Nc/llmchain functions (langchain-ai#1699)

* Refactor openai functions chains to use output parsers

* Lint

* Rename

* Add docs

docs/docs/modules/chains/openai_functions/index.mdx

@@ -0,0 +1,24 @@
+---
+hide_table_of_contents: true
+sidebar_position: 4
+---
+
+import CodeBlock from "@theme/CodeBlock";
+import Extraction from "@examples/chains/openai_functions_extraction.ts";
+import Tagging from "@examples/chains/openai_functions_tagging.ts";
+
+# OpenAI Functions Chains
+
+These chains are designed to be used with the [OpenAI Functions](https://platform.openai.com/docs/guides/gpt/function-calling) API.
+
+## Extraction
+
+This chain is designed to extract lists of objects from an input text and schema of desired info.
+
+<CodeBlock language="typescript">{Extraction}</CodeBlock>
+
+## Tagging
+
+This chain is designed to tag an input text according to properties defined in a schema.
+
+<CodeBlock language="typescript">{Tagging}</CodeBlock>

examples/src/chains/openai_functions_extraction.ts

@@ -0,0 +1,37 @@
+import { z } from "zod";
+import { ChatOpenAI } from "langchain/chat_models/openai";
+import { createExtractionChainFromZod } from "langchain/chains";
+
+const chain = createExtractionChainFromZod(
+  z.object({
+    "person-name": z.string().optional(),
+    "person-age": z.number().optional(),
+    "person-hair_color": z.string().optional(),
+    "dog-name": z.string().optional(),
+    "dog-breed": z.string().optional(),
+  }),
+  new ChatOpenAI({ modelName: "gpt-3.5-turbo-0613", temperature: 0 })
+);
+
+console.log(
+  await chain.run(`Alex is 5 feet tall. Claudia is 4 feet taller Alex and jumps higher than him. Claudia is a brunette and Alex is blonde.
+Alex's dog Frosty is a labrador and likes to play hide and seek.`)
+);
+/*
+[
+  {
+    'person-name': 'Alex',
+    'person-age': 0,
+    'person-hair_color': 'blonde',
+    'dog-name': 'Frosty',
+    'dog-breed': 'labrador'
+  },
+  {
+    'person-name': 'Claudia',
+    'person-age': 0,
+    'person-hair_color': 'brunette',
+    'dog-name': '',
+    'dog-breed': ''
+  }
+]
+*/

examples/src/chains/openai_functions_tagging.ts

@@ -0,0 +1,24 @@
+import { createTaggingChain } from "langchain/chains";
+import { ChatOpenAI } from "langchain/chat_models/openai";
+
+const chain = createTaggingChain(
+  {
+    type: "object",
+    properties: {
+      sentiment: { type: "string" },
+      tone: { type: "string" },
+      language: { type: "string" },
+    },
+    required: ["tone"],
+  },
+  new ChatOpenAI({ modelName: "gpt-4-0613", temperature: 0 })
+);
+
+console.log(
+  await chain.run(
+    `Estoy increiblemente contento de haberte conocido! Creo que seremos muy buenos amigos!`
+  )
+);
+/*
+{ tone: 'positive', language: 'Spanish' }
+*/

examples/src/index.ts

@@ -1,3 +1,4 @@
+import { awaitAllCallbacks } from "langchain/callbacks";
 import path from "path";
 import url from "url";
 
@@ -44,10 +45,11 @@ if (runExample) {
   const maybePromise = runExample(args);
 
   if (maybePromise instanceof Promise) {
-    maybePromise.catch((e) => {
-      console.error(`Example failed with:`);
-      console.error(e);
-      process.exit(1);
-    });
+    maybePromise
+      .catch((e) => {
+        console.error(`Example failed with:`);
+        console.error(e);
+      })
+      .finally(() => awaitAllCallbacks());
   }
 }

langchain/.gitignore

@@ -394,6 +394,9 @@ experimental/plan_and_execute.d.ts
 client.cjs
 client.js
 client.d.ts
+evaluation.cjs
+evaluation.js
+evaluation.d.ts
 index.cjs
 index.js
 index.d.ts

langchain/package.json

@@ -406,6 +406,9 @@
     "client.cjs",
     "client.js",
     "client.d.ts",
+    "evaluation.cjs",
+    "evaluation.js",
+    "evaluation.d.ts",
     "index.cjs",
     "index.js",
     "index.d.ts"
@@ -1426,6 +1429,11 @@
       "import": "./client.js",
       "require": "./client.cjs"
     },
+    "./evaluation": {
+      "types": "./evaluation.d.ts",
+      "import": "./evaluation.js",
+      "require": "./evaluation.cjs"
+    },
     "./package.json": "./package.json"
   }
 }

langchain/src/chains/index.ts

@@ -84,12 +84,6 @@ export {
 export { MultiPromptChain } from "./router/multi_prompt.js";
 export { MultiRetrievalQAChain } from "./router/multi_retrieval_qa.js";
 export { TransformChain, TransformChainFields } from "./transform.js";
-export {
-  OpenAIFunctionsChain,
-  OpenAIFunctionsChainFields,
-  parseToArguments,
-  parseToNamedArgument,
-} from "./openai_functions/index.js";
 export {
   createExtractionChain,
   createExtractionChainFromZod,

langchain/src/chains/llm_chain.ts

@@ -2,19 +2,27 @@ import { BaseChain, ChainInputs } from "./base.js";
 import { BasePromptTemplate } from "../prompts/base.js";
 import { BaseLanguageModel } from "../base_language/index.js";
 import { ChainValues, Generation, BasePromptValue } from "../schema/index.js";
-import { BaseOutputParser } from "../schema/output_parser.js";
+import {
+  BaseLLMOutputParser,
+  BaseOutputParser,
+} from "../schema/output_parser.js";
 import { SerializedLLMChain } from "./serde.js";
 import { CallbackManager } from "../callbacks/index.js";
 import { CallbackManagerForChainRun, Callbacks } from "../callbacks/manager.js";
+import { NoOpOutputParser } from "../output_parsers/noop.js";
 
