@promptbook/fake-llm - npm Package Compare versions

Comparing version 0.72.0 to 0.73.0

esm/typings/src/commands/TEMPLATE/TemplateTypes.d.ts

@@ -15,2 +15,2 @@ import type { TupleToUnion } from 'type-fest';
  */
-export declare const TemplateTypes: readonly ["PROMPT_TEMPLATE", "SIMPLE_TEMPLATE", "SCRIPT_TEMPLATE", "DIALOG_TEMPLATE", "SAMPLE", "KNOWLEDGE", "INSTRUMENT", "ACTION"];
+export declare const TemplateTypes: readonly ["PROMPT_TEMPLATE", "SIMPLE_TEMPLATE", "SCRIPT_TEMPLATE", "DIALOG_TEMPLATE", "EXAMPLE", "KNOWLEDGE", "INSTRUMENT", "ACTION"];

esm/typings/src/config.d.ts

@@ -124,3 +124,3 @@ import type { CsvSettings } from './formats/csv/CsvSettings';
  */
-export declare const RESERVED_PARAMETER_NAMES: readonly ["content", "context", "knowledge", "samples", "modelName", "currentDate"];
+export declare const RESERVED_PARAMETER_NAMES: readonly ["content", "context", "knowledge", "examples", "modelName", "currentDate"];
 /**
@@ -127,0 +127,0 @@ * @@@

esm/typings/src/conversion/prettify/renderPipelineMermaidOptions.d.ts

@@ -25,7 +25,7 @@ import type { PipelineJson } from '../../types/PipelineJson/PipelineJson';
 /**
- * TODO: !!!!! FOREACH in mermaid graph
- * TODO: !!!!! Knowledge in mermaid graph
- * TODO: !!!!! Personas in mermaid graph
+ * TODO: [🧠] !! FOREACH in mermaid graph
+ * TODO: [🧠] !! Knowledge in mermaid graph
+ * TODO: [🧠] !! Personas in mermaid graph
  * TODO: Maybe use some Mermaid package instead of string templating
  * TODO: [🕌] When more than 2 functionalities, split into separate functions
  */

esm/typings/src/conversion/utils/stringifyPipelineJson.d.ts

@@ -12,3 +12,3 @@ import type { string_json } from '../../types/typeAliases';
 /**
- * TODO: [🐝] Not Working propperly @see https://promptbook.studio/samples/mixed-knowledge.ptbk.md
+ * TODO: [🐝] Not Working propperly @see https://promptbook.studio/examples/mixed-knowledge.ptbk.md
  * TODO: [🧠][0] Maybe rename to `stringifyPipelineJson`, `stringifyIndexedJson`,...
@@ -15,0 +15,0 @@ * TODO: [🧠] Maybe more elegant solution than replacing via regex

esm/typings/src/conversion/validation/_importPipeline.d.ts

@@ -10,3 +10,3 @@ import type { PipelineJson } from '../../types/PipelineJson/PipelineJson';
  *
- * @param path - The path to the file relative to samples/pipelines directory
+ * @param path - The path to the file relative to examples/pipelines directory
  * @private internal function of tests
@@ -13,0 +13,0 @@ */

esm/typings/src/conversion/validation/validatePipeline.d.ts

@@ -23,3 +23,3 @@ import type { PipelineJson } from '../../types/PipelineJson/PipelineJson';
 /**
- * TODO: !!!!! [🧞‍♀️] Do not allow joker + foreach
+ * TODO: !! [🧞‍♀️] Do not allow joker + foreach
  * TODO: [🧠] Work with promptbookVersion
@@ -36,3 +36,3 @@ * TODO: Use here some json-schema, Zod or something similar and change it to:
 /**
- * TODO: [🧳][main] !!!! Validate that all samples match expectations
+ * TODO: [🧳][main] !!!! Validate that all examples match expectations
  * TODO: [🧳][🐝][main] !!!! Validate that knowledge is valid (non-void)
@@ -39,0 +39,0 @@ * TODO: [🧳][main] !!!! Validate that persona can be used only with CHAT variant

esm/typings/src/formats/_common/FormatDefinition.d.ts

@@ -18,3 +18,3 @@ import type { string_mime_type } from '../../types/typeAliases';
      *
-     * @sample "JSON"
+     * @example "JSON"
      */
@@ -29,3 +29,3 @@ readonly formatName: string_name & string_SCREAMING_CASE;
      *
-     * @sample "application/json"
+     * @example "application/json"
      */
@@ -32,0 +32,0 @@ readonly mimeType?: string_mime_type;

