urdu translation

i18n/ur/docusaurus-plugin-content-docs/current.json

@@ -0,0 +1,71 @@
+{
+  "sidebar.tutorialSidebar.category.😃 Basics": {
+    "message": "😃 بنیادی باتیں "
+  },
+  "sidebar.tutorialSidebar.category.😃 Basics.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.💼 Basic Applications": {
+    "message": "💼 بنیادی ایپلی کیشنز "
+  },
+  "sidebar.tutorialSidebar.category.🧙‍♂️ Intermediate": {
+    "message": "🧙‍♂️ انٹرمیڈیٹ "
+  },
+  "sidebar.tutorialSidebar.category.🧙‍♂️ Intermediate.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.🧪 Applied Prompting": {
+    "message": "🧪 اپلائیڈ پرامٹنگ "
+  },
+  "sidebar.tutorialSidebar.category.🧪 Applied Prompting.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.🚀 Advanced Applications": {
+    "message": "🚀 اعلی درجے کی ایپلی کیشنز "
+  },
+  "sidebar.tutorialSidebar.category.🚀 Advanced Applications.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.⚖️ Reliability": {
+    "message": "⚖️ بھروسہ"
+  },
+  "sidebar.tutorialSidebar.category.⚖️ Reliability.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.🖼️ Image Prompting": {
+    "message": "🖼️ امیج پرامپٹنگ "
+  },
+  "sidebar.tutorialSidebar.category.🖼️ Image Prompting.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.🔓 Prompt Hacking": {
+    "message": "🔓  پرامپٹ ہیکنگ"
+  },
+  "sidebar.tutorialSidebar.category.🔓 Prompt Hacking.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.🔨 Tooling": {
+    "message": "🔨 ٹولنگ"
+  },
+  "sidebar.tutorialSidebar.category.🔨 Tooling.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.Prompt Engineering IDEs": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.Prompt Engineering IDEs.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.💪 Prompt Tuning": {
+    "message": "💪 پرامپٹ ٹیوننگ"
+  },
+  "sidebar.tutorialSidebar.category.💪 Prompt Tuning.link.generated-index.description": {
+    "message": ""
+  },
+  "sidebar.tutorialSidebar.category.🎲 Miscellaneous": {
+    "message": "🎲 متفرق"
+  },
+  "sidebar.tutorialSidebar.category.🎲 Miscellaneous.link.generated-index.description": {
+    "message": ""
+  }
+}

