Use different import maps for core vs main langchain

langchain-core/src/load/index.ts

@@ -6,7 +6,7 @@ import {
   get_lc_unique_name,
 } from "./serializable.js";
 import { optionalImportEntrypoints as defaultOptionalImportEntrypoints } from "./import_constants.js";
-import * as defaultImportMap from "./import_map.js";
+import * as coreImportMap from "./import_map.js";
 import type { OptionalImportMap, SecretMap } from "./import_type.js";
 import { type SerializedFields, keyFromJson, mapKeys } from "./map_keys.js";
 import { getEnvironmentVariable } from "../utils/env.js";
@@ -98,10 +98,11 @@ async function reviver(
     const str = JSON.stringify(serialized);
     const [name, ...namespaceReverse] = serialized.id.slice().reverse();
     const namespace = namespaceReverse.reverse();
-    const finalImportMap = { ...defaultImportMap, ...importMap };
+    const importMaps = { langchain_core: coreImportMap, langchain: importMap };
 
     let module:
-      | (typeof finalImportMap)[keyof typeof finalImportMap]
+      | (typeof importMaps)["langchain_core"][keyof (typeof importMaps)["langchain_core"]]
+      | (typeof importMaps)["langchain"][keyof (typeof importMaps)["langchain"]]
       | OptionalImportMap[keyof OptionalImportMap]
       | null = null;
 
@@ -132,14 +133,12 @@ async function reviver(
         );
       }
     } else {
-      // Currently, we only support langchain imports.
-      if (
-        namespace[0] === "langchain" ||
-        namespace[0] === "langchain_core" ||
-        namespace[0] === "langchain_community" ||
-        namespace[0] === "langchain_anthropic" ||
-        namespace[0] === "langchain_openai"
-      ) {
+      let finalImportMap:
+        | (typeof importMaps)["langchain"]
+        | (typeof importMaps)["langchain_core"];
+      // Currently, we only support langchain and langchain_core imports.
+      if (namespace[0] === "langchain" || namespace[0] === "langchain_core") {
+        finalImportMap = importMaps[namespace[0]];
         namespace.shift();
       } else {
         throw new Error(`Invalid namespace: ${pathStr} -> ${str}`);

langchain-core/src/runnables/base.ts

@@ -1487,6 +1487,8 @@ export class RunnableLambda<RunInput, RunOutput> extends Runnable<
   }
 }
 
+export class RunnableParallel<RunInput> extends RunnableMap<RunInput> {}
+
 /**
  * A Runnable that can fallback to other Runnables if it fails.
  */

langchain-core/src/runnables/index.ts

@@ -10,6 +10,7 @@ export {
   RunnableRetry,
   RunnableSequence,
   RunnableMap,
+  RunnableParallel,
   RunnableLambda,
   RunnableWithFallbacks,
   _coerceToRunnable,

langchain/src/load/tests/cross_language.int.test.ts

@@ -3,7 +3,7 @@ import { fileURLToPath } from "node:url";
 import { readFileSync } from "node:fs";
 import * as path from "node:path";
 
-// import { load } from "../index.js";
+import { load } from "../index.js";
 
 const IMPORTANT_IMPORTS = JSON.parse(
   readFileSync(
@@ -15,24 +15,78 @@ const IMPORTANT_IMPORTS = JSON.parse(
   ).toString()
 );
 
