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34 Commits
Author | SHA1 | Date |
---|---|---|
blob42 | 2b776bec55 | 1 year ago |
Jon Luo | 882f7964fb | 1 year ago |
JonLuca De Caro | 443992c4d5 | 1 year ago |
Eugene Yurtsev | a83a371069 | 1 year ago |
Nuno Campos | 499e76b199 | 1 year ago |
Kacper Łukawski | 8947797250 | 1 year ago |
Jason Gill | 1989e7d4c2 | 1 year ago |
Harrison Chase | dda5259f68 | 1 year ago |
Kacper Łukawski | f032609f8d | 1 year ago |
Kacper Łukawski | 9ac442624c | 1 year ago |
Francisco Ingham | 34abcd31b9 | 1 year ago |
Ankush Gola | fe30be6fba | 1 year ago |
Lakshya Agarwal | cfed0497ac | 1 year ago |
Ryan Dao | 59157b6891 | 1 year ago |
Harrison Chase | e178008b75 | 1 year ago |
Harrison Chase | 1cd8996074 | 1 year ago |
yakigac | cfae03042d | 1 year ago |
Harrison Chase | 4b5e850361 | 1 year ago |
Harrison Chase | 4d4b43cf5a | 1 year ago |
Harrison Chase | c01f9100e4 | 1 year ago |
Christie Jacob | edb3915ee7 | 1 year ago |
Harrison Chase | fe7dbecfe6 | 1 year ago |
Harrison Chase | 02ec72df87 | 1 year ago |
Jon Luo | 92ab27e4b8 | 1 year ago |
Ankush Gola | 82baecc892 | 1 year ago |
Jon Luo | 35f1e8f569 | 1 year ago |
kurehajime | 6c629b54e6 | 1 year ago |
James Brotchie | 3574418a40 | 1 year ago |
Jon Luo | 5bf8772f26 | 1 year ago |
Harrison Chase | 924bba5ce9 | 1 year ago |
Harrison Chase | 786852e9e6 | 1 year ago |
Tim Asp | 72ef69d1ba | 1 year ago |
Matt Robinson | 1aa41b5741 | 1 year ago |
Eugene Yurtsev | c14cff60d0 | 1 year ago |
@ -0,0 +1,202 @@
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{
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||||
"cells": [
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||||
{
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||||
"cell_type": "markdown",
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"id": "7094e328",
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||||
"metadata": {},
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||||
"source": [
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||||
"# CSV Agent\n",
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"\n",
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"This notebook shows how to use agents to interact with a csv. It is mostly optimized for question answering.\n",
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"\n",
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"**NOTE: this agent calls the Pandas DataFrame agent under the hood, which in turn calls the Python agent, which executes LLM generated Python code - this can be bad if the LLM generated Python code is harmful. Use cautiously.**\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": 1,
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"id": "827982c7",
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"metadata": {},
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||||
"outputs": [],
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"source": [
|
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"from langchain.agents import create_csv_agent"
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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": "caae0bec",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.llms import OpenAI"
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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": 11,
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"id": "16c4dc59",
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"metadata": {},
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"outputs": [],
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"source": [
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"agent = create_csv_agent(OpenAI(temperature=0), 'titanic.csv', 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": 12,
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"id": "46b9489d",
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"metadata": {},
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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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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mThought: I need to count the number of rows\n",
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"Action: python_repl_ast\n",
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"Action Input: len(df)\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3m891\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
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"Final Answer: There are 891 rows in the dataframe.\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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},
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{
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"data": {
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"text/plain": [
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"'There are 891 rows in the dataframe.'"
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]
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},
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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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],
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"source": [
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"agent.run(\"how many rows are there?\")"
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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": "a96309be",
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"metadata": {},
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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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"\n",
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"\n",
|
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
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"\u001b[32;1m\u001b[1;3mThought: I need to count the number of people with more than 3 siblings\n",
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"Action: python_repl_ast\n",
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"Action Input: df[df['SibSp'] > 3].shape[0]\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3m30\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
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"Final Answer: 30 people have more than 3 siblings.\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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},
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{
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"data": {
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"text/plain": [
|
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"'30 people have more than 3 siblings.'"
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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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"agent.run(\"how many people have more than 3 sibligngs\")"
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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": 7,
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"id": "964a09f7",
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"metadata": {},
|
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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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"\n",
|
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"\n",
|
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
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"\u001b[32;1m\u001b[1;3mThought: I need to calculate the average age first\n",
|
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"Action: python_repl_ast\n",
|
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"Action Input: df['Age'].mean()\u001b[0m\n",
|
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"Observation: \u001b[36;1m\u001b[1;3m29.69911764705882\u001b[0m\n",
|
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"Thought:\u001b[32;1m\u001b[1;3m I can now calculate the square root\n",
|
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"Action: python_repl_ast\n",
|
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"Action Input: math.sqrt(df['Age'].mean())\u001b[0m\n",
|
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"Observation: \u001b[36;1m\u001b[1;3mname 'math' is not defined\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to import the math library\n",
|
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"Action: python_repl_ast\n",
|
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"Action Input: import math\u001b[0m\n",
|
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"Observation: \u001b[36;1m\u001b[1;3mNone\u001b[0m\n",
|
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"Thought:\u001b[32;1m\u001b[1;3m I can now calculate the square root\n",
|
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"Action: python_repl_ast\n",
|
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"Action Input: math.sqrt(df['Age'].mean())\u001b[0m\n",
|
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"Observation: \u001b[36;1m\u001b[1;3m5.449689683556195\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
