workflows/courses/suggest_expectations.py

from langchain import hub
from langchain_core.output_parsers import JsonOutputParser
from langchain_openai import ChatOpenAI
from pydantic import BaseModel, Field
from typing import List
from pydantic import BaseModel
from typing import List, Optional
import os

class Expectation(BaseModel):
    expectation: str = Field(description="The learning outcome that the course designer has identified for the learner to demonstrate upon successful completion of the module.")
    check_question: str = Field(description="Targeted question that the course designer have developed to assess the learner's understanding of the learning outcomes.")

class Expectations(BaseModel):
    expectations: List[Expectation]

class Inputs(BaseModel):
    course: str
    module: str
    tasks: List[str]


class SuggestExpectations:
    def kickoff(self, inputs={}):
        self.course = inputs["course"]
        self.module = inputs["module"]
        self.tasks = inputs["tasks"]
        return self._get_suggestions()

    def _get_suggestions(self):
        parser = JsonOutputParser(pydantic_object=Expectations)
        prompt = hub.pull("course_learn_suggest_expectations_from_learner")
        llm = ChatOpenAI(model=os.environ['OPENAI_MODEL'], temperature=0.2)
        chain = (prompt | llm | parser).with_config({
            "tags": ["course_learn", "suggest_expectations"], "run_name": "Suggest Module Expectations",
            "metadata" : {
                "versoin": "v1.0.0",
                "growth_activity": "course_learn",
                "env": os.environ["ENV"],
                "model": os.environ["OPENAI_MODEL"],
            }
        })

        response = chain.invoke({
            "course": self.course, "module": self.module, "tasks": "* " + ("\n* ".join(self.tasks)),
            "format_instructions": parser.get_format_instructions()
          })

        return response


# Example usage
# suggester = SuggestExpectations()
# response = suggester.kickoff(inputs={
#     "course": "SQL",
#     "module": "Query Optimization Techniques",
#     "tasks": [
#         "Watch this video https://youtu.be/BHwzDmr6d7s?si=sfFYnd73y9w0EjGB to understand SQL execution order and some optimization techniques.",
#         "Watch this video https://youtu.be/FoznjTU929c?si=6M3xUIUwAxE6EbKS to understand SQL explain command usage.",
#         "Go over these articles https://intellipaat.com/blog/sql-optimization-techniques/ & https://www.thoughtspot.com/data-trends/data-modeling/optimizing-sql-queries  to understand various query optimization techniques."
#     ]
# })
# print(response)