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import os |
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from google import genai |
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from dotenv import load_dotenv |
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from PIL import Image |
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load_dotenv() |
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class ClaimsIntakeAgent: |
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def __init__(self): |
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api_key = os.getenv("GEMINI_API_KEY") |
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if not api_key: |
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print("Warning: GEMINI_API_KEY not found in environment variables.") |
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else: |
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self.client = genai.Client(api_key=api_key) |
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def process_claim(self, user_input, image=None, document_path=None): |
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""" |
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Processes a user claim report. |
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Args: |
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user_input (str): The user's description of the accident. |
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image (PIL.Image): Optional image of the damage. |
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document_path (str): Optional path to a uploaded document (PDF/Doc). |
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Returns: |
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str: The agent's response. |
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""" |
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if not hasattr(self, 'client'): |
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return "Error: Gemini API key not configured. Please check your .env file." |
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from utils import convert_doc_to_markdown |
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doc_content = "" |
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if document_path: |
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doc_content = convert_doc_to_markdown(document_path) |
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doc_content = f"\n\n**Uploaded Document Content:**\n{doc_content}\n" |
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print("Extracted content:",doc_content) |
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prompt = f""" |
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You are an AI assistant for an auto insurance company. Your goal is to help users report vehicle claims and provide a preliminary assessment for the back-office. |
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Analyze the user's input, any provided images, and any uploaded document content. |
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If an image is provided, estimate the damage severity and cost (in GBP) based on visual inspection. |
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Extract vehicle information if possible. |
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Analyze the text and documents for consistency and potential fraud indicators. |
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**Uploaded Document Content:** |
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{doc_content} |
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Return a structured response in the following format: |
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**Claim Assessment** |
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* **Submitter Name:** [Name if found in text/docs, else 'Anonymous'] |
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* **Vehicle:** [Vehicle Make/Model/Year if identifiable, else 'Unknown'] |
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* **Damage Severity:** [Minor/Moderate/Severe] |
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* **Estimated Repair Cost:** [Amount in £] |
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* **Fraud Risk:** [Low/Medium/High] - [Brief reason] |
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* **Adjuster Classification:** [Junior Adjuster/Senior Adjuster] (Route complex/high-risk/high-value >£5000 claims to Senior) |
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* **Policy Check:** Coverage appears valid (Simulated). |
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* **Summary:** [Concise summary of the incident and findings] |
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* **Next Steps:** [Brief instruction to user] |
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If no image is provided, ask the user to upload one for a better assessment, but still acknowledge the report. |
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""" |
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try: |
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inputs = [prompt, user_input] |
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if image: |
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inputs.append(image) |
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response = self.client.models.generate_content( |
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model='gemini-2.5-flash', |
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contents=inputs |
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) |
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return response.text |
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except Exception as e: |
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return f"Error processing claim: {str(e)}" |
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def analyze_document(self, file_path): |
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""" |
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Analyzes an uploaded document (PDF/Image) for claim info. |
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For MVP, this handles images primarily, but could be expanded for PDFs. |
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""" |
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return "Document received. Analysis feature is in beta (MVP)." |
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