChain } from "../llm_chain";
 import { loadChain } from "../load";
-test("Test OpenAI", () => __awaiter(void 0, void 0, void 0, function* () {
+test("Test OpenAI", async () => {
     const model = new OpenAI({});
@@ -22,10 +13,16 @@ const prompt = new PromptTemplate({
     const chain = new LLMChain({ prompt, llm: model });
-    const res = yield chain.call({ foo: "my favorite color" });
+    const res = await chain.call({ foo: "my favorite color" });
     console.log({ res });
-}));
-test("Load chain from hub", () => __awaiter(void 0, void 0, void 0, function* () {
-    const chain = yield loadChain("lc://chains/hello-world/chain.json");
-    const res = yield chain.call({ topic: "my favorite color" });
+});
+test("Load chain from hub", async () => {
+    const chain = await loadChain("lc://chains/hello-world/chain.json");
+    const res = await chain.call({ topic: "my favorite color" });
     console.log({ res });
-}));
+});
+test("Test ConversationChain", async () => {
+    const model = new OpenAI({});
+    const chain = new ConversationChain({ llm: model });
+    const res = await chain.call({ input: "my favorite color" });
+    console.log({ res });
+});
 //# sourceMappingURL=llm_chain.test.js.map

dist/esm/llms/base.d.ts

@@ -5,20 +5,61 @@ import { LLMCallbackManager, LLMResult } from "./index";
 } & Record<string, any>;
+/**
+ * LLM Wrapper. Provides an {@link call} (an {@link generate}) function that takes in a prompt (or prompts) and returns a string.
+ */
 export declare abstract class BaseLLM {
+    /**
+     * The name of the LLM class
+     */
     name: string;
     cache?: boolean;
     callbackManager: LLMCallbackManager;
+    /**
+     * Whether to print out response text.
+     */
     verbose?: boolean;
     constructor(callbackManager?: LLMCallbackManager, verbose?: boolean);
+    /**
+     * Run the LLM on the given prompts and input.
+     */
     abstract _generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /** @ignore */
     _generateUncached(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /**
+     * Run the LLM on the given propmts an input, handling caching.
+     */
     generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /**
+     * Convenience wrapper for {@link generate} that takes in a single string prompt and returns a single string output.
+     */
     call(prompt: string, stop?: string[]): Promise<string>;
+    /**
+     * Get the identifying parameters of the LLM.
+     */
     _identifyingParams(): Record<string, any>;
+    /**
+     * Return the string type key uniquely identifying this class of LLM.
+     */
     abstract _llmType(): string;
+    /**
+     * Return a json-like object representing this LLM.
+     */
     serialize(): SerializedLLM;
+    /**
+     * Load an LLM from a json-like object describing it.
+     */
     static deserialize(data: SerializedLLM): Promise<BaseLLM>;
 }
+/**
+ * LLM class that provides a simpler interface to subclass than {@link BaseLLM}.
+ *
+ * Requires only implementing a simpler {@link _call} method instead of {@link _generate}.
+ *
+ * @augments BaseLLM
+ */
 export declare abstract class LLM extends BaseLLM {
+    /**
+     * Run the LLM on the given prompt and input.
+     */
     abstract _call(prompt: string, stop?: string[]): Promise<string>;
     _generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
 }

