Upload 18 files

chatbot_multiagent.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -27,9 +27,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_core/_api/deprecation.py:141: LangChainDeprecationWarning: The class `GooglePlacesTool` was deprecated in LangChain 0.0.33 and will be removed in 0.3.0. An updated version of the class exists in the langchain-google-community package and should be used instead. To use it run `pip install -U langchain-google-community` and import as `from langchain_google_community import GooglePlacesTool`.\n",
+      "  warn_deprecated(\n",
+      "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_core/_api/deprecation.py:141: LangChainDeprecationWarning: The class `GooglePlacesAPIWrapper` was deprecated in LangChain 0.0.33 and will be removed in 0.3.0. An updated version of the class exists in the langchain-google-community package and should be used instead. To use it run `pip install -U langchain-google-community` and import as `from langchain_google_community import GooglePlacesAPIWrapper`.\n",
+      "  warn_deprecated(\n"
+     ]
+    }
+   ],
    "source": [
     "from langchain_core.messages import HumanMessage\n",
     "import operator\n",
@@ -94,7 +105,7 @@
     "\n",
     "## tools and LLM\n",
     "retriever_tool = Tool(\n",
-    "    name=\"population, community and household expenditures data\",\n",
+    "    name=\"population_community_ousehold_expenditures_data\",\n",
     "    func=retriever.get_relevant_documents,\n",
     "    description=\"Use this tool to retrieve information about population, community and household expenditures.\"\n",
     ")\n",
@@ -125,10 +136,10 @@
     "    )\n",
     "    prompt = prompt.partial(system_message=system_message)\n",
     "    prompt = prompt.partial(tool_names=\", \".join([tool.name for tool in tools]))\n",
-    "    llm_with_tools = llm.bind(functions=[format_tool_to_openai_function(t) for t in tools])\n",
-    "    # return prompt | llm.bind_tools(tools)\n",
-    "    agent = prompt | llm_with_tools\n",
-    "    return agent\n",
+    "    #llm_with_tools = llm.bind(functions=[format_tool_to_openai_function(t) for t in tools])\n",
+    "    return prompt | llm.bind_tools(tools)\n",
+    "    #agent = prompt | llm_with_tools\n",
+    "    #return agent\n",
     "\n",
     "\n",
     "## Define state\n",
@@ -208,11 +219,11 @@
     "workflow.add_conditional_edges(\n",
     "    \"analyst\",\n",
     "    router,\n",
-    "    {\"continue\": \"data collector\", \"call_tool\": \"call_tool\", \"__end__\": END}\n",
+    "    {\"continue\": \"data_collector\", \"call_tool\": \"call_tool\", \"__end__\": END}\n",
     ")\n",
     "\n",
     "workflow.add_conditional_edges(\n",
-    "    \"data collector\",\n",
+    "    \"data_collector\",\n",
     "    router,\n",
     "    {\"call_tool\": \"call_tool\", \"continue\": \"reporter\", \"__end__\": END}\n",
     ")\n",
@@ -220,7 +231,7 @@
     "workflow.add_conditional_edges(\n",
     "    \"reporter\",\n",
     "    router,\n",
-    "    {\"continue\": \"data collector\", \"call_tool\": \"call_tool\", \"__end__\": END}\n",
+    "    {\"continue\": \"data_collector\", \"call_tool\": \"call_tool\", \"__end__\": END}\n",
     ")\n",
     "\n",
     "workflow.add_conditional_edges(\n",
@@ -230,11 +241,7 @@
     "    # this edge will route back to the original agent\n",
     "    # who invoked the tool\n",
     "    lambda x: x[\"sender\"],\n",
-    "    {\n",
-    "        \"data collector\":\"data collector\",\n",
-    "        \"analyst\":\"analyst\",\n",
-    "        \"reporter\":\"reporter\",\n",
-    "        },\n",
+    "    {name:name for name in agent_name},\n",
     ")\n",
     "workflow.add_edge(START, \"analyst\")\n",
     "graph = workflow.compile()"
@@ -242,7 +249,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -257,28 +264,112 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "*********name: analyst\n",
-      "{'analyst': {'messages': [AIMessage(content=\"To assist with the feasibility analysis for a bookstore near New York, I will extract the relevant information:\\n\\n- **Location**: New York\\n- **Keyword**: Bookstore\\n\\nI will now instruct the Data Collector to gather relevant data based on this input. \\n\\nLet's proceed with the data collection.\", additional_kwargs={'function_call': {'arguments': '{\"input_dict\":{\"keyword\":\"bookstore\",\"location_name\":\"New York\",\"radius\":5000,\"place_type\":\"bookstore\"}}', 'name': 'nearby_search'}, 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 98, 'prompt_tokens': 335, 'total_tokens': 433}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_48196bc67a', 'finish_reason': 'function_call', 'logprobs': None}, name='analyst', id='run-f7896776-cbec-4359-93ca-71d0f7fedeb7-0', usage_metadata={'input_tokens': 335, 'output_tokens': 98, 'total_tokens': 433})], 'sender': 'analyst'}}\n",
-      "*********name: data collector\n",
-      "{'data collector': {'messages': [AIMessage(content='', additional_kwargs={'function_call': {'arguments': '{\"location\":\"New York\"}', 'name': 'find_place_from_text'}, 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 17, 'prompt_tokens': 592, 'total_tokens': 609}, 'model_name': 'gpt-4o-mini-2024-07-18', 'system_fingerprint': 'fp_48196bc67a', 'finish_reason': 'function_call', 'logprobs': None}, name='data collector', id='run-28ebbebf-faad-44a5-b972-29b6f8bc3455-0', usage_metadata={'input_tokens': 592, 'output_tokens': 17, 'total_tokens': 609})], 'sender': 'data collector'}}\n",
-      "*********name: reporter\n"
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "Name: analyst\n",
+      "Tool Calls:\n",
+      "  google_places (call_2Hbm9MiYjKsCMj4pttLAwZmf)\n",
+      " Call ID: call_2Hbm9MiYjKsCMj4pttLAwZmf\n",
+      "  Args:\n",
+      "    query: มาบุญครอง\n",
+      "  nearby_search (call_6VClh72nZWUaQJ7NQqkxnv6I)\n",
+      " Call ID: call_6VClh72nZWUaQJ7NQqkxnv6I\n",
+      "  Args:\n",
+      "    input_dict: {'keyword': 'coffee shop', 'location_name': 'มาบุญครอง', 'radius': 1000, 'place_type': 'cafe'}\n",
+      "=================================\u001b[1m Tool Message \u001b[0m=================================\n",
+      "Name: google_places\n",
+      "\n",
+      "1. MBK Center\n",
+      "Address: 444 Phaya Thai Rd, Khwaeng Wang Mai, Pathum Wan, Krung Thep Maha Nakhon 10330, Thailand\n",
