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https://github.com/katanemo/plano.git
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dc57f119a0
* initial commit of the insurange agent demo, with the CLI tool * committing the cli * fixed some field descriptions for generate-prompt-targets * CLI works with buil, up and down commands. Function calling example works stand-alone * fixed README to install archgw cli * fixing based on feedback * fixing based on feedback --------- Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-261.local>
122 lines
4.5 KiB
Python
122 lines
4.5 KiB
Python
import openai
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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from typing import Optional
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app = FastAPI()
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openai.api_base = "http://127.0.0.1:10000/v1" # Local proxy
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# Data models
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class PolicyCoverageRequest(BaseModel):
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policy_type: str = Field(..., description="The type of a policy held by the customer For, e.g. car, boat, house, motorcycle)")
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class PolicyRequest(BaseModel):
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policy_type: str = Field(..., description="The type of a policy held by the customer For, e.g. car, boat, house, motorcycle)")
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details: str # Additional details like model, year, etc.
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class ClaimUpdate(BaseModel):
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policy_id: int
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claim_id: int
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update: str # Status or details of the claim
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class DeductibleUpdate(BaseModel):
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policy_id: int
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new_deductible: float
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class CoverageResponse(BaseModel):
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policy_type: str
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coverage: str # Description of coverage
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premium: float # The premium cost
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# Get information about policy coverage
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@app.post("/policy/coverage", response_model=CoverageResponse)
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async def get_policy_coverage(req: PolicyCoverageRequest):
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"""
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Retrieve the coverage details for a given policy type (car, boat, house, motorcycle).
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"""
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policy_coverage = {
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"car": {"coverage": "Full car coverage with collision, liability", "premium": 500.0},
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"boat": {"coverage": "Full boat coverage including theft and storm damage", "premium": 700.0},
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"house": {"coverage": "Full house coverage including fire, theft, flood", "premium": 1000.0},
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"motorcycle": {"coverage": "Full motorcycle coverage with liability", "premium": 400.0},
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}
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if req.policy_type not in policy_coverage:
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raise HTTPException(status_code=404, detail="Policy type not found")
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return CoverageResponse(
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policy_type=req.policy_type,
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coverage=policy_coverage[req.policy_type]["coverage"],
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premium=policy_coverage[req.policy_type]["premium"]
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)
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# Initiate policy coverage
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@app.post("/policy/initiate")
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async def initiate_policy(policy_request: PolicyRequest):
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"""
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Initiate policy coverage for a car, boat, house, or motorcycle.
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"""
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if policy_request.policy_type not in ["car", "boat", "house", "motorcycle"]:
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raise HTTPException(status_code=400, detail="Invalid policy type")
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return {"message": f"Policy initiated for {policy_request.policy_type}", "details": policy_request.details}
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# Update claim details
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@app.post("/policy/claim")
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async def update_claim(req: ClaimUpdate):
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"""
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Update the status or details of a claim.
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"""
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# For simplicity, this is a mock update response
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return {"message": f"Claim {claim_update.claim_id} for policy {claim_update.policy_id} has been updated",
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"update": claim_update.update}
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# Update deductible amount
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@app.post("/policy/deductible")
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async def update_deductible(deductible_update: DeductibleUpdate):
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"""
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Update the deductible amount for a specific policy.
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"""
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# For simplicity, this is a mock update response
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return {"message": f"Deductible for policy {deductible_update.policy_id} has been updated",
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"new_deductible": deductible_update.new_deductible}
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# Post method for policy Q/A
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@app.post("/policy/qa")
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async def policy_qa():
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"""
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This method handles Q/A related to general issues in insurance.
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It forwards the conversation to the OpenAI client via a local proxy and returns the response.
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"""
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try:
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# Get the latest user message from the conversation
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user_message = conversation.messages[-1].content # Assuming the last message is from the user
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# Call the OpenAI API through the Python client
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response = openai.Completion.create(
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model="gpt-4o", # Replace with the model you want to use
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prompt=user_message,
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max_tokens=150
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)
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# Extract the response text from OpenAI
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completion = response.choices[0].text.strip()
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# Build the assistant's response message
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assistant_message = Message(role="assistant", content=completion)
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# Append the assistant's response to the conversation and return it
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updated_conversation = Conversation(
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messages=conversation.messages + [assistant_message]
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)
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return updated_conversation
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except openai.error.OpenAIError as e:
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raise HTTPException(status_code=500, detail=f"LLM error: {str(e)}")
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except Exception as e:
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raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
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# Run the app using:
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# uvicorn main:app --reload
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