Show how to render prompts #718
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
github-actions
bot
added
.NET
glahaye
reviewed
Apr 28, 2023
glahaye
reviewed
Apr 28, 2023
samples/dotnet/kernel-syntax-examples/Resources/EmbeddedResource.cs
Outdated
Show resolved
Hide resolved
glahaye
reviewed
Apr 28, 2023
dluc
force-pushed
the
dluc127prompts
branch
3 times, most recently
from
20309f4
to
b0b4f00
Compare
lemillermicrosoft
approved these changes
Apr 28, 2023
shawncal
reviewed
Apr 28, 2023
dotnet/src/SemanticKernel.Abstractions/AI/ChatCompletion/IChatCompletion.cs
Show resolved
Hide resolved
github-actions
bot
added
the
kernel
dluc
added a commit
that referenced
this pull request
Apr 29, 2023
### Motivation and Context New code example showing how to render prompts, e.g. in cases where one wants to leverage semantic functions but execute them with a custom flow, e.g. passing prompts to GPT Turbo 3.5. The example shows the basics of how one could add a chat UI into an app, selecting some piece of content, and asking AI to extract data. In this case, instead of calling a semantic function, the code calls a Chat model directly, to leverage chat model protections against prompt injection. ### Description * New syntax example, explaining how to use `PromptTemplateEngine` * Make one chat service param optional, to simplify the code
dehoward
pushed a commit
to lemillermicrosoft/semantic-kernel
that referenced
this pull request
Jun 1, 2023
### Motivation and Context New code example showing how to render prompts, e.g. in cases where one wants to leverage semantic functions but execute them with a custom flow, e.g. passing prompts to GPT Turbo 3.5. The example shows the basics of how one could add a chat UI into an app, selecting some piece of content, and asking AI to extract data. In this case, instead of calling a semantic function, the code calls a Chat model directly, to leverage chat model protections against prompt injection. ### Description * New syntax example, explaining how to use `PromptTemplateEngine` * Make one chat service param optional, to simplify the code
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Motivation and Context
New code example showing how to render prompts, e.g. in cases where one wants to leverage semantic functions but execute them with a custom flow, e.g. passing prompts to GPT Turbo 3.5.
The example shows the basics of how one could add a chat UI into an app, selecting some piece of content, and asking AI to extract data. In this case, instead of calling a semantic function, the code calls a Chat model directly, to leverage chat model protections against prompt injection.
Description
PromptTemplateEngine