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"Final Answer: 5.449689683556195\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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},
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{
|
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"data": {
|
||||
"text/plain": [
|
||||
"'5.449689683556195'"
|
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]
|
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},
|
||||
"execution_count": 7,
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||||
"metadata": {},
|
||||
"output_type": "execute_result"
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}
|
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],
|
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"source": [
|
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"agent.run(\"whats the square root of the average age?\")"
|
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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": "551de2be",
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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": {
|
||||
"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",
|
||||
"pygments_lexer": "ipython3",
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"version": "3.9.1"
|
||||
}
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},
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||||
"nbformat": 4,
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"nbformat_minor": 5
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||||
}
|
@ -0,0 +1,190 @@
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||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
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||||
"id": "85fb2c03-ab88-4c8c-97e3-a7f2954555ab",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# JSON Agent\n",
|
||||
"\n",
|
||||
"This notebook showcases an agent designed to interact with large JSON/dict objects. This is useful when you want to answer questions about a JSON blob that's too large to fit in the context window of an LLM. The agent is able to iteratively explore the blob to find what it needs to answer the user's question.\n",
|
||||
"\n",
|
||||
"In the below example, we are using the OpenAPI spec for the OpenAI API, which you can find [here](https://github.com/openai/openai-openapi/blob/master/openapi.yaml).\n",
|
||||
"\n",
|
||||
"We will use the JSON agent to answer some questions about the API spec."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "893f90fd-f8f6-470a-a76d-1f200ba02e2f",
|
||||
"metadata": {},
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||||
"source": [
|
||||
"## Initialization"
|
||||
]
|
||||
},
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||||
{
|
||||
"cell_type": "code",
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||||
"execution_count": 1,
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||||
"id": "ff988466-c389-4ec6-b6ac-14364a537fd5",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
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||||
"outputs": [],
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||||
"source": [
|
||||
"import os\n",
|
||||
"import yaml\n",
|
||||
"\n",
|
||||
"from langchain.agents import (\n",
|
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" create_json_agent,\n",
|
||||
" AgentExecutor\n",
|
||||
")\n",
|
||||
"from langchain.agents.agent_toolkits import JsonToolkit\n",
|
||||
"from langchain.chains import LLMChain\n",
|
||||
"from langchain.llms.openai import OpenAI\n",
|
||||
"from langchain.requests import RequestsWrapper\n",
|
||||
"from langchain.tools.json.tool import JsonSpec"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "9ecd1ba0-3937-4359-a41e-68605f0596a1",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"with open(\"openai_openapi.yml\") as f:\n",
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||||
" data = yaml.load(f, Loader=yaml.FullLoader)\n",
|
||||
"json_spec = JsonSpec(dict_=data, max_value_length=4000)\n",
|
||||
"json_toolkit = JsonToolkit(spec=json_spec)\n",
|
||||
"\n",
|
||||
"json_agent_executor = create_json_agent(\n",
|
||||
" llm=OpenAI(temperature=0),\n",
|
||||
" toolkit=json_toolkit,\n",
|
||||
" verbose=True\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "05cfcb24-4389-4b8f-ad9e-466e3fca8db0",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Example: getting the required POST parameters for a request"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "faf13702-50f0-4d1b-b91f-48c750ccfd98",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
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||||
"output_type": "stream",
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"text": [
|
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"\n",
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"\n",
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||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mAction: json_spec_list_keys\n",
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"Action Input: data\u001b[0m\n",
|
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"Observation: \u001b[36;1m\u001b[1;3m['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the paths key to see what endpoints exist\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['/engines', '/engines/{engine_id}', '/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/engines/{engine_id}/search', '/files', '/files/{file_id}', '/files/{file_id}/content', '/answers', '/classifications', '/fine-tunes', '/fine-tunes/{fine_tune_id}', '/fine-tunes/{fine_tune_id}/cancel', '/fine-tunes/{fine_tune_id}/events', '/models', '/models/{model}', '/moderations']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the /completions endpoint to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['post']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the post key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['operationId', 'tags', 'summary', 'requestBody', 'responses', 'x-oaiMeta']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the requestBody key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['required', 'content']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the required key to see what parameters are required\n",
|
||||
"Action: json_spec_get_value\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"required\"]\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3mTrue\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the content key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['application/json']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the application/json key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['schema']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the schema key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"][\"schema\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['$ref']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the $ref key to see what parameters are required\n",
|
||||
"Action: json_spec_get_value\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"][\"schema\"][\"$ref\"]\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m#/components/schemas/CreateCompletionRequest\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the CreateCompletionRequest schema to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"components\"][\"schemas\"][\"CreateCompletionRequest\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['type', 'properties', 'required']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the required key to see what parameters are required\n",
|
||||
"Action: json_spec_get_value\n",
|
||||
"Action Input: data[\"components\"][\"schemas\"][\"CreateCompletionRequest\"][\"required\"]\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m['model']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: The required parameters in the request body to the /completions endpoint are 'model'.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"The required parameters in the request body to the /completions endpoint are 'model'.\""
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"json_agent_executor.run(\"What are the required parameters in the request body to the /completions endpoint?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ba9c9d30",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.9"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,242 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "85fb2c03-ab88-4c8c-97e3-a7f2954555ab",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# OpenAPI Agent\n",
|
||||
"\n",
|
||||
"This notebook showcases an agent designed to interact with an OpenAPI spec and make a correct API request based on the information it has gathered from the spec.\n",
|
||||
"\n",
|
||||
"In the below example, we are using the OpenAPI spec for the OpenAI API, which you can find [here](https://github.com/openai/openai-openapi/blob/master/openapi.yaml)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "893f90fd-f8f6-470a-a76d-1f200ba02e2f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Initialization"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "ff988466-c389-4ec6-b6ac-14364a537fd5",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import yaml\n",
|
||||
"\n",
|
||||
"from langchain.agents import create_openapi_agent\n",
|
||||