dist/esm/llms/base.js

@@ -1,21 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-var __rest = (this && this.__rest) || function (s, e) {
-    var t = {};
-    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
-        t[p] = s[p];
-    if (s != null && typeof Object.getOwnPropertySymbols === "function")
-        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
-            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
-                t[p[i]] = s[p[i]];
-        }
-    return t;
-};
 import { OpenAI } from "./index";
@@ -36,4 +16,10 @@ import { InMemoryCache } from "../cache";
 const cache = new InMemoryCache();
+/**
+ * LLM Wrapper. Provides an {@link call} (an {@link generate}) function that takes in a prompt (or prompts) and returns a string.
+ */
 export class BaseLLM {
     constructor(callbackManager, verbose) {
+        /**
+         * The name of the LLM class
+         */
         Object.defineProperty(this, "name", {
@@ -57,2 +43,5 @@ enumerable: true,
         });
+        /**
+         * Whether to print out response text.
+         */
         Object.defineProperty(this, "verbose", {
@@ -67,59 +56,63 @@ enumerable: true,
     }
-    _generateUncached(prompts, stop) {
-        return __awaiter(this, void 0, void 0, function* () {
-            this.callbackManager.handleStart({ name: this.name }, prompts, this.verbose);
-            let output;
-            try {
-                output = yield this._generate(prompts, stop);
-            }
-            catch (err) {
-                this.callbackManager.handleError(`${err}`, this.verbose);
-                throw err;
-            }
-            this.callbackManager.handleEnd(output, this.verbose);
-            return output;
-        });
+    /** @ignore */
+    async _generateUncached(prompts, stop) {
+        this.callbackManager.handleStart({ name: this.name }, prompts, this.verbose);
+        let output;
+        try {
+            output = await this._generate(prompts, stop);
+        }
+        catch (err) {
+            this.callbackManager.handleError(`${err}`, this.verbose);
+            throw err;
+        }
+        this.callbackManager.handleEnd(output, this.verbose);
+        return output;
     }
-    generate(prompts, stop) {
+    /**
+     * Run the LLM on the given propmts an input, handling caching.
+     */
+    async generate(prompts, stop) {
         var _a;
-        return __awaiter(this, void 0, void 0, function* () {
-            if (!Array.isArray(prompts)) {
-                throw new Error("Argument 'prompts' is expected to be a string[]");
+        if (!Array.isArray(prompts)) {
+            throw new Error("Argument 'prompts' is expected to be a string[]");
+        }
+        if (this.cache === true && cache === null) {
+            throw new Error("Requested cache, but no cache found");
+        }
+        if (cache === null || this.cache === false) {
+            return this._generateUncached(prompts, stop);
+        }
+        const params = this.serialize();
+        params.stop = stop;
+        const llmStringKey = `${Object.entries(params).sort()}`;
+        const missingPromptIndices = [];
+        const generations = prompts.map((prompt, index) => {
+            const result = cache.lookup(prompt, llmStringKey);
+            if (!result) {
+                missingPromptIndices.push(index);
             }
-            if (this.cache === true && cache === null) {
-                throw new Error("Requested cache, but no cache found");
-            }
-            if (cache === null || this.cache === false) {
-                return this._generateUncached(prompts, stop);
-            }
-            const params = this.serialize();
-            params.stop = stop;
-            const llmStringKey = `${Object.entries(params).sort()}`;
-            const missingPromptIndices = [];
-            const generations = prompts.map((prompt, index) => {
-                const result = cache.lookup(prompt, llmStringKey);
-                if (!result) {
-                    missingPromptIndices.push(index);
-                }
-                return result;
+            return result;
+        });
+        let llmOutput = {};
+        if (missingPromptIndices.length > 0) {
+            const results = await this._generateUncached(missingPromptIndices.map((i) => prompts[i]), stop);
+            results.generations.forEach((generation, index) => {
+                const promptIndex = missingPromptIndices[index];
+                generations[promptIndex] = generation;
+                cache.update(prompts[promptIndex], llmStringKey, generation);
             });
-            let llmOutput = {};
-            if (missingPromptIndices.length > 0) {
-                const results = yield this._generateUncached(missingPromptIndices.map((i) => prompts[i]), stop);
-                results.generations.forEach((generation, index) => {
-                    const promptIndex = missingPromptIndices[index];
-                    generations[promptIndex] = generation;
-                    cache.update(prompts[promptIndex], llmStringKey, generation);
-                });
-                llmOutput = (_a = results.llmOutput) !== null && _a !== void 0 ? _a : {};
-            }
-            return { generations, llmOutput };
-        });
+            llmOutput = (_a = results.llmOutput) !== null && _a !== void 0 ? _a : {};
+        }
+        return { generations, llmOutput };
     }
-    call(prompt, stop) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const { generations } = yield this.generate([prompt], stop);
-            return generations[0][0].text;
-        });
+    /**
+     * Convenience wrapper for {@link generate} that takes in a single string prompt and returns a single string output.
+     */
+    async call(prompt, stop) {
+        const { generations } = await this.generate([prompt], stop);
+        return generations[0][0].text;
     }
+    /**
+     * Get the identifying parameters of the LLM.
+     */
     // eslint-disable-next-line @typescript-eslint/no-explicit-any
@@ -129,30 +122,42 @@ _identifyingParams() {
     }
+    /**
+     * Return a json-like object representing this LLM.
+     */
     serialize() {
-        return Object.assign(Object.assign({}, this._identifyingParams()), { _type: this._llmType() });
+        return {
+            ...this._identifyingParams(),
+            _type: this._llmType(),
+        };
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const { _type } = data, rest = __rest(data, ["_type"]);
-            const Cls = {
-                openai: OpenAI,
-            }[_type];
-            if (Cls === undefined) {
-                throw new Error(`Cannot load  LLM with type ${_type}`);
-            }
-            return new Cls(rest);
-        });
+    /**
+     * Load an LLM from a json-like object describing it.
+     */
+    static async deserialize(data) {
+        const { _type, ...rest } = data;
+        const Cls = {
+            openai: OpenAI,
+        }[_type];
+        if (Cls === undefined) {
+            throw new Error(`Cannot load  LLM with type ${_type}`);
+        }
+        return new Cls(rest);
     }
 }
+/**
+ * LLM class that provides a simpler interface to subclass than {@link BaseLLM}.
+ *
+ * Requires only implementing a simpler {@link _call} method instead of {@link _generate}.
+ *
+ * @augments BaseLLM
+ */
 export class LLM extends BaseLLM {
-    _generate(prompts, stop) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const generations = [];
-            for (let i = 0; i < prompts.length; i += 1) {
-                const text = yield this._call(prompts[i], stop);
-                generations.push([{ text }]);
-            }
-            return { generations };
-        });
+    async _generate(prompts, stop) {
+        const generations = [];
+        for (let i = 0; i < prompts.length; i += 1) {
+            const text = await this._call(prompts[i], stop);
+            generations.push([{ text }]);
+        }
+        return { generations };
     }
 }
 //# sourceMappingURL=base.js.map

dist/esm/llms/index.d.ts

@@ -11,9 +11,28 @@ export { BaseLLM, LLM, SerializedLLM } from "./base";
 };
+/**
+ * Output of a single generation.
+ */
 export type Generation = {
+    /**
+     * Generated text output
+     */
     text: string;
+    /**
+     * Raw generation info response from the provider.
+     * May include things like reason for finishing (e.g. in {@link OpenAI})
+     */
     generationInfo?: Record<string, any>;
 };
+/**
+ * Contains all relevant information returned by an LLM.
+ */
 export type LLMResult = {
+    /**
+     * List of the things generated. Each input could have multiple {@link Generation | generations}, hence this is a list of lists.
+     */
     generations: Generation[][];
+    /**
+     * Dictionary of arbitrary LLM-provider specific output.
+     */
     llmOutput?: Record<string, any>;
 };

dist/esm/llms/load.d.ts

 import { BaseLLM } from "./base";
-export declare const loadLLM: typeof BaseLLM.deserialize;
-export declare const loadLLMFromFile: (file: string) => Promise<BaseLLM>;
+/**
+ * Load an LLM from a local file.
+ *
+ * @example
+ * ```ts
+ * import { loadLLM } from "langchain/llms";
+ * const model = await loadLLM("/path/to/llm.json");
+ * ```
+ */
+export declare const loadLLM: (file: string) => Promise<BaseLLM>;

dist/esm/llms/load.js

 import { BaseLLM } from "./base";
 import { parseFileConfig } from "../util";
-export const loadLLM = BaseLLM.deserialize;
-export const loadLLMFromFile = (file) => loadLLM(parseFileConfig(file));
+/**
+ * Load an LLM from a local file.
+ *
+ * @example
+ * ```ts
+ * import { loadLLM } from "langchain/llms";
+ * const model = await loadLLM("/path/to/llm.json");
+ * ```
+ */
+export const loadLLM = (file) => BaseLLM.deserialize(parseFileConfig(file));
 //# sourceMappingURL=load.js.map

