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63 lines
1.4 KiB
63 lines
1.4 KiB
"""
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Todo
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- You send structured data to the swarm through the users form they make
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- then connect rag for every agent using llama index to remember all the students data
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- structured outputs
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"""
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import os
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from dotenv import load_dotenv
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from swarms.utils.litellm_wrapper import LiteLLM
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from pydantic import BaseModel
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from typing import List
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class CollegeLog(BaseModel):
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college_name: str
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college_description: str
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college_admission_requirements: str
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class CollegesRecommendation(BaseModel):
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colleges: List[CollegeLog]
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reasoning: str
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load_dotenv()
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# Get the API key from environment variable
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api_key = os.getenv("GROQ_API_KEY")
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# Initialize the model
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model = LiteLLM(
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model_name="groq/llama-3.1-70b-versatile",
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temperature=0.1,
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)
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function_caller = LiteLLM(
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model_name="gpt-4.1",
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system_prompt="""You are a college selection final decision maker. Your role is to:
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- Balance all relevant factors and stakeholder input.
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- Only return the output in the schema format.
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""",
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response_format=CollegesRecommendation,
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temperature=0.1,
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)
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print(
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function_caller.run(
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"""
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Student Profile: Kye Gomez
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- GPA: 3.8
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- SAT: 1450
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- Interests: Computer Science, Robotics
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- Location Preference: East Coast
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- Extracurriculars: Robotics Club President, Math Team
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- Budget: Need financial aid
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- Preferred Environment: Medium-sized urban campus
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"""
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)
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)
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