+      "Google place ID: ChIJ7TZ3I5Of4jAR3lZ2lx-zXkA\n",
+      "Phone: 02 853 9000\n",
+      "Website: https://www.mbk-center.co.th/\n",
+      "\n",
+      "\n",
+      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
+      "Name: analyst\n",
+      "\n",
+      "I have gathered the following information regarding coffee shops near MBK Center (มาบุญครอง):\n",
+      "\n",
+      "### Coffee Shops Nearby:\n",
+      "1. **BEANS Coffee Roaster Paragon**\n",
+      "   - Address: 991/1 Rama I Rd, Pathum Wan\n",
+      "   - Rating: 5\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7458781, Longitude 100.5341476\n",
+      "\n",
+      "2. **Redwood Coffee and Eatery**\n",
+      "   - Address: 1873 Rama IV Rd, Khlong Tan Nuea, Watthana\n",
+      "   - Rating: 4.8\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7335441, Longitude 100.5377224\n",
+      "\n",
+      "3. **LabyRinth Cafe**\n",
+      "   - Address: 1527 Rama IV Rd, Pathum Wan\n",
+      "   - Rating: 4.5\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7338764, Longitude 100.5266737\n",
+      "\n",
+      "4. **Sip 'n Drip**\n",
+      "   - Address: 36, 6 Kasem San 1 Alley, Wang Mai, Pathum Wan\n",
+      "   - Rating: 4.9\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7477989, Longitude 100.5296324\n",
+      "\n",
+      "5. **Café BAGA Central World**\n",
+      "   - Address: 3rd Floor, CentralWorld, Ratchadamri Rd, Pathum Wan\n",
+      "   - Rating: 4.7\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7470656, Longitude 100.5397062\n",
+      "\n",
+      "6. **CRANNIES Coffee & Brunch**\n",
+      "   - Address: 126 ถนนเพชรบุรี 50 Wang Mai, Pathum Wan\n",
+      "   - Rating: 5\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7344961, Longitude 100.5268998\n",
+      "\n",
+      "7. **Alto Coffee Roasters (Central@Central World)**\n",
+      "   - Address: 5th floor เซ็นทรัลเวิลด์, Ratchadamri Rd, Pathum Wan\n",
+      "   - Rating: 4.4\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7453043, Longitude 100.5393611\n",
+      "\n",
+      "8. **Red Diamond Cafe at Central World 5th Floor**\n",
+      "   - Address: Centara Grand and Bangkok Convention Centre, 5th floor, Khwaeng Pathum Wan, Pathum Wan\n",
+      "   - Rating: 4.5\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.7465966, Longitude 100.5393615\n",
+      "\n",
+      "9. **BrewLab Cafe Roompini**\n",
+      "   - Address: 231/6 Sarasin Rd, Lumphini, Pathum Wan\n",
+      "   - Rating: 4.8\n",
+      "   - Open Now: Yes\n",
+      "   - Location: Latitude 13.734501, Longitude 100.5393547\n",
+      "\n",
+      "10. **Casa Lapin Specialty Coffee x Ratchathewi**\n",
+      "    - Address: 318 Phaya Thai Rd, Khwaeng Thanon Phetchaburi, Khet Ratchathewi\n",
+      "    - Rating: 4.2\n",
+      "    - Open Now: Yes\n",
+      "    - Location: Latitude 13.75069, Longitude 100.5312\n",
+      "\n",
+      "### Next Steps:\n",
+      "To analyze the population data for the area, please specify the type of demographic information you are interested in (e.g., total population, age distribution, income levels, etc.).\n"
      ]
     },
     {
-     "ename": "BadRequestError",
-     "evalue": "Error code: 400 - {'error': {'message': \"Invalid 'messages[3].name': string does not match pattern. Expected a string that matches the pattern '^[a-zA-Z0-9_-]+$'.\", 'type': 'invalid_request_error', 'param': 'messages[3].name', 'code': 'invalid_value'}}",
+     "ename": "InternalServerError",
+     "evalue": "Error code: 500 - {'error': {'message': 'The model produced invalid content. Consider modifying your prompt if you are seeing this error persistently.', 'type': 'model_error', 'param': None, 'code': None}}",
      "output_type": "error",
      "traceback": [
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mBadRequestError\u001b[0m                           Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[11], line 16\u001b[0m\n\u001b[1;32m      3\u001b[0m graph \u001b[38;5;241m=\u001b[39m workflow\u001b[38;5;241m.\u001b[39mcompile()\n\u001b[1;32m      5\u001b[0m events \u001b[38;5;241m=\u001b[39m graph\u001b[38;5;241m.\u001b[39mstream(\n\u001b[1;32m      6\u001b[0m     {\n\u001b[1;32m      7\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m: [\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     14\u001b[0m     {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrecursion_limit\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m20\u001b[39m},\n\u001b[1;32m     15\u001b[0m )\n\u001b[0;32m---> 16\u001b[0m \u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mevents\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m     17\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43mprint\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     18\u001b[0m     \u001b[38;5;66;03m# a = list(s.items())[0]\u001b[39;00m\n\u001b[1;32m     19\u001b[0m     \u001b[38;5;66;03m# a[1]['messages'][0].pretty_print()\u001b[39;00m\n",
+      "\u001b[0;31mInternalServerError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[5], line 16\u001b[0m\n\u001b[1;32m      3\u001b[0m graph \u001b[38;5;241m=\u001b[39m workflow\u001b[38;5;241m.\u001b[39mcompile()\n\u001b[1;32m      5\u001b[0m events \u001b[38;5;241m=\u001b[39m graph\u001b[38;5;241m.\u001b[39mstream(\n\u001b[1;32m      6\u001b[0m     {\n\u001b[1;32m      7\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m: [\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     14\u001b[0m     {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrecursion_limit\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m20\u001b[39m},\n\u001b[1;32m     15\u001b[0m )\n\u001b[0;32m---> 16\u001b[0m \u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mevents\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m     17\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;66;43;03m# print(s)\u001b[39;49;00m\n\u001b[1;32m     18\u001b[0m \u001b[43m    \u001b[49m\u001b[43ma\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m     19\u001b[0m \u001b[43m    \u001b[49m\u001b[43ma\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmessages\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpretty_print\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langgraph/pregel/__init__.py:1018\u001b[0m, in \u001b[0;36mPregel.stream\u001b[0;34m(self, input, config, stream_mode, output_keys, interrupt_before, interrupt_after, debug)\u001b[0m\n\u001b[1;32m   1015\u001b[0m         \u001b[38;5;28;01mdel\u001b[39;00m fut, task\n\u001b[1;32m   1017\u001b[0m \u001b[38;5;66;03m# panic on failure or timeout\u001b[39;00m\n\u001b[0;32m-> 1018\u001b[0m \u001b[43m_panic_or_proceed\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdone\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minflight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstep\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1019\u001b[0m \u001b[38;5;66;03m# don't keep futures around in memory longer than needed\u001b[39;00m\n\u001b[1;32m   1020\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m done, inflight, futures\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langgraph/pregel/__init__.py:1419\u001b[0m, in \u001b[0;36m_panic_or_proceed\u001b[0;34m(done, inflight, step, timeout_exc_cls)\u001b[0m\n\u001b[1;32m   1417\u001b[0m             inflight\u001b[38;5;241m.\u001b[39mpop()\u001b[38;5;241m.\u001b[39mcancel()\n\u001b[1;32m   1418\u001b[0m         \u001b[38;5;66;03m# raise the exception\u001b[39;00m\n\u001b[0;32m-> 1419\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m exc\n\u001b[1;32m   1421\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m inflight:\n\u001b[1;32m   1422\u001b[0m     \u001b[38;5;66;03m# if we got here means we timed out\u001b[39;00m\n\u001b[1;32m   1423\u001b[0m     \u001b[38;5;28;01mwhile\u001b[39;00m inflight:\n\u001b[1;32m   1424\u001b[0m         \u001b[38;5;66;03m# cancel all pending tasks\u001b[39;00m\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langgraph/pregel/executor.py:60\u001b[0m, in \u001b[0;36mBackgroundExecutor.done\u001b[0;34m(self, task)\u001b[0m\n\u001b[1;32m     58\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdone\u001b[39m(\u001b[38;5;28mself\u001b[39m, task: concurrent\u001b[38;5;241m.\u001b[39mfutures\u001b[38;5;241m.\u001b[39mFuture) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m     59\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 60\u001b[0m         \u001b[43mtask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresult\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     61\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m GraphInterrupt:\n\u001b[1;32m     62\u001b[0m         \u001b[38;5;66;03m# This exception is an interruption signal, not an error\u001b[39;00m\n\u001b[1;32m     63\u001b[0m         \u001b[38;5;66;03m# so we don't want to re-raise it on exit\u001b[39;00m\n\u001b[1;32m     64\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtasks\u001b[38;5;241m.\u001b[39mpop(task)\n",
@@ -288,7 +379,7 @@
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langgraph/pregel/retry.py:25\u001b[0m, in \u001b[0;36mrun_with_retry\u001b[0;34m(task, retry_policy)\u001b[0m\n\u001b[1;32m     23\u001b[0m task\u001b[38;5;241m.\u001b[39mwrites\u001b[38;5;241m.\u001b[39mclear()\n\u001b[1;32m     24\u001b[0m \u001b[38;5;66;03m# run the task\u001b[39;00m\n\u001b[0;32m---> 25\u001b[0m \u001b[43mtask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mproc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minput\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtask\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     26\u001b[0m \u001b[38;5;66;03m# if successful, end\u001b[39;00m\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mbreak\u001b[39;00m\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_core/runnables/base.py:2876\u001b[0m, in \u001b[0;36mRunnableSequence.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   2874\u001b[0m context\u001b[38;5;241m.\u001b[39mrun(_set_config_context, config)\n\u001b[1;32m   2875\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m i \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 2876\u001b[0m     \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2877\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   2878\u001b[0m     \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m context\u001b[38;5;241m.\u001b[39mrun(step\u001b[38;5;241m.\u001b[39minvoke, \u001b[38;5;28minput\u001b[39m, config)\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langgraph/utils.py:102\u001b[0m, in \u001b[0;36mRunnableCallable.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    100\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m accepts_config(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfunc):\n\u001b[1;32m    101\u001b[0m         kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mconfig\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m config\n\u001b[0;32m--> 102\u001b[0m     ret \u001b[38;5;241m=\u001b[39m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    103\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, Runnable) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrecurse:\n\u001b[1;32m    104\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m ret\u001b[38;5;241m.\u001b[39minvoke(\u001b[38;5;28minput\u001b[39m, config)\n",
-      "Cell \u001b[0;32mIn[9], line 112\u001b[0m, in \u001b[0;36magent_node\u001b[0;34m(state, agent, name)\u001b[0m\n\u001b[1;32m    110\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21magent_node\u001b[39m(state, agent, name):\n\u001b[1;32m    111\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m*********name: \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m+\u001b[39m name)\n\u001b[0;32m--> 112\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43magent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    113\u001b[0m     \u001b[38;5;66;03m# We convert the agent output into a format that is suitable to append to the global state\u001b[39;00m\n\u001b[1;32m    114\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(result, ToolMessage):\n",
