update sample

Author: mattgotteiner

Quickstart-Agentic-Retrieval/quickstart-agentic-retrieval.ipynb

@@ -379,7 +379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "918ded26",
    "metadata": {},
    "outputs": [],
@@ -397,7 +397,7 @@
     "    \"\"\"\n",
     "})\n",
     "\n",
-    "retrieval_result = agent_client.knowledge_retrieval.retrieve(\n",
+    "retrieval_result = agent_client.retrieve(\n",
     "    retrieval_request=KnowledgeAgentRetrievalRequest(\n",
     "        messages=[KnowledgeAgentMessage(role=msg[\"role\"], content=[KnowledgeAgentMessageTextContent(text=msg[\"content\"])]) for msg in messages if msg[\"role\"] != \"system\"],\n",
     "        target_index_params=[KnowledgeAgentIndexParams(index_name=index_name, reranker_threshold=2.5)]\n",
@@ -694,7 +694,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "7034e480",
    "metadata": {},
    "outputs": [],
@@ -704,7 +704,7 @@
     "    \"content\": \"How do I find lava at night?\"\n",
     "})\n",
     "\n",
-    "retrieval_result = agent_client.knowledge_retrieval.retrieve(\n",
+    "retrieval_result = agent_client.retrieve(\n",
     "    retrieval_request=KnowledgeAgentRetrievalRequest(\n",
     "        messages=[KnowledgeAgentMessage(role=msg[\"role\"], content=[KnowledgeAgentMessageTextContent(text=msg[\"content\"])]) for msg in messages if msg[\"role\"] != \"system\"],\n",
     "        target_index_params=[KnowledgeAgentIndexParams(index_name=index_name, reranker_threshold=2.5)]\n",
@@ -1082,7 +1082,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.10"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

agentic-retrieval-pipeline-example/agent-example.ipynb

@@ -358,7 +358,7 @@
     "    # Reverse the order so the most recent message is last\n",
     "    messages = list(messages)\n",
     "    messages.reverse()\n",
-    "    retrieval_result = agent_client.knowledge_retrieval.retrieve(\n",
+    "    retrieval_result = agent_client.retrieve(\n",
     "        retrieval_request=KnowledgeAgentRetrievalRequest(\n",
     "            messages=[KnowledgeAgentMessage(role=msg[\"role\"], content=[KnowledgeAgentMessageTextContent(text=msg.content[0].text)]) for msg in messages if msg[\"role\"] != \"system\"],\n",
     "            target_index_params=[KnowledgeAgentIndexParams(index_name=index_name, reranker_threshold=2.5)]\n",