dist/esm/llms/openai.d.ts

 import type { CreateCompletionRequest } from "openai";
 import { BaseLLM, LLMResult, LLMCallbackManager } from ".";
 interface ModelParams {
+    /** Sampling temperature to use */
     temperature: number;
+    /**
+     * Maximum number of tokens to generate in the completion. -1 returns as many
+     * tokens as possible given the prompt and the model's maximum context size.
+     */
     maxTokens: number;
+    /** Total probability mass of tokens to consider at each step */
     topP: number;
+    /** Penalizes repeated tokens according to frequency */
     frequencyPenalty: number;
+    /** Penalizes repeated tokens */
     presencePenalty: number;
+    /** Number of completions to generate for each prompt */
     n: number;
+    /** Generates `bestOf` completions server side and returns the "best" */
     bestOf: number;
+    /** Dictionary used to adjust the probability of specific tokens being generated */
     logitBias?: Record<string, number>;
 }
+/**
+ * Input to OpenAI class.
+ * @augments ModelParams
+ */
+interface OpenAIInput extends ModelParams {
+    /** Model name to use */
+    modelName: string;
+    /** Holds any additional parameters that are valid to pass to {@link
+     * https://platform.openai.com/docs/api-reference/completions/create |
+     * `openai.createCompletion`} that are not explicitly specified on this class.
+     */
+    modelKwargs?: Kwargs;
+    /** Batch size to use when passing multiple documents to generate */
+    batchSize: number;
+    /** Maximum number of retries to make when generating */
+    maxRetries: number;
+    /** List of stop words to use when generating */
+    stop?: string[];
+}
 type Kwargs = Record<string, any>;
-export declare class OpenAI extends BaseLLM implements ModelParams {
+/**
+ * Wrapper around OpenAI large language models.
+ *
+ * To use you should have the `openai` package installed, with the
+ * `OPENAI_API_KEY` environment variable set.
+ *
+ * @remarks
+ * Any parameters that are valid to be passed to {@link
+ * https://platform.openai.com/docs/api-reference/completions/create |
+ * `openai.createCompletion`} can be passed through {@link modelKwargs}, even
+ * if not explicitly available on this class.
+ *
+ * @augments BaseLLM
+ * @augments OpenAIInput
+ */
+export declare class OpenAI extends BaseLLM implements OpenAIInput {
     temperature: number;
@@ -29,13 +74,14 @@ maxTokens: number;
     private client;
-    constructor(fields?: Partial<ModelParams> & {
+    constructor(fields?: Partial<OpenAIInput> & {
         callbackManager?: LLMCallbackManager;
         verbose?: boolean;
-        modelName?: string;
-        modelKwargs?: Kwargs;
         openAIApiKey?: string;
-        batchSize?: number;
-        maxRetries?: number;
-        stop?: string[];
     });
+    /**
+     * Get the parameters used to invoke the model
+     */
     invocationParams(): CreateCompletionRequest & Kwargs;
+    /**
+     * Get the identifyin parameters for the model
+     */
     identifyingParams(): {
@@ -60,3 +106,19 @@ model: string;
     };
+    /**
+     * Call out to OpenAI's endpoint with k unique prompts
+     *
+     * @param prompts - The prompts to pass into the model.
+     * @param [stop] - Optional list of stop words to use when generating.
+     *
+     * @returns The full LLM output.
+     *
+     * @example
+     * ```ts
+     * import { OpenAI } from "langchain/llms";
+     * const openai = new OpenAI();
+     * const response = await openai.generate(["Tell me a joke."]);
+     * ```
+     */
     _generate(prompts: string[], stop?: string[]): Promise<LLMResult>;
+    /** @ignore */
     completionWithRetry(request: CreateCompletionRequest): Promise<import("axios").AxiosResponse<import("openai").CreateCompletionResponse, any>>;
@@ -63,0 +125,0 @@ _llmType(): string;

dist/esm/llms/openai.js

@@ -1,11 +0,3 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { backOff } from "exponential-backoff";
+import { chunkArray } from "../util";
 import { BaseLLM } from ".";
@@ -15,3 +7,3 @@ let Configuration = null;
 try {
-    // eslint-disable-next-line global-require
+    // eslint-disable-next-line global-require,import/no-extraneous-dependencies
     ({ Configuration, OpenAIApi } = require("openai"));
@@ -22,9 +14,17 @@ }
 }
-const chunkArray = (arr, chunkSize) => arr.reduce((chunks, elem, index) => {
-    const chunkIndex = Math.floor(index / chunkSize);
-    const chunk = chunks[chunkIndex] || [];
-    // eslint-disable-next-line no-param-reassign
-    chunks[chunkIndex] = chunk.concat([elem]);
-    return chunks;
-}, []);
+/**
+ * Wrapper around OpenAI large language models.
+ *
+ * To use you should have the `openai` package installed, with the
+ * `OPENAI_API_KEY` environment variable set.
+ *
+ * @remarks
+ * Any parameters that are valid to be passed to {@link
+ * https://platform.openai.com/docs/api-reference/completions/create |
+ * `openai.createCompletion`} can be passed through {@link modelKwargs}, even
+ * if not explicitly available on this class.
+ *
+ * @augments BaseLLM
+ * @augments OpenAIInput
+ */
 export class OpenAI extends BaseLLM {
@@ -119,3 +119,3 @@ constructor(fields) {
         if (Configuration === null || OpenAIApi === null) {
-            throw new Error("Please install openai as a dependency with, e.g. `npm install -S openai`");
+            throw new Error("Please install openai as a dependency with, e.g. `npm i openai`");
         }
@@ -140,50 +140,88 @@ this.modelName = (_a = fields === null || fields === void 0 ? void 0 : fields.modelName) !== null && _a !== void 0 ? _a : this.modelName;
     }
+    /**
+     * Get the parameters used to invoke the model
+     */
     invocationParams() {
-        return Object.assign({ model: this.modelName, temperature: this.temperature, max_tokens: this.maxTokens, top_p: this.topP, frequency_penalty: this.frequencyPenalty, presence_penalty: this.presencePenalty, n: this.n, best_of: this.bestOf, logit_bias: this.logitBias, stop: this.stop }, this.modelKwargs);
+        return {
+            model: this.modelName,
+            temperature: this.temperature,
+            max_tokens: this.maxTokens,
+            top_p: this.topP,
+            frequency_penalty: this.frequencyPenalty,
+            presence_penalty: this.presencePenalty,
+            n: this.n,
+            best_of: this.bestOf,
+            logit_bias: this.logitBias,
+            stop: this.stop,
+            ...this.modelKwargs,
+        };
     }
+    /**
+     * Get the identifyin parameters for the model
+     */
     identifyingParams() {
-        return Object.assign({ model_name: this.modelName }, this.invocationParams());
+        return {
+            model_name: this.modelName,
+            ...this.invocationParams(),
+        };
     }
-    _generate(prompts, stop) {
+    /**
+     * Call out to OpenAI's endpoint with k unique prompts
+     *
+     * @param prompts - The prompts to pass into the model.
+     * @param [stop] - Optional list of stop words to use when generating.
+     *
+     * @returns The full LLM output.
+     *
+     * @example
+     * ```ts
+     * import { OpenAI } from "langchain/llms";
+     * const openai = new OpenAI();
+     * const response = await openai.generate(["Tell me a joke."]);
+     * ```
+     */
+    async _generate(prompts, stop) {
         var _a, _b, _c, _d;
-        return __awaiter(this, void 0, void 0, function* () {
-            const subPrompts = chunkArray(prompts, this.batchSize);
-            const choices = [];
-            const tokenUsage = {};
-            if (this.stop && stop) {
-                throw new Error("Stop found in input and default params");
+        const subPrompts = chunkArray(prompts, this.batchSize);
+        const choices = [];
+        const tokenUsage = {};
+        if (this.stop && stop) {
+            throw new Error("Stop found in input and default params");
+        }
+        const params = this.invocationParams();
+        params.stop = stop !== null && stop !== void 0 ? stop : params.stop;
+        for (let i = 0; i < subPrompts.length; i += 1) {
+            const { data } = await this.completionWithRetry({
+                ...params,
+                prompt: subPrompts[i],
+            });
+            choices.push(...data.choices);
+            const { completion_tokens: completionTokens, prompt_tokens: promptTokens, total_tokens: totalTokens, } = (_a = data.usage) !== null && _a !== void 0 ? _a : {};
+            if (completionTokens) {
+                tokenUsage.completionTokens =
+                    ((_b = tokenUsage.completionTokens) !== null && _b !== void 0 ? _b : 0) + completionTokens;
             }
-            const params = this.invocationParams();
-            params.stop = stop !== null && stop !== void 0 ? stop : params.stop;
-            for (let i = 0; i < subPrompts.length; i += 1) {
-                const { data } = yield this.completionWithRetry(Object.assign(Object.assign({}, params), { prompt: subPrompts[i] }));
-                choices.push(...data.choices);
-                const { completion_tokens: completionTokens, prompt_tokens: promptTokens, total_tokens: totalTokens, } = (_a = data.usage) !== null && _a !== void 0 ? _a : {};
-                if (completionTokens) {
-                    tokenUsage.completionTokens =
-                        ((_b = tokenUsage.completionTokens) !== null && _b !== void 0 ? _b : 0) + completionTokens;
-                }
-                if (promptTokens) {
-                    tokenUsage.promptTokens = ((_c = tokenUsage.promptTokens) !== null && _c !== void 0 ? _c : 0) + promptTokens;
-                }
-                if (totalTokens) {
-                    tokenUsage.totalTokens = ((_d = tokenUsage.totalTokens) !== null && _d !== void 0 ? _d : 0) + totalTokens;
-                }
+            if (promptTokens) {
+                tokenUsage.promptTokens = ((_c = tokenUsage.promptTokens) !== null && _c !== void 0 ? _c : 0) + promptTokens;
             }
-            const generations = chunkArray(choices, this.n).map((promptChoices) => promptChoices.map((choice) => {
-                var _a;
-                return ({
-                    text: (_a = choice.text) !== null && _a !== void 0 ? _a : "",
-                    generationInfo: {
-                        finishReason: choice.finish_reason,
-                        logprobs: choice.logprobs,
-                    },
-                });
-            }));
-            return {
-                generations,
-                llmOutput: { tokenUsage },
-            };
-        });
+            if (totalTokens) {
+                tokenUsage.totalTokens = ((_d = tokenUsage.totalTokens) !== null && _d !== void 0 ? _d : 0) + totalTokens;
+            }
+        }
+        const generations = chunkArray(choices, this.n).map((promptChoices) => promptChoices.map((choice) => {
+            var _a;
+            return ({
+                text: (_a = choice.text) !== null && _a !== void 0 ? _a : "",
+                generationInfo: {
+                    finishReason: choice.finish_reason,
+                    logprobs: choice.logprobs,
+                },
+            });
+        }));
+        return {
+            generations,
+            llmOutput: { tokenUsage },
+        };
     }
+    /** @ignore */
     completionWithRetry(request) {
@@ -190,0 +228,0 @@ const makeCompletionRequest = () => this.client.createCompletion(request);

