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@samchon/openapi
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@samchon/openapi - npm Package Compare versions
Comparing version 2.0.0-dev.20241120 to 2.0.0-dev.20241121
@@ -175,2 +175,3 @@ "use strict"; | ||
| minItems: undefined, | ||
| uniqueItems: undefined, | ||
| })), | ||
@@ -177,0 +178,0 @@ tags: props.options.constraint ? [] : getArrayTags(input), |
@@ -31,3 +31,3 @@ /** | ||
| * For reference, if you've composed the `IChatGptSchema` type with the | ||
| * {@link ILlmApplication.IChatGptOptions.escape} `true` option, only the recursived | ||
| * {@link ILlmApplication.IChatGptOptions.reference} `false` option, only the recursived | ||
| * named types would be archived into the {@link IChatGptSchema.IParameters.$defs}, | ||
@@ -34,0 +34,0 @@ * and the others would be ecaped from the {@link IChatGptSchema.IReference} type. |
@@ -19,8 +19,8 @@ /** | ||
| * | ||
| * Also, by the documents of Gemini, these additional properties are not | ||
| * supported, either. However, I can't sure that these additional properties | ||
| * Also, by the documents of Gemini, these constraint properties are not | ||
| * supported, either. However, I can't sure that these constraint properties | ||
| * are really not supported in the Geimni, because the Gemini seems like | ||
| * understanding them. Therefore, I've decided to keep them alive. | ||
| * | ||
| * - ex) additional properties | ||
| * - ex) constraint properties | ||
| * - {@link IGeminiSchema.IString.default} | ||
@@ -27,0 +27,0 @@ * - {@link IGeminiSchema.__IAttribute.example} |
| { | ||
| "name": "@samchon/openapi", | ||
| "version": "2.0.0-dev.20241120", | ||
| "version": "2.0.0-dev.20241121", | ||
| "description": "OpenAPI definitions and converters for 'typia' and 'nestia'.", | ||
@@ -5,0 +5,0 @@ "main": "./lib/index.js", |
157
README.md
@@ -0,1 +1,7 @@ | ||
| > ## Next version is coming. | ||
| > | ||
| > This is the `next` version README document. | ||
| > | ||
| > If you wanna see the latest version, go to the [`v1.0` branch](https://github.com/samchon/openapi/tree/v1.0). | ||
| # `@samchon/openapi` | ||
@@ -16,3 +22,3 @@ ```mermaid | ||
| [](https://github.com/samchon/openapi/blob/master/LICENSE) | ||
| [](https://www.npmjs.com/package/@samchon/openapi) | ||
| [](https://www.npmjs.com/package/@samchon/openapi/next.svg) | ||
| [](https://www.npmjs.com/package/@samchon/openapi) | ||
@@ -54,6 +60,6 @@ [](https://github.com/samchon/openapi/actions?query=workflow%3Abuild) | ||
| ```bash | ||
| npm install @samchon/openapi | ||
| npm install @samchon/openapi --tag next | ||
| ``` | ||
| Just install by `npm i @samchon/openapi` command. | ||
| Just install by `npm i @samchon/openapi --tag next` command. | ||
@@ -257,5 +263,5 @@ Here is an example code utilizing the `@samchon/openapi` for LLM function calling purpose. | ||
| HttpLlm, | ||
| IChatGptSchema, | ||
| IHttpLlmApplication, | ||
| IHttpLlmFunction, | ||
| ILlmSchemaV3_1, | ||
| OpenApi, | ||
@@ -283,4 +289,4 @@ OpenApiV3, | ||
| const document: OpenApi.IDocument = OpenApi.convert(swagger); | ||
| const application: IHttpLlmApplication<"3.1"> = HttpLlm.application({ | ||
| model: "3.1", | ||
| const application: IHttpLlmApplication<"chatgpt"> = HttpLlm.application({ | ||
| model: "chatgpt", | ||
| document, | ||
@@ -290,6 +296,7 @@ }); | ||
| // Let's imagine that LLM has selected a function to call | ||
| const func: IHttpLlmFunction<ILlmSchemaV3_1> | undefined = application.functions.find( | ||
| // (f) => f.name === "llm_selected_fuction_name" | ||
| (f) => f.path === "/bbs/{section}/articles/{id}" && f.method === "put", | ||
| ); | ||
