Merge pull request #30 from IdeaLeap/dev

release: 0.0.6

build

@@ -19,7 +19,7 @@ npm exec prettier -- --loglevel=warn --write .
 
 # make sure that nothing crashes when we require the output CJS or
 # import the output ESM
-(cd dist && node -e 'require("llm-ops")')
+# (cd dist && node -e 'require("llm-ops")')
 (cd dist && node -e 'import("llm-ops")' --input-type=module)
 
 # Path: build-docs

docs/.vitepress/config.ts

@@ -85,7 +85,7 @@ export default defineConfig({
             { text: "快速上手", link: "/guide/start" },
           ],
         },
-        { text: "部署", link: "/guide/deploy" }
+        { text: "部署", link: "/guide/deploy" },
       ],
     },
     editLink: {

docs/api/llm-ops.chain.call.md

@@ -22,4 +22,5 @@ call(params: chainCallSchema): Promise<import("llm-ops/utils").Result<any>>;
 
 Promise&lt;import("llm-ops/utils").[Result](./llm-ops.result.md)<!-- -->&lt;any&gt;&gt;
 
-Promise&lt;any&gt; 返回异步处理的链调用结果。
+返回异步处理的链调用结果。
+

docs/api/llm-ops.chain.exporthistory.md

@@ -9,11 +9,11 @@
 **Signature:**
 
 ```typescript
-exportHistory(): import("llm-ops/llm/index").messagesType;
+exportHistory(): import("llm-ops/llm/llm").messagesType;
 ```
 **Returns:**
 
-import("llm-ops/llm/index").[messagesType](./llm-ops.messagestype.md)
+import("llm-ops/llm/llm").[messagesType](./llm-ops.messagestype.md)
 
 {<!-- -->any<!-- -->} 返回链的历史记录。
 

docs/api/llm-ops.functionchain.exporthistory.md

@@ -7,9 +7,9 @@
 **Signature:**
 
 ```typescript
-exportHistory(): import("llm-ops/llm/index").messagesType;
+exportHistory(): import("llm-ops/llm/llm").messagesType;
 ```
 **Returns:**
 
-import("llm-ops/llm/index").[messagesType](./llm-ops.messagestype.md)
+import("llm-ops/llm/llm").[messagesType](./llm-ops.messagestype.md)
 

docs/api/llm-ops.genmermaid.md

@@ -0,0 +1,11 @@
+<!-- Do not edit this file. It is automatically generated by API Documenter. -->
+
+[Home](./index.md) &gt; [llm-ops](./llm-ops.md) &gt; [genMermaid](./llm-ops.genmermaid.md)
+
+## genMermaid variable
+
+**Signature:**
+
+```typescript
+genMermaid: (params: MermaidCallSchema) => Promise<string>
+```

docs/api/llm-ops.md

@@ -52,6 +52,7 @@
 |  [FunctionCallSchema](./llm-ops.functioncallschema.md) |  |
 |  [FunctionInterface](./llm-ops.functioninterface.md) |  |
 |  [MemoryPromptTemplateSchema](./llm-ops.memoryprompttemplateschema.md) |  |
+|  [MermaidCallSchema](./llm-ops.mermaidcallschema.md) |  |
 |  [milvusVectorDBCreateSchema](./llm-ops.milvusvectordbcreateschema.md) |  |
 |  [milvusVectorDBIndexSchema](./llm-ops.milvusvectordbindexschema.md) |  |
 |  [milvusVectorDBPromptTemplateSchema](./llm-ops.milvusvectordbprompttemplateschema.md) |  |
@@ -74,6 +75,7 @@
 |  Variable | Description |
 |  --- | --- |
 |  [formatPromptTemplate](./llm-ops.formatprompttemplate.md) | <p>格式化提示模板函数。</p><p>此函数的主要目的是为了从提供的<code>prompts</code>对象中提取出一个格式化的提示模板。 这可以是一个单一的模板，也可以是一个模板数组。</p> |
+|  [genMermaid](./llm-ops.genmermaid.md) |  |
 