+      "Cell \u001b[0;32mIn[3], line 111\u001b[0m, in \u001b[0;36magent_node\u001b[0;34m(state, agent, name)\u001b[0m\n\u001b[1;32m    110\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21magent_node\u001b[39m(state, agent, name):\n\u001b[0;32m--> 111\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43magent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstate\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    112\u001b[0m     \u001b[38;5;66;03m# We convert the agent output into a format that is suitable to append to the global state\u001b[39;00m\n\u001b[1;32m    113\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(result, ToolMessage):\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_core/runnables/base.py:2878\u001b[0m, in \u001b[0;36mRunnableSequence.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   2876\u001b[0m             \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m context\u001b[38;5;241m.\u001b[39mrun(step\u001b[38;5;241m.\u001b[39minvoke, \u001b[38;5;28minput\u001b[39m, config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m   2877\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2878\u001b[0m             \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m context\u001b[38;5;241m.\u001b[39mrun(step\u001b[38;5;241m.\u001b[39minvoke, \u001b[38;5;28minput\u001b[39m, config)\n\u001b[1;32m   2879\u001b[0m \u001b[38;5;66;03m# finish the root run\u001b[39;00m\n\u001b[1;32m   2880\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_core/runnables/base.py:5094\u001b[0m, in \u001b[0;36mRunnableBindingBase.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   5088\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m   5089\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   5090\u001b[0m     \u001b[38;5;28minput\u001b[39m: Input,\n\u001b[1;32m   5091\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   5092\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[1;32m   5093\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Output:\n\u001b[0;32m-> 5094\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbound\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   5095\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5096\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_merge_configs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5097\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   5098\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:276\u001b[0m, in \u001b[0;36mBaseChatModel.invoke\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m    265\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m    266\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    267\u001b[0m     \u001b[38;5;28minput\u001b[39m: LanguageModelInput,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    271\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m    272\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m BaseMessage:\n\u001b[1;32m    273\u001b[0m     config \u001b[38;5;241m=\u001b[39m ensure_config(config)\n\u001b[1;32m    274\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m cast(\n\u001b[1;32m    275\u001b[0m         ChatGeneration,\n\u001b[0;32m--> 276\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenerate_prompt\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    277\u001b[0m \u001b[43m            \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_convert_input\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    278\u001b[0m \u001b[43m            \u001b[49m\u001b[43mstop\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    279\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcallbacks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    280\u001b[0m \u001b[43m            \u001b[49m\u001b[43mtags\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtags\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    281\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmetadata\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    282\u001b[0m \u001b[43m            \u001b[49m\u001b[43mrun_name\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrun_name\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    283\u001b[0m \u001b[43m            \u001b[49m\u001b[43mrun_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpop\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mrun_id\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    284\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    285\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mgenerations[\u001b[38;5;241m0\u001b[39m][\u001b[38;5;241m0\u001b[39m],\n\u001b[1;32m    286\u001b[0m     )\u001b[38;5;241m.\u001b[39mmessage\n",
@@ -301,31 +392,35 @@
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/resources/chat/completions.py:668\u001b[0m, in \u001b[0;36mCompletions.create\u001b[0;34m(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, parallel_tool_calls, presence_penalty, response_format, seed, service_tier, stop, stream, stream_options, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m    633\u001b[0m \u001b[38;5;129m@required_args\u001b[39m([\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m], [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[1;32m    634\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcreate\u001b[39m(\n\u001b[1;32m    635\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    665\u001b[0m     timeout: \u001b[38;5;28mfloat\u001b[39m \u001b[38;5;241m|\u001b[39m httpx\u001b[38;5;241m.\u001b[39mTimeout \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m|\u001b[39m NotGiven \u001b[38;5;241m=\u001b[39m NOT_GIVEN,\n\u001b[1;32m    666\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ChatCompletion \u001b[38;5;241m|\u001b[39m Stream[ChatCompletionChunk]:\n\u001b[1;32m    667\u001b[0m     validate_response_format(response_format)\n\u001b[0;32m--> 668\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    669\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m/chat/completions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    670\u001b[0m \u001b[43m        \u001b[49m\u001b[43mbody\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    671\u001b[0m \u001b[43m            \u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m    672\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmessages\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    673\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmodel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    674\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfrequency_penalty\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfrequency_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    675\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfunction_call\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunction_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    