dist/esm/llms/tests/openai.test.js

@@ -1,17 +0,8 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { test } from "@jest/globals";
 import { OpenAI } from "../openai";
-test("Test OpenAI", () => __awaiter(void 0, void 0, void 0, function* () {
+test("Test OpenAI", async () => {
     const model = new OpenAI({ maxTokens: 5 });
-    const res = yield model.call("Print hello world");
+    const res = await model.call("Print hello world");
     console.log({ res });
-}));
+});
 //# sourceMappingURL=openai.test.js.map

dist/esm/prompt/base.d.ts

@@ -6,6 +6,20 @@ import { BaseOutputParser } from "./parser";
 export type InputValues = Record<string, any>;
+/**
+ * Input common to all prompt templates.
+ */
 export interface BasePromptTemplateInput {
+    /**
+     * A list of variable names the prompt template expects
+     */
     inputVariables: string[];
+    /**
+     * How to parse the output of calling an LLM on this formatted prompt
+     */
     outputParser?: BaseOutputParser;
 }
+/**
+ * Base class for prompt templates. Exposes a format method that returns a
+ * string prompt given a set of input values.
+ * @augments BasePromptTemplateInput
+ */
 export declare abstract class BasePromptTemplate implements BasePromptTemplateInput {
@@ -15,7 +29,32 @@ inputVariables: string[];
     constructor(input: BasePromptTemplateInput);
+    /**
+     * Format the prompt given the input values.
+     *
+     * @param inputValues - A dictionary of arguments to be passed to the prompt template.
+     * @returns A formatted prompt string.
+     *
+     * @example
+     * ```ts
+     * prompt.format({ foo: "bar" });
+     * ```
+     */
     abstract format(values: InputValues): string;
+    /**
+     * Return the string type key uniquely identifying this class of prompt template.
+     */
     abstract _getPromptType(): string;
+    /**
+     * Return a json-like object representing this prompt template.
+     */
     abstract serialize(): SerializedBasePromptTemplate;
+    /**
+     * Load a prompt template from a json-like object describing it.
+     *
+     * @remarks
+     * Deserializing needs to be async because templates (e.g. {@link FewShotPromptTemplate}) can
+     * reference remote resources that we read asynchronously with a web
+     * request.
+     */
     static deserialize(data: SerializedBasePromptTemplate): Promise<BasePromptTemplate>;
 }
 export {};

dist/esm/prompt/base.js

@@ -1,12 +0,8 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { PromptTemplate, FewShotPromptTemplate } from "./index";
 const templateClasses = [PromptTemplate, FewShotPromptTemplate];
+/**
+ * Base class for prompt templates. Exposes a format method that returns a
+ * string prompt given a set of input values.
+ * @augments BasePromptTemplateInput
+ */
 export class BasePromptTemplate {
@@ -32,20 +28,23 @@ constructor(input) {
     }
-    // Deserializing needs to be async because templates (e.g. few_shot) can
-    // reference remote resources that we read asynchronously with a web
-    // request.
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            switch (data._type) {
-                case "prompt":
-                    return PromptTemplate.deserialize(data);
-                case undefined:
-                    return PromptTemplate.deserialize(Object.assign(Object.assign({}, data), { _type: "prompt" }));
-                case "few_shot":
-                    return FewShotPromptTemplate.deserialize(data);
-                default:
-                    throw new Error(`Invalid prompt type in config: ${data._type}`);
-            }
-        });
+    /**
+     * Load a prompt template from a json-like object describing it.
+     *
+     * @remarks
+     * Deserializing needs to be async because templates (e.g. {@link FewShotPromptTemplate}) can
+     * reference remote resources that we read asynchronously with a web
+     * request.
+     */
+    static async deserialize(data) {
+        switch (data._type) {
+            case "prompt":
+                return PromptTemplate.deserialize(data);
+            case undefined:
+                return PromptTemplate.deserialize({ ...data, _type: "prompt" });
+            case "few_shot":
+                return FewShotPromptTemplate.deserialize(data);
+            default:
+                throw new Error(`Invalid prompt type in config: ${data._type}`);
+        }
     }
 }
 //# sourceMappingURL=base.js.map

