Clean up, add QR Codes

Author: stephen37

bootcamp/tutorials/integration/openai_agents_milvus.ipynb

@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -58,9 +58,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'auto_id': False, 'description': '', 'fields': [{'name': 'id', 'description': '', 'type': <DataType.INT64: 5>, 'is_primary': True, 'auto_id': True}, {'name': 'text', 'description': '', 'type': <DataType.VARCHAR: 21>, 'params': {'max_length': 1000, 'enable_analyzer': True}}, {'name': 'sparse', 'description': '', 'type': <DataType.SPARSE_FLOAT_VECTOR: 104>}], 'enable_dynamic_field': False}"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "from pymilvus import DataType, FunctionType, MilvusClient\n",
     "\n",
@@ -89,7 +100,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -98,7 +109,7 @@
        "{'auto_id': False, 'description': '', 'fields': [{'name': 'id', 'description': '', 'type': <DataType.INT64: 5>, 'is_primary': True, 'auto_id': True}, {'name': 'text', 'description': '', 'type': <DataType.VARCHAR: 21>, 'params': {'max_length': 1000, 'enable_analyzer': True}}, {'name': 'sparse', 'description': '', 'type': <DataType.SPARSE_FLOAT_VECTOR: 104>, 'is_function_output': True}], 'enable_dynamic_field': False, 'functions': [{'name': 'text_bm25_emb', 'description': '', 'type': <FunctionType.BM25: 1>, 'input_field_names': ['text'], 'output_field_names': ['sparse'], 'params': {}}]}"
       ]
      },
-     "execution_count": 32,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -130,16 +141,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'insert_count': 100, 'ids': [456486814660619039, 456486814660619040, 456486814660619041, 456486814660619042, 456486814660619043, 456486814660619044, 456486814660619045, 456486814660619046, 456486814660619047, 456486814660619048, 456486814660619049, 456486814660619050, 456486814660619051, 456486814660619052, 456486814660619053, 456486814660619054, 456486814660619055, 456486814660619056, 456486814660619057, 456486814660619058, 456486814660619059, 456486814660619060, 456486814660619061, 456486814660619062, 456486814660619063, 456486814660619064, 456486814660619065, 456486814660619066, 456486814660619067, 456486814660619068, 456486814660619069, 456486814660619070, 456486814660619071, 456486814660619072, 456486814660619073, 456486814660619074, 456486814660619075, 456486814660619076, 456486814660619077, 456486814660619078, 456486814660619079, 456486814660619080, 456486814660619081, 456486814660619082, 456486814660619083, 456486814660619084, 456486814660619085, 456486814660619086, 456486814660619087, 456486814660619088, 456486814660619089, 456486814660619090, 456486814660619091, 456486814660619092, 456486814660619093, 456486814660619094, 456486814660619095, 456486814660619096, 456486814660619097, 456486814660619098, 456486814660619099, 456486814660619100, 456486814660619101, 456486814660619102, 456486814660619103, 456486814660619104, 456486814660619105, 456486814660619106, 456486814660619107, 456486814660619108, 456486814660619109, 456486814660619110, 456486814660619111, 456486814660619112, 456486814660619113, 456486814660619114, 456486814660619115, 456486814660619116, 456486814660619117, 456486814660619118, 456486814660619119, 456486814660619120, 456486814660619121, 456486814660619122, 456486814660619123, 456486814660619124, 456486814660619125, 456486814660619126, 456486814660619127, 456486814660619128, 456486814660619129, 456486814660619130, 456486814660619131, 456486814660619132, 456486814660619133, 456486814660619134, 456486814660619135, 456486814660619136, 456486814660619137, 456486814660619138], 'cost': 0}"
+       "{'insert_count': 37, 'ids': [456486814660619140, 456486814660619141, 456486814660619142, 456486814660619143, 456486814660619144, 456486814660619145, 456486814660619146, 456486814660619147, 456486814660619148, 456486814660619149, 456486814660619150, 456486814660619151, 456486814660619152, 456486814660619153, 456486814660619154, 456486814660619155, 456486814660619156, 456486814660619157, 456486814660619158, 456486814660619159, 456486814660619160, 456486814660619161, 456486814660619162, 456486814660619163, 456486814660619164, 456486814660619165, 456486814660619166, 456486814660619167, 456486814660619168, 456486814660619169, 456486814660619170, 456486814660619171, 456486814660619172, 456486814660619173, 456486814660619174, 456486814660619175, 456486814660619176], 'cost': 0}"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -212,20 +223,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