i18n/ur/docusaurus-plugin-content-docs/current/additional.md

@@ -0,0 +1,59 @@
+---
+sidebar_position: 3000
+---
+
+# 🛸 اضافی وسائل
+
+## انٹرایکٹو ٹیوٹوریلز
+* [agents.blue](https://www.agents.blue/) - پرامپٹ انجینئرنگ پر ایک مفت، رہنمائی والا ٹیوٹوریل۔
+
+## حوالہ جات
+
+* [نیشن کے پرامپٹ لیک ہونے پر مضمون](https://lspace.swyx.io/p/reverse-prompt-eng)
+* [ایپلی کیشنز پر ایک زبردست مضمون](https://huyenchip.com/2023/04/11/llm-engineering.html)<br/>
+* [ایک لاجواب PE تعارفی ویڈیو](https://youtube.com/watch?v=dOxUroR57xs&feature=shares)<br/>
+* [ایک بہت ہی عمدہ، مختصر پرامپٹ انجینئرنگ گائیڈ](https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-openai-api)<br/>
+* [ایک زبردست پرامپٹ انجینئرنگ تعارف](https://humanloop.com/blog/prompt-engineering-101)<br/>
+* [پرامپٹ انجینئرنگ پیپرز کا ایک عمدہ مجموعہ](https://github.com/dair-ai/Prompt-Engineering-Guide)<br/>
+* [بہت سے پرامپٹ انجینئرنگ پیپرز](https://github.com/thunlp/PromptPapers)<br/>
+* [CMU کلاس آن پرامپٹ انجینئرنگ](https://youtu.be/5ef83Wljm-M)<br/>
+* [کوپائلٹ کیسے کام کرتا ہے](https://thakkarparth007.github.io/copilot-explorer/posts/copilot-internals.html)<br/>
+* [زپیئر کی طرف سے فوری تحریر کے لیے ایک ابتدائی رہنما](https://zapier.com/blog/gpt-3-prompt/)<br/>
+* [بہت اچھے A-Z پرامپٹ-انجینئرنگ وسائل کی فہرست](https://github.com/promptslab/Awesome-Prompt-Engineering)<br/>
+* [500 ChatGPT پرامپٹ ٹیمپلیٹس](https://www.notion.so/500-ChatGPT-Prompt-Templates-d9541e901b2b4e8f800e819bdc0256da)<br/>
+* [پرامپٹ بیس](https://promptbase.com/) <br/>
+* [پرامپٹ وائبس](https://www.promptvibes.com/) <br/>
+* [پرامپٹ ہیرو](https://prompthero.com/)
+* [مڈجرنی کمیونٹی شوکیس پرامپٹس کے ساتھ](https://www.midjourney.com/showcase/recent/)<br/>
+* [ڈیٹا سائنس پرامپٹس](https://github.com/travistangvh/ChatGPT-Data-Science-Prompts.git)
+* [مڈجرنی کے لیے تمام طرزیں اور حوالہ جات](https://github.com/willwulfken/MidJourney-Styles-and-Keywords-Reference)<br/>
+* [ایڈوانسڈ پرامپٹ انجینئرنگ](https://jamesbachini.com/advanced-midjourney-prompt-engineering/#midjourney-flags)
+* [عام لوگوں کا پرامپٹ](https://www.ordinarypeopleprompts.com/)
+
+### جی پی ٹی-3 پرامپٹ مثالیں/آئیڈیاز
+
+https://sharegpt.com <br/>
+https://www.learngpt.com <br/>
+https://chatgpt.getlaunchlist.com <br/>
+https://prompts.chat
+
+
+## حقائق
+
+GPT-3 *نہیں* تعییناتی ہے: https://twitter.com/BorisMPower/status/1608522707372740609
+
+## پیروی کرنے والے لوگ
+
+میں ان لوگوں سے اہم مواد حاصل کرتا ہوں۔
+
+[@chillzaza_](https://mobile.twitter.com/chillzaza_) پرامپٹ انجینئرنگ، ٹولز، ٹول بوٹ<br/>
+[@mathemagic1an](https://mobile.twitter.com/mathemagic1an) مختلف پرامپٹ، PE، GPT3 کی معلومات<br/>
+[@goodside](https://twitter.com/goodside/status/1588247865503010816) پرامپٹ انجیکشن، پی ای ٹولنگ<br/>
+[@hwchase17](https://twitter.com/hwchase17) langchain کا بنیادی دیو<br/>
+[@omarsar0](https://twitter.com/omarsar0) DAIR AI لیڈ
+
+ان اکاؤنٹس کو بھی چیک کریں جن کی میں پیروی کرتا ہوں: https://twitter.com/learnprompting/following
+
+## اس سے بھی زیادہ
+
+چیک کریں [اوپن ایشوز](https://github.com/trigaten/Learn_Prompting/issues) اور [PRs](https://github.com/trigaten/Learn_Prompting/pulls) :)

i18n/ur/docusaurus-plugin-content-docs/current/advanced_applications/_category_.json

@@ -0,0 +1,8 @@
+{
+  "label": "🚀 Advanced Applications",
+  "position": 20,
+  "link": {
+    "type": "generated-index",
+    "description": "Some very powerful, but more advanced applications of prompt engineering."
+  }
+}