"from langchain.agents.agent_toolkits import OpenAPIToolkit\n",
|
||||
"from langchain.llms.openai import OpenAI\n",
|
||||
"from langchain.requests import RequestsWrapper\n",
|
||||
"from langchain.tools.json.tool import JsonSpec"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "9ecd1ba0-3937-4359-a41e-68605f0596a1",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"with open(\"openai_openapi.yml\") as f:\n",
|
||||
" data = yaml.load(f, Loader=yaml.FullLoader)\n",
|
||||
"json_spec=JsonSpec(dict_=data, max_value_length=4000)\n",
|
||||
"headers = {\n",
|
||||
" \"Authorization\": f\"Bearer {os.getenv('OPENAI_API_KEY')}\"\n",
|
||||
"}\n",
|
||||
"requests_wrapper=RequestsWrapper(headers=headers)\n",
|
||||
"openapi_toolkit = OpenAPIToolkit.from_llm(OpenAI(temperature=0), json_spec, requests_wrapper, verbose=True)\n",
|
||||
"openapi_agent_executor = create_openapi_agent(\n",
|
||||
" llm=OpenAI(temperature=0),\n",
|
||||
" toolkit=openapi_toolkit,\n",
|
||||
" verbose=True\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f111879d-ae84-41f9-ad82-d3e6b72c41ba",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Example: agent capable of analyzing OpenAPI spec and making requests"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "548db7f7-337b-4ba8-905c-e7fd58c01799",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mAction: json_explorer\n",
|
||||
"Action Input: What is the base url for the API?\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mAction: json_spec_list_keys\n",
|
||||
"Action Input: data\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the servers key to see what the base url is\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"servers\"][0]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mValueError('Value at path `data[\"servers\"][0]` is not a dict, get the value directly.')\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should get the value of the servers key\n",
|
||||
"Action: json_spec_get_value\n",
|
||||
"Action Input: data[\"servers\"][0]\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m{'url': 'https://api.openai.com/v1'}\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the base url for the API\n",
|
||||
"Final Answer: The base url for the API is https://api.openai.com/v1\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3mThe base url for the API is https://api.openai.com/v1\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should find the path for the /completions endpoint.\n",
|
||||
"Action: json_explorer\n",
|
||||
"Action Input: What is the path for the /completions endpoint?\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mAction: json_spec_list_keys\n",
|
||||
"Action Input: data\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the paths key to see what endpoints exist\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['/engines', '/engines/{engine_id}', '/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/engines/{engine_id}/search', '/files', '/files/{file_id}', '/files/{file_id}/content', '/answers', '/classifications', '/fine-tunes', '/fine-tunes/{fine_tune_id}', '/fine-tunes/{fine_tune_id}/cancel', '/fine-tunes/{fine_tune_id}/events', '/models', '/models/{model}', '/moderations']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the path for the /completions endpoint\n",
|
||||
"Final Answer: data[\"paths\"][2]\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3mdata[\"paths\"][2]\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should find the required parameters for the POST request.\n",
|
||||
"Action: json_explorer\n",
|
||||
"Action Input: What are the required parameters for a POST request to the /completions endpoint?\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mAction: json_spec_list_keys\n",
|
||||
"Action Input: data\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the paths key to see what endpoints exist\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['/engines', '/engines/{engine_id}', '/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/engines/{engine_id}/search', '/files', '/files/{file_id}', '/files/{file_id}/content', '/answers', '/classifications', '/fine-tunes', '/fine-tunes/{fine_tune_id}', '/fine-tunes/{fine_tune_id}/cancel', '/fine-tunes/{fine_tune_id}/events', '/models', '/models/{model}', '/moderations']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the /completions endpoint to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['post']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the post key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['operationId', 'tags', 'summary', 'requestBody', 'responses', 'x-oaiMeta']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the requestBody key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['required', 'content']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the content key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['application/json']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the application/json key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['schema']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the schema key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"][\"schema\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['$ref']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the $ref key to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"][\"schema\"][\"$ref\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mValueError('Value at path `data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"][\"schema\"][\"$ref\"]` is not a dict, get the value directly.')\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the $ref key to get the value directly\n",
|
||||
"Action: json_spec_get_value\n",
|
||||
"Action Input: data[\"paths\"][\"/completions\"][\"post\"][\"requestBody\"][\"content\"][\"application/json\"][\"schema\"][\"$ref\"]\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m#/components/schemas/CreateCompletionRequest\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the CreateCompletionRequest schema to see what parameters are required\n",
|
||||
"Action: json_spec_list_keys\n",
|
||||
"Action Input: data[\"components\"][\"schemas\"][\"CreateCompletionRequest\"]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m['type', 'properties', 'required']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I should look at the required key to see what parameters are required\n",
|
||||
"Action: json_spec_get_value\n",
|
||||
"Action Input: data[\"components\"][\"schemas\"][\"CreateCompletionRequest\"][\"required\"]\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m['model']\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: The required parameters for a POST request to the /completions endpoint are 'model'.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n",
|
||||
"\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3mThe required parameters for a POST request to the /completions endpoint are 'model'.\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the parameters needed to make the request.\n",
|
||||
"Action: requests_post\n",
|
||||
"Action Input: { \"url\": \"https://api.openai.com/v1/completions\", \"data\": { \"model\": \"davinci\", \"prompt\": \"tell me a joke\" } }\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m{\"id\":\"cmpl-6oeEcNETfq8TOuIUQvAct6NrBXihs\",\"object\":\"text_completion\",\"created\":1677529082,\"model\":\"davinci\",\"choices\":[{\"text\":\"\\n\\n\\n\\nLove is a battlefield\\n\\n\\n\\nIt's me...And some\",\"index\":0,\"logprobs\":null,\"finish_reason\":\"length\"}],\"usage\":{\"prompt_tokens\":4,\"completion_tokens\":16,\"total_tokens\":20}}\n",
|
||||
"\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n",
|
||||
"Final Answer: Love is a battlefield. It's me...And some.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"Love is a battlefield. It's me...And some.\""
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"openapi_agent_executor.run(\"Make a post request to openai /completions. The prompt should be 'tell me a joke.'\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "6ec9582b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.9"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
@ -0,0 +1,204 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c81da886",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Pandas Dataframe Agent\n",
|
||||
"\n",
|
||||
"This notebook shows how to use agents to interact with a pandas dataframe. It is mostly optimized for question answering.\n",
|
||||
"\n",
|
||||
"**NOTE: this agent calls the Python agent under the hood, which executes LLM generated Python code - this can be bad if the LLM generated Python code is harmful. Use cautiously.**"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "0cdd9bf5",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.agents import create_pandas_dataframe_agent"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "051ebe84",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.llms import OpenAI\n",
|
||||
"import pandas as pd\n",
|
||||
"\n",
|
||||
"df = pd.read_csv('titanic.csv')"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "4185ff46",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"agent = create_pandas_dataframe_agent(OpenAI(temperature=0), df, verbose=True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "a9207a2e",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mThought: I need to count the number of rows\n",
