Salmanap/fix demos (#140)

* Comitting to bring in main

* insurance agent updated

* updated the insurance agent

---------

Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-261.local>

demos/insurance_agent/insurance_agent_main.py

@@ -1,28 +1,24 @@
-import openai
 from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from typing import Optional
+from pydantic import BaseModel, Field
 
 app = FastAPI()
-openai.api_base = "http://127.0.0.1:10000/v1"  # Local proxy
 
-# Data models
+class Conversation(BaseModel):
+    arch_messages: list
 
 class PolicyCoverageRequest(BaseModel):
     policy_type: str = Field(..., description="The type of a policy held by the customer For, e.g. car, boat, house, motorcycle)")
 
-class PolicyRequest(BaseModel):
-    policy_type: str = Field(..., description="The type of a policy held by the customer For, e.g. car, boat, house, motorcycle)")
-    details: str  # Additional details like model, year, etc.
+class PolicyInitiateRequest(PolicyCoverageRequest):
+    deductible: float = Field(..., description="The deductible amount set of the policy")
 
 class ClaimUpdate(BaseModel):
-    policy_id: int
-    claim_id: int
-    update: str  # Status or details of the claim
+    claim_id: str
+    notes: str  # Status or details of the claim
 
 class DeductibleUpdate(BaseModel):
-    policy_id: int
-    new_deductible: float
+    policy_id: str
+    deductible: float
 
 class CoverageResponse(BaseModel):
     policy_type: str
@@ -53,14 +49,14 @@ async def get_policy_coverage(req: PolicyCoverageRequest):
 
 # Initiate policy coverage
 @app.post("/policy/initiate")
-async def initiate_policy(policy_request: PolicyRequest):
+async def initiate_policy(policy_request: PolicyInitiateRequest):
     """
     Initiate policy coverage for a car, boat, house, or motorcycle.
     """
     if policy_request.policy_type not in ["car", "boat", "house", "motorcycle"]:
         raise HTTPException(status_code=400, detail="Invalid policy type")
 
-    return {"message": f"Policy initiated for {policy_request.policy_type}", "details": policy_request.details}
+    return {"message": f"Policy initiated for {policy_request.policy_type}", "deductible": policy_request.deductible}
 
 # Update claim details
 @app.post("/policy/claim")
@@ -69,8 +65,8 @@ async def update_claim(req: ClaimUpdate):
     Update the status or details of a claim.
     """
     # For simplicity, this is a mock update response
-    return {"message": f"Claim {claim_update.claim_id} for policy {claim_update.policy_id} has been updated",
-            "update": claim_update.update}
+    return {"message": f"Claim {claim_update.claim_id} for policy {claim_update.claim_id} has been updated",
+            "update": claim_update.notes}
 
 # Update deductible amount
 @app.post("/policy/deductible")
@@ -80,43 +76,31 @@ async def update_deductible(deductible_update: DeductibleUpdate):
     """
     # For simplicity, this is a mock update response
     return {"message": f"Deductible for policy {deductible_update.policy_id} has been updated",
-            "new_deductible": deductible_update.new_deductible}
+            "new_deductible": deductible_update.deductible}
 
 # Post method for policy Q/A
 @app.post("/policy/qa")
-async def policy_qa():
+async def policy_qa(conversation: Conversation):
     """
     This method handles Q/A related to general issues in insurance.
     It forwards the conversation to the OpenAI client via a local proxy and returns the response.
     """
-    try:
-        # Get the latest user message from the conversation
-        user_message = conversation.messages[-1].content  # Assuming the last message is from the user
-
-        # Call the OpenAI API through the Python client
-        response = openai.Completion.create(
-            model="gpt-4o",  # Replace with the model you want to use
-            prompt=user_message,
-            max_tokens=150
-        )
-
-        # Extract the response text from OpenAI
-        completion = response.choices[0].text.strip()
-
-        # Build the assistant's response message
-        assistant_message = Message(role="assistant", content=completion)
-
-        # Append the assistant's response to the conversation and return it
-        updated_conversation = Conversation(
-            messages=conversation.messages + [assistant_message]
-        )
-
-        return updated_conversation
-
-    except openai.error.OpenAIError as e:
-        raise HTTPException(status_code=500, detail=f"LLM error: {str(e)}")
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error: {str(e)}")
+    return {
+            "choices": [
+              {
+                "message": {
+                  "role": "assistant",
+                  "content": "I am a helpful insurance agent, and can only help with insurance things"
+                },
+                "finish_reason": "completed",
+                "index": 0
+              }
+            ],
+            "model": "insurance_agent",
+            "usage": {
+              "completion_tokens": 0
+            }
+          }
 
 # Run the app using:
 # uvicorn main:app --reload