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fix some indentations, update mkdocs deps,
and make the last code snippet be able to be pasted to
python interpreter directly.
Signed-off-by: Yihong Wang <yh.wang@ibm.com>
@@ -55,7 +55,7 @@ and brittle prompts with structured, maintainable, robust, and efficient AI work
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## Let's setup Mellea to work locally
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1.Open up a terminal, and run the following commands:
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Open up a terminal, and run the following commands:
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```bash
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python3.11 -m venv venv
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source venv/bin/activate
@@ -66,138 +66,151 @@ pip install mellea
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If you see something about the Rust compiler, please confirm you are using python3.11, or python3.12 anything above that has a Rust dependency.
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1. Start python:
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```bash
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python
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```
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```bash
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python
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```
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1. Run a simple Mellea session:
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```python
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import mellea
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m = mellea.start_session()
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print(m.chat("tell me some fun trivia about IBM and the early history of AI.").content)
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```
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You can either add this to a file like `main.py` or run it in the python REPL, if you get output
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you are set up to dig deeper with Mellea.
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```python
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import mellea
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m = mellea.start_session()
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print(m.chat("tell me some fun trivia about IBM and the early history of AI.").content)
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```
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You can either add this to a file like `main.py` or run it in the python REPL, if you get output
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you are set up to dig deeper with Mellea.
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## Simple email examples
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!!! note
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The following work should be done via a text editor, there should be a couple installed on your laptop, if you aren't sure raise your hand and a helper will help you out.
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1. Let's leverage Mellea to do some email generation for us, the first example is a simple example:
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```python
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import mellea
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m = mellea.start_session()
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email = m.instruct("Write an email inviting interns to an office party at 3:30pm.")
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print(str(email))
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```
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```python
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import mellea
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m = mellea.start_session()
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email = m.instruct("Write an email inviting interns to an office party at 3:30pm.")
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print(str(email))
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```
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1. As you can see, it outputs a standard email with only a couple lines of code, lets expand on this:
"Write an email to {{name}} using the notes following: {{notes}}.",
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user_variables={"name": name, "notes": notes},
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)
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return email.value # str(email) also works.
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print(
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write_email(
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m,
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"Olivia",
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"Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery.",
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print(
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write_email(
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m,
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"Olivia",
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"Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery.",
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)
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)
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)
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```
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With this more advance example we now have the ability to customize the email to be more directed and
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personalized for the recipient. But this is just a more programmatic prompt engineering, lets see where
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Mellea really shines.
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```
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With this more advance example we now have the ability to customize the email to be more directed and
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personalized for the recipient. But this is just a more programmatic prompt engineering, lets see where
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Mellea really shines.
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### Simple email with boundaries and requirements
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1. The first step with the power of Mellea, is adding requirements to something like this email, take a look at this first
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example:
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```python
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import mellea
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m = mellea.start_session()
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defwrite_email_with_requirements(
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m: mellea.MelleaSession, name: str, notes: str
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) -> str:
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email = m.instruct(
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"Write an email to {{name}} using the notes following: {{notes}}.",
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requirements=[
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"The email should have a salutation",
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"Use only lower-case letters",
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],
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user_variables={"name": name, "notes": notes},
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example:
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```python
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import mellea
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m = mellea.start_session()
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def write_email_with_requirements(
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m: mellea.MelleaSession, name: str, notes: str
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) -> str:
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email = m.instruct(
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"Write an email to {{name}} using the notes following: {{notes}}.",
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requirements=[
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"The email should have a salutation",
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"Use only lower-case letters",
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],
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user_variables={"name": name, "notes": notes},
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)
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return str(email)
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print(
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write_email_with_requirements(
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m,
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name="Olivia",
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notes="Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery.",
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)
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)
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returnstr(email)
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```
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As you can see with this output now, you force the Mellea framework to start checking itself to create what you need.
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Imagine this possibility, now you can start making sure your LLMs only generate things that you want. Test this theory
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by changing from "only lower-case" to "only upper-case" and see that it will follow your instructions.
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print(
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write_email_with_requirements(
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m,
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name="Olivia",
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notes="Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery.",
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)
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)
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```
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As you can see with this output now, you force the Mellea framework to start checking itself to create what you need.
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Imagine this possibility, now you can start making sure your LLMs only generate things that you want. Test this theory
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by changing from "only lower-case" to "only upper-case" and see that it will follow your instructions.
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Pretty neat eh? Lets go even deeper.
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Pretty neat eh? Lets go even deeper.
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Let's create an email with some sampling and have Mellea find the best option for what we are looking for:
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We add two requirements to the instruction which will be added to the model request.
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But we don't check yet if these requirements are satisfied, we add a strategy for validating the requirements.
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Let's create an email with some sampling and have Mellea find the best option for what we are looking for:
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We add two requirements to the instruction which will be added to the model request.
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But we don't check yet if these requirements are satisfied, we add a strategy for validating the requirements.
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1. This sampling strategy (`RejectionSamplingStrategy()`) checks if all requirements are met and if any requirement fails, the sampling strategy will sample a new email from the LLM.
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```python
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import mellea
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m = mellea.start_session()
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from mellea.stdlib.sampling import RejectionSamplingStrategy
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```python
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import mellea
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m = mellea.start_session()
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from mellea.stdlib.sampling import RejectionSamplingStrategy
"Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery.",
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)
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)
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```
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You might notice it fails with the above example, because the name "Olivia" has an upper-case letter in it. Remove the `"Use only lower-case letters",` line, and it should pass on the first re-run. This brings up some interesting opportunities, so make sure that the writing you expect is within the boundaries and it'll keep trying till it gets it right.
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You might notice it fails with the above example, because the name "Olivia" has an upper-case letter in it. Remove the `"Use only lower-case letters",`
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line, and it should pass on the first re-run. This brings up some interesting opportunities, so make sure that the writing you expect is within the
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boundaries and it'll keep trying till it gets it right.
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## Instruct Validate Repair
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1.The first `instruct-validate-repair` pattern is as follows:
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The first `instruct-validate-repair` pattern is as follows:
"Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery."))
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print(
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write_email(
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m,
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"Olivia",
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"Olivia helped the lab over the last few weeks by organizing intern events, advertising the speaker series, and handling issues with snack delivery.",
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)
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)
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```
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Most of this should look familiar by now, but the `validation_fn` and `check` should be new.
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