esm/typings/src/formats/_common/FormatSubvalueDefinition.d.ts

@@ -14,3 +14,3 @@ import type { Promisable } from 'type-fest';
      *
-     * @sample "CELL"
+     * @example "CELL"
      */
@@ -17,0 +17,0 @@ readonly subvalueName: string_name & string_SCREAMING_CASE;

esm/typings/src/personas/preparePersona.d.ts

@@ -13,3 +13,3 @@ import type { ExecutionTools } from '../execution/ExecutionTools';
 /**
- * TODO: [🔃][main] !!!!! If the persona was prepared with different version or different set of models, prepare it once again
+ * TODO: [🔃][main] !! If the persona was prepared with different version or different set of models, prepare it once again
  * TODO: [🏢] !! Check validity of `modelName` in pipeline
@@ -16,0 +16,0 @@ * TODO: [🏢] !! Check validity of `systemMessage` in pipeline

esm/typings/src/prepare/isPipelinePrepared.d.ts

@@ -9,3 +9,3 @@ import type { PipelineJson } from '../types/PipelineJson/PipelineJson';
 /**
- * TODO: [🔃][main] !!!!! If the pipeline was prepared with different version or different set of models, prepare it once again
+ * TODO: [🔃][main] !! If the pipeline was prepared with different version or different set of models, prepare it once again
  * TODO: [🐠] Maybe base this on `makeValidator`
@@ -15,4 +15,4 @@ * TODO: [🧊] Pipeline can be partially prepared, this should return true ONLY if fully prepared
  *     - [🏍] ? Is context in each template
- *     - [♨] Are samples prepared
+ *     - [♨] Are examples prepared
  *     - [♨] Are templates prepared
  */

esm/typings/src/prepare/prepareTemplates.d.ts

@@ -27,3 +27,3 @@ import type { ExecutionTools } from '../execution/ExecutionTools';
  * TODO: [🧠] What is better name `prepareTemplate` or `prepareTemplateAndParameters`
- * TODO: [♨][main] !!! Prepare index the samples and maybe templates
+ * TODO: [♨][main] !!! Prepare index the examples and maybe templates
  * TODO: Write tests for `preparePipeline`
@@ -30,0 +30,0 @@ * TODO: [🏏] Leverage the batch API and build queues @see https://platform.openai.com/docs/guides/batch

esm/typings/src/scrapers/document-legacy/LegacyDocumentScraper.test.d.ts

 export {};
 /**
- * TODO: [📓] Maybe test all file in samples (not just 10-simple.doc)
+ * TODO: [📓] Maybe test all file in examples (not just 10-simple.doc)
  */

esm/typings/src/scrapers/document/DocumentScraper.test.d.ts

 export {};
 /**
- * TODO: [📓] Maybe test all file in samples (not just 10-simple.docx)
+ * TODO: [📓] Maybe test all file in examples (not just 10-simple.docx)
  */

esm/typings/src/scrapers/markdown/MarkdownScraper.test.d.ts

 export {};
 /**
- * TODO: [📓] Maybe test all file in samples (not just 10-simple.md)
+ * TODO: [📓] Maybe test all file in examples (not just 10-simple.md)
  */

esm/typings/src/types/PipelineJson/ParameterJson.d.ts

@@ -30,6 +30,6 @@ import type { string_markdown_text } from '../typeAliases';
     /**
-     * Sample values of the parameter
+     * Example values of the parameter
      * Note: This values won't be actually used as some default values, but they are just for better understanding of the parameter
      */
-    readonly sampleValues?: Array<string_parameter_value>;
+    readonly exampleValues?: Array<string_parameter_value>;
 };
@@ -36,0 +36,0 @@ /**

esm/typings/src/types/PipelineJson/PreparationJson.d.ts

@@ -21,3 +21,3 @@ import type { PromptResultUsage } from '../../execution/PromptResultUsage';
  * TODO: Maybe put here used `modelName`
- * TODO: [🍥] When using `date` it changes all samples .ptbk.json files each time so until some more elegant solution omit the time from prepared pipeline
+ * TODO: [🍥] When using `date` it changes all examples .ptbk.json files each time so until some more elegant solution omit the time from prepared pipeline
  */

package.json

 {
     "name": "@promptbook/fake-llm",
-    "version": "0.72.0",
+    "version": "0.73.0",
     "description": "Supercharge your use of large language models",
@@ -34,3 +34,4 @@ "private": false,
         "o1-preview",
-        "anthropic"
+        "anthropic",
+        "LLMOps"
     ],
@@ -56,3 +57,3 @@ "license": "CC-BY-4.0",
     "peerDependencies": {
-        "@promptbook/core": "0.72.0"
+        "@promptbook/core": "0.73.0"
     },
@@ -59,0 +60,0 @@ "dependencies": {