|
||||
"Action: python_repl_ast\n",
|
||||
"Action Input: len(df)\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m891\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: There are 891 rows in the dataframe.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'There are 891 rows in the dataframe.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent.run(\"how many rows are there?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "bd43617c",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mThought: I need to count the number of people with more than 3 siblings\n",
|
||||
"Action: python_repl_ast\n",
|
||||
"Action Input: df[df['SibSp'] > 3].shape[0]\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m30\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: 30 people have more than 3 siblings.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'30 people have more than 3 siblings.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent.run(\"how many people have more than 3 sibligngs\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "94e64b58",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3mThought: I need to calculate the average age first\n",
|
||||
"Action: python_repl_ast\n",
|
||||
"Action Input: df['Age'].mean()\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m29.69911764705882\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I can now calculate the square root\n",
|
||||
"Action: python_repl_ast\n",
|
||||
"Action Input: math.sqrt(df['Age'].mean())\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mname 'math' is not defined\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to import the math library\n",
|
||||
"Action: python_repl_ast\n",
|
||||
"Action Input: import math\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mNone\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I can now calculate the square root\n",
|
||||
"Action: python_repl_ast\n",
|
||||
"Action Input: math.sqrt(df['Age'].mean())\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m5.449689683556195\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: 5.449689683556195\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'5.449689683556195'"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent.run(\"whats the square root of the average age?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "eba13b4d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
@ -0,0 +1,228 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "82a4c2cc-20ea-4b20-a565-63e905dee8ff",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Python Agent\n",
|
||||
"\n",
|
||||
"This notebook showcases an agent designed to write and execute python code to answer a question."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "f98e9c90-5c37-4fb9-af3e-d09693af8543",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.agents.agent_toolkits import create_python_agent\n",
|
||||
"from langchain.tools.python.tool import PythonREPLTool\n",
|
||||
"from langchain.python import PythonREPL\n",
|
||||
"from langchain.llms.openai import OpenAI"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "cc422f53-c51c-4694-a834-72ecd1e68363",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"agent_executor = create_python_agent(\n",
|
||||
" llm=OpenAI(temperature=0, max_tokens=1000),\n",
|
||||
" tool=PythonREPLTool(),\n",
|
||||
" verbose=True\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "c16161de",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Fibonacci Example\n",
|
||||
"This example was created by [John Wiseman](https://twitter.com/lemonodor/status/1628270074074398720?s=20)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "25cd4f92-ea9b-4fe6-9838-a4f85f81eebe",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to calculate the 10th fibonacci number\n",
|
||||
"Action: Python REPL\n",
|
||||
"Action Input: def fibonacci(n):\n",
|
||||
" if n == 0:\n",
|
||||
" return 0\n",
|
||||
" elif n == 1:\n",
|
||||
" return 1\n",
|
||||
" else:\n",
|
||||
" return fibonacci(n-1) + fibonacci(n-2)\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to call the function with 10 as the argument\n",
|
||||
"Action: Python REPL\n",
|
||||
"Action Input: fibonacci(10)\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: 55\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'55'"
|
||||
]
|
||||
},
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"What is the 10th fibonacci number?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7caa30de",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Training neural net\n",
|
||||
"This example was created by [Samee Ur Rehman](https://twitter.com/sameeurehman/status/1630130518133207046?s=20)."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "4b9f60e7-eb6a-4f14-8604-498d863d4482",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to write a neural network in PyTorch and train it on the given data.\n",
|
||||
"Action: Python REPL\n",
|
||||
"Action Input: \n",
|
||||
"import torch\n",
|
||||
"\n",
|
||||
"# Define the model\n",
|
||||
"model = torch.nn.Sequential(\n",
|
||||
" torch.nn.Linear(1, 1)\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"# Define the loss\n",
|
||||
"loss_fn = torch.nn.MSELoss()\n",
|
||||
"\n",
|
||||
"# Define the optimizer\n",
|
||||
"optimizer = torch.optim.SGD(model.parameters(), lr=0.01)\n",
|
||||
"\n",
|
||||
"# Define the data\n",
|
||||
"x_data = torch.tensor([[1.0], [2.0], [3.0], [4.0]])\n",
|
||||
"y_data = torch.tensor([[2.0], [4.0], [6.0], [8.0]])\n",
|
||||
"\n",
|
||||
"# Train the model\n",
|
||||
"for epoch in range(1000):\n",
|
||||
" # Forward pass\n",
|
||||
" y_pred = model(x_data)\n",
|
||||
"\n",
|
||||
" # Compute and print loss\n",
|
||||
" loss = loss_fn(y_pred, y_data)\n",
|
||||
" if (epoch+1) % 100 == 0:\n",
|
||||
" print(f'Epoch {epoch+1}: loss = {loss.item():.4f}')\n",
|
||||
"\n",
|
||||
" # Zero the gradients\n",
|
||||
" optimizer.zero_grad()\n",
|
||||
"\n",
|
||||
" # Backward pass\n",
|
||||
" loss.backward()\n",
|
||||
"\n",
|
||||
" # Update the weights\n",
|
||||
" optimizer.step()\n",
|
||||
"\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3mEpoch 100: loss = 0.0013\n",
|
||||
"Epoch 200: loss = 0.0007\n",
|
||||
"Epoch 300: loss = 0.0004\n",
|
||||
"Epoch 400: loss = 0.0002\n",
|
||||
"Epoch 500: loss = 0.0001\n",
|
||||
"Epoch 600: loss = 0.0001\n",
|
||||
"Epoch 700: loss = 0.0000\n",
|
||||
"Epoch 800: loss = 0.0000\n",
|
||||
"Epoch 900: loss = 0.0000\n",
|
||||
"Epoch 1000: loss = 0.0000\n",
|
||||
"\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: The prediction for x = 5 is 10.0.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'The prediction for x = 5 is 10.0.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"\"\"Understand, write a single neuron neural network in PyTorch.\n",
|
||||
"Take synthetic data for y=2x. Train for 1000 epochs and print every 100 epochs.\n",
|
||||
"Return prediction for x = 5\"\"\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "eb654671",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
@ -0,0 +1,892 @@
|
||||
PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked
|
||||
1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S
|
||||
2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C
|
||||
3,1,3,"Heikkinen, Miss. Laina",female,26,0,0,STON/O2. 3101282,7.925,,S
|
||||
4,1,1,"Futrelle, Mrs. Jacques Heath (Lily May Peel)",female,35,1,0,113803,53.1,C123,S
|
||||
5,0,3,"Allen, Mr. William Henry",male,35,0,0,373450,8.05,,S
|
||||
6,0,3,"Moran, Mr. James",male,,0,0,330877,8.4583,,Q
|
||||
7,0,1,"McCarthy, Mr. Timothy J",male,54,0,0,17463,51.8625,E46,S
|
||||
8,0,3,"Palsson, Master. Gosta Leonard",male,2,3,1,349909,21.075,,S
|
||||
9,1,3,"Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)",female,27,0,2,347742,11.1333,,S
|
||||
10,1,2,"Nasser, Mrs. Nicholas (Adele Achem)",female,14,1,0,237736,30.0708,,C
|
||||
11,1,3,"Sandstrom, Miss. Marguerite Rut",female,4,1,1,PP 9549,16.7,G6,S
|
||||
12,1,1,"Bonnell, Miss. Elizabeth",female,58,0,0,113783,26.55,C103,S
|
||||
13,0,3,"Saundercock, Mr. William Henry",male,20,0,0,A/5. 2151,8.05,,S
|
||||
14,0,3,"Andersson, Mr. Anders Johan",male,39,1,5,347082,31.275,,S
|
||||
15,0,3,"Vestrom, Miss. Hulda Amanda Adolfina",female,14,0,0,350406,7.8542,,S
|
||||
16,1,2,"Hewlett, Mrs. (Mary D Kingcome) ",female,55,0,0,248706,16,,S
|
||||
17,0,3,"Rice, Master. Eugene",male,2,4,1,382652,29.125,,Q
|
||||
18,1,2,"Williams, Mr. Charles Eugene",male,,0,0,244373,13,,S
|
||||
19,0,3,"Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)",female,31,1,0,345763,18,,S
|
||||
20,1,3,"Masselmani, Mrs. Fatima",female,,0,0,2649,7.225,,C
|
||||
21,0,2,"Fynney, Mr. Joseph J",male,35,0,0,239865,26,,S
|
||||
22,1,2,"Beesley, Mr. Lawrence",male,34,0,0,248698,13,D56,S
|
||||
23,1,3,"McGowan, Miss. Anna ""Annie""",female,15,0,0,330923,8.0292,,Q
|
||||
24,1,1,"Sloper, Mr. William Thompson",male,28,0,0,113788,35.5,A6,S
|
||||
25,0,3,"Palsson, Miss. Torborg Danira",female,8,3,1,349909,21.075,,S
|
||||
26,1,3,"Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)",female,38,1,5,347077,31.3875,,S
|
||||
27,0,3,"Emir, Mr. Farred Chehab",male,,0,0,2631,7.225,,C