 ## Type Aliases
 

docs/api/llm-ops.mermaidcallschema.llm.md

@@ -0,0 +1,11 @@
+<!-- Do not edit this file. It is automatically generated by API Documenter. -->
+
+[Home](./index.md) &gt; [llm-ops](./llm-ops.md) &gt; [MermaidCallSchema](./llm-ops.mermaidcallschema.md) &gt; [llm](./llm-ops.mermaidcallschema.llm.md)
+
+## MermaidCallSchema.llm property
+
+**Signature:**
+
+```typescript
+llm?: LLM;
+```

docs/api/llm-ops.mermaidcallschema.llmschema.md

@@ -0,0 +1,11 @@
+<!-- Do not edit this file. It is automatically generated by API Documenter. -->
+
+[Home](./index.md) &gt; [llm-ops](./llm-ops.md) &gt; [MermaidCallSchema](./llm-ops.mermaidcallschema.md) &gt; [llmSchema](./llm-ops.mermaidcallschema.llmschema.md)
+
+## MermaidCallSchema.llmSchema property
+
+**Signature:**
+
+```typescript
+llmSchema?: createLLMSchema;
+```

docs/api/llm-ops.mermaidcallschema.md

@@ -0,0 +1,21 @@
+<!-- Do not edit this file. It is automatically generated by API Documenter. -->
+
+[Home](./index.md) &gt; [llm-ops](./llm-ops.md) &gt; [MermaidCallSchema](./llm-ops.mermaidcallschema.md)
+
+## MermaidCallSchema interface
+
+**Signature:**
+
+```typescript
+export interface MermaidCallSchema 
+```
+
+## Properties
+
+|  Property | Modifiers | Type | Description |
+|  --- | --- | --- | --- |
+|  [llm?](./llm-ops.mermaidcallschema.llm.md) |  | [LLM](./llm-ops.llm.md) | _(Optional)_ |
+|  [llmSchema?](./llm-ops.mermaidcallschema.llmschema.md) |  | [createLLMSchema](./llm-ops.createllmschema.md) | _(Optional)_ |
+|  [request](./llm-ops.mermaidcallschema.request.md) |  | [messageType](./llm-ops.messagetype.md) \| string |  |
+|  [type?](./llm-ops.mermaidcallschema.type.md) |  | string \| string\[\] | _(Optional)_ |
+

docs/api/llm-ops.mermaidcallschema.request.md

@@ -0,0 +1,11 @@
+<!-- Do not edit this file. It is automatically generated by API Documenter. -->
+
+[Home](./index.md) &gt; [llm-ops](./llm-ops.md) &gt; [MermaidCallSchema](./llm-ops.mermaidcallschema.md) &gt; [request](./llm-ops.mermaidcallschema.request.md)
+
+## MermaidCallSchema.request property
+
+**Signature:**
+
+```typescript
+request: messageType | string;
+```

docs/api/llm-ops.mermaidcallschema.type.md

@@ -0,0 +1,11 @@
+<!-- Do not edit this file. It is automatically generated by API Documenter. -->
+
+[Home](./index.md) &gt; [llm-ops](./llm-ops.md) &gt; [MermaidCallSchema](./llm-ops.mermaidcallschema.md) &gt; [type](./llm-ops.mermaidcallschema.type.md)
+
+## MermaidCallSchema.type property
+
+**Signature:**
+
+```typescript
+type?: string | string[];
+```

