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233 lines
9.6 KiB
Plaintext
233 lines
9.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "9502d5b0",
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"metadata": {},
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"source": [
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"# OpenAI Multi Functions Agent\n",
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"\n",
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"This notebook showcases using an agent that uses the OpenAI functions ability to respond to the prompts of the user using a Large Language Model\n",
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"\n",
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"Install openai,google-search-results packages which are required as the langchain packages call them internally\n",
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"\n",
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">pip install openai google-search-results\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "c0a83623",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain import SerpAPIWrapper\n",
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"from langchain.agents import initialize_agent, Tool\n",
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"from langchain.agents import AgentType\n",
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"from langchain.chat_models import ChatOpenAI"
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]
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},
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{
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"cell_type": "markdown",
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"id": "86198d9c",
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"metadata": {},
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"source": [
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"The agent is given ability to perform search functionalities with the respective tool\n",
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"\n",
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"SerpAPIWrapper:\n",
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">This initializes the SerpAPIWrapper for search functionality (search).\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "6fefaba2",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Initialize the OpenAI language model\n",
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"#Replace <your_api_key> in openai_api_key=\"<your_api_key>\" with your actual OpenAI key.\n",
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"llm = ChatOpenAI(temperature=0, model=\"gpt-3.5-turbo-0613\")\n",
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"\n",
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"# Initialize the SerpAPIWrapper for search functionality\n",
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"#Replace <your_api_key> in openai_api_key=\"<your_api_key>\" with your actual SerpAPI key.\n",
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"search = SerpAPIWrapper()\n",
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"\n",
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"# Define a list of tools offered by the agent\n",
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"tools = [\n",
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" Tool(\n",
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" name=\"Search\",\n",
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" func=search.run,\n",
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" description=\"Useful when you need to answer questions about current events. You should ask targeted questions.\"\n",
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" ),\n",
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"]\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "9ff6cee9",
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"metadata": {},
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"outputs": [],
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"source": [
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"mrkl = initialize_agent(tools, llm, agent=AgentType.OPENAI_MULTI_FUNCTIONS, verbose=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "cbe95c81",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Do this so we can exactly what's going on under the hood\n",
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"import langchain\n",
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"langchain.debug = True"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "ba8e4cbe",
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"metadata": {
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"scrolled": false
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},
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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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"\u001b[32;1m\u001b[1;3m[chain/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor] Entering Chain run with input:\n",
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"\u001b[0m{\n",
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" \"input\": \"What is the weather in LA and SF?\"\n",
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"}\n",
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"\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 2:llm:ChatOpenAI] Entering LLM run with input:\n",
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"\u001b[0m{\n",
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" \"prompts\": [\n",
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" \"System: You are a helpful AI assistant.\\nHuman: What is the weather in LA and SF?\"\n",
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" ]\n",
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"}\n",
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"\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 2:llm:ChatOpenAI] [2.91s] Exiting LLM run with output:\n",
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"\u001b[0m{\n",
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" \"generations\": [\n",
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" [\n",
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" {\n",
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" \"text\": \"\",\n",
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" \"generation_info\": null,\n",
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" \"message\": {\n",
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" \"content\": \"\",\n",
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" \"additional_kwargs\": {\n",
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" \"function_call\": {\n",
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" \"name\": \"tool_selection\",\n",
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" \"arguments\": \"{\\n \\\"actions\\\": [\\n {\\n \\\"action_name\\\": \\\"Search\\\",\\n \\\"action\\\": {\\n \\\"tool_input\\\": \\\"weather in Los Angeles\\\"\\n }\\n },\\n {\\n \\\"action_name\\\": \\\"Search\\\",\\n \\\"action\\\": {\\n \\\"tool_input\\\": \\\"weather in San Francisco\\\"\\n }\\n }\\n ]\\n}\"\n",
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" }\n",
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" },\n",