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28,0,1,"Fortune, Mr. Charles Alexander",male,19,3,2,19950,263,C23 C25 C27,S
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29,1,3,"O'Dwyer, Miss. Ellen ""Nellie""",female,,0,0,330959,7.8792,,Q
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30,0,3,"Todoroff, Mr. Lalio",male,,0,0,349216,7.8958,,S
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31,0,1,"Uruchurtu, Don. Manuel E",male,40,0,0,PC 17601,27.7208,,C
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32,1,1,"Spencer, Mrs. William Augustus (Marie Eugenie)",female,,1,0,PC 17569,146.5208,B78,C
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33,1,3,"Glynn, Miss. Mary Agatha",female,,0,0,335677,7.75,,Q
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34,0,2,"Wheadon, Mr. Edward H",male,66,0,0,C.A. 24579,10.5,,S
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35,0,1,"Meyer, Mr. Edgar Joseph",male,28,1,0,PC 17604,82.1708,,C
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36,0,1,"Holverson, Mr. Alexander Oskar",male,42,1,0,113789,52,,S
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37,1,3,"Mamee, Mr. Hanna",male,,0,0,2677,7.2292,,C
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38,0,3,"Cann, Mr. Ernest Charles",male,21,0,0,A./5. 2152,8.05,,S
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39,0,3,"Vander Planke, Miss. Augusta Maria",female,18,2,0,345764,18,,S
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40,1,3,"Nicola-Yarred, Miss. Jamila",female,14,1,0,2651,11.2417,,C
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41,0,3,"Ahlin, Mrs. Johan (Johanna Persdotter Larsson)",female,40,1,0,7546,9.475,,S
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42,0,2,"Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)",female,27,1,0,11668,21,,S
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43,0,3,"Kraeff, Mr. Theodor",male,,0,0,349253,7.8958,,C
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44,1,2,"Laroche, Miss. Simonne Marie Anne Andree",female,3,1,2,SC/Paris 2123,41.5792,,C
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45,1,3,"Devaney, Miss. Margaret Delia",female,19,0,0,330958,7.8792,,Q
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46,0,3,"Rogers, Mr. William John",male,,0,0,S.C./A.4. 23567,8.05,,S
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47,0,3,"Lennon, Mr. Denis",male,,1,0,370371,15.5,,Q
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48,1,3,"O'Driscoll, Miss. Bridget",female,,0,0,14311,7.75,,Q
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49,0,3,"Samaan, Mr. Youssef",male,,2,0,2662,21.6792,,C
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50,0,3,"Arnold-Franchi, Mrs. Josef (Josefine Franchi)",female,18,1,0,349237,17.8,,S
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51,0,3,"Panula, Master. Juha Niilo",male,7,4,1,3101295,39.6875,,S
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52,0,3,"Nosworthy, Mr. Richard Cater",male,21,0,0,A/4. 39886,7.8,,S
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53,1,1,"Harper, Mrs. Henry Sleeper (Myna Haxtun)",female,49,1,0,PC 17572,76.7292,D33,C
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54,1,2,"Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)",female,29,1,0,2926,26,,S
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55,0,1,"Ostby, Mr. Engelhart Cornelius",male,65,0,1,113509,61.9792,B30,C
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56,1,1,"Woolner, Mr. Hugh",male,,0,0,19947,35.5,C52,S
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57,1,2,"Rugg, Miss. Emily",female,21,0,0,C.A. 31026,10.5,,S
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58,0,3,"Novel, Mr. Mansouer",male,28.5,0,0,2697,7.2292,,C
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59,1,2,"West, Miss. Constance Mirium",female,5,1,2,C.A. 34651,27.75,,S
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60,0,3,"Goodwin, Master. William Frederick",male,11,5,2,CA 2144,46.9,,S
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61,0,3,"Sirayanian, Mr. Orsen",male,22,0,0,2669,7.2292,,C
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62,1,1,"Icard, Miss. Amelie",female,38,0,0,113572,80,B28,
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63,0,1,"Harris, Mr. Henry Birkhardt",male,45,1,0,36973,83.475,C83,S
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64,0,3,"Skoog, Master. Harald",male,4,3,2,347088,27.9,,S
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65,0,1,"Stewart, Mr. Albert A",male,,0,0,PC 17605,27.7208,,C
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66,1,3,"Moubarek, Master. Gerios",male,,1,1,2661,15.2458,,C
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67,1,2,"Nye, Mrs. (Elizabeth Ramell)",female,29,0,0,C.A. 29395,10.5,F33,S
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68,0,3,"Crease, Mr. Ernest James",male,19,0,0,S.P. 3464,8.1583,,S
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69,1,3,"Andersson, Miss. Erna Alexandra",female,17,4,2,3101281,7.925,,S
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70,0,3,"Kink, Mr. Vincenz",male,26,2,0,315151,8.6625,,S
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71,0,2,"Jenkin, Mr. Stephen Curnow",male,32,0,0,C.A. 33111,10.5,,S
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72,0,3,"Goodwin, Miss. Lillian Amy",female,16,5,2,CA 2144,46.9,,S
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73,0,2,"Hood, Mr. Ambrose Jr",male,21,0,0,S.O.C. 14879,73.5,,S
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74,0,3,"Chronopoulos, Mr. Apostolos",male,26,1,0,2680,14.4542,,C
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75,1,3,"Bing, Mr. Lee",male,32,0,0,1601,56.4958,,S
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76,0,3,"Moen, Mr. Sigurd Hansen",male,25,0,0,348123,7.65,F G73,S
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77,0,3,"Staneff, Mr. Ivan",male,,0,0,349208,7.8958,,S
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78,0,3,"Moutal, Mr. Rahamin Haim",male,,0,0,374746,8.05,,S
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79,1,2,"Caldwell, Master. Alden Gates",male,0.83,0,2,248738,29,,S
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80,1,3,"Dowdell, Miss. Elizabeth",female,30,0,0,364516,12.475,,S
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81,0,3,"Waelens, Mr. Achille",male,22,0,0,345767,9,,S
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82,1,3,"Sheerlinck, Mr. Jan Baptist",male,29,0,0,345779,9.5,,S
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83,1,3,"McDermott, Miss. Brigdet Delia",female,,0,0,330932,7.7875,,Q
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84,0,1,"Carrau, Mr. Francisco M",male,28,0,0,113059,47.1,,S
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85,1,2,"Ilett, Miss. Bertha",female,17,0,0,SO/C 14885,10.5,,S
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86,1,3,"Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)",female,33,3,0,3101278,15.85,,S
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87,0,3,"Ford, Mr. William Neal",male,16,1,3,W./C. 6608,34.375,,S
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88,0,3,"Slocovski, Mr. Selman Francis",male,,0,0,SOTON/OQ 392086,8.05,,S
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89,1,1,"Fortune, Miss. Mabel Helen",female,23,3,2,19950,263,C23 C25 C27,S
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90,0,3,"Celotti, Mr. Francesco",male,24,0,0,343275,8.05,,S
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91,0,3,"Christmann, Mr. Emil",male,29,0,0,343276,8.05,,S
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92,0,3,"Andreasson, Mr. Paul Edvin",male,20,0,0,347466,7.8542,,S
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93,0,1,"Chaffee, Mr. Herbert Fuller",male,46,1,0,W.E.P. 5734,61.175,E31,S
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94,0,3,"Dean, Mr. Bertram Frank",male,26,1,2,C.A. 2315,20.575,,S
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95,0,3,"Coxon, Mr. Daniel",male,59,0,0,364500,7.25,,S
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96,0,3,"Shorney, Mr. Charles Joseph",male,,0,0,374910,8.05,,S
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97,0,1,"Goldschmidt, Mr. George B",male,71,0,0,PC 17754,34.6542,A5,C
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98,1,1,"Greenfield, Mr. William Bertram",male,23,0,1,PC 17759,63.3583,D10 D12,C
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99,1,2,"Doling, Mrs. John T (Ada Julia Bone)",female,34,0,1,231919,23,,S
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100,0,2,"Kantor, Mr. Sinai",male,34,1,0,244367,26,,S
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101,0,3,"Petranec, Miss. Matilda",female,28,0,0,349245,7.8958,,S
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102,0,3,"Petroff, Mr. Pastcho (""Pentcho"")",male,,0,0,349215,7.8958,,S
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103,0,1,"White, Mr. Richard Frasar",male,21,0,1,35281,77.2875,D26,S
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104,0,3,"Johansson, Mr. Gustaf Joel",male,33,0,0,7540,8.6542,,S
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105,0,3,"Gustafsson, Mr. Anders Vilhelm",male,37,2,0,3101276,7.925,,S
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106,0,3,"Mionoff, Mr. Stoytcho",male,28,0,0,349207,7.8958,,S