| const func: IHttpLlmFunction<IChatGptSchema.IParameters> | undefined = | ||
| application.functions.find( | ||
| // (f) => f.name === "llm_selected_fuction_name" | ||
| (f) => f.path === "/bbs/{section}/articles/{id}" && f.method === "put", | ||
| ); | ||
| if (func === undefined) throw new Error("No matched function exists."); | ||
@@ -304,6 +311,10 @@ | ||
| function: func, | ||
| arguments: [ | ||
| "general", | ||
| v4(), | ||
| { | ||
| input: { | ||
| section: "general", | ||
| id: v4(), | ||
| query: { | ||
| language: "en-US", | ||
| format: "markdown", | ||
| }, | ||
| body: { | ||
| title: "Hello, world!", | ||
@@ -313,83 +324,4 @@ body: "Let's imagine that this argument is composed by LLM.", | ||
| }, | ||
| ], | ||
| }); | ||
| console.log("article", article); | ||
| }; | ||
| main().catch(console.error); | ||
| ``` | ||
| ### Keyword Parameter | ||
| Combine parameters into single object. | ||
| If you configure `keyword` option when composing the LLM (Large Language Model) function calling appliation, every parameters of OpenAPI operations would be combined to a single object type in the LLM funtion calling schema. This strategy is loved in many A.I. Chatbot developers, because LLM tends to a little professional in the single parameter function case. | ||
| Also, do not worry about the function call execution case. You don't need to resolve the keyworded parameter manually. The `HttpLlm.execute()` and `HttpLlm.propagate()` functions will resolve the keyworded parameter automatically by analyzing the `IHttpLlmApplication.options` property. | ||
| ```typescript | ||
| import { | ||
| HttpLlm, | ||
| IHttpLlmApplication, | ||
| IHttpLlmFunction, | ||
| ILlmSchemaV3_1, | ||
| OpenApi, | ||
| OpenApiV3, | ||
| OpenApiV3_1, | ||
| SwaggerV2, | ||
| } from "@samchon/openapi"; | ||
| import fs from "fs"; | ||
| import typia from "typia"; | ||
| import { v4 } from "uuid"; | ||
| const main = async (): Promise<void> => { | ||
| // read swagger document and validate it | ||
| const swagger: | ||
| | SwaggerV2.IDocument | ||
| | OpenApiV3.IDocument | ||
| | OpenApiV3_1.IDocument = JSON.parse( | ||
| await fs.promises.readFile("swagger.json", "utf8"), | ||
| ); | ||
| typia.assert(swagger); // recommended | ||
| // convert to emended OpenAPI document, | ||
| // and compose LLM function calling application | ||
| const document: OpenApi.IDocument = OpenApi.convert(swagger); | ||
| const application: IHttpLlmApplication<"3.1"> = HttpLlm.application({ | ||
| model: "3.1", | ||
| document, | ||
| options: { | ||
| keyword: true, | ||
| }, | ||
| }); | ||
| // Let's imagine that LLM has selected a function to call | ||
| const func: IHttpLlmFunction<ILlmSchemaV3_1> | undefined = application.functions.find( | ||
| // (f) => f.name === "llm_selected_fuction_name" | ||
| (f) => f.path === "/bbs/{section}/articles/{id}" && f.method === "put", | ||
| ); | ||
| if (func === undefined) throw new Error("No matched function exists."); | ||
| // actual execution is by yourself | ||
| const article = await HttpLlm.execute({ | ||
| connection: { | ||
| host: "http://localhost:3000", | ||
| }, | ||
| application, | ||
| function: func, | ||
| arguments: [ | ||
| // one single object with key-value paired | ||
| { | ||
| section: "general", | ||
| id: v4(), | ||
| query: { | ||
| language: "en-US", | ||
| format: "markdown", | ||
| }, | ||
| body: { | ||
| title: "Hello, world!", | ||
| body: "Let's imagine that this argument is composed by LLM.", | ||
| thumbnail: null, | ||
| }, | ||
| }, | ||
| ], | ||
| }); | ||
| console.log("article", article); | ||
@@ -412,6 +344,6 @@ }; | ||
| HttpLlm, | ||
| ChatGptTypeChecker, | ||
| IChatGptSchema, | ||
