Upload config.py

src/config.py

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+import os
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+class Config:
+    """Configuration class for Insurance Helper RAG application"""
+    
+    # API Keys
+    GEMINI_API_KEY = os.getenv("GOOGLE_API_KEY")
+    QDRANT_API_KEY = os.getenv("QDRANT_API_KEY")
+    QDRANT_URL = os.getenv("QDRANT_HOST")
+    
+    # Gemini Model Configuration
+    GEMINI_MODEL = "gemini-2.5-flash" 
+    GEMINI_TEMPERATURE = 0.2 
+    GEMINI_MAX_OUTPUT_TOKENS = 2048
+    
+    # Embedding Configuration
+    EMBEDDING_MODEL = "models/text-embedding-004"
+    EMBEDDING_DIMENSION = 768
+    
+    # PDF Processing Configuration
+    CHUNK_SIZE = 1000  
+    CHUNK_OVERLAP = 200  
+    
+    # Chunking separators optimized for insurance documents
+    SEPARATORS = [
+        "\n\n",  # Paragraph breaks
+        "\n",    # Line breaks
+        ". ",    # Sentence breaks
+        ", ",    # Clause breaks
+        " ",     # Word breaks
+        ""       # Character breaks
+    ]
+    
+    # Qdrant Configuration
+    COLLECTION_NAME = "insurance_documents"
+    VECTOR_SIZE = EMBEDDING_DIMENSION
+    DISTANCE_METRIC = "Cosine"
+    
+    # Retrieval Configuration
+    TOP_K = 5  
+    SIMILARITY_THRESHOLD = 0.7  
+    
+    # RAG Prompt Template
+    RAG_PROMPT_TEMPLATE = """You are an expert insurance advisor helping users understand their insurance documents.
+Use the following context from insurance documents to answer the user's question.
+Provide clear, accurate information and explain insurance terms in simple language.
+
+Context from insurance documents:
+{context}
+
+User Question: {question}
+
+Instructions:
+- Answer based primarily on the provided context
+- If the context doesn't contain enough information, clearly state that
+- Explain insurance jargon in plain language
+- For add-on recommendations, compare coverage, costs, and benefits
+- Highlight important exclusions or limitations
+- Be precise about coverage details and conditions
+
+Answer:"""
+
+    # System Instructions for Gemini
+    SYSTEM_INSTRUCTION = """You are an expert insurance advisor. Your role is to:
+1. Help users understand complex insurance documents
+2. Explain insurance terms and conditions in simple language
+3. Provide recommendations for add-ons based on coverage gaps
+4. Compare different coverage options clearly
+5. Highlight important exclusions and limitations
+6. Always prioritize accuracy and clarity
+
+Remember: You provide informational guidance only, not professional insurance advice."""
+
+    @classmethod
+    def validate_config(cls):
+        """Validate that all required configuration is present"""
+        required_keys = [
+            ("GEMINI_API_KEY", cls.GEMINI_API_KEY),
+            ("QDRANT_API_KEY", cls.QDRANT_API_KEY),
+            ("QDRANT_URL", cls.QDRANT_URL)
+        ]
+        
+        missing = [key for key, value in required_keys if not value]
+        
+        if missing:
+            raise ValueError(
+                f"Missing required environment variables: {', '.join(missing)}\n"
+                "Please set them in your .env file"
+            )
+        
+        return True
+    
+    @classmethod
+    def get_qdrant_config(cls):
+        """Returns Qdrant configuration dictionary"""
+        return {
+            "url": cls.QDRANT_URL,
+            "api_key": cls.QDRANT_API_KEY,
+            "collection_name": cls.COLLECTION_NAME,
+            "vector_size": cls.VECTOR_SIZE,
+            "distance": cls.DISTANCE_METRIC
+        }
+    
+    @classmethod
+    def get_chunking_config(cls):
+        """Returns chunking configuration dictionary"""
+        return {
+            "chunk_size": cls.CHUNK_SIZE,
+            "chunk_overlap": cls.CHUNK_OVERLAP,
+            "separators": cls.SEPARATORS
+        }
+    
+    @classmethod
+    def get_retrieval_config(cls):
+        """Returns retrieval configuration dictionary"""
+        return {
+            "top_k": cls.TOP_K,
+            "similarity_threshold": cls.SIMILARITY_THRESHOLD
+        }