676\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfunctions\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunctions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    677\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlogit_bias\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogit_bias\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    678\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlogprobs\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mlogprobs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    679\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmax_tokens\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    680\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mn\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    681\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mparallel_tool_calls\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mparallel_tool_calls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    682\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpresence_penalty\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpresence_penalty\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    683\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mresponse_format\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m 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\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstream\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    688\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstream_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    689\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtemperature\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    690\u001b[0m \u001b[43m                \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtool_choice\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m 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\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43muser\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43muser\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    695\u001b[0m \u001b[43m            \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    696\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcompletion_create_params\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mCompletionCreateParams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    697\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    698\u001b[0m \u001b[43m        \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    699\u001b[0m \u001b[43m            \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtimeout\u001b[49m\n\u001b[1;32m    700\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    701\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mChatCompletion\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    702\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    703\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mStream\u001b[49m\u001b[43m[\u001b[49m\u001b[43mChatCompletionChunk\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    704\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:1260\u001b[0m, in \u001b[0;36mSyncAPIClient.post\u001b[0;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1246\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\n\u001b[1;32m   1247\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   1248\u001b[0m     path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1255\u001b[0m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1256\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[1;32m   1257\u001b[0m     opts \u001b[38;5;241m=\u001b[39m FinalRequestOptions\u001b[38;5;241m.\u001b[39mconstruct(\n\u001b[1;32m   1258\u001b[0m         method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpost\u001b[39m\u001b[38;5;124m\"\u001b[39m, url\u001b[38;5;241m=\u001b[39mpath, json_data\u001b[38;5;241m=\u001b[39mbody, files\u001b[38;5;241m=\u001b[39mto_httpx_files(files), \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39moptions\n\u001b[1;32m   1259\u001b[0m     )\n\u001b[0;32m-> 1260\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:937\u001b[0m, in \u001b[0;36mSyncAPIClient.request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    928\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrequest\u001b[39m(\n\u001b[1;32m    929\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    930\u001b[0m     cast_to: Type[ResponseT],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    935\u001b[0m     stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    936\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m ResponseT \u001b[38;5;241m|\u001b[39m _StreamT:\n\u001b[0;32m--> 937\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    938\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    939\u001b[0m \u001b[43m        \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    940\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    941\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    942\u001b[0m \u001b[43m        \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining_retries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    943\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1024\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[1;32m   1025\u001b[0m     err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m-> 1026\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1027\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1028\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1029\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1030\u001b[0m \u001b[43m        \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1031\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1032\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1033\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1035\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[1;32m   1036\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[1;32m   1037\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:1075\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1071\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[1;32m   1072\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[1;32m   1073\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[0;32m-> 1075\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1076\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1077\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1078\u001b[0m \u001b[43m    \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1079\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1080\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1081\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:1026\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1024\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m retries \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_retry(err\u001b[38;5;241m.