+const CURRENT_KNOWN_FAILURES = [
+  "langchain/schema/agent/AgentAction",
+  "langchain/schema/agent/AgentFinish",
+  "langchain/schema/prompt_template/BasePromptTemplate",
+  "langchain/schema/agent/AgentActionMessageLog",
+  "langchain/schema/agent/OpenAIToolAgentAction",
+  "langchain/prompts/chat/BaseMessagePromptTemplate",
+  "langchain/schema/output/ChatGeneration",
+  "langchain/schema/output/Generation",
+  "langchain/schema/document/Document",
+  "langchain/schema/runnable/DynamicRunnable",
+  "langchain/schema/prompt/PromptValue",
+  "langchain/llms/openai/BaseOpenAI",
+  "langchain/llms/openai/AzureOpenAI",
+  "langchain/schema/prompt_template/BaseChatPromptTemplate",
+  "langchain/prompts/few_shot_with_templates/FewShotPromptWithTemplates",
+  "langchain/prompts/base/StringPromptTemplate",
+  "langchain/prompts/chat/BaseStringMessagePromptTemplate",
+  "langchain/prompts/chat/ChatPromptValue",
+  "langchain/prompts/chat/ChatPromptValueConcrete",
+  "langchain/schema/runnable/HubRunnable",
+  "langchain/schema/runnable/RunnableBindingBase",
+  "langchain/schema/runnable/OpenAIFunctionsRouter",
+  "langchain/schema/runnable/RunnableEachBase",
+  "langchain/schema/runnable/RunnableConfigurableAlternatives",
+  "langchain/schema/runnable/RunnableConfigurableFields",
+  "langchain_core/agents/AgentAction",
+  "langchain_core/agents/AgentFinish",
+  "langchain_core/agents/AgentActionMessageLog",
+  "langchain/agents/output_parsers/openai_tools/OpenAIToolAgentAction",
+  "langchain_core/outputs/chat_generation/ChatGeneration",
+  "langchain_core/outputs/generation/Generation",
+  "langchain_core/runnables/configurable/DynamicRunnable",
+  "langchain_core/prompt_values/PromptValue",
+  "langchain/llms/openai/BaseOpenAI",
+  "langchain/llms/openai/AzureOpenAI",
+  "langchain_core/prompts/few_shot_with_templates/FewShotPromptWithTemplates",
+  "langchain_core/prompts/string/StringPromptTemplate",
+  "langchain_core/prompts/chat/BaseStringMessagePromptTemplate",
+  "langchain_core/prompt_values/ChatPromptValueConcrete",
+  "langchain/runnables/hub/HubRunnable",
+  "langchain_core/runnables/base/RunnableBindingBase",
+  "langchain/runnables/openai_functions/OpenAIFunctionsRouter",
+  "langchain_core/runnables/base/RunnableEachBase",
+  "langchain_core/runnables/configurable/RunnableConfigurableAlternatives",
+  "langchain_core/runnables/configurable/RunnableConfigurableFields",
+];
+
+const CROSS_LANGUAGE_ENTRYPOINTS = Object.keys(IMPORTANT_IMPORTS)
+  .concat(Object.values(IMPORTANT_IMPORTS))
+  .filter((v) => !CURRENT_KNOWN_FAILURES.includes(v));
+
 describe("Test cross language serialization of important modules", () => {
   // https://github.com/langchain-ai/langchain/blob/master/libs/core/langchain_core/load/mapping.py
-  test.each(Object.keys(IMPORTANT_IMPORTS))(
+  test.each(CROSS_LANGUAGE_ENTRYPOINTS)(
     "Test matching serialization names for: %s",
-    async (_item) => {
-      // const idComponents = item.split("/");
-      // const mockItem = {
-      //   lc: 1,
-      //   type: "constructor",
-      //   id: idComponents,
-      //   kwargs: {}
-      // };
-      // try {
-      //   const result = await load(JSON.stringify(mockItem)) as any;
-      //   expect(result.constructor.name).toEqual(idComponents[idComponents.length - 1]);
-      // } catch (e: any) {
-      //   expect(e.message).not.toContain("Invalid identifer: $");
-      // }
+    async (item) => {
+      const idComponents = item.split("/");
+      const mockItem = {
+        lc: 1,
+        type: "constructor",
+        id: idComponents,
+        kwargs: {},
+      };
+      try {
+        const result = (await load(JSON.stringify(mockItem))) as any;
+        expect(result.constructor.name).toEqual(
+          idComponents[idComponents.length - 1]
+        );
+      } catch (e: any) {
+        expect(e.message).not.toContain("Invalid identifer: $");
+      }
     }
   );
 });