dist/esm/prompt/few_shot.d.ts

@@ -22,11 +22,46 @@ import { BasePromptTemplate, InputValues, BasePromptTemplateInput } from "./index";
 export interface FewShotPromptTemplateInput extends BasePromptTemplateInput {
+    /**
+     * Examples to format into the prompt. Exactly one of this or
+     * {@link exampleSelector} must be
+     * provided.
+     */
     examples?: Example[];
+    /**
+     * An {@link ExampleSelector} Examples to format into the prompt. Exactly one of this or
+     * {@link examples} must be
+     * provided.
+     */
+    exampleSelector?: ExampleSelector;
+    /**
+     * An {@link PromptTemplate} used to format a single example.
+     */
     examplePrompt: PromptTemplate;
-    exampleSelector?: ExampleSelector;
+    /**
+     * String separator used to join the prefix, the examples, and suffix.
+     */
     exampleSeparator: string;
+    /**
+     * A prompt template string to put before the examples.
+     *
+     * @defaultValue `""`
+     */
     prefix: string;
+    /**
+     * A prompt template string to put after the examples.
+     */
     suffix: string;
+    /**
+     * The format of the prompt template. Options are: 'f-string', 'jinja-2'
+     */
     templateFormat: TemplateFormat;
+    /**
+     * Whether or not to try validating the template on initialization.
+     */
     validateTemplate?: boolean;
 }
+/**
+ * Prompt template that contains few-shot examples.
+ * @augments BasePromptTemplate
+ * @augments FewShotPromptTemplateInput
+ */
 export declare class FewShotPromptTemplate extends BasePromptTemplate implements FewShotPromptTemplateInput {
@@ -33,0 +68,0 @@ examples?: InputValues[];

dist/esm/prompt/few_shot.js

@@ -1,10 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { BasePromptTemplate, } from "./index";
@@ -15,2 +6,7 @@ import { checkValidTemplate, renderTemplate } from "./template";
 import { BaseOutputParser } from "./parser";
+/**
+ * Prompt template that contains few-shot examples.
+ * @augments BasePromptTemplate
+ * @augments FewShotPromptTemplateInput
+ */
 export class FewShotPromptTemplate extends BasePromptTemplate {
@@ -113,26 +109,24 @@ constructor(input) {
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const serializedPrompt = resolveConfigFromFile("example_prompt", data);
-            const examplePrompt = yield PromptTemplate.deserialize(serializedPrompt);
-            let examples;
-            if (typeof data.examples === "string") {
-                examples = parseFileConfig(data.examples, [".json", ".yml", ".yaml"]);
-            }
-            else if (Array.isArray(data.examples)) {
-                examples = data.examples;
-            }
-            else {
-                throw new Error("Invalid examples format. Only list or string are supported.");
-            }
-            return new FewShotPromptTemplate({
-                inputVariables: data.input_variables,
-                outputParser: data.output_parser && BaseOutputParser.deserialize(data.output_parser),
-                examplePrompt,
-                examples,
-                exampleSeparator: data.example_separator,
-                prefix: resolveTemplateFromFile("prefix", data),
-                suffix: resolveTemplateFromFile("suffix", data),
-                templateFormat: data.template_format,
-            });
+    static async deserialize(data) {
+        const serializedPrompt = resolveConfigFromFile("example_prompt", data);
+        const examplePrompt = await PromptTemplate.deserialize(serializedPrompt);
+        let examples;
+        if (typeof data.examples === "string") {
+            examples = parseFileConfig(data.examples, [".json", ".yml", ".yaml"]);
+        }
+        else if (Array.isArray(data.examples)) {
+            examples = data.examples;
+        }
+        else {
+            throw new Error("Invalid examples format. Only list or string are supported.");
+        }
+        return new FewShotPromptTemplate({
+            inputVariables: data.input_variables,
+            outputParser: data.output_parser && BaseOutputParser.deserialize(data.output_parser),
+            examplePrompt,
+            examples,
+            exampleSeparator: data.example_separator,
+            prefix: resolveTemplateFromFile("prefix", data),
+            suffix: resolveTemplateFromFile("suffix", data),
+            templateFormat: data.template_format,
         });
@@ -139,0 +133,0 @@ }

dist/esm/prompt/index.d.ts

 export { BasePromptTemplate, BasePromptTemplateInput, SerializedBasePromptTemplate, InputValues, } from "./base";
 export { PromptTemplate, PromptTemplateInput, SerializedPromptTemplate, } from "./prompt";
 export { FewShotPromptTemplate, FewShotPromptTemplateInput, SerializedFewShotTemplate, } from "./few_shot";
+export { loadPrompt } from "./load";

dist/esm/prompt/index.js

 export { BasePromptTemplate, } from "./base";
 export { PromptTemplate, } from "./prompt";
 export { FewShotPromptTemplate, } from "./few_shot";
+export { loadPrompt } from "./load";
 //# sourceMappingURL=index.js.map

dist/esm/prompt/load.d.ts

 import { BasePromptTemplate } from ".";
+/**
+ * Load a prompt from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("lc://prompts/hello-world/prompt.yaml");
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("/path/to/prompt.json");
+ * ```
+ */
 export declare const loadPrompt: (uri: string) => Promise<BasePromptTemplate>;

dist/esm/prompt/load.js

@@ -1,16 +0,24 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { BasePromptTemplate } from ".";
 import { loadFromHub } from "../util/hub";
 import { parseFileConfig } from "../util";
-const loadPromptFromFile = (file) => __awaiter(void 0, void 0, void 0, function* () { return BasePromptTemplate.deserialize(parseFileConfig(file)); });
-export const loadPrompt = (uri) => __awaiter(void 0, void 0, void 0, function* () {
-    const hubResult = yield loadFromHub(uri, loadPromptFromFile, "prompts", new Set(["py", "json", "yaml"]));
+const loadPromptFromFile = async (file) => BasePromptTemplate.deserialize(parseFileConfig(file));
+/**
+ * Load a prompt from {@link https://github.com/hwchase17/langchain-hub | LangchainHub} or local filesystem.
+ *
+ * @example
+ * Loading from LangchainHub:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("lc://prompts/hello-world/prompt.yaml");
+ * ```
+ *
+ * @example
+ * Loading from local filesystem:
+ * ```ts
+ * import { loadPrompt } from "langchain/prompt";
+ * const prompt = await loadPrompt("/path/to/prompt.json");
+ * ```
+ */
+export const loadPrompt = async (uri) => {
+    const hubResult = await loadFromHub(uri, loadPromptFromFile, "prompts", new Set(["py", "json", "yaml"]));
     if (hubResult) {
@@ -20,3 +28,3 @@ return hubResult;
     return loadPromptFromFile(uri);
-});
+};
 //# sourceMappingURL=load.js.map

dist/esm/prompt/parser.d.ts

 export type SerializedOutputParser = SerializedRegexParser | SerializedCommaSeparatedListOutputParser;
+/**
+ * Class to parse the output of an LLM call.
+ */
 export declare abstract class BaseOutputParser {
+    /**
+     * Parse the output of an LLM call.
+     *
+     * @param text - LLM output to parse.
+     * @returns Parsed output.
+     */
     abstract parse(text: string): string | string[] | Record<string, string>;
+    /**
+     * Return the string type key uniquely identifying this class of parser
+     */
     _type(): string;
+    /**
+     * Return a json-like object representing this output parser.
+     */
     abstract serialize(): SerializedOutputParser;
+    /**
+     * Load an output parser from a json-like object describing the parser.
+     */
     static deserialize(data: SerializedOutputParser): BaseOutputParser;
 }
+/**
+ * Class to parse the output of an LLM call to a list.
+ * @augments BaseOutputParser
+ */
 export declare abstract class ListOutputParser extends BaseOutputParser {
@@ -14,2 +36,6 @@ abstract parse(text: string): string[];
 };
+/**
+ * Class to parse the output of an LLM call as a comma-separated list.
+ * @augments ListOutputParser
+ */
 export declare class CommaSeparatedListOutputParser extends ListOutputParser {
@@ -26,2 +52,6 @@ parse(text: string): string[];
 };
+/**
+ * Class to parse the output of an LLM call into a dictionary.
+ * @augments BaseOutputParser
+ */
 export declare class RegexParser extends BaseOutputParser {
@@ -28,0 +58,0 @@ regex: string | RegExp;

dist/esm/prompt/parser.js

@@ -0,5 +1,14 @@
+/**
+ * Class to parse the output of an LLM call.
+ */
 export class BaseOutputParser {
+    /**
+     * Return the string type key uniquely identifying this class of parser
+     */
     _type() {
         throw new Error("_type not implemented");
     }
+    /**
+     * Load an output parser from a json-like object describing the parser.
+     */
     static deserialize(data) {
@@ -15,4 +24,12 @@ switch (data._type) {
 }
+/**
+ * Class to parse the output of an LLM call to a list.
+ * @augments BaseOutputParser
+ */
 export class ListOutputParser extends BaseOutputParser {
 }
+/**
+ * Class to parse the output of an LLM call as a comma-separated list.
+ * @augments ListOutputParser
+ */
 export class CommaSeparatedListOutputParser extends ListOutputParser {
@@ -31,2 +48,6 @@ parse(text) {
 }
+/**
+ * Class to parse the output of an LLM call into a dictionary.
+ * @augments BaseOutputParser
+ */
 export class RegexParser extends BaseOutputParser {
@@ -33,0 +54,0 @@ constructor(regex, outputKeys, defaultOutputKey) {

dist/esm/prompt/prompt.d.ts

@@ -12,7 +12,39 @@ import { BasePromptTemplate, BasePromptTemplateInput, InputValues } from "./index";
 };
+/**
+ * Inputs to create a {@link PromptTemplate}
+ * @augments BasePromptTemplateInput
+ */
 export interface PromptTemplateInput extends BasePromptTemplateInput {
+    /**
+     * The propmt template
+     */
     template: string;
+    /**
+     * The format of the prompt template. Options are 'f-string', 'jinja-2'
+     *
+     * @defaultValue 'f-string'
+     */
     templateFormat?: TemplateFormat;
+    /**
+     * Whether or not to try validating the template on initialization
+     *
+     * @defaultValue `true`
+     */
     validateTemplate?: boolean;
 }
+/**
+ * Schema to represent a basic prompt for an LLM.
+ * @augments BasePromptTemplate
+ * @augments PromptTemplateInput
+ *
+ * @example
+ * ```ts
+ * import { PromptTemplate } from "@langchain/prompt";
+ *
+ * const prompt = new PromptTemplate({
+ *   inputVariables: ["foo"],
+ *   template: "Say {foo}",
+ * });
+ * ```
+ */
 export declare class PromptTemplate extends BasePromptTemplate implements PromptTemplateInput {
@@ -25,3 +57,19 @@ template: string;
     format(values: InputValues): string;
+    /**
+     * Take examples in list format with prefix and suffix to create a prompt.
+     *
+     * Intendend to be used a a way to dynamically create a prompt from examples.
+     *
+     * @param examples - List of examples to use in the prompt.
+     * @param suffix - String to go after the list of examples. Should generally set up the user's input.
+     * @param inputVariables - A list of variable names the final prompt template will expect
+     * @param exampleSeparator - The separator to use in between examples
+     * @param prefix - String that should go before any examples. Generally includes examples.
+     *
+     * @returns The final prompt template generated.
+     */
     static fromExamples(examples: string[], suffix: string, inputVariables: string[], exampleSeparator?: string, prefix?: string): PromptTemplate;
+    /**
+     * Load prompt template from a template f-string
+     */
     static fromTemplate(template: string): PromptTemplate;
@@ -28,0 +76,0 @@ serialize(): SerializedPromptTemplate;

