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Community: Adding tool calling and some new parameters to the langchain-predictionguard docs. (#30953)
- [x] **PR message**: - **Description:** Updates the documentation for the langchain-predictionguard package, adding tool calling functionality and some new parameters.
This commit is contained in:
Jacob Mansdorfer
GitHub
parent
8574442c57
commit
e8a84b05a4
@ -57,8 +57,8 @@
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"cell_type": "code",
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@ -70,7 +70,7 @@
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],
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"id": "fa57fba89276da13",
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"outputs": [],
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"execution_count": 1
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"execution_count": 2
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@ -82,12 +82,25 @@
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"id": "87dc1742af7b053"
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}
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},
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"cell_type": "code",
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"source": "%pip install -qU langchain-predictionguard",
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"id": "b816ae8553cba021",
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"outputs": [],
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"execution_count": null
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"execution_count": 3
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},
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{
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"cell_type": "markdown",
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@ -103,13 +116,13 @@
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"metadata": {
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"start_time": "2025-04-21T18:23:39.666881Z"
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}
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},
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"source": "from langchain_predictionguard import ChatPredictionGuard",
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"outputs": [],
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"execution_count": 2
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"execution_count": 4
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},
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{
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"cell_type": "code",
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@ -117,8 +130,8 @@
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"metadata": {
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"id": "Ua7Mw1N4HcER",
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"start_time": "2024-11-08T19:44:54.502846Z"
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"end_time": "2025-04-21T18:23:41.590296Z",
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"start_time": "2025-04-21T18:23:41.253237Z"
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}
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},
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"source": [
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@ -126,7 +139,7 @@
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"chat = ChatPredictionGuard(model=\"Hermes-3-Llama-3.1-8B\")"
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],
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"outputs": [],
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"execution_count": 3
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"execution_count": 5
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},
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{
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"metadata": {},
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@ -221,6 +234,132 @@
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],
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"execution_count": 6
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"## Tool Calling\n",
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"\n",
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"Prediction Guard has a tool calling API that lets you describe tools and their arguments, which enables the model return a JSON object with a tool to call and the inputs to that tool. Tool-calling is very useful for building tool-using chains and agents, and for getting structured outputs from models more generally.\n"
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],
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"id": "1227780d6e6728ba"
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"### ChatPredictionGuard.bind_tools()\n",
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"\n",
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"Using `ChatPredictionGuard.bind_tools()`, you can pass in Pydantic classes, dict schemas, and Langchain tools as tools to the model, which are then reformatted to allow for use by the model."
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],
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"id": "23446aa52e01d1ba"
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},
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{
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"metadata": {},
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"cell_type": "code",
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"outputs": [],
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"execution_count": null,
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"source": [
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"from pydantic import BaseModel, Field\n",
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"\n",
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"\n",
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"class GetWeather(BaseModel):\n",
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" \"\"\"Get the current weather in a given location\"\"\"\n",
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"\n",
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" location: str = Field(..., description=\"The city and state, e.g. San Francisco, CA\")\n",
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"\n",
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"\n",
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"class GetPopulation(BaseModel):\n",
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" \"\"\"Get the current population in a given location\"\"\"\n",
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"\n",
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" location: str = Field(..., description=\"The city and state, e.g. San Francisco, CA\")\n",
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"\n",
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"\n",
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"llm_with_tools = chat.bind_tools(\n",
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" [GetWeather, GetPopulation]\n",
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" # strict = True # enforce tool args schema is respected\n",
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")"
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],
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"id": "135efb0bfc5916c1"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-21T18:42:41.834079Z",
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"start_time": "2025-04-21T18:42:40.289095Z"
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}
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},
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"cell_type": "code",
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"source": [
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"ai_msg = llm_with_tools.invoke(\n",
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" \"Which city is hotter today and which is bigger: LA or NY?\"\n",
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")\n",
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"ai_msg"
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],
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"id": "8136f19a8836cd58",
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'chatcmpl-tool-b1204a3c70b44cd8802579df48df0c8c', 'type': 'function', 'index': 0, 'function': {'name': 'GetWeather', 'arguments': '{\"location\": \"Los Angeles, CA\"}'}}, {'id': 'chatcmpl-tool-e299116c05bf4ce498cd6042928ae080', 'type': 'function', 'index': 0, 'function': {'name': 'GetWeather', 'arguments': '{\"location\": \"New York, NY\"}'}}, {'id': 'chatcmpl-tool-19502a60f30348669ffbac00ff503388', 'type': 'function', 'index': 0, 'function': {'name': 'GetPopulation', 'arguments': '{\"location\": \"Los Angeles, CA\"}'}}, {'id': 'chatcmpl-tool-4b8d56ef067f447795d9146a56e43510', 'type': 'function', 'index': 0, 'function': {'name': 'GetPopulation', 'arguments': '{\"location\": \"New York, NY\"}'}}]}, response_metadata={}, id='run-4630cfa9-4e95-42dd-8e4a-45db78180a10-0', tool_calls=[{'name': 'GetWeather', 'args': {'location': 'Los Angeles, CA'}, 'id': 'chatcmpl-tool-b1204a3c70b44cd8802579df48df0c8c', 'type': 'tool_call'}, {'name': 'GetWeather', 'args': {'location': 'New York, NY'}, 'id': 'chatcmpl-tool-e299116c05bf4ce498cd6042928ae080', 'type': 'tool_call'}, {'name': 'GetPopulation', 'args': {'location': 'Los Angeles, CA'}, 'id': 'chatcmpl-tool-19502a60f30348669ffbac00ff503388', 'type': 'tool_call'}, {'name': 'GetPopulation', 'args': {'location': 'New York, NY'}, 'id': 'chatcmpl-tool-4b8d56ef067f447795d9146a56e43510', 'type': 'tool_call'}])"
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 7
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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"source": [
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"### AIMessage.tool_calls\n",
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"\n",
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"Notice that the AIMessage has a tool_calls attribute. This contains in a standardized ToolCall format that is model-provider agnostic."
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],
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"id": "84f405c45a35abe5"
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-04-21T18:43:00.429453Z",
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"start_time": "2025-04-21T18:43:00.426399Z"
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}
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},
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"cell_type": "code",
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"source": "ai_msg.tool_calls",
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"id": "bdcee85475019719",
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[{'name': 'GetWeather',\n",
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" 'args': {'location': 'Los Angeles, CA'},\n",
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" 'id': 'chatcmpl-tool-b1204a3c70b44cd8802579df48df0c8c',\n",
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" 'type': 'tool_call'},\n",
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" {'name': 'GetWeather',\n",
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" 'args': {'location': 'New York, NY'},\n",
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" 'id': 'chatcmpl-tool-e299116c05bf4ce498cd6042928ae080',\n",
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" 'type': 'tool_call'},\n",
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" {'name': 'GetPopulation',\n",
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" 'args': {'location': 'Los Angeles, CA'},\n",
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" 'id': 'chatcmpl-tool-19502a60f30348669ffbac00ff503388',\n",
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" 'type': 'tool_call'},\n",
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" {'name': 'GetPopulation',\n",
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" 'args': {'location': 'New York, NY'},\n",
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" 'id': 'chatcmpl-tool-4b8d56ef067f447795d9146a56e43510',\n",
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" 'type': 'tool_call'}]"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"execution_count": 8
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},
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{
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"cell_type": "markdown",
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"id": "ff1b51a8",
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