-export interface LLMChainInput<T extends string | object = string>
-  extends ChainInputs {
+export interface LLMChainInput<
+  T extends string | object = string,
+  L extends BaseLanguageModel = BaseLanguageModel
+> extends ChainInputs {
   /** Prompt object to use */
   prompt: BasePromptTemplate;
   /** LLM Wrapper to use */
-  llm: BaseLanguageModel;
+  llm: L;
+  /** Kwargs to pass to LLM */
+  llmKwargs?: this["llm"]["CallOptions"];
   /** OutputParser to use */
-  outputParser?: BaseOutputParser<T>;
+  outputParser?: BaseLLMOutputParser<T>;
   /** Key to use for output, defaults to `text` */
   outputKey?: string;
 }
@@ -32,19 +40,24 @@ export interface LLMChainInput<T extends string | object = string>
  * const llm = new LLMChain({ llm: new OpenAI(), prompt });
  * ```
  */
-export class LLMChain<T extends string | object = string>
+export class LLMChain<
+    T extends string | object = string,
+    L extends BaseLanguageModel = BaseLanguageModel
+  >
   extends BaseChain
   implements LLMChainInput<T>
 {
   lc_serializable = true;
 
   prompt: BasePromptTemplate;
 
-  llm: BaseLanguageModel;
+  llm: L;
+
+  llmKwargs?: this["llm"]["CallOptions"];
 
   outputKey = "text";
 
-  outputParser?: BaseOutputParser<T>;
+  outputParser?: BaseLLMOutputParser<T>;
 
   get inputKeys() {
     return this.prompt.inputVariables;
@@ -54,14 +67,16 @@ export class LLMChain<T extends string | object = string>
     return [this.outputKey];
   }
 
-  constructor(fields: LLMChainInput<T>) {
+  constructor(fields: LLMChainInput<T, L>) {
     super(fields);
     this.prompt = fields.prompt;
     this.llm = fields.llm;
+    this.llmKwargs = fields.llmKwargs;
     this.outputKey = fields.outputKey ?? this.outputKey;
-    this.outputParser = fields.outputParser ?? this.outputParser;
+    this.outputParser =
+      fields.outputParser ?? (new NoOpOutputParser() as BaseOutputParser<T>);
     if (this.prompt.outputParser) {
-      if (this.outputParser) {
+      if (fields.outputParser) {
         throw new Error("Cannot set both outputParser and prompt.outputParser");
       }
       this.outputParser = this.prompt.outputParser as BaseOutputParser<T>;
@@ -85,16 +100,15 @@ export class LLMChain<T extends string | object = string>
     promptValue: BasePromptValue,
     runManager?: CallbackManagerForChainRun
   ): Promise<unknown> {
-    const completion = generations[0].text;
     let finalCompletion: unknown;
     if (this.outputParser) {
-      finalCompletion = await this.outputParser.parseWithPrompt(
-        completion,
+      finalCompletion = await this.outputParser.parseResultWithPrompt(
+        generations,
         promptValue,
         runManager?.getChild()
       );
     } else {
-      finalCompletion = completion;
+      finalCompletion = generations[0].text;
     }
     return finalCompletion;
   }
@@ -117,7 +131,9 @@ export class LLMChain<T extends string | object = string>
     runManager?: CallbackManagerForChainRun
   ): Promise<ChainValues> {
     const valuesForPrompt = { ...values };
-    const valuesForLLM: this["llm"]["CallOptions"] = {};
+    const valuesForLLM: this["llm"]["CallOptions"] = {
+      ...this.llmKwargs,
+    };
     for (const key of this.llm.callKeys) {
       if (key in values) {
         valuesForLLM[key as keyof this["llm"]["CallOptions"]] = values[key];

langchain/src/chains/openai_functions/extraction.ts

@@ -4,13 +4,11 @@ import { JsonSchema7ObjectType } from "zod-to-json-schema/src/parsers/object.js"
 
 import { ChatOpenAI } from "../../chat_models/openai.js";
 import { PromptTemplate } from "../../prompts/prompt.js";
-import { TransformChain } from "../transform.js";
-import { SimpleSequentialChain } from "../sequential_chain.js";
 import {
   FunctionParameters,
-  OpenAIFunctionsChain,
-  parseToNamedArgument,
-} from "./index.js";
+  JsonKeyOutputFunctionsParser,
+} from "../../output_parsers/openai_functions.js";
+import { LLMChain } from "../llm_chain.js";
 
 function getExtractionFunctions(schema: FunctionParameters) {
   return [
@@ -47,13 +45,14 @@ export function createExtractionChain(
 ) {
   const functions = getExtractionFunctions(schema);
   const prompt = PromptTemplate.fromTemplate(_EXTRACTION_TEMPLATE);
-  const chain = new OpenAIFunctionsChain({ llm, prompt, functions });
-  const parsing_chain = new TransformChain({
-    transform: parseToNamedArgument.bind(null, "info"),
-    inputVariables: ["input"],
-    outputVariables: ["output"],
+  const outputParser = new JsonKeyOutputFunctionsParser({ attrName: "info" });
+  return new LLMChain({
+    llm,
+    prompt,
+    llmKwargs: { functions },
+    outputParser,
+    tags: ["openai_functions", "extraction"],
   });
-  return new SimpleSequentialChain({ chains: [chain, parsing_chain] });
 }
 
 export function createExtractionChainFromZod(