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107,1,3,"Salkjelsvik, Miss. Anna Kristine",female,21,0,0,343120,7.65,,S
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108,1,3,"Moss, Mr. Albert Johan",male,,0,0,312991,7.775,,S
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109,0,3,"Rekic, Mr. Tido",male,38,0,0,349249,7.8958,,S
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110,1,3,"Moran, Miss. Bertha",female,,1,0,371110,24.15,,Q
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111,0,1,"Porter, Mr. Walter Chamberlain",male,47,0,0,110465,52,C110,S
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112,0,3,"Zabour, Miss. Hileni",female,14.5,1,0,2665,14.4542,,C
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113,0,3,"Barton, Mr. David John",male,22,0,0,324669,8.05,,S
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114,0,3,"Jussila, Miss. Katriina",female,20,1,0,4136,9.825,,S
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115,0,3,"Attalah, Miss. Malake",female,17,0,0,2627,14.4583,,C
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116,0,3,"Pekoniemi, Mr. Edvard",male,21,0,0,STON/O 2. 3101294,7.925,,S
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117,0,3,"Connors, Mr. Patrick",male,70.5,0,0,370369,7.75,,Q
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118,0,2,"Turpin, Mr. William John Robert",male,29,1,0,11668,21,,S
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119,0,1,"Baxter, Mr. Quigg Edmond",male,24,0,1,PC 17558,247.5208,B58 B60,C
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120,0,3,"Andersson, Miss. Ellis Anna Maria",female,2,4,2,347082,31.275,,S
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121,0,2,"Hickman, Mr. Stanley George",male,21,2,0,S.O.C. 14879,73.5,,S
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122,0,3,"Moore, Mr. Leonard Charles",male,,0,0,A4. 54510,8.05,,S
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123,0,2,"Nasser, Mr. Nicholas",male,32.5,1,0,237736,30.0708,,C
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124,1,2,"Webber, Miss. Susan",female,32.5,0,0,27267,13,E101,S
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125,0,1,"White, Mr. Percival Wayland",male,54,0,1,35281,77.2875,D26,S
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126,1,3,"Nicola-Yarred, Master. Elias",male,12,1,0,2651,11.2417,,C
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127,0,3,"McMahon, Mr. Martin",male,,0,0,370372,7.75,,Q
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128,1,3,"Madsen, Mr. Fridtjof Arne",male,24,0,0,C 17369,7.1417,,S
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129,1,3,"Peter, Miss. Anna",female,,1,1,2668,22.3583,F E69,C
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130,0,3,"Ekstrom, Mr. Johan",male,45,0,0,347061,6.975,,S
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131,0,3,"Drazenoic, Mr. Jozef",male,33,0,0,349241,7.8958,,C
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132,0,3,"Coelho, Mr. Domingos Fernandeo",male,20,0,0,SOTON/O.Q. 3101307,7.05,,S
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133,0,3,"Robins, Mrs. Alexander A (Grace Charity Laury)",female,47,1,0,A/5. 3337,14.5,,S
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134,1,2,"Weisz, Mrs. Leopold (Mathilde Francoise Pede)",female,29,1,0,228414,26,,S
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135,0,2,"Sobey, Mr. Samuel James Hayden",male,25,0,0,C.A. 29178,13,,S
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136,0,2,"Richard, Mr. Emile",male,23,0,0,SC/PARIS 2133,15.0458,,C
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137,1,1,"Newsom, Miss. Helen Monypeny",female,19,0,2,11752,26.2833,D47,S
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138,0,1,"Futrelle, Mr. Jacques Heath",male,37,1,0,113803,53.1,C123,S
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139,0,3,"Osen, Mr. Olaf Elon",male,16,0,0,7534,9.2167,,S
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140,0,1,"Giglio, Mr. Victor",male,24,0,0,PC 17593,79.2,B86,C
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141,0,3,"Boulos, Mrs. Joseph (Sultana)",female,,0,2,2678,15.2458,,C
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142,1,3,"Nysten, Miss. Anna Sofia",female,22,0,0,347081,7.75,,S
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143,1,3,"Hakkarainen, Mrs. Pekka Pietari (Elin Matilda Dolck)",female,24,1,0,STON/O2. 3101279,15.85,,S
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144,0,3,"Burke, Mr. Jeremiah",male,19,0,0,365222,6.75,,Q
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145,0,2,"Andrew, Mr. Edgardo Samuel",male,18,0,0,231945,11.5,,S
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146,0,2,"Nicholls, Mr. Joseph Charles",male,19,1,1,C.A. 33112,36.75,,S
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147,1,3,"Andersson, Mr. August Edvard (""Wennerstrom"")",male,27,0,0,350043,7.7958,,S
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148,0,3,"Ford, Miss. Robina Maggie ""Ruby""",female,9,2,2,W./C. 6608,34.375,,S
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149,0,2,"Navratil, Mr. Michel (""Louis M Hoffman"")",male,36.5,0,2,230080,26,F2,S
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150,0,2,"Byles, Rev. Thomas Roussel Davids",male,42,0,0,244310,13,,S
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151,0,2,"Bateman, Rev. Robert James",male,51,0,0,S.O.P. 1166,12.525,,S
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152,1,1,"Pears, Mrs. Thomas (Edith Wearne)",female,22,1,0,113776,66.6,C2,S
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153,0,3,"Meo, Mr. Alfonzo",male,55.5,0,0,A.5. 11206,8.05,,S
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154,0,3,"van Billiard, Mr. Austin Blyler",male,40.5,0,2,A/5. 851,14.5,,S
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155,0,3,"Olsen, Mr. Ole Martin",male,,0,0,Fa 265302,7.3125,,S
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156,0,1,"Williams, Mr. Charles Duane",male,51,0,1,PC 17597,61.3792,,C
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157,1,3,"Gilnagh, Miss. Katherine ""Katie""",female,16,0,0,35851,7.7333,,Q
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158,0,3,"Corn, Mr. Harry",male,30,0,0,SOTON/OQ 392090,8.05,,S
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159,0,3,"Smiljanic, Mr. Mile",male,,0,0,315037,8.6625,,S
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160,0,3,"Sage, Master. Thomas Henry",male,,8,2,CA. 2343,69.55,,S
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161,0,3,"Cribb, Mr. John Hatfield",male,44,0,1,371362,16.1,,S
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162,1,2,"Watt, Mrs. James (Elizabeth ""Bessie"" Inglis Milne)",female,40,0,0,C.A. 33595,15.75,,S
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163,0,3,"Bengtsson, Mr. John Viktor",male,26,0,0,347068,7.775,,S
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164,0,3,"Calic, Mr. Jovo",male,17,0,0,315093,8.6625,,S
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165,0,3,"Panula, Master. Eino Viljami",male,1,4,1,3101295,39.6875,,S
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166,1,3,"Goldsmith, Master. Frank John William ""Frankie""",male,9,0,2,363291,20.525,,S
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167,1,1,"Chibnall, Mrs. (Edith Martha Bowerman)",female,,0,1,113505,55,E33,S
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168,0,3,"Skoog, Mrs. William (Anna Bernhardina Karlsson)",female,45,1,4,347088,27.9,,S
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169,0,1,"Baumann, Mr. John D",male,,0,0,PC 17318,25.925,,S
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170,0,3,"Ling, Mr. Lee",male,28,0,0,1601,56.4958,,S
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171,0,1,"Van der hoef, Mr. Wyckoff",male,61,0,0,111240,33.5,B19,S
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172,0,3,"Rice, Master. Arthur",male,4,4,1,382652,29.125,,Q
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173,1,3,"Johnson, Miss. Eleanor Ileen",female,1,1,1,347742,11.1333,,S
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174,0,3,"Sivola, Mr. Antti Wilhelm",male,21,0,0,STON/O 2. 3101280,7.925,,S
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175,0,1,"Smith, Mr. James Clinch",male,56,0,0,17764,30.6958,A7,C
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176,0,3,"Klasen, Mr. Klas Albin",male,18,1,1,350404,7.8542,,S
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177,0,3,"Lefebre, Master. Henry Forbes",male,,3,1,4133,25.4667,,S
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178,0,1,"Isham, Miss. Ann Elizabeth",female,50,0,0,PC 17595,28.7125,C49,C
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179,0,2,"Hale, Mr. Reginald",male,30,0,0,250653,13,,S
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180,0,3,"Leonard, Mr. Lionel",male,36,0,0,LINE,0,,S
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181,0,3,"Sage, Miss. Constance Gladys",female,,8,2,CA. 2343,69.55,,S
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182,0,2,"Pernot, Mr. Rene",male,,0,0,SC/PARIS 2131,15.05,,C
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183,0,3,"Asplund, Master. Clarence Gustaf Hugo",male,9,4,2,347077,31.3875,,S
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184,1,2,"Becker, Master. Richard F",male,1,2,1,230136,39,F4,S