README.md

@@ -21,2 +21,4 @@ <!-- ⚠️ WARNING: This code has been generated so that any manual changes will be overwritten -->
 
+-   💙 Working on [the **Book** language v1](https://github.com/webgptorg/book)
+-   📚 Support of `.docx`, `.doc` and `.pdf` documents
 -   ✨ **Support of [OpenAI o1 model](https://openai.com/o1/)**
@@ -53,7 +55,5 @@
 
-
-
 If you have a simple, single prompt for ChatGPT, GPT-4, Anthropic Claude, Google Gemini, Llama 3, or whatever, it doesn't matter how you integrate it. Whether it's calling a REST API directly, using the SDK, hardcoding the prompt into the source code, or importing a text file, the process remains the same.
 
-But often you will struggle with the **limitations of LLMs**, such as **hallucinations, off-topic responses, poor quality output, language and prompt drift, word repetition repetition repetition repetition or misuse, lack of context, or just plain w𝒆𝐢rd responses**. When this happens, you generally have three options:
+But often you will struggle with the **limitations of LLMs**, such as **hallucinations, off-topic responses, poor quality output, language and prompt drift, word repetition repetition repetition repetition or misuse, lack of context, or just plain w𝒆𝐢rd resp0nses**. When this happens, you generally have three options:
 
@@ -66,245 +66,35 @@ 1. **Fine-tune** the model to your specifications or even train your own.
 
--   [**Separates concerns**](https://github.com/webgptorg/promptbook/discussions/32) between prompt-engineer and programmer, between code files and prompt files, and between prompts and their execution logic.
--   Establishes a [**common format `.ptbk.md`**](https://github.com/webgptorg/promptbook/discussions/85) that can be used to describe your prompt business logic without having to write code or deal with the technicalities of LLMs.
--   **Forget** about **low-level details** like choosing the right model, tokens, context size, temperature, top-k, top-p, or kernel sampling. **Just write your intent** and [**persona**](https://github.com/webgptorg/promptbook/discussions/22) who should be responsible for the task and let the library do the rest.
--   Has built-in **orchestration** of [pipeline](https://github.com/webgptorg/promptbook/discussions/64) execution and many tools to make the process easier, more reliable, and more efficient, such as caching, [compilation+preparation](https://github.com/webgptorg/promptbook/discussions/78), [just-in-time fine-tuning](https://github.com/webgptorg/promptbook/discussions/33), [expectation-aware generation](https://github.com/webgptorg/promptbook/discussions/37), [agent adversary expectations](https://github.com/webgptorg/promptbook/discussions/39), and more.
+-   [**Separates concerns**](https://github.com/webgptorg/promptbook/discussions/32) between prompt-engineer and programmer, between code files and prompt files, and between prompts and their execution logic. For this purpose, it introduces a new language called [the **💙 Book**](https://github.com/webgptorg/book).
+-   Book allows you to **focus on the business** logic without having to write code or deal with the technicalities of LLMs.
+-   **Forget** about **low-level details** like choosing the right model, tokens, context size, `temperature`, `top-k`, `top-p`, or kernel sampling. **Just write your intent** and [**persona**](https://github.com/webgptorg/promptbook/discussions/22) who should be responsible for the task and let the library do the rest.
+-   We have built-in **orchestration** of [pipeline](https://github.com/webgptorg/promptbook/discussions/64) execution and many tools to make the process easier, more reliable, and more efficient, such as caching, [compilation+preparation](https://github.com/webgptorg/promptbook/discussions/78), [just-in-time fine-tuning](https://github.com/webgptorg/promptbook/discussions/33), [expectation-aware generation](https://github.com/webgptorg/promptbook/discussions/37), [agent adversary expectations](https://github.com/webgptorg/promptbook/discussions/39), and more.
 -   Sometimes even the best prompts with the best framework like Promptbook `:)` can't avoid the problems. In this case, the library has built-in **[anomaly detection](https://github.com/webgptorg/promptbook/discussions/40) and logging** to help you find and fix the problems.
--   Promptbook has built in versioning. You can test multiple **A/B versions** of pipelines and see which one works best.
--   Promptbook is designed to do [**RAG** (Retrieval-Augmented Generation)](https://github.com/webgptorg/promptbook/discussions/41) and other advanced techniques. You can use **knowledge** to improve the quality of the output.
+-   Versioning is build in. You can test multiple **A/B versions** of pipelines and see which one works best.
+-   Promptbook is designed to use [**RAG** (Retrieval-Augmented Generation)](https://github.com/webgptorg/promptbook/discussions/41) and other advanced techniques to bring the context of your business to generic LLM. You can use **knowledge** to improve the quality of the output.
 
 
 
-## 🧔 Pipeline _(for prompt-engeneers)_
+## 💙 Book language _(for prompt-engineer)_
 
-**P**romp**t** **b**oo**k** markdown file (or `.ptbk.md` file) is document that describes a **pipeline** - a series of prompts that are chained together to form somewhat reciepe for transforming natural language input.
+Promptbook [pipelines](https://github.com/webgptorg/promptbook/discussions/64) are written in markdown-like language called [Book](https://github.com/webgptorg/book). It is designed to be understandable by non-programmers and non-technical people.
 
--   Multiple pipelines forms a **collection** which will handle core **know-how of your LLM application**.
--   Theese pipelines are designed such as they **can be written by non-programmers**.
 
 
+```markdown
+# 🌟 My first Book
 
-### Sample:
+-   PERSONA Jane, marketing specialist with prior experience in writing articles about technology and artificial intelligence
+-   KNOWLEDGE https://ptbk.io
+-   KNOWLEDGE ./promptbook.pdf
+-   EXPECT MIN 1 Sentence
+-   EXPECT MAX 1 Paragraph
 
-File `write-website-content.ptbk.md`:
+> Write an article about the future of artificial intelligence in the next 10 years and how metalanguages will change the way AI is used in the world.
+> Look specifically at the impact of Promptbook on the AI industry.
 
-
-
-
-
-> # 🌍 Create website content
->
-> Instructions for creating web page content.
->
-> -   PIPELINE URL https://promptbook.studio/webgpt/write-website-content.ptbk.md
-> -   INPUT  PARAM `{rawTitle}` Automatically suggested a site name or empty text
-> -   INPUT  PARAM `{rawAssigment}` Automatically generated site entry from image recognition
-> -   OUTPUT PARAM `{websiteContent}` Web content
-> -   OUTPUT PARAM `{keywords}` Keywords
->
-> ## 👤 Specifying the assigment
->
-> What is your web about?
->
-> -   DIALOG TEMPLATE
->
-> ```
-> {rawAssigment}
-> ```
->
-> `-> {assigment}` Website assignment and specification
->
-> ## ✨ Improving the title
->
-> -   PERSONA Jane, Copywriter and Marketing Specialist.
->
-> ```
-> As an experienced marketing specialist, you have been entrusted with improving the name of your client's business.
->
-> A suggested name from a client:
-> "{rawTitle}"
->
-> Assignment from customer:
->
-> > {assigment}
->
-> ## Instructions:
->
-> -   Write only one name suggestion
-> -   The name will be used on the website, business cards, visuals, etc.
-> ```
->
-> `-> {enhancedTitle}` Enhanced title
->
-> ## 👤 Website title approval
->
-> Is the title for your website okay?
->
-> -   DIALOG TEMPLATE
->
-> ```
-> {enhancedTitle}
-> ```
->
-> `-> {title}` Title for the website
->
-> ## 🐰 Cunning subtitle
->
-> -   PERSONA Josh, a copywriter, tasked with creating a claim for the website.
->
-> ```
-> As an experienced copywriter, you have been entrusted with creating a claim for the "{title}" web page.
->
-> A website assignment from a customer:
->
-> > {assigment}
->
-> ## Instructions:
->
-> -   Write only one name suggestion
-> -   Claim will be used on website, business cards, visuals, etc.
-> -   Claim should be punchy, funny, original
-> ```
->
-> `-> {claim}` Claim for the web
->
-> ## 🚦 Keyword analysis
->
-> -   PERSONA Paul, extremely creative SEO specialist.
->
-> ```
-> As an experienced SEO specialist, you have been entrusted with creating keywords for the website "{title}".
->
-> Website assignment from the customer:
->
-> > {assigment}
->
-> ## Instructions:
->
-> -   Write a list of keywords
-> -   Keywords are in basic form
->
-> ## Example:
->
-> -   Ice cream
-> -   Olomouc
-> -   Quality
-> -   Family
-> -   Tradition
-> -   Italy
-> -   Craft
->
-> ```
->
-> `-> {keywords}` Keywords
->
-> ## 🔗 Combine the beginning
->
-> -   SIMPLE TEMPLATE
->
-> ```
->
-> # {title}
->
-> > {claim}
->
-> ```
->
-> `-> {contentBeginning}` Beginning of web content
->
-> ## 🖋 Write the content
->
-> -   PERSONA Jane
->
-> ```
-> As an experienced copywriter and web designer, you have been entrusted with creating text for a new website {title}.
->
-> A website assignment from a customer:
->
-> > {assigment}
->
-> ## Instructions:
->
-> -   Text formatting is in Markdown
-> -   Be concise and to the point
-> -   Use keywords, but they should be naturally in the text
-> -   This is the complete content of the page, so don't forget all the important information and elements the page should contain
-> -   Use headings, bullets, text formatting
->
-> ## Keywords:
->
-> {keywords}
->
-> ## Web Content:
->
-> {contentBeginning}
-> ```
->
-> `-> {contentBody}` Middle of the web content
->
-> ## 🔗 Combine the content
->
-> -   SIMPLE TEMPLATE
->
-> ```markdown
-> {contentBeginning}
->
-> {contentBody}
-> ```
->
-> `-> {websiteContent}`
-
-
-
-Following is the scheme how the promptbook above is executed:
-
-```mermaid
-%% 🔮 Tip: Open this on GitHub or in the VSCode website to see the Mermaid graph visually
-
-flowchart LR
-  subgraph "🌍 Create website content"
-
-      direction TB
-
-      input((Input)):::input
-      templateSpecifyingTheAssigment(👤 Specifying the assigment)
-      input--"{rawAssigment}"-->templateSpecifyingTheAssigment
-      templateImprovingTheTitle(✨ Improving the title)
-      input--"{rawTitle}"-->templateImprovingTheTitle
-      templateSpecifyingTheAssigment--"{assigment}"-->templateImprovingTheTitle
-      templateWebsiteTitleApproval(👤 Website title approval)
-      templateImprovingTheTitle--"{enhancedTitle}"-->templateWebsiteTitleApproval
-      templateCunningSubtitle(🐰 Cunning subtitle)
-      templateWebsiteTitleApproval--"{title}"-->templateCunningSubtitle
-      templateSpecifyingTheAssigment--"{assigment}"-->templateCunningSubtitle
-      templateKeywordAnalysis(🚦 Keyword analysis)
-      templateWebsiteTitleApproval--"{title}"-->templateKeywordAnalysis
-      templateSpecifyingTheAssigment--"{assigment}"-->templateKeywordAnalysis
-      templateCombineTheBeginning(🔗 Combine the beginning)
-      templateWebsiteTitleApproval--"{title}"-->templateCombineTheBeginning
-      templateCunningSubtitle--"{claim}"-->templateCombineTheBeginning
-      templateWriteTheContent(🖋 Write the content)
-      templateWebsiteTitleApproval--"{title}"-->templateWriteTheContent
-      templateSpecifyingTheAssigment--"{assigment}"-->templateWriteTheContent
-      templateKeywordAnalysis--"{keywords}"-->templateWriteTheContent
-      templateCombineTheBeginning--"{contentBeginning}"-->templateWriteTheContent
-      templateCombineTheContent(🔗 Combine the content)
-      templateCombineTheBeginning--"{contentBeginning}"-->templateCombineTheContent
-      templateWriteTheContent--"{contentBody}"-->templateCombineTheContent
-
-      templateCombineTheContent--"{websiteContent}"-->output
-      output((Output)):::output
-
-      classDef input color: grey;
-      classDef output color: grey;
-
-  end;
+-> {article}
 ```
 
--   [More template samples](./samples/pipelines/)
--   [Read more about `.ptbk.md` file format here](https://github.com/webgptorg/promptbook/discussions/categories/concepts?discussions_q=is%3Aopen+label%3A.ptbk.md+category%3AConcepts)
+## 📦 Packages _(for developers)_
 
-_Note: We are using [postprocessing functions](#postprocessing-functions) like `unwrapResult` that can be used to postprocess the result._
-
-## 📦 Packages
-
 This library is divided into several packages, all are published from [single monorepo](https://github.com/webgptorg/promptbook).
@@ -350,4 +140,2 @@ You can install all of them at once:
 
-
-
 ### Core concepts
@@ -383,4 +171,4 @@
 
--   [Simple usage](./samples/usage/simple-script)
--   [Usage with client and remote server](./samples/usage/remote)
+-   [Simple usage](./examples/usage/simple-script)
+-   [Usage with client and remote server](./examples/usage/remote)
 
@@ -387,0 +175,0 @@ ## ➕➖ When to use Promptbook?

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Found 1 instance in 1 package

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774352

decreased by-0.67%

Number of lines in readme file

236

decreased by-47.32%

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