\u001b[39mresponse):\n\u001b[1;32m   1025\u001b[0m     err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mclose()\n\u001b[0;32m-> 1026\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_retry_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1027\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1028\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1029\u001b[0m \u001b[43m        \u001b[49m\u001b[43mretries\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1030\u001b[0m \u001b[43m        \u001b[49m\u001b[43merr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mresponse\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1031\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1032\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1033\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1035\u001b[0m \u001b[38;5;66;03m# If the response is streamed then we need to explicitly read the response\u001b[39;00m\n\u001b[1;32m   1036\u001b[0m \u001b[38;5;66;03m# to completion before attempting to access the response text.\u001b[39;00m\n\u001b[1;32m   1037\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mis_closed:\n",
+      "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:1075\u001b[0m, in \u001b[0;36mSyncAPIClient._retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1071\u001b[0m \u001b[38;5;66;03m# In a synchronous context we are blocking the entire thread. Up to the library user to run the client in a\u001b[39;00m\n\u001b[1;32m   1072\u001b[0m \u001b[38;5;66;03m# different thread if necessary.\u001b[39;00m\n\u001b[1;32m   1073\u001b[0m time\u001b[38;5;241m.\u001b[39msleep(timeout)\n\u001b[0;32m-> 1075\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1076\u001b[0m \u001b[43m    \u001b[49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1077\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1078\u001b[0m \u001b[43m    \u001b[49m\u001b[43mremaining_retries\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mremaining\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1079\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1080\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream_cls\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1081\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
       "File \u001b[0;32m/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/_base_client.py:1041\u001b[0m, in \u001b[0;36mSyncAPIClient._request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1038\u001b[0m         err\u001b[38;5;241m.\u001b[39mresponse\u001b[38;5;241m.\u001b[39mread()\n\u001b[1;32m   1040\u001b[0m     log\u001b[38;5;241m.\u001b[39mdebug(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mRe-raising status error\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m-> 1041\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_make_status_error_from_response(err\u001b[38;5;241m.\u001b[39mresponse) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1043\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_process_response(\n\u001b[1;32m   1044\u001b[0m     cast_to\u001b[38;5;241m=\u001b[39mcast_to,\n\u001b[1;32m   1045\u001b[0m     options\u001b[38;5;241m=\u001b[39moptions,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1049\u001b[0m     retries_taken\u001b[38;5;241m=\u001b[39moptions\u001b[38;5;241m.\u001b[39mget_max_retries(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmax_retries) \u001b[38;5;241m-\u001b[39m retries,\n\u001b[1;32m   1050\u001b[0m )\n",
-      "\u001b[0;31mBadRequestError\u001b[0m: Error code: 400 - {'error': {'message': \"Invalid 'messages[3].name': string does not match pattern. Expected a string that matches the pattern '^[a-zA-Z0-9_-]+$'.\", 'type': 'invalid_request_error', 'param': 'messages[3].name', 'code': 'invalid_value'}}"
+      "\u001b[0;31mInternalServerError\u001b[0m: Error code: 500 - {'error': {'message': 'The model produced invalid content. Consider modifying your prompt if you are seeing this error persistently.', 'type': 'model_error', 'param': None, 'code': None}}"
      ]
     }
    ],
    "source": [
-    "question = \"Feasibility analysis for a bookstore near New york\"\n",
-    "\n",
-    "graph = workflow.compile()\n",
-    "\n",
-    "events = graph.stream(\n",
-    "    {\n",
-    "        \"messages\": [\n",
-    "            HumanMessage(\n",
-    "                question\n",
-    "            )\n",
-    "        ],\n",
-    "    },\n",
-    "    # Maximum number of steps to take in the graph\n",
-    "    {\"recursion_limit\": 20},\n",
-    ")\n",
-    "for s in events:\n",
-    "    print(s)\n",
-    "    # a = list(s.items())[0]\n",
-    "    # a[1]['messages'][0].pretty_print()"
+    "# question = \"ค้นหาร้านกาแฟใกล้มาบุญครอง พร้อมวิเคราะห์จำนวนประชากร\"\n",
+    "\n",
+    "# graph = workflow.compile()\n",
+    "\n",
+    "# events = graph.stream(\n",
+    "#     {\n",
+    "#         \"messages\": [\n",
+    "#             HumanMessage(\n",
+    "#                 question\n",
+    "#             )\n",
+    "#         ],\n",
+    "#     },\n",
+    "#     # Maximum number of steps to take in the graph\n",
+    "#     {\"recursion_limit\": 20},\n",
+    "# )\n",
+    "# for s in events:\n",
+    "#     # print(s)\n",
+    "#     a = list(s.items())[0]\n",
+    "#     a[1]['messages'][0].pretty_print()"
    ]
   },
   {
@@ -341,7 +436,7 @@
     "        {\n",
     "            \"messages\": [\n",
     "                HumanMessage(\n",
-    "                    question\n",
+    "                    user_input\n",
     "                )\n",
     "            ],\n",
     "        },\n",