i18n/ur/docusaurus-plugin-content-docs/current/advanced_applications/mrkl.md

@@ -0,0 +1,126 @@
+---
+sidebar_position: 2
+---
+
+# 🟡 LLMs Using Tools
+
+MRKL Systems(@karpas2022mrkl) (Modular Reasoning, Knowledge and Language, pronounced "miracle") 
+are a **neuro-symbolic architecture** that combine LLMs (neural computation) and external 
+tools like calculators (symbolic computation), to solve complex problems. 
+
+A MRKL system is composed of a set of modules (e.g. a calculator, weather API, database, etc.) and a router that decides how to 'route' incoming natural language queries to the appropriate module.
+
+A simple example of a MRKL system is a LLM that can 
+use a calculator app. This is a single module system, where the LLM is the router.
+When asked, `What is 100*100?`, the LLM can choose to
+extract the numbers from the prompt, and then tell the MRKL System to use a calculator 
+app to compute the result. This might look like the following:
+
+<pre>
+<p>What is 100*100?</p>
+
+<span className="bluegreen-highlight">CALCULATOR[100*100]</span>
+</pre>
+
+The MRKL system would see the word `CALCULATOR` and plug `100*100` into the calculator app.
+This simple idea can easily be expanded to various symbolic computing tools.
+
+Consider the following additional examples of applications: 
+
+- A chatbot that is able to respond to questions about a financial database by 
+extracting information to form a SQL query from a users' text.
+
+<pre>
+<p>What is the price of Apple stock right now?</p>
+
+<span className="bluegreen-highlight">The current price is DATABASE[SELECT price FROM stock WHERE company = "Apple" AND time = "now"].</span>
+</pre>
+
+- A chatbot that is able to respond to questions about the weather by extracting
+information from the prompt and using a weather API to retrieve the information.
+
+<pre>
+<p>What is the weather like in New York?</p>
+
+<span className="bluegreen-highlight">The weather is WEATHER_API[New York].</span>
+</pre>
+
+- Or even much more complex tasks that depend on multiple datasources, such as the
+following:
+
+
+import mrkl_task from '@site/docs/assets/advanced/mrkl_task.webp';
+import dataset from '@site/docs/assets/advanced/mrkl/dataset.webp';
+import load_dataset from '@site/docs/assets/advanced/mrkl/load_dataset.webp';
+import model from '@site/docs/assets/advanced/mrkl/model.webp';
+import extract from '@site/docs/assets/advanced/mrkl/extract.webp';
+import search from '@site/docs/assets/advanced/mrkl/search.webp';
+import final from '@site/docs/assets/advanced/mrkl/final.webp';
+
+<div style={{textAlign: 'center'}}>
+  <img src={mrkl_task} style={{width: "500px"}}/>
+</div>
+
+<div style={{textAlign: 'center'}}>
+Example MRKL System (AI21)
+</div>
+
+
+## An Example
+
+I have reproduced an example MRKL System from the original paper, using Dust.tt, 
+linked [here](https://dust.tt/w/ddebdfcdde/a/98bdd65cb7). 
+The system reads a math problem (e.g. `What is 20 times 5^6?`), extracts the numbers and the operations,
+and reformats them for a calculator app (e.g. `20*5^6`). It then sends the reformatted equation 
+to Google's calculator app, and returns the result. Note that the original paper performs prompt tuning on the router (the LLM), but I do not in this example. Let's walk through how this works:
+
+First, I made a simple dataset in the Dust `Datasets` tab.
+
+
+<div style={{textAlign: 'center'}}>
+  <LazyLoadImage src={dataset} style={{width: "750px"}} />
+</div>
+
+Then, I switched to the `Specification` tab and loaded the dataset using an `input` block.
+
+<div style={{textAlign: 'center'}}>
+  <LazyLoadImage src={load_dataset} style={{width: "750px"}} />
+</div>
+
+Next, I created a `llm` block that extracts the numbers and operations. Notice how
+in the prompt I told it we would be using Google's calculator. The model I use (GPT-3)
+likely has some knowledge of Google's calculator from pretraining.
+
+<div style={{textAlign: 'center'}}>
+  <LazyLoadImage src={model} style={{width: "750px"}} />
+</div>
+
+Then, I made a `code` block, which runs some simple javascript code to remove 
+spaces from the completion.
+
+<div style={{textAlign: 'center'}}>
+  <LazyLoadImage src={extract} style={{width: "750px"}} />
+</div>
+
+Finally, I made a `search` block that sends the reformatted equation to Google's calculator.
+
+<div style={{textAlign: 'center'}}>
+  <LazyLoadImage src={search} style={{width: "750px"}} />
+</div>
+
+Below we can see the final results, which are all correct!
+
+<div style={{textAlign: 'center'}}>
+  <LazyLoadImage src={final} style={{width: "750px"}} />
+</div>
+
+Feel free to clone and experiment with this playground [here](https://dust.tt/w/ddebdfcdde/a/98bdd65cb7).
+
+## Notes
+MRKL was developed by [AI21](https://www.ai21.com/) and originally used their 
+J-1 (Jurassic 1)(@lieberjurassic) LLM.
+
+## More
+
+See [this example](https://python.langchain.com/docs/modules/agents/how_to/mrkl) of a MRKL System
+built with LangChain.

i18n/ur/docusaurus-plugin-content-docs/current/advanced_applications/overview.md

@@ -0,0 +1,10 @@
+---
+sidebar_position: 1
+---
+
+# 🟢 Introduction
+
+We have seen a number of prompting/prompt engineering methods thus far. 
+Now we will cover some advanced applications of prompting that can solve
+complex reasoning tasks by performing searches for information via the internet,
+or other external sources.