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https://github.com/ncrmro/yams
Yams are LLM chat histories declared as yaml (with markdown strings).
https://github.com/ncrmro/yams
bash low-code ollama shell yaml
Last synced: 23 days ago
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Yams are LLM chat histories declared as yaml (with markdown strings).
- Host: GitHub
- URL: https://github.com/ncrmro/yams
- Owner: ncrmro
- License: bsd-3-clause
- Created: 2024-06-26T01:08:03.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-07-26T21:50:27.000Z (3 months ago)
- Last Synced: 2024-09-30T23:01:30.281Z (about 1 month ago)
- Topics: bash, low-code, ollama, shell, yaml
- Language: Shell
- Homepage: https://yams.fyi
- Size: 34.2 KB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# YAMs
YAMs are chat histories with LLMs declared as YAML, containing markdown strings used primarily to communicate with an Ollama API and aid in ideation or in agentic workflows.
**Advantages**:
- Extremely low-code with high developer ergonomics and inspectability.
- Provide an example workflow for developing LLM prompts involving structured data input and outputs.
- commiting and collaborating of chat's to VCS allows for rapid ideation
**Example YAM**
Generally a VCS Git repo might hav a `docs` or `documentation` folder, we can then create `docs/yams/000-template.yaml` and use that to jumpstart any new YAMs before commiting them.
This allows YAMs to be further refined with peers in pull reqiests.
Here we might have a folder of `recipies` and the following YAM might be `recipies/001-penut-butter-and-jelly.yaml`
````yaml
# YAMs context doc
# - everything in this file gets converted to JSON and sent to an Ollama LLM endpoint
# - single prompt with a context block provided as a markdown yaml codeblock
# - returns either the context block back a yaml, markdown or plain text
model: mistral
messages:
- role: user
content: >-
Using the following context:
```yaml
type: recipe
slug: ""
title: "Peanut butter and jelly"
ingredients:
- name: Crunchy Peanut Butter
quantity: 2
unit: Tbsp
steps:
- Spread Peanut Butter on bread.
```
Complete the document in the YAML code block.
```yaml
```
# After we run bin/yams ./pbj.yaml
# The following object will be added from the LLM's response
- role: assistant
content: |2-
```yaml
type: recipe
slug: "peanut-butter-and-jelly"
title: "Peanut Butter and Jelly Sandwich"
ingredients:
- name: Crunchy Peanut Butter
quantity: 2
unit: Tbsp
- name: Smooth Jelly or Jam (Strawberry, Grape, etc.)
quantity: 3
unit: Tbsp
steps:
- Spread a layer of Peanut Butter on one slice of bread.
- Spread a layer of Jelly or Jam on another slice of bread.
- Place the two slices together with their respective layers facing each other.
```
````
**Whats in this Repo?**
- [bin/yams](bin/yams)
- Copy and customize this in your repos!
- Use TODOs and an LLM to make quick modifictions to `bin/yams` if required (or re-implment and link to that here)
- [examples/recipes/peanut-butter-and-jelly.yaml](examples/recipes/peanut-butter-and-jelly.yaml)
- committed after running the `bin/yams` script.
- New Prompt skeleton prompts are easy to generate by asking an LLM
- Example: How would you define `x` as yaml (do note less is more on templates)
- [screenplay](https://chatgpt.com/share/9c4626d9-2603-4bd5-80b3-582d41137ec2)
- [recipe](https://chatgpt.com/share/76eead06-8b3d-425e-96bd-e35a9938faf6)
- [business plan](https://chatgpt.com/share/0f698383-0146-4862-9816-b6e12f1f1fe9)
**Process**:
- The chat history request body is specified as a YAML file.
- Model is set as a top-level key in the YAMs with parameters from the [Ollama API](https://github.com/ollama/ollama/blob/main/docs/api.md).
- YAML markdown codeblocks are used to pass structured data into an LLM prompt.
- Outputs are requested can be YAML markdown codeblocks or other structured and extracted for further processing
**Implementation Notes**:
- Located in `bin/yams`.
- Structured examples provide desired context for minimal YAML input.
- YAML is preferred for its natural language similarity and large corpus.
- Suitable for declarative LLM chats on private or public APIs.
# TODOs
- [ ] Content key could be yaml directly rather than a markdown codeblock
- [ ] Provide notes on using hosted Ollama endpoints.
- [ ] Address YAML reformatting issues in initial message prompts.
- [ ] Improve templating.
- [ ] Rerun on file changes (with original prompt?)
- [ ] Stream results directly from curl responses into YAML for impact.
# Naive Shell Implementation Example
This is a basic implementation of YAMs to complete a document generating a peanut butter and jelly recipe. We can complete
it by running `bin/yams examples/recipes/peanut-butter-and-jelly.yaml` which will send this request to the specified Ollama API endpoint for completion.
Inside of `examples/screenplays/cyberpunk-spirited-away.yaml` is a starter YAMs I generated from this [prompt](https://chatgpt.com/c/3f21cf03-c65a-42b6-a705-b8a3ef368ddb) to declare a screenplay as yaml. On