chatbot_multiagent.py

@@ -75,7 +75,7 @@ retriever = vectorstore.as_retriever()
 
 ## tools and LLM
 retriever_tool = Tool(
-    name="population, community and household expenditures data",
+    name="population_community_ousehold_expenditures_data",
     func=retriever.get_relevant_documents,
     description="Use this tool to retrieve information about population, community and household expenditures."
 )
@@ -106,10 +106,10 @@ def create_agent(llm, tools, system_message: str):
     )
     prompt = prompt.partial(system_message=system_message)
     prompt = prompt.partial(tool_names=", ".join([tool.name for tool in tools]))
-    llm_with_tools = llm.bind(functions=[format_tool_to_openai_function(t) for t in tools])
-    # return prompt | llm.bind_tools(tools)
-    agent = prompt | llm_with_tools
-    return agent
+    #llm_with_tools = llm.bind(functions=[format_tool_to_openai_function(t) for t in tools])
+    return prompt | llm.bind_tools(tools)
+    #agent = prompt | llm_with_tools
+    #return agent
 
 
 ## Define state
@@ -189,11 +189,11 @@ workflow.add_node("call_tool", tool_node)
 workflow.add_conditional_edges(
     "analyst",
     router,
-    {"continue": "data collector", "call_tool": "call_tool", "__end__": END}
+    {"continue": "data_collector", "call_tool": "call_tool", "__end__": END}
 )
 
 workflow.add_conditional_edges(
-    "data collector",
+    "data_collector",
     router,
     {"call_tool": "call_tool", "continue": "reporter", "__end__": END}
 )
@@ -201,7 +201,7 @@ workflow.add_conditional_edges(
 workflow.add_conditional_edges(
     "reporter",
     router,
-    {"continue": "data collector", "call_tool": "call_tool", "__end__": END}
+    {"continue": "data_collector", "call_tool": "call_tool", "__end__": END}
 )
 
 workflow.add_conditional_edges(
@@ -211,11 +211,7 @@ workflow.add_conditional_edges(
     # this edge will route back to the original agent
     # who invoked the tool
     lambda x: x["sender"],
-    {
-        "data collector":"data collector",
-        "analyst":"analyst",
-        "reporter":"reporter",
-        },
+    {name:name for name in agent_name},
 )
 workflow.add_edge(START, "analyst")
 graph = workflow.compile()
@@ -230,7 +226,25 @@ graph = workflow.compile()
 #     pass
 
 # %%
-
+# question = "ค้นหาร้านกาแฟใกล้มาบุญครอง พร้อมวิเคราะห์จำนวนประชากร"
+
+# graph = workflow.compile()
+
+# events = graph.stream(
+#     {
+#         "messages": [
+#             HumanMessage(
+#                 question
+#             )
+#         ],
+#     },
+#     # Maximum number of steps to take in the graph
+#     {"recursion_limit": 20},
+# )
+# for s in events:
+#     # print(s)
+#     a = list(s.items())[0]
+#     a[1]['messages'][0].pretty_print()
 