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185,1,3,"Kink-Heilmann, Miss. Luise Gretchen",female,4,0,2,315153,22.025,,S
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186,0,1,"Rood, Mr. Hugh Roscoe",male,,0,0,113767,50,A32,S
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187,1,3,"O'Brien, Mrs. Thomas (Johanna ""Hannah"" Godfrey)",female,,1,0,370365,15.5,,Q
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188,1,1,"Romaine, Mr. Charles Hallace (""Mr C Rolmane"")",male,45,0,0,111428,26.55,,S
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189,0,3,"Bourke, Mr. John",male,40,1,1,364849,15.5,,Q
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190,0,3,"Turcin, Mr. Stjepan",male,36,0,0,349247,7.8958,,S
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191,1,2,"Pinsky, Mrs. (Rosa)",female,32,0,0,234604,13,,S
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192,0,2,"Carbines, Mr. William",male,19,0,0,28424,13,,S
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193,1,3,"Andersen-Jensen, Miss. Carla Christine Nielsine",female,19,1,0,350046,7.8542,,S
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194,1,2,"Navratil, Master. Michel M",male,3,1,1,230080,26,F2,S
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195,1,1,"Brown, Mrs. James Joseph (Margaret Tobin)",female,44,0,0,PC 17610,27.7208,B4,C
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196,1,1,"Lurette, Miss. Elise",female,58,0,0,PC 17569,146.5208,B80,C
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197,0,3,"Mernagh, Mr. Robert",male,,0,0,368703,7.75,,Q
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198,0,3,"Olsen, Mr. Karl Siegwart Andreas",male,42,0,1,4579,8.4042,,S
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199,1,3,"Madigan, Miss. Margaret ""Maggie""",female,,0,0,370370,7.75,,Q
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200,0,2,"Yrois, Miss. Henriette (""Mrs Harbeck"")",female,24,0,0,248747,13,,S
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201,0,3,"Vande Walle, Mr. Nestor Cyriel",male,28,0,0,345770,9.5,,S
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202,0,3,"Sage, Mr. Frederick",male,,8,2,CA. 2343,69.55,,S
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203,0,3,"Johanson, Mr. Jakob Alfred",male,34,0,0,3101264,6.4958,,S
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204,0,3,"Youseff, Mr. Gerious",male,45.5,0,0,2628,7.225,,C
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205,1,3,"Cohen, Mr. Gurshon ""Gus""",male,18,0,0,A/5 3540,8.05,,S
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206,0,3,"Strom, Miss. Telma Matilda",female,2,0,1,347054,10.4625,G6,S
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207,0,3,"Backstrom, Mr. Karl Alfred",male,32,1,0,3101278,15.85,,S
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208,1,3,"Albimona, Mr. Nassef Cassem",male,26,0,0,2699,18.7875,,C
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209,1,3,"Carr, Miss. Helen ""Ellen""",female,16,0,0,367231,7.75,,Q
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210,1,1,"Blank, Mr. Henry",male,40,0,0,112277,31,A31,C
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211,0,3,"Ali, Mr. Ahmed",male,24,0,0,SOTON/O.Q. 3101311,7.05,,S
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212,1,2,"Cameron, Miss. Clear Annie",female,35,0,0,F.C.C. 13528,21,,S
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213,0,3,"Perkin, Mr. John Henry",male,22,0,0,A/5 21174,7.25,,S
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214,0,2,"Givard, Mr. Hans Kristensen",male,30,0,0,250646,13,,S
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215,0,3,"Kiernan, Mr. Philip",male,,1,0,367229,7.75,,Q
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216,1,1,"Newell, Miss. Madeleine",female,31,1,0,35273,113.275,D36,C
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217,1,3,"Honkanen, Miss. Eliina",female,27,0,0,STON/O2. 3101283,7.925,,S
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218,0,2,"Jacobsohn, Mr. Sidney Samuel",male,42,1,0,243847,27,,S
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219,1,1,"Bazzani, Miss. Albina",female,32,0,0,11813,76.2917,D15,C
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220,0,2,"Harris, Mr. Walter",male,30,0,0,W/C 14208,10.5,,S
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221,1,3,"Sunderland, Mr. Victor Francis",male,16,0,0,SOTON/OQ 392089,8.05,,S
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222,0,2,"Bracken, Mr. James H",male,27,0,0,220367,13,,S
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223,0,3,"Green, Mr. George Henry",male,51,0,0,21440,8.05,,S
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224,0,3,"Nenkoff, Mr. Christo",male,,0,0,349234,7.8958,,S
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225,1,1,"Hoyt, Mr. Frederick Maxfield",male,38,1,0,19943,90,C93,S
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226,0,3,"Berglund, Mr. Karl Ivar Sven",male,22,0,0,PP 4348,9.35,,S
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227,1,2,"Mellors, Mr. William John",male,19,0,0,SW/PP 751,10.5,,S
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228,0,3,"Lovell, Mr. John Hall (""Henry"")",male,20.5,0,0,A/5 21173,7.25,,S
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229,0,2,"Fahlstrom, Mr. Arne Jonas",male,18,0,0,236171,13,,S
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230,0,3,"Lefebre, Miss. Mathilde",female,,3,1,4133,25.4667,,S
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231,1,1,"Harris, Mrs. Henry Birkhardt (Irene Wallach)",female,35,1,0,36973,83.475,C83,S
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232,0,3,"Larsson, Mr. Bengt Edvin",male,29,0,0,347067,7.775,,S
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233,0,2,"Sjostedt, Mr. Ernst Adolf",male,59,0,0,237442,13.5,,S
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234,1,3,"Asplund, Miss. Lillian Gertrud",female,5,4,2,347077,31.3875,,S
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235,0,2,"Leyson, Mr. Robert William Norman",male,24,0,0,C.A. 29566,10.5,,S
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236,0,3,"Harknett, Miss. Alice Phoebe",female,,0,0,W./C. 6609,7.55,,S
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237,0,2,"Hold, Mr. Stephen",male,44,1,0,26707,26,,S
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238,1,2,"Collyer, Miss. Marjorie ""Lottie""",female,8,0,2,C.A. 31921,26.25,,S
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239,0,2,"Pengelly, Mr. Frederick William",male,19,0,0,28665,10.5,,S
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240,0,2,"Hunt, Mr. George Henry",male,33,0,0,SCO/W 1585,12.275,,S
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241,0,3,"Zabour, Miss. Thamine",female,,1,0,2665,14.4542,,C
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242,1,3,"Murphy, Miss. Katherine ""Kate""",female,,1,0,367230,15.5,,Q
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243,0,2,"Coleridge, Mr. Reginald Charles",male,29,0,0,W./C. 14263,10.5,,S
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244,0,3,"Maenpaa, Mr. Matti Alexanteri",male,22,0,0,STON/O 2. 3101275,7.125,,S
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245,0,3,"Attalah, Mr. Sleiman",male,30,0,0,2694,7.225,,C
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246,0,1,"Minahan, Dr. William Edward",male,44,2,0,19928,90,C78,Q
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247,0,3,"Lindahl, Miss. Agda Thorilda Viktoria",female,25,0,0,347071,7.775,,S
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248,1,2,"Hamalainen, Mrs. William (Anna)",female,24,0,2,250649,14.5,,S
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249,1,1,"Beckwith, Mr. Richard Leonard",male,37,1,1,11751,52.5542,D35,S
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250,0,2,"Carter, Rev. Ernest Courtenay",male,54,1,0,244252,26,,S
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251,0,3,"Reed, Mr. James George",male,,0,0,362316,7.25,,S
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252,0,3,"Strom, Mrs. Wilhelm (Elna Matilda Persson)",female,29,1,1,347054,10.4625,G6,S
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253,0,1,"Stead, Mr. William Thomas",male,62,0,0,113514,26.55,C87,S
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254,0,3,"Lobb, Mr. William Arthur",male,30,1,0,A/5. 3336,16.1,,S
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255,0,3,"Rosblom, Mrs. Viktor (Helena Wilhelmina)",female,41,0,2,370129,20.2125,,S
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256,1,3,"Touma, Mrs. Darwis (Hanne Youssef Razi)",female,29,0,2,2650,15.2458,,C
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257,1,1,"Thorne, Mrs. Gertrude Maybelle",female,,0,0,PC 17585,79.2,,C
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258,1,1,"Cherry, Miss. Gladys",female,30,0,0,110152,86.5,B77,S
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259,1,1,"Ward, Miss. Anna",female,35,0,0,PC 17755,512.3292,,C
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260,1,2,"Parrish, Mrs. (Lutie Davis)",female,50,0,1,230433,26,,S
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261,0,3,"Smith, Mr. Thomas",male,,0,0,384461,7.75,,Q
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262,1,3,"Asplund, Master. Edvin Rojj Felix",male,3,4,2,347077,31.3875,,S
