Added the support and product functionality

app/notebooks/rag_updated.ipynb

@@ -343,7 +343,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.5"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

app/rag.py

@@ -38,6 +38,7 @@ BLOGS_COLLECTION = "blogs"
 TECHNOLOGY_COLLECTION = "technology"
 REVOLUTION_COLLECTION = "revolution"
 SUPPORT_COLLECTION = "support"
+PRODUCT_COLLECTION = "product"
 
 
 # %%
@@ -97,6 +98,45 @@ User Question:
 Response:
 """
 
+@tool("Retrieve_Products")
+def retrieve_products(query: str) -> list[dict[str, str | float]]:
+    """
+    Retrieves detailed product information from Auro Wellness's product documentation.
+
+    Includes:
+      • Product descriptions, benefits, and usage instructions
+      • Ingredient details, formulation notes, and safety information
+      • Bundles, sizes, and availability
+      • High-level summaries of product features
+
+    Use this tool when the user asks about:
+      • Specific product information ("What is Glutaryl Plus?", "How do I use Rise & Revive?")
+      • Ingredients, benefits, or usage instructions
+      • Product bundles, availability, or ordering details
+
+    Do NOT use this tool for:
+      • Customer support, shipping, or policy questions → use Retrieve_Support
+      • General wellness education → use Retrieve_Blogs
+      • Technology/mechanism details → use Retrieve_Technology
+      • High-level company philosophy → use Retrieve_Revolution
+      • Short FAQs → use Retrieve_FAQs
+
+    Prioritize this tool for questions explicitly about **products themselves**.
+    """
+    
+    product_store = QdrantVectorStore(
+        client=client,
+        collection_name=PRODUCT_COLLECTION,
+        embedding=embeddings,
+    )
+    
+    docs = product_store.similarity_search_with_score(query, k=5)
+    return [
+        {"content": doc.page_content, "score": score}
+        for doc, score in docs if score > 0.85
+    ]
+
+
 @tool("Retrieve_Support")
 def retrieve_support(query: str) -> List[dict[str,str | float]]:
     """
@@ -284,7 +324,7 @@ def retrieve_revolution(query: str) -> List[dict[str,str | float]]:
     for doc, score in docs if score > 0.8]
 
 # %%
-all_tools = [retrieve_support, retrieve_faqs, retrieve_blogs, retrieve_technology, retrieve_revolution]
+all_tools = [retrieve_products, retrieve_support, retrieve_faqs, retrieve_blogs, retrieve_technology, retrieve_revolution]
 
 tool_descriptions = "\n".join(f"{tool.name}: {tool.description}" for tool in all_tools)
 tool_names = ", ".join(tool.name for tool in all_tools)