 # %%
 def submitUserMessage(user_input: str) -> str:

prompt.py

@@ -1,43 +1,25 @@
 agent_meta = [
     {
         "name": "analyst",
-        "prompt": """
-        You are the Analyst responsible for extracting key information from the user and guiding the data collection process. When the user asks about analyzing a location for a business opportunity, you will:
-        Ensure that all communications and data are handled in English
-        - Extract the location the user wants to analyze and the keyword representing the type of place (e.g., “shop,” “coffee shop,” which represents the competitor).
-        - Communicate this information clearly to the Data Collector, instructing them to gather relevant data based on the user’s input.
-        """
+        "prompt": """You are the Analyst responsible for understanding the user's needs and guiding the data collection process. 
+        When the user asks about opening a shop or business at a specific location, 
+        you will: Comprehend the user's request and determine what analytical insights(about feasibility analysis) they need about competitors and market opportunities. 
+        Identify the necessary data required for analysis, including information about the place nearby, district or location of the specified place (for competator analysis),
+        and type of community, household expenditures, and population in the district(for market opportunities, and feasibility analysis). 
+        Clearly communicate these data requirements to the Data Collector. Additionally keep the converstion in English."""
     },
     {
         "name": "data collector",
-        "prompt": """
-        You are the Data Collector responsible for gathering data based on the Analyst’s instructions. When you receive a request that are the locacation and the type of place from the Analyst, you will:
-	    -	Use the tools to gather data related to the location and type of place(keyword) provided by the Analyst.
-	    -	Provide the following data:
-	    -	The number of competitors.
-	    -	A list of competitors nearby.
-	    -	Products sold by competitors (assume if no specific data is provided).
-	    -	Number of population nearby.
-	    -	Community type.
-	    -	Household expenditures.
-	    -	Population data.
-	    - The tools at your disposal include:
-	    1.	Population, Community, and Household Expenditures Data: Contains community type by district, household expenditures by province, and population data by district.
-	    2.	find_place_from_text: Provides address (district, province), and name of the place.
-	    3.	nearby_search: Provides a list of competitors nearby according to the keyword, including address, location, name, opening hours, rating, and plus code.
-	    - After collecting the data, send it to the Reporter. Ensure that all communications and data are handled in English.
-        """
+        "prompt": """You are the Data Collector responsible for gathering data based on the Analyst's instructions. 
+        When you receive a request from the Analyst, you will: Use the necessary tools to gather data related to the specified location, 
+        including information about nearby places, districts, community types, household expenditures, and population demographics. 
+        Then send the data to Reporter. Additionally keep the converstion in English."""
     },
     {
         "name": "reporter",
-        "prompt": """
-        You are the Reporter responsible for feasibility analysis . You role is to compiling the data into a clear and informative report for the user. When you receive the data from the Data Collector, you will:
-        Ensure that all communications and data are handled in English 
-	    -	Organize and analyze the data to generate insights about the competitive landscape and market opportunities at the specified location.
-	    -	Ensure that your report includes both numerical data (such as the number of competitors, population figures, and household expenditures) and analytical insights (such as market opportunities and recommendations).
-	    -	If the Data Collector is unable to find certain data(or not povide data anymore), you will still provide a final answer based on the available information.
-	    -	Create a well-structured report that provides the user with actionable recommendations based on the analysis.
-        -   Don't forget to give Descriptive anlytical summary at last.
-        """
+        "prompt": """You are the Reporter responsible for compiling the data into a clear and informative report for the user. 
+        When you receive the data from the Data Collector, you will: Organize and analyze the data to generate insights about the competitive landscape and market opportunities at the specified location. 
+        Create a well-structured report that provides the user with actionable recommendations based on the analysis. 
+        Ensure the report is clear, concise, and delivered in the same language as the user's original request. But it okay if it not have some data povide."""
     }
 ]

tools.py

@@ -19,6 +19,11 @@ def find_place_from_text(location:str):
     location: {r['geometry']['location']}\n
     location_name: {r['name']}\n
     """
+    # return f"""
+    # address: {r['formatted_address']}\n
+    # location: {r['geometry']['location']}\n
+    # location_name: {r['name']}\n
+    # """
     
 # def nearby_search(keyword:str, location:str, radius=2000, place_type=None):
 #     """Searches for many places nearby the location based on a keyword. using keyword like \"coffee shop\", \"restaurants\". radius is the range to search from the location"""
@@ -69,6 +74,14 @@ def nearby_search(input_dict: NearbySearchInput):
         rating: {rating}\n
         plus code: {plus_code}\n\n
         """
+        
+        # strout += f"""
+        # address: {address}\n
+        # lacation_name: {name}\n
+        # opening hours: {opening_hours}\n
+        # rating: {rating}\n
+        # plus code: {plus_code}\n\n
+        # """
     return strout
 
 
@@ -76,10 +89,13 @@ def nearby_search(input_dict: NearbySearchInput):
 # gplace_tools.py
 from langgraph.prebuilt import ToolNode
 from langchain_core.tools import tool
+from langchain_community.tools import GooglePlacesTool
 
-find_place_from_text = tool(find_place_from_text)
+# find_place_from_text = tool(find_place_from_text)
+find_place_from_text = GooglePlacesTool()
 nearby_search = tool(nearby_search)
 
+
 tools = [find_place_from_text, nearby_search]
 
 # Create ToolNodes for each tool

user_question_testsets.txt

@@ -0,0 +1,14 @@
+coffee shop near mbk center
+วิเคราะห์การเปิดร้านกาแฟใกล้มาบุญครอง
+วิเคราะห์ร้านอาหารแถวลุมพินี เซ็นเตอร์ ลาดพร้าว
+ค้นหาร้านกาแฟใกล้มาบุญครอง พร้อมวิเคราะห์จำนวนประชากร
+Coffee shop near Central World
+Analyze the feasibility of opening a restaurant near Siam Paragon
+Analyze competitors of a bakery near Chatuchak Market
+Search for grocery stores near Victory Monument and analyze the population
+Feasibility analysis for a bookstore near Thonglor
+ร้านกาแฟใกล้เซ็นทรัลเวิลด์
+วิเคราะห์การเปิดร้านอาหารใกล้สยามพารากอน
+วิเคราะห์คู่แข่งของร้านเบเกอรี่ใกล้ตลาดจตุจักร
+ค้นหาร้านของชำใกล้อนุสาวรีย์ชัยฯ พร้อมวิเคราะห์จำนวนประชากร
+วิเคราะห์ความเป็นไปได้ในการเปิดร้านหนังสือใกล้ทองหล่อ