     "from pydantic import BaseModel\n",
-    "from typing import List\n",
     "\n",
     "# Simplified output model for search results\n",
     "class MilvusSearchResult(BaseModel):\n",
     "    id: int\n",
     "    text: str\n",
     "\n",
     "class MilvusSearchResults(BaseModel):\n",
-    "    results: List[MilvusSearchResult]\n",
+    "    results: list[MilvusSearchResult]\n",
     "    query: str"
    ]
   },
@@ -243,12 +253,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
     "import json\n",
-    "from typing import List, Dict, Any, Optional\n",
+    "from typing import Any\n",
     "from pymilvus import MilvusClient\n",
     "from agents import function_tool, RunContextWrapper\n",
     "\n",
@@ -307,7 +317,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -331,19 +341,30 @@
     "            agent,\n",
     "            \"Find documents in the 'demo' collection that are similar to this concept: 'information retrieval'\"\n",
     "        )\n",
-    "        print(result.final_output.results)"
+    "        # print(result.final_output.results)\n",
+    "        formatted_results = \"\\n\".join(\n",
+    "            f\"{i+1}. ID: {res.id}, Text: {res.text}\"\n",
+    "            for i, res in enumerate(result.final_output.results)\n",
+    "        )\n",
+    "        print(f\"Search results:\\n{formatted_results}\")\n",
+    "        "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "[MilvusSearchResult(id=456486814660619045, text='Boolean retrieval is one of the earliest information retrieval methods.'), MilvusSearchResult(id=456486814660619071, text='Zero-shot retrieval is gaining traction in open-domain information retrieval.'), MilvusSearchResult(id=456486814660619043, text='Machine learning improves ranking algorithms in information retrieval.'), MilvusSearchResult(id=456486814660619042, text='Vector search is revolutionising modern information retrieval systems.'), MilvusSearchResult(id=456486814660619048, text='Knowledge graphs enhance information retrieval by structuring relationships.')]\n"
+      "Search results:\n",
+      "1. ID: 456486814660619146, Text: Boolean retrieval is one of the earliest information retrieval methods.\n",
+      "2. ID: 456486814660619144, Text: Machine learning improves ranking algorithms in information retrieval.\n",
+      "3. ID: 456486814660619143, Text: Vector search is revolutionising modern information retrieval systems.\n",
+      "4. ID: 456486814660619140, Text: Information retrieval helps users find relevant documents in large datasets.\n",
+      "5. ID: 456486814660619141, Text: Search engines use information retrieval techniques to index and rank web pages.\n"
      ]
     }
    ],
@@ -352,20 +373,36 @@
    ]
   },
   {
+   "attachments": {
+    "74d6c61c-cb1d-4882-868d-f7e9fbd4c021.png": {
+     "image/png": "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"
+    },
+    "a4abc7aa-3e70-4266-8ec8-169ffc83bc26.png": {
+     "image/png": "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"
+    }
+   },
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Next Steps\n",
+    "# ⭐️ Github\n",
+    "We hope you liked this tutorial showcasing how to use Milvus with OpenAI Agents. If you liked it and our project, please give us a star on Github! ⭐\n",
+    "\n",
+    "![image.png](attachment:74d6c61c-cb1d-4882-868d-f7e9fbd4c021.png)\n",
+    "\n",
+    "# 🤝 Add me on Linkedin!\n",
+    "If you have some questions related to Milvus, GenAI, etc, I am Stephen Batifol, you can add me on LinkedIn and I'll gladly help you.\n",
+    "\n",
+    "![image.png](attachment:a4abc7aa-3e70-4266-8ec8-169ffc83bc26.png)\n",
     "\n",
-    "This notebook demonstrates a basic implementation of a Milvus search with OpenAI Agents.\n",
+    "# 💬 Join our Discord\n",
     "\n",
-    "The combination of Milvus's powerful search capabilities and OpenAI's agent framework opens up exciting possibilities for building intelligent search applications!"
+    "If you're interested in learning more about Milvus or you wanna share some feedback, feel free to join our [Discord channel](https://zilliz.com/discord)."
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -383,5 +420,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }