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update openai functions docs (#9278)
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Bagatur
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afba2be3dc
@ -83,10 +83,8 @@
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
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"Human: Use the given format to extract information from the following input:\n",
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"Human: Sally is 13\n",
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"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
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" {'function_call': {'name': '_OutputFormatter', 'arguments': '{\\n \"output\": {\\n \"name\": \"Sally\",\\n \"age\": 13,\\n \"fav_food\": \"Unknown\"\\n }\\n}'}}\n",
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"Human: Use the given format to extract information from the following input: Sally is 13\n",
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"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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@ -105,18 +103,13 @@
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"source": [
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"# If we pass in a model explicitly, we need to make sure it supports the OpenAI function-calling API.\n",
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"llm = ChatOpenAI(model=\"gpt-4\", temperature=0)\n",
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"\n",
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"prompt_msgs = [\n",
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" SystemMessage(\n",
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" content=\"You are a world class algorithm for extracting information in structured formats.\"\n",
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" ),\n",
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" HumanMessage(\n",
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" content=\"Use the given format to extract information from the following input:\"\n",
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" ),\n",
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" HumanMessagePromptTemplate.from_template(\"{input}\"),\n",
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" HumanMessage(content=\"Tips: Make sure to answer in the correct format\"),\n",
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"]\n",
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"prompt = ChatPromptTemplate(messages=prompt_msgs)\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\"system\", \"You are a world class algorithm for extracting information in structured formats.\"),\n",
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" (\"human\", \"Use the given format to extract information from the following input: {input}\"),\n",
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" (\"human\", \"Tip: Make sure to answer in the correct format\"),\n",
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" ]\n",
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")\n",
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"\n",
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"chain = create_structured_output_chain(Person, llm, prompt, verbose=True)\n",
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"chain.run(\"Sally is 13\")"
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@ -132,7 +125,7 @@
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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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"execution_count": 5,
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"id": "4d8ea815",
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"metadata": {},
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"outputs": [
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@ -145,10 +138,8 @@
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
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"Human: Use the given format to extract information from the following input:\n",
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"Human: Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally, so she's 23.\n",
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"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
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" {'function_call': {'name': '_OutputFormatter', 'arguments': '{\\n \"output\": {\\n \"people\": [\\n {\\n \"name\": \"Sally\",\\n \"age\": 13,\\n \"fav_food\": \"\"\\n },\\n {\\n \"name\": \"Joey\",\\n \"age\": 12,\\n \"fav_food\": \"spinach\"\\n },\\n {\\n \"name\": \"Caroline\",\\n \"age\": 23,\\n \"fav_food\": \"\"\\n }\\n ]\\n }\\n}'}}\n",
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"Human: Use the given format to extract information from the following input: Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally.\n",
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"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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@ -159,7 +150,7 @@
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"People(people=[Person(name='Sally', age=13, fav_food=''), Person(name='Joey', age=12, fav_food='spinach'), Person(name='Caroline', age=23, fav_food='')])"
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]
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},
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"execution_count": 4,
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -176,7 +167,7 @@
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"\n",
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"chain = create_structured_output_chain(People, llm, prompt, verbose=True)\n",
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"chain.run(\n",
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" \"Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally, so she's 23.\"\n",
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" \"Sally is 13, Joey just turned 12 and loves spinach. Caroline is 10 years older than Sally.\"\n",
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")"
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]
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},
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@ -229,10 +220,8 @@
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for extracting information in structured formats.\n",
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"Human: Use the given format to extract information from the following input:\n",
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"Human: Sally is 13\n",
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"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
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" {'function_call': {'name': 'output_formatter', 'arguments': '{\\n \"name\": \"Sally\",\\n \"age\": 13\\n}'}}\n",
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"Human: Use the given format to extract information from the following input: Sally is 13\n",
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"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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@ -279,7 +268,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 9,
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"id": "17f52508",
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"metadata": {},
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"outputs": [],
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@ -302,7 +291,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 10,
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"id": "a4658ad8",
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"metadata": {},
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"outputs": [
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@ -314,11 +303,9 @@
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"\n",
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
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"Human: Make calls to the relevant function to record the entities in the following input:\n",
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"Human: Harry was a chubby brown beagle who loved chicken\n",
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"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
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" {'function_call': {'name': 'RecordDog', 'arguments': '{\\n \"name\": \"Harry\",\\n \"color\": \"brown\",\\n \"fav_food\": \"chicken\"\\n}'}}\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities.\n",
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"Human: Make calls to the relevant function to record the entities in the following input: Harry was a chubby brown beagle who loved chicken\n",
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"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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@ -329,21 +316,19 @@
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"RecordDog(name='Harry', color='brown', fav_food='chicken')"
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]
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},
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"execution_count": 9,
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"execution_count": 10,
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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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"prompt_msgs = [\n",
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" SystemMessage(content=\"You are a world class algorithm for recording entities\"),\n",
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" HumanMessage(\n",
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" content=\"Make calls to the relevant function to record the entities in the following input:\"\n",
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" ),\n",
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" HumanMessagePromptTemplate.from_template(\"{input}\"),\n",
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" HumanMessage(content=\"Tips: Make sure to answer in the correct format\"),\n",
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"]\n",
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"prompt = ChatPromptTemplate(messages=prompt_msgs)\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\"system\", \"You are a world class algorithm for recording entities.\"),\n",
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" (\"human\", \"Make calls to the relevant function to record the entities in the following input: {input}\"),\n",
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" (\"human\", \"Tip: Make sure to answer in the correct format\"),\n",
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" ]\n",
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")\n",
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"\n",
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"chain = create_openai_fn_chain([RecordPerson, RecordDog], llm, prompt, verbose=True)\n",
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"chain.run(\"Harry was a chubby brown beagle who loved chicken\")"
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@ -362,7 +347,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 11,
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"id": "95ac5825",
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"metadata": {},
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"outputs": [
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@ -374,11 +359,9 @@
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"\n",
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
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"Human: Make calls to the relevant function to record the entities in the following input:\n",
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"Human: The most important thing to remember about Tommy, my 12 year old, is that he'll do anything for apple pie.\n",
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"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
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" {'function_call': {'name': 'record_person', 'arguments': '{\\n \"name\": \"Tommy\",\\n \"age\": 12,\\n \"fav_food\": {\\n \"food\": \"apple pie\"\\n }\\n}'}}\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities.\n",
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"Human: Make calls to the relevant function to record the entities in the following input: The most important thing to remember about Tommy, my 12 year old, is that he'll do anything for apple pie.\n",
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"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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@ -389,7 +372,7 @@
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"{'name': 'Tommy', 'age': 12, 'fav_food': {'food': 'apple pie'}}"
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]
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},
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"execution_count": 10,
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -434,7 +417,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 12,
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"id": "8b0d11de",
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"metadata": {},
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"outputs": [
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@ -446,11 +429,9 @@
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"\n",
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"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
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"Prompt after formatting:\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities\n",
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"Human: Make calls to the relevant function to record the entities in the following input:\n",
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"Human: I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?\n",
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"Human: Tips: Make sure to answer in the correct format\u001b[0m\n",
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" {'function_call': {'name': 'record_dog', 'arguments': '{\\n \"name\": \"Henry\",\\n \"color\": \"brown\",\\n \"fav_food\": {\\n \"food\": null\\n }\\n}'}}\n",
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"\u001b[32;1m\u001b[1;3mSystem: You are a world class algorithm for recording entities.\n",
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"Human: Make calls to the relevant function to record the entities in the following input: I can't find my dog Henry anywhere, he's a small brown beagle. Could you send a message about him?\n",
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"Human: Tip: Make sure to answer in the correct format\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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@ -462,7 +443,7 @@
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" 'arguments': {'name': 'Henry', 'color': 'brown', 'fav_food': {'food': None}}}"
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]
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},
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"execution_count": 11,
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -502,9 +483,9 @@
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],
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"metadata": {
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"kernelspec": {
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"display_name": "venv",
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"display_name": "poetry-venv",
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"language": "python",
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"name": "venv"
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"name": "poetry-venv"
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},
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"language_info": {
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"codemirror_mode": {
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@ -516,7 +497,7 @@
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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": "3.11.3"
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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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@ -226,9 +226,9 @@ def create_openai_fn_chain(
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from langchain.chains.openai_functions import create_openai_fn_chain
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from langchain.chat_models import ChatOpenAI
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from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
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from langchain.prompts import ChatPromptTemplate
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from pydantic_v1 import BaseModel, Field
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from pydantic import BaseModel, Field
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class RecordPerson(BaseModel):
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@ -247,17 +247,15 @@ def create_openai_fn_chain(
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fav_food: Optional[str] = Field(None, description="The dog's favorite food")
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llm = ChatOpenAI(model="gpt-3.5-turbo-0613", temperature=0)
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prompt_msgs = [
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SystemMessage(
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content="You are a world class algorithm for recording entities"
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),
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HumanMessage(content="Make calls to the relevant function to record the entities in the following input:"),
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HumanMessagePromptTemplate.from_template("{input}"),
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HumanMessage(content="Tips: Make sure to answer in the correct format"),
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llm = ChatOpenAI(model="gpt-4", temperature=0)
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prompt = ChatPromptTemplate.from_messages(
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[
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("system", "You are a world class algorithm for recording entities."),
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("human", "Make calls to the relevant function to record the entities in the following input: {input}"),
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("human", "Tip: Make sure to answer in the correct format"),
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]
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prompt = ChatPromptTemplate(messages=prompt_msgs)
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chain = create_openai_fn_chain([RecordPerson, RecordDog])
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)
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chain = create_openai_fn_chain([RecordPerson, RecordDog], llm, prompt)
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chain.run("Harry was a chubby brown beagle who loved chicken")
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# -> RecordDog(name="Harry", color="brown", fav_food="chicken")
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""" # noqa: E501
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@ -312,9 +310,9 @@ def create_structured_output_chain(
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from langchain.chains.openai_functions import create_structured_output_chain
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from langchain.chat_models import ChatOpenAI
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from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
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from langchain.prompts import ChatPromptTemplate
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from pydantic_v1 import BaseModel, Field
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from pydantic import BaseModel, Field
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class Dog(BaseModel):
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\"\"\"Identifying information about a dog.\"\"\"
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@ -324,15 +322,13 @@ def create_structured_output_chain(
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fav_food: Optional[str] = Field(None, description="The dog's favorite food")
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llm = ChatOpenAI(model="gpt-3.5-turbo-0613", temperature=0)
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prompt_msgs = [
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SystemMessage(
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content="You are a world class algorithm for extracting information in structured formats."
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),
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HumanMessage(content="Use the given format to extract information from the following input:"),
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HumanMessagePromptTemplate.from_template("{input}"),
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HumanMessage(content="Tips: Make sure to answer in the correct format"),
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prompt = ChatPromptTemplate.from_messages(
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[
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("system", "You are a world class algorithm for extracting information in structured formats."),
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("human", "Use the given format to extract information from the following input: {input}"),
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("human", "Tip: Make sure to answer in the correct format"),
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]
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prompt = ChatPromptTemplate(messages=prompt_msgs)
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)
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chain = create_structured_output_chain(Dog, llm, prompt)
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chain.run("Harry was a chubby brown beagle who loved chicken")
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# -> Dog(name="Harry", color="brown", fav_food="chicken")
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