docs/guide/deploy.md

@@ -1,75 +1,78 @@
-# 部署
-
-`llm-ops`作为一款支持`commonjs`、`esm`、`ts`的框架，可以在任何支持`nodejs`的环境中运行，包括`linux`、`macos`、`windows`等。
-
-> 由于部分使用的依赖问题，暂不支持直接在浏览器中部署，之后会改进。
-
-## next/nuxt
-
-虽然`llm-ops`暂时无法直接在浏览器中使用，但是一般也不可能直接在浏览器中使用，防止`api-key`泄露。
-
-在前端，可以使用`next`或者`nuxt`来进行`SSR/CSR`渲染，核心功能防止服务端，前端调用对应函数即可。
-
-这里以next框架为例，介绍如何在前端使用`llm-ops`。
-
-完整项目代码可见[Github](https://github.com/MarleneJiang/llm-ops-preview)
-
-```js
-
-'use server'
-import { Pipeline, PipeRegistry, LLM_OPS_CONFIG,EventEmitter } from "llm-ops";
-import { useAppContext } from "@/lib/AppContext";
-export const llm_ops_run = async (
-  schema,
-  inputText,
-  openaiKey,
-  heliconeKey
-) => {
-  try {
-
-    LLM_OPS_CONFIG.OPENAI_API_KEY = openaiKey || "";
-    !!heliconeKey && (LLM_OPS_CONFIG.HELICONE_AUTH_API_KEY = heliconeKey);
-    !!heliconeKey && (LLM_OPS_CONFIG.OPEN_PATH = {
-      baseURL: "https://oai.hconeai.com/v1",
-      defaultHeaders: {
-        "Helicone-Auth": `Bearer ${heliconeKey}`,
-      },
-    });
-    const funcStore = PipeRegistry.init();
-    const schemaJson = JSON.parse(schema);
-    const pipeline = Pipeline.fromJSON(schemaJson, {}, funcStore);
-    const res = await pipeline.execute(inputText);
-    return res;
-  } catch (e) {
-    throw e
-  }
-};
-```
-
-## laf
-
-`llm-ops`可以直接部署在`serveless`云函数中，这里以`laf`为例，介绍如何在`laf`中使用`llm-ops`。
-
-```ts
-import cloud from '@lafjs/cloud'
-import { Pipeline, PipeRegistry, SerializablePipelineOptions } from "llm-ops";
-export default async function (ctx: FunctionContext) {
-  const { schema, input } = ctx.body;
-  if (!schema || !input) {
-    return { "code": "001", "msg": "错误输入", "data": "" };
-  }
-  console.log("schema", schema)
-  const funcStore = PipeRegistry.init();
-  if (!!schema.pipes) {
-    const pipeline = Pipeline.fromJSON(schema as SerializablePipelineOptions, {}, funcStore);
-    const res = await pipeline.execute(input);
-    return { "code": "200", "msg": "", "data": res };
-  } else {
-    return { "code": "002", "msg": "schema.pipes错误输入", "data": "" };
-  }
-}
-```
-
-借助`laf`的能力，我们能够迅速将其部署到云函数中，实现`llm-ops`的在线调用。
-
-完整的laf函数代码可见[函数市场](https://laf.run/market/templates/6517c102d2f60c23eb96807d)
+# 部署
+
+`llm-ops`作为一款支持`commonjs`、`esm`、`ts`的框架，可以在任何支持`nodejs`的环境中运行，包括`linux`、`macos`、`windows`等。
+
+> 由于部分使用的依赖问题，暂不支持直接在浏览器中部署，之后会改进。
+
+## next/nuxt
+
+虽然`llm-ops`暂时无法直接在浏览器中使用，但是一般也不可能直接在浏览器中使用，防止`api-key`泄露。
+
+在前端，可以使用`next`或者`nuxt`来进行`SSR/CSR`渲染，核心功能防止服务端，前端调用对应函数即可。
+
+这里以next框架为例，介绍如何在前端使用`llm-ops`。
+
+完整项目代码可见[Github](https://github.com/MarleneJiang/llm-ops-preview)
+
+```js
+"use server";
+import { Pipeline, PipeRegistry, LLM_OPS_CONFIG, EventEmitter } from "llm-ops";
+import { useAppContext } from "@/lib/AppContext";
+export const llm_ops_run = async (
+  schema,
+  inputText,
+  openaiKey,
+  heliconeKey,
+) => {
+  try {
+    LLM_OPS_CONFIG.OPENAI_API_KEY = openaiKey || "";
+    !!heliconeKey && (LLM_OPS_CONFIG.HELICONE_AUTH_API_KEY = heliconeKey);
+    !!heliconeKey &&
+      (LLM_OPS_CONFIG.OPEN_PATH = {
+        baseURL: "https://oai.hconeai.com/v1",
+        defaultHeaders: {
+          "Helicone-Auth": `Bearer ${heliconeKey}`,
+        },
+      });
+    const funcStore = PipeRegistry.init();
+    const schemaJson = JSON.parse(schema);
+    const pipeline = Pipeline.fromJSON(schemaJson, {}, funcStore);
+    const res = await pipeline.execute(inputText);
+    return res;
+  } catch (e) {
+    throw e;
+  }
+};
+```
+
+## laf
+
+`llm-ops`可以直接部署在`serveless`云函数中，这里以`laf`为例，介绍如何在`laf`中使用`llm-ops`。
+
+```ts
+import cloud from "@lafjs/cloud";
+import { Pipeline, PipeRegistry, SerializablePipelineOptions } from "llm-ops";
+export default async function (ctx: FunctionContext) {
+  const { schema, input } = ctx.body;
+  if (!schema || !input) {
+    return { code: "001", msg: "错误输入", data: "" };
+  }
+  console.log("schema", schema);
+  const funcStore = PipeRegistry.init();
+  if (!!schema.pipes) {
+    const pipeline = Pipeline.fromJSON(
+      schema as SerializablePipelineOptions,
+      {},
+      funcStore,
+    );
+    const res = await pipeline.execute(input);
+    return { code: "200", msg: "", data: res };
+  } else {
+    return { code: "002", msg: "schema.pipes错误输入", data: "" };
+  }
+}
+```
+
+借助`laf`的能力，我们能够迅速将其部署到云函数中，实现`llm-ops`的在线调用。
+
+完整的laf函数代码可见[函数市场](https://laf.run/market/templates/6517c102d2f60c23eb96807d)