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" \"example\": false\n",
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" }\n",
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" }\n",
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" ]\n",
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" ],\n",
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" \"llm_output\": {\n",
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" \"token_usage\": {\n",
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" \"prompt_tokens\": 81,\n",
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" \"completion_tokens\": 75,\n",
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" \"total_tokens\": 156\n",
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" },\n",
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" \"model_name\": \"gpt-3.5-turbo-0613\"\n",
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" },\n",
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" \"run\": null\n",
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"}\n",
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"\u001b[32;1m\u001b[1;3m[tool/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 3:tool:Search] Entering Tool run with input:\n",
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"\u001b[0m\"{'tool_input': 'weather in Los Angeles'}\"\n",
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"\u001b[36;1m\u001b[1;3m[tool/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 3:tool:Search] [608.693ms] Exiting Tool run with output:\n",
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"\u001b[0m\"Mostly cloudy early, then sunshine for the afternoon. High 76F. Winds SW at 5 to 10 mph. Humidity59%.\"\n",
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"\u001b[32;1m\u001b[1;3m[tool/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 4:tool:Search] Entering Tool run with input:\n",
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"\u001b[0m\"{'tool_input': 'weather in San Francisco'}\"\n",
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"\u001b[36;1m\u001b[1;3m[tool/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 4:tool:Search] [517.475ms] Exiting Tool run with output:\n",
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"\u001b[0m\"Partly cloudy this evening, then becoming cloudy after midnight. Low 53F. Winds WSW at 10 to 20 mph. Humidity83%.\"\n",
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"\u001b[32;1m\u001b[1;3m[llm/start]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 5:llm:ChatOpenAI] Entering LLM run with input:\n",
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"\u001b[0m{\n",
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" \"prompts\": [\n",
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" \"System: You are a helpful AI assistant.\\nHuman: What is the weather in LA and SF?\\nAI: {'name': 'tool_selection', 'arguments': '{\\\\n \\\"actions\\\": [\\\\n {\\\\n \\\"action_name\\\": \\\"Search\\\",\\\\n \\\"action\\\": {\\\\n \\\"tool_input\\\": \\\"weather in Los Angeles\\\"\\\\n }\\\\n },\\\\n {\\\\n \\\"action_name\\\": \\\"Search\\\",\\\\n \\\"action\\\": {\\\\n \\\"tool_input\\\": \\\"weather in San Francisco\\\"\\\\n }\\\\n }\\\\n ]\\\\n}'}\\nFunction: Mostly cloudy early, then sunshine for the afternoon. High 76F. Winds SW at 5 to 10 mph. Humidity59%.\\nAI: {'name': 'tool_selection', 'arguments': '{\\\\n \\\"actions\\\": [\\\\n {\\\\n \\\"action_name\\\": \\\"Search\\\",\\\\n \\\"action\\\": {\\\\n \\\"tool_input\\\": \\\"weather in Los Angeles\\\"\\\\n }\\\\n },\\\\n {\\\\n \\\"action_name\\\": \\\"Search\\\",\\\\n \\\"action\\\": {\\\\n \\\"tool_input\\\": \\\"weather in San Francisco\\\"\\\\n }\\\\n }\\\\n ]\\\\n}'}\\nFunction: Partly cloudy this evening, then becoming cloudy after midnight. Low 53F. Winds WSW at 10 to 20 mph. Humidity83%.\"\n",
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" ]\n",
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"}\n",
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"\u001b[36;1m\u001b[1;3m[llm/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor > 5:llm:ChatOpenAI] [2.33s] Exiting LLM run with output:\n",
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"\u001b[0m{\n",
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" \"generations\": [\n",
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" [\n",
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" {\n",
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" \"text\": \"The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.\",\n",
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" \"generation_info\": null,\n",
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" \"message\": {\n",
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" \"content\": \"The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.\",\n",
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" \"additional_kwargs\": {},\n",
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" \"example\": false\n",
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" }\n",
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" }\n",
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" ]\n",
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" ],\n",
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" \"llm_output\": {\n",
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" \"token_usage\": {\n",
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" \"prompt_tokens\": 307,\n",
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" \"completion_tokens\": 54,\n",
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" \"total_tokens\": 361\n",
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" },\n",
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" \"model_name\": \"gpt-3.5-turbo-0613\"\n",
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" },\n",
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" \"run\": null\n",
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"}\n",
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"\u001b[36;1m\u001b[1;3m[chain/end]\u001b[0m \u001b[1m[1:chain:AgentExecutor] [6.37s] Exiting Chain run with output:\n",
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"\u001b[0m{\n",
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" \"output\": \"The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.\"\n",
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"}\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'The weather in Los Angeles is mostly cloudy with a high of 76°F and a humidity of 59%. The weather in San Francisco is partly cloudy in the evening, becoming cloudy after midnight, with a low of 53°F and a humidity of 83%.'"
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]
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},
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"execution_count": 6,
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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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"source": [
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"mrkl.run(\n",
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" \"What is the weather in LA and SF?\"\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9f5f6743",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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