langchain/src/load/tests/load.int.test.ts

@@ -0,0 +1,14 @@
+import { test, expect } from "@jest/globals";
+import { RunnableSequence } from "@langchain/core/runnables";
+
+import { load } from "../index.js";
+
+test("Should load and invoke real-world serialized chain", async () => {
+  const serializedValue = `{"lc": 1, "type": "constructor", "id": ["langchain_core", "runnables", "RunnableSequence"], "kwargs": {"first": {"lc": 1, "type": "constructor", "id": ["langchain_core", "runnables", "RunnableParallel"], "kwargs": {"steps": {"equation_statement": {"lc": 1, "type": "constructor", "id": ["langchain_core", "runnables", "RunnablePassthrough"], "kwargs": {"func": null, "afunc": null, "input_type": null}}}}}, "middle": [{"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "chat", "ChatPromptTemplate"], "kwargs": {"input_variables": ["equation_statement"], "messages": [{"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "chat", "SystemMessagePromptTemplate"], "kwargs": {"prompt": {"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "prompt", "PromptTemplate"], "kwargs": {"input_variables": [], "template": "Write out the following equation using algebraic symbols then solve it. Use the format\\n\\nEQUATION:...\\nSOLUTION:...\\n\\n", "template_format": "f-string", "partial_variables": {}}}}}, {"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "chat", "HumanMessagePromptTemplate"], "kwargs": {"prompt": {"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "prompt", "PromptTemplate"], "kwargs": {"input_variables": ["equation_statement"], "template": "{equation_statement}", "template_format": "f-string", "partial_variables": {}}}}}]}}, {"lc": 1, "type": "constructor", "id": ["langchain", "chat_models", "openai", "ChatOpenAI"], "kwargs": {"temperature": 0.0, "openai_api_key": {"lc": 1, "type": "secret", "id": ["OPENAI_API_KEY"]}}}], "last": {"lc": 1, "type": "constructor", "id": ["langchain_core", "output_parsers", "string", "StrOutputParser"], "kwargs": {}}}}`;
+  const chain = await load<RunnableSequence>(serializedValue);
+  const result = await chain.invoke(
+    "x raised to the third plus seven equals 12"
+  );
+  console.log(result);
+  expect(typeof result).toBe("string");
+});

langchain/src/load/tests/load.test.ts

@@ -521,3 +521,20 @@ test("Should load traces even if the constructor name changes (minified environm
   console.log(JSON.stringify(llm2, null, 2));
   expect(JSON.stringify(llm2, null, 2)).toBe(str);
 });
+
+test("Should load a real-world serialized chain", async () => {
+  const serializedValue = `{"lc": 1, "type": "constructor", "id": ["langchain_core", "runnables", "RunnableSequence"], "kwargs": {"first": {"lc": 1, "type": "constructor", "id": ["langchain_core", "runnables", "RunnableParallel"], "kwargs": {"steps": {"equation_statement": {"lc": 1, "type": "constructor", "id": ["langchain_core", "runnables", "RunnablePassthrough"], "kwargs": {"func": null, "afunc": null, "input_type": null}}}}}, "middle": [{"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "chat", "ChatPromptTemplate"], "kwargs": {"input_variables": ["equation_statement"], "messages": [{"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "chat", "SystemMessagePromptTemplate"], "kwargs": {"prompt": {"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "prompt", "PromptTemplate"], "kwargs": {"input_variables": [], "template": "Write out the following equation using algebraic symbols then solve it. Use the format\\n\\nEQUATION:...\\nSOLUTION:...\\n\\n", "template_format": "f-string", "partial_variables": {}}}}}, {"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "chat", "HumanMessagePromptTemplate"], "kwargs": {"prompt": {"lc": 1, "type": "constructor", "id": ["langchain_core", "prompts", "prompt", "PromptTemplate"], "kwargs": {"input_variables": ["equation_statement"], "template": "{equation_statement}", "template_format": "f-string", "partial_variables": {}}}}}]}}, {"lc": 1, "type": "constructor", "id": ["langchain", "chat_models", "openai", "ChatOpenAI"], "kwargs": {"temperature": 0.0, "openai_api_key": {"lc": 1, "type": "secret", "id": ["OPENAI_API_KEY"]}}}], "last": {"lc": 1, "type": "constructor", "id": ["langchain_core", "output_parsers", "string", "StrOutputParser"], "kwargs": {}}}}`;
+  const chain = await load<RunnableSequence>(serializedValue, {
+    OPENAI_API_KEY: "openai-key",
+  });
+  // @ts-expect-error testing
+  expect(chain.first.constructor.lc_name()).toBe("RunnableMap");
+  // @ts-expect-error testing
+  expect(chain.middle.length).toBe(2);
+  // @ts-expect-error testing
+  expect(chain.middle[0].constructor.lc_name()).toBe(`ChatPromptTemplate`);
+  // @ts-expect-error testing
+  expect(chain.middle[1].constructor.lc_name()).toBe(`ChatOpenAI`);
+  // @ts-expect-error testing
+  expect(chain.last.constructor.lc_name()).toBe(`StrOutputParser`);
+});

langchain/src/schema/runnable/base.ts

@@ -10,6 +10,7 @@ export {
   RunnableRetry,
   RunnableSequence,
   RunnableMap,
+  RunnableParallel,
   RunnableLambda,
   RunnableWithFallbacks,
   _coerceToRunnable,