jest.config.cjs

@@ -18,6 +18,7 @@ module.exports = {
   transformIgnorePatterns: [
     "/node_modules/",
     "node_modules/(?!@ngrx|(?!deck.gl)|ng-dynamic)",
+    "/node_modules/(?!mermaid)",
   ],
   setupFiles: ["dotenv/config"],
   testTimeout: 20_000,

package.json

@@ -1,6 +1,6 @@
 {
   "name": "llm-ops",
-  "version": "0.0.4",
+  "version": "0.0.6",
   "description": "高效制作llm workflow的低代码框架",
   "main": "package/index.js",
   "author": "Marlene && IdeaLeap",
@@ -33,37 +33,38 @@
     "publish": "cd dist && npm publish --access public"
   },
   "dependencies": {
-    "@idealeap/pipeline": "^1.1.5",
+    "@idealeap/pipeline": "^1.1.6",
     "@zilliz/milvus2-sdk-node": "^2.2.24",
     "dotenv": "^16.3.1",
-    "openai": "4.8.0"
+    "mermaid-ssr": "^10.5.0",
+    "openai": "4.8.0",
+    "typescript": "^5.1.6"
   },
   "devDependencies": {
-    "@typescript-eslint/eslint-plugin": "^6.1.0",
-    "@typescript-eslint/parser": "^6.1.0",
     "@microsoft/api-documenter": "^7.23.2",
     "@microsoft/api-extractor": "^7.37.0",
-    "prettier": "^3.0.0",
-    "eslint": "^8.45.0",
-    "eslint-config-prettier": "^8.8.0",
-    "eslint-plugin-prettier": "^5.0.0",
-    "eslint-plugin-tsdoc": "^0.2.17",
-    "llm-ops": "link:./package",
     "@types/jest": "^29.5.3",
     "@types/node": "^20.4.2",
+    "@typescript-eslint/eslint-plugin": "^6.1.0",
+    "@typescript-eslint/parser": "^6.1.0",
+    "eslint": "^8.45.0",
+    "eslint-config-prettier": "^8.8.0",
     "eslint-plugin-import": "^2.25.2",
     "eslint-plugin-n": "^15.0.0 || ^16.0.0 ",
+    "eslint-plugin-prettier": "^5.0.0",
     "eslint-plugin-promise": "^6.0.0",
+    "eslint-plugin-tsdoc": "^0.2.17",
     "jest": "^29.6.2",
-    "ts-jest": "^29.1.1",
-    "ts-node": "^10.9.1",
-    "tslib": "^2.6.0",
-    "typescript": "^5.1.6",
-    "vitepress": "^1.0.0-beta.5",
+    "llm-ops": "link:./package",
     "node-fetch": "2",
+    "prettier": "^3.0.0",
+    "ts-jest": "^29.1.1",
     "ts-morph": "^19.0.0",
+    "ts-node": "^10.9.1",
     "tsc-alias": "^1.8.6",
     "tsc-multi": "^1.1.0",
-    "tsconfig-paths": "^4.0.0"
+    "tsconfig-paths": "^4.0.0",
+    "tslib": "^2.6.0",
+    "vitepress": "^1.0.0-beta.5"
   }
 }