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"""
Todo
- You send structured data to the swarm through the users form they make
- then connect rag for every agent using llama index to remember all the students data
- structured outputs
"""
import os
from dotenv import load_dotenv
from swarm_models import OpenAIChat, OpenAIFunctionCaller
from pydantic import BaseModel
from typing import List
class CollegeLog(BaseModel):
college_name: str
college_description: str
college_admission_requirements: str
class CollegesRecommendation(BaseModel):
colleges: List[CollegeLog]
reasoning: str
load_dotenv()
# Get the API key from environment variable
api_key = os.getenv("GROQ_API_KEY")
# Initialize the model
model = OpenAIChat(
openai_api_base="https://api.groq.com/openai/v1",
openai_api_key=api_key,
model_name="llama-3.1-70b-versatile",
temperature=0.1,
)
function_caller = OpenAIFunctionCaller(
system_prompt="""You are a college selection final decision maker. Your role is to:
- Balance all relevant factors and stakeholder input.
- Only return the output in the schema format.
""",
openai_api_key=os.getenv("OPENAI_API_KEY"),
base_model=CollegesRecommendation,
# parallel_tool_calls=True,
)
print(
function_caller.run(
"""
Student Profile: Kye Gomez
- GPA: 3.8
- SAT: 1450
- Interests: Computer Science, Robotics
- Location Preference: East Coast
- Extracurriculars: Robotics Club President, Math Team
- Budget: Need financial aid
- Preferred Environment: Medium-sized urban campus
"""
)
)
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