dist/esm/prompt/prompt.js

@@ -1,10 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { BasePromptTemplate, } from "./index";
@@ -14,2 +5,17 @@ import { checkValidTemplate, renderTemplate, parseFString, } from "./template";
 import { BaseOutputParser } from "./parser";
+/**
+ * Schema to represent a basic prompt for an LLM.
+ * @augments BasePromptTemplate
+ * @augments PromptTemplateInput
+ *
+ * @example
+ * ```ts
+ * import { PromptTemplate } from "@langchain/prompt";
+ *
+ * const prompt = new PromptTemplate({
+ *   inputVariables: ["foo"],
+ *   template: "Say {foo}",
+ * });
+ * ```
+ */
 export class PromptTemplate extends BasePromptTemplate {
@@ -47,2 +53,15 @@ constructor(input) {
     }
+    /**
+     * Take examples in list format with prefix and suffix to create a prompt.
+     *
+     * Intendend to be used a a way to dynamically create a prompt from examples.
+     *
+     * @param examples - List of examples to use in the prompt.
+     * @param suffix - String to go after the list of examples. Should generally set up the user's input.
+     * @param inputVariables - A list of variable names the final prompt template will expect
+     * @param exampleSeparator - The separator to use in between examples
+     * @param prefix - String that should go before any examples. Generally includes examples.
+     *
+     * @returns The final prompt template generated.
+     */
     static fromExamples(examples, suffix, inputVariables, exampleSeparator = "\n\n", prefix = "") {
@@ -55,2 +74,5 @@ const template = [prefix, ...examples, suffix].join(exampleSeparator);
     }
+    /**
+     * Load prompt template from a template f-string
+     */
     static fromTemplate(template) {
@@ -78,14 +100,12 @@ const names = new Set();
     }
-    static deserialize(data) {
-        return __awaiter(this, void 0, void 0, function* () {
-            const res = new PromptTemplate({
-                inputVariables: data.input_variables,
-                outputParser: data.output_parser && BaseOutputParser.deserialize(data.output_parser),
-                template: resolveTemplateFromFile("template", data),
-                templateFormat: data.template_format,
-            });
-            return res;
+    static async deserialize(data) {
+        const res = new PromptTemplate({
+            inputVariables: data.input_variables,
+            outputParser: data.output_parser && BaseOutputParser.deserialize(data.output_parser),
+            template: resolveTemplateFromFile("template", data),
+            templateFormat: data.template_format,
         });
+        return res;
     }
 }
 //# sourceMappingURL=prompt.js.map

dist/esm/prompt/tests/load.test.js

@@ -1,10 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 import { expect, test } from "@jest/globals";
@@ -14,13 +5,13 @@ import path from "path";
 const PROMPTS_DIR = path.join(__dirname, "prompts");
-test("Load Hello World Prompt", () => __awaiter(void 0, void 0, void 0, function* () {
+test("Load Hello World Prompt", async () => {
     const helloWorld = path.join(PROMPTS_DIR, "hello_world.yaml");
-    const prompt = yield loadPrompt(helloWorld);
+    const prompt = await loadPrompt(helloWorld);
     expect(prompt._getPromptType()).toBe("prompt");
     expect(prompt.format({})).toBe("Say hello world.");
-}));
-test("Load hub prompt", () => __awaiter(void 0, void 0, void 0, function* () {
-    const prompt = yield loadPrompt("lc@abb92d8://prompts/hello-world/prompt.yaml");
+});
+test("Load hub prompt", async () => {
+    const prompt = await loadPrompt("lc@abb92d8://prompts/hello-world/prompt.yaml");
     expect(prompt._getPromptType()).toBe("prompt");
     expect(prompt.format({})).toBe("Say hello world.");
-}));
+});
 //# sourceMappingURL=load.test.js.map

dist/esm/util/hub.d.ts

@@ -1,1 +0,2 @@
-export declare const loadFromHub: <T>(uri: string, loader: (a: string) => T, validPrefix: string, validSuffixes: Set<string>) => Promise<T | undefined>;
+export type LoadValues = Record<string, any>;
+export declare const loadFromHub: <T>(uri: string, loader: (a: string, values: LoadValues) => T, validPrefix: string, validSuffixes: Set<string>, values?: LoadValues) => Promise<T | undefined>;

dist/esm/util/hub.js

@@ -1,10 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
 var _a, _b;
@@ -18,3 +9,3 @@ import path from "path";
 const URL_BASE = (_b = process.env.LANGCHAIN_HUB_URL_BASE) !== null && _b !== void 0 ? _b : "https://raw.githubusercontent.com/hwchase17/langchain-hub/";
-export const loadFromHub = (uri, loader, validPrefix, validSuffixes) => __awaiter(void 0, void 0, void 0, function* () {
+export const loadFromHub = async (uri, loader, validPrefix, validSuffixes, values = {}) => {
     const match = uri.match(HUB_PATH_REGEX);
@@ -34,12 +25,12 @@ if (!match) {
     const url = [URL_BASE, ref, remotePath].join("/");
-    const res = yield fetchWithTimeout(url, { timeout: 5000 });
+    const res = await fetchWithTimeout(url, { timeout: 5000 });
     if (res.status !== 200) {
         throw new Error(`Could not find file at ${url}`);
     }
-    const text = yield res.text();
+    const text = await res.text();
     const tmpdir = fs.mkdtempSync(path.join(os.tmpdir(), "langchain"));
     const file = path.join(tmpdir, path.basename(remotePath));
     fs.writeFileSync(file, text);
-    return loader(file);
-});
+    return loader(file, values);
+};
 //# sourceMappingURL=hub.js.map

dist/esm/util/index.d.ts

@@ -13,1 +13,2 @@ import { RequestInit } from "node-fetch";
 export declare const parseFileConfig: (file: string, supportedTypes?: string[]) => any;
+export declare const chunkArray: <T>(arr: T[], chunkSize: number) => T[][];

dist/esm/util/index.js

@@ -1,21 +0,1 @@
-var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
-    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
-    return new (P || (P = Promise))(function (resolve, reject) {
-        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
-        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
-        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
-        step((generator = generator.apply(thisArg, _arguments || [])).next());
-    });
-};
-var __rest = (this && this.__rest) || function (s, e) {
-    var t = {};
-    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
-        t[p] = s[p];
-    if (s != null && typeof Object.getOwnPropertySymbols === "function")
-        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
-            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
-                t[p[i]] = s[p[i]];
-        }
-    return t;
-};
 import path from "path";
@@ -25,11 +5,11 @@ import fetch from "node-fetch";
 import * as yaml from "yaml";
-export const fetchWithTimeout = (url, init) => __awaiter(void 0, void 0, void 0, function* () {
-    const { timeout } = init, rest = __rest(init, ["timeout"]);
+export const fetchWithTimeout = async (url, init) => {
+    const { timeout, ...rest } = init;
     const controller = new AbortController();
     const timeoutId = setTimeout(() => controller.abort(), timeout);
     // eslint-disable-next-line @typescript-eslint/no-explicit-any
-    const res = yield fetch(url, Object.assign(Object.assign({}, rest), { signal: controller.signal }));
+    const res = await fetch(url, { ...rest, signal: controller.signal });
     clearTimeout(timeoutId);
     return res;
-});
+};
 const loadFileContents = (contents, format) => {
@@ -75,2 +55,9 @@ switch (format) {
 };
+export const chunkArray = (arr, chunkSize) => arr.reduce((chunks, elem, index) => {
+    const chunkIndex = Math.floor(index / chunkSize);
+    const chunk = chunks[chunkIndex] || [];
+    // eslint-disable-next-line no-param-reassign
+    chunks[chunkIndex] = chunk.concat([elem]);
+    return chunks;
+}, []);
 //# sourceMappingURL=index.js.map

