Set version 0.1.0

Project.toml

@@ -1,7 +1,7 @@
 name = "PromptingTools"
 uuid = "670122d1-24a8-4d70-bfce-740807c42192"
 authors = ["J S @svilupp and contributors"]
-version = "0.1.0-DEV"
+version = "0.1.0"
 
 [deps]
 HTTP = "cd3eb016-35fb-5094-929b-558a96fad6f3"

README.md

@@ -91,11 +91,10 @@ Some features:
 ## Advanced Examples
 
 TODO:
-[ ] Add more practical examples (DataFrames!)
-[ ] Show mini tasks with structured extraction
-[ ] Add an example of how to build RAG in 50 lines
-
 
+[ ] Add more practical examples (DataFrames!)
+[ ] Add mini tasks with structured extraction
+[ ] Add an example of how to build a RAG app in 50 lines
 
 ### Advanced Prompts / Conversations
 
@@ -188,7 +187,7 @@ aiclassify(:IsStatementTrue; statement = "Is two plus three a vegetable on Mars?
 # unknown
 ```
 
-In the above example, we used a prompt template `:IsStatementTrue`, which automatically expands into the following system prompt: 
+In the above example, we used a prompt template `:IsStatementTrue`, which automatically expands into the following system prompt (and a separate user prompt): 
 
 > "You are an impartial AI judge evaluating whether the provided statement is \"true\" or \"false\". Answer \"unknown\" if you cannot decide."
 
@@ -200,6 +199,8 @@ TBU... with `aiextract`
 
 ### More Examples
 
+TBU...
+
 Find more examples in the [examples/](examples/) folder.
 
 ## Package Interface
@@ -211,6 +212,8 @@ The package is built around three key elements:
 
 Why this design? Different APIs require different prompt formats. For example, OpenAI's API requires an array of dictionaries with `role` and `content` fields, while Ollama's API for Zephyr-7B model requires a ChatML schema with one big string and separators like `<|im_start|>user\nABC...<|im_end|>user`. For separating sections in your prompt, OpenAI prefers markdown headers (`##Response`) vs Anthropic performs better with HTML tags (`<text>{{TEXT}}</text>`).
 
+This package is heavily inspired by [Instructor](https://github.com/jxnl/instructor) and it's clever use of function calling API.
+
 **Prompt Schemas**
 
 The key type used for customization of logic of preparing inputs for LLMs and calling them (via multiple dispatch).