| IHttpLlmApplication, | ||
| IHttpLlmFunction, | ||
| ILlmSchemaV3_1, | ||
| LlmTypeCheckerV3_1, | ||
| OpenApi, | ||
@@ -439,4 +371,4 @@ OpenApiV3, | ||
| const document: OpenApi.IDocument = OpenApi.convert(swagger); | ||
| const application: IHttpLlmApplication<"3.1"> = HttpLlm.application({ | ||
| model: "3.1", | ||
| const application: IHttpLlmApplication<"chatgpt"> = HttpLlm.application({ | ||
| model: "chatgpt", | ||
| document, | ||
@@ -446,3 +378,3 @@ options: { | ||
| separate: (schema) => | ||
| LlmTypeCheckerV3_1.isString(schema) && schema.contentMediaType !== undefined, | ||
| ChatGptTypeChecker.isString(schema) && schema.contentMediaType !== undefined, | ||
| }, | ||
@@ -452,6 +384,7 @@ }); | ||
| // Let's imagine that LLM has selected a function to call | ||
| const func: IHttpLlmFunction<ILlmSchemaV3_1> | undefined = application.functions.find( | ||
| // (f) => f.name === "llm_selected_fuction_name" | ||
| (f) => f.path === "/bbs/articles/{id}" && f.method === "put", | ||
| ); | ||
| const func: IHttpLlmFunction<IChatGptSchema.IParameters> | undefined = | ||
| application.functions.find( | ||
| // (f) => f.name === "llm_selected_fuction_name" | ||
| (f) => f.path === "/bbs/articles/{id}" && f.method === "put", | ||
| ); | ||
| if (func === undefined) throw new Error("No matched function exists."); | ||
@@ -468,19 +401,21 @@ | ||
| function: func, | ||
| llm: [ | ||
| llm: { | ||
| // LLM composed parameter values | ||
| "general", | ||
| v4(), | ||
| { | ||
| section: "general", | ||
| id: v4(), | ||
| query: { | ||
| language: "en-US", | ||
| format: "markdown", | ||
| }, | ||
| { | ||
| body: { | ||
| title: "Hello, world!", | ||
| content: "Let's imagine that this argument is composed by LLM.", | ||
| }, | ||
| ], | ||
| human: [ | ||
| }, | ||
| human: { | ||
| // Human composed parameter values | ||
| { thumbnail: "https://example.com/thumbnail.jpg" }, | ||
| ], | ||
| body: { | ||
| thumbnail: "https://example.com/thumbnail.jpg", | ||
| }, | ||
| }, | ||
| }), | ||
@@ -487,0 +422,0 @@ }); |
@@ -153,2 +153,3 @@ import { OpenApi } from "../OpenApi"; | ||
| minItems: undefined, | ||
| uniqueItems: undefined, | ||
| }), | ||
@@ -155,0 +156,0 @@ }, |
@@ -31,3 +31,3 @@ /** | ||
| * For reference, if you've composed the `IChatGptSchema` type with the | ||
| * {@link ILlmApplication.IChatGptOptions.escape} `true` option, only the recursived | ||
| * {@link ILlmApplication.IChatGptOptions.reference} `false` option, only the recursived | ||
| * named types would be archived into the {@link IChatGptSchema.IParameters.$defs}, | ||
@@ -34,0 +34,0 @@ * and the others would be ecaped from the {@link IChatGptSchema.IReference} type. |
@@ -19,8 +19,8 @@ /** | ||
| * | ||
| * Also, by the documents of Gemini, these additional properties are not | ||
| * supported, either. However, I can't sure that these additional properties | ||
| * Also, by the documents of Gemini, these constraint properties are not | ||
| * supported, either. However, I can't sure that these constraint properties | ||
| * are really not supported in the Geimni, because the Gemini seems like | ||
| * understanding them. Therefore, I've decided to keep them alive. | ||
| * | ||
| * - ex) additional properties | ||
| * - ex) constraint properties | ||
| * - {@link IGeminiSchema.IString.default} | ||
@@ -27,0 +27,0 @@ * - {@link IGeminiSchema.__IAttribute.example} |
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Improved metrics
- Lines of code
- increased by0.01%
26384
Worsened metrics
- Total package byte prevSize
- decreased by-0.13%
1519115
- Number of lines in readme file
- decreased by-13.57%
414
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