package.json

 {
   "name": "langchain",
-  "version": "0.0.4",
+  "version": "0.0.5",
   "description": "Typescript bindings for langchain",
@@ -11,37 +11,6 @@ "main": "./dist/cjs/index.js",
   ],
-  "exports": {
-    ".": {
-      "types": "./dist/cjs/index.d.ts",
-      "require": "./dist/cjs/index.js",
-      "import": "./dist/esm/index.js"
-    },
-    "./agents": {
-      "types": "./dist/cjs/agents/index.d.ts",
-      "require": "./dist/cjs/agents/index.js",
-      "import": "./dist/esm/agents/index.js"
-    },
-    "./tools": {
-      "types": "./dist/cjs/agents/tools/index.d.ts",
-      "require": "./dist/cjs/agents/tools/index.js",
-      "import": "./dist/esm/agents/tools/index.js"
-    },
-    "./prompt": {
-      "types": "./dist/cjs/prompt/index.d.ts",
-      "require": "./dist/cjs/prompt/index.js",
-      "import": "./dist/esm/prompt/index.js"
-    },
-    "./chains": {
-      "types": "./dist/cjs/chains/index.d.ts",
-      "require": "./dist/cjs/chains/index.js",
-      "import": "./dist/esm/chains/index.js"
-    },
-    "./llms": {
-      "types": "./dist/cjs/llms/index.d.ts",
-      "require": "./dist/cjs/llms/index.js",
-      "import": "./dist/esm/llms/index.js"
-    }
-  },
   "scripts": {
     "build": "tsc --declaration --outDir dist/esm --module esnext && tsc --declaration --outDir dist/cjs",
     "lint": "eslint .",
+    "doc": "typedoc",
     "lint:fix": "yarn lint --fix",
@@ -71,2 +40,3 @@ "precommit": "tsc --noEmit && lint-staged",
     "eslint-plugin-prettier": "^4.2.1",
+    "hnswlib-node": "^1.2.0",
     "husky": "^8.0.3",
@@ -77,4 +47,7 @@ "jest": "^29.4.2",
     "prettier": "^2.8.3",
-    "serpapi": "^1.1.0",
+    "serpapi": "^1.1.1",
     "ts-jest": "^29.0.5",
+    "ts-node": "^10.9.1",
+    "typedoc": "^0.23.25",
+    "typedoc-plugin-missing-exports": "^1.0.0",
     "typescript": "^4.9.5"
@@ -84,9 +57,6 @@ },
     "exponential-backoff": "^3.1.0",
+    "expr-eval": "^2.0.2",
     "node-fetch": "2",
     "yaml": "^2.2.1"
   },
-  "optionalDependencies": {
-    "openai": "^3.1.0",
-    "serpapi": "^1.1.0"
-  },
   "lint-staged": {
@@ -98,2 +68,59 @@ "**/*.{ts,tsx}": [
   },
+  "exports": {
+    ".": {
+      "types": "./dist/cjs/index.d.ts",
+      "require": "./dist/cjs/index.js",
+      "import": "./dist/esm/index.js"
+    },
+    "./agents": {
+      "types": "./dist/cjs/agents/index.d.ts",
+      "require": "./dist/cjs/agents/index.js",
+      "import": "./dist/esm/agents/index.js"
+    },
+    "./tools": {
+      "types": "./dist/cjs/agents/tools/index.d.ts",
+      "require": "./dist/cjs/agents/tools/index.js",
+      "import": "./dist/esm/agents/tools/index.js"
+    },
+    "./prompt": {
+      "types": "./dist/cjs/prompt/index.d.ts",
+      "require": "./dist/cjs/prompt/index.js",
+      "import": "./dist/esm/prompt/index.js"
+    },
+    "./chains": {
+      "types": "./dist/cjs/chains/index.d.ts",
+      "require": "./dist/cjs/chains/index.js",
+      "import": "./dist/esm/chains/index.js"
+    },
+    "./llms": {
+      "types": "./dist/cjs/llms/index.d.ts",
+      "require": "./dist/cjs/llms/index.js",
+      "import": "./dist/esm/llms/index.js"
+    },
+    "./embeddings": {
+      "types": "./dist/cjs/embeddings/index.d.ts",
+      "require": "./dist/cjs/embeddings/index.js",
+      "import": "./dist/esm/embeddings/index.js"
+    },
+    "./vectorstores": {
+      "types": "./dist/cjs/vectorstores/index.d.ts",
+      "require": "./dist/cjs/vectorstores/index.js",
+      "import": "./dist/esm/vectorstores/index.js"
+    },
+    "./text_splitter": {
+      "types": "./dist/cjs/text_splitter.d.ts",
+      "require": "./dist/cjs/text_splitter.js",
+      "import": "./dist/esm/text_splitter.js"
+    },
+    "./memory": {
+      "types": "./dist/cjs/memory/index.d.ts",
+      "require": "./dist/cjs/memory/index.js",
+      "import": "./dist/esm/memory/index.js"
+    },
+    "./document": {
+      "types": "./dist/cjs/document.d.ts",
+      "require": "./dist/cjs/document.js",
+      "import": "./dist/esm/document.js"
+    }
+  },
   "publishConfig": {
@@ -100,0 +127,0 @@ "access": "public"

New alerts

License Policy Violation

License

This package is not allowed per your license policy. Review the package's license to ensure compliance.

Found 1 instance in 1 package

Filesystem access

Supply chain risk

Accesses the file system, and could potentially read sensitive data.

Found 1 instance in 1 package

Fixed alerts

License Policy Violation

License

This package is not allowed per your license policy. Review the package's license to ensure compliance.

Found 1 instance in 1 package

New author

Supply chain risk

A new npm collaborator published a version of the package for the first time. New collaborators are usually benign additions to a project, but do indicate a change to the security surface area of a package.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

528716

increased by79.04%

Dependency count

4

decreased by-20%

Number of package files

391

increased by80.18%

Lines of code

8903

increased by90.85%

Number of medium supply chain risk alerts

1

decreased by-50%

Worsened metrics

Dev dependency count

26

increased by18.18%

Number of low supply chain risk alerts

19

increased by46.15%

Dependency changes

• + Addedexpr-eval@^2.0.2

• + Addedexpr-eval@2.0.2(transitive)

• - Removed@fastify/busboy@2.1.1(transitive)

• - Removedasynckit@0.4.0(transitive)

• - Removedaxios@0.26.1(transitive)

• - Removedcombined-stream@1.0.8(transitive)

• - Removeddelayed-stream@1.0.0(transitive)

• - Removedfollow-redirects@1.15.9(transitive)

• - Removedform-data@4.0.0(transitive)

• - Removedmime-db@1.52.0(transitive)

• - Removedmime-types@2.1.35(transitive)

• - Removedopenai@3.3.0(transitive)

• - Removedserpapi@1.1.1(transitive)

• - Removedundici@5.28.4(transitive)