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263,0,1,"Taussig, Mr. Emil",male,52,1,1,110413,79.65,E67,S
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264,0,1,"Harrison, Mr. William",male,40,0,0,112059,0,B94,S
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265,0,3,"Henry, Miss. Delia",female,,0,0,382649,7.75,,Q
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266,0,2,"Reeves, Mr. David",male,36,0,0,C.A. 17248,10.5,,S
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267,0,3,"Panula, Mr. Ernesti Arvid",male,16,4,1,3101295,39.6875,,S
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268,1,3,"Persson, Mr. Ernst Ulrik",male,25,1,0,347083,7.775,,S
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269,1,1,"Graham, Mrs. William Thompson (Edith Junkins)",female,58,0,1,PC 17582,153.4625,C125,S
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270,1,1,"Bissette, Miss. Amelia",female,35,0,0,PC 17760,135.6333,C99,S
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271,0,1,"Cairns, Mr. Alexander",male,,0,0,113798,31,,S
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272,1,3,"Tornquist, Mr. William Henry",male,25,0,0,LINE,0,,S
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273,1,2,"Mellinger, Mrs. (Elizabeth Anne Maidment)",female,41,0,1,250644,19.5,,S
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274,0,1,"Natsch, Mr. Charles H",male,37,0,1,PC 17596,29.7,C118,C
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275,1,3,"Healy, Miss. Hanora ""Nora""",female,,0,0,370375,7.75,,Q
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276,1,1,"Andrews, Miss. Kornelia Theodosia",female,63,1,0,13502,77.9583,D7,S
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277,0,3,"Lindblom, Miss. Augusta Charlotta",female,45,0,0,347073,7.75,,S
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278,0,2,"Parkes, Mr. Francis ""Frank""",male,,0,0,239853,0,,S
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279,0,3,"Rice, Master. Eric",male,7,4,1,382652,29.125,,Q
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280,1,3,"Abbott, Mrs. Stanton (Rosa Hunt)",female,35,1,1,C.A. 2673,20.25,,S
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281,0,3,"Duane, Mr. Frank",male,65,0,0,336439,7.75,,Q
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282,0,3,"Olsson, Mr. Nils Johan Goransson",male,28,0,0,347464,7.8542,,S
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283,0,3,"de Pelsmaeker, Mr. Alfons",male,16,0,0,345778,9.5,,S
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284,1,3,"Dorking, Mr. Edward Arthur",male,19,0,0,A/5. 10482,8.05,,S
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285,0,1,"Smith, Mr. Richard William",male,,0,0,113056,26,A19,S
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286,0,3,"Stankovic, Mr. Ivan",male,33,0,0,349239,8.6625,,C
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287,1,3,"de Mulder, Mr. Theodore",male,30,0,0,345774,9.5,,S
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288,0,3,"Naidenoff, Mr. Penko",male,22,0,0,349206,7.8958,,S
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289,1,2,"Hosono, Mr. Masabumi",male,42,0,0,237798,13,,S
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290,1,3,"Connolly, Miss. Kate",female,22,0,0,370373,7.75,,Q
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291,1,1,"Barber, Miss. Ellen ""Nellie""",female,26,0,0,19877,78.85,,S
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292,1,1,"Bishop, Mrs. Dickinson H (Helen Walton)",female,19,1,0,11967,91.0792,B49,C
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293,0,2,"Levy, Mr. Rene Jacques",male,36,0,0,SC/Paris 2163,12.875,D,C
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294,0,3,"Haas, Miss. Aloisia",female,24,0,0,349236,8.85,,S
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295,0,3,"Mineff, Mr. Ivan",male,24,0,0,349233,7.8958,,S
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296,0,1,"Lewy, Mr. Ervin G",male,,0,0,PC 17612,27.7208,,C
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297,0,3,"Hanna, Mr. Mansour",male,23.5,0,0,2693,7.2292,,C
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298,0,1,"Allison, Miss. Helen Loraine",female,2,1,2,113781,151.55,C22 C26,S
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299,1,1,"Saalfeld, Mr. Adolphe",male,,0,0,19988,30.5,C106,S
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300,1,1,"Baxter, Mrs. James (Helene DeLaudeniere Chaput)",female,50,0,1,PC 17558,247.5208,B58 B60,C
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301,1,3,"Kelly, Miss. Anna Katherine ""Annie Kate""",female,,0,0,9234,7.75,,Q
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302,1,3,"McCoy, Mr. Bernard",male,,2,0,367226,23.25,,Q
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303,0,3,"Johnson, Mr. William Cahoone Jr",male,19,0,0,LINE,0,,S
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304,1,2,"Keane, Miss. Nora A",female,,0,0,226593,12.35,E101,Q
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305,0,3,"Williams, Mr. Howard Hugh ""Harry""",male,,0,0,A/5 2466,8.05,,S
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306,1,1,"Allison, Master. Hudson Trevor",male,0.92,1,2,113781,151.55,C22 C26,S
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307,1,1,"Fleming, Miss. Margaret",female,,0,0,17421,110.8833,,C
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308,1,1,"Penasco y Castellana, Mrs. Victor de Satode (Maria Josefa Perez de Soto y Vallejo)",female,17,1,0,PC 17758,108.9,C65,C
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309,0,2,"Abelson, Mr. Samuel",male,30,1,0,P/PP 3381,24,,C
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310,1,1,"Francatelli, Miss. Laura Mabel",female,30,0,0,PC 17485,56.9292,E36,C
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311,1,1,"Hays, Miss. Margaret Bechstein",female,24,0,0,11767,83.1583,C54,C
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312,1,1,"Ryerson, Miss. Emily Borie",female,18,2,2,PC 17608,262.375,B57 B59 B63 B66,C
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313,0,2,"Lahtinen, Mrs. William (Anna Sylfven)",female,26,1,1,250651,26,,S
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314,0,3,"Hendekovic, Mr. Ignjac",male,28,0,0,349243,7.8958,,S
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315,0,2,"Hart, Mr. Benjamin",male,43,1,1,F.C.C. 13529,26.25,,S
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316,1,3,"Nilsson, Miss. Helmina Josefina",female,26,0,0,347470,7.8542,,S
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317,1,2,"Kantor, Mrs. Sinai (Miriam Sternin)",female,24,1,0,244367,26,,S
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318,0,2,"Moraweck, Dr. Ernest",male,54,0,0,29011,14,,S
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319,1,1,"Wick, Miss. Mary Natalie",female,31,0,2,36928,164.8667,C7,S
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320,1,1,"Spedden, Mrs. Frederic Oakley (Margaretta Corning Stone)",female,40,1,1,16966,134.5,E34,C
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321,0,3,"Dennis, Mr. Samuel",male,22,0,0,A/5 21172,7.25,,S
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322,0,3,"Danoff, Mr. Yoto",male,27,0,0,349219,7.8958,,S
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323,1,2,"Slayter, Miss. Hilda Mary",female,30,0,0,234818,12.35,,Q
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324,1,2,"Caldwell, Mrs. Albert Francis (Sylvia Mae Harbaugh)",female,22,1,1,248738,29,,S
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325,0,3,"Sage, Mr. George John Jr",male,,8,2,CA. 2343,69.55,,S
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326,1,1,"Young, Miss. Marie Grice",female,36,0,0,PC 17760,135.6333,C32,C
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327,0,3,"Nysveen, Mr. Johan Hansen",male,61,0,0,345364,6.2375,,S
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328,1,2,"Ball, Mrs. (Ada E Hall)",female,36,0,0,28551,13,D,S
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329,1,3,"Goldsmith, Mrs. Frank John (Emily Alice Brown)",female,31,1,1,363291,20.525,,S
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330,1,1,"Hippach, Miss. Jean Gertrude",female,16,0,1,111361,57.9792,B18,C
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331,1,3,"McCoy, Miss. Agnes",female,,2,0,367226,23.25,,Q
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332,0,1,"Partner, Mr. Austen",male,45.5,0,0,113043,28.5,C124,S
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333,0,1,"Graham, Mr. George Edward",male,38,0,1,PC 17582,153.4625,C91,S
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334,0,3,"Vander Planke, Mr. Leo Edmondus",male,16,2,0,345764,18,,S
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335,1,1,"Frauenthal, Mrs. Henry William (Clara Heinsheimer)",female,,1,0,PC 17611,133.65,,S
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336,0,3,"Denkoff, Mr. Mitto",male,,0,0,349225,7.8958,,S
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337,0,1,"Pears, Mr. Thomas Clinton",male,29,1,0,113776,66.6,C2,S
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338,1,1,"Burns, Miss. Elizabeth Margaret",female,41,0,0,16966,134.5,E40,C
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339,1,3,"Dahl, Mr. Karl Edwart",male,45,0,0,7598,8.05,,S
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340,0,1,"Blackwell, Mr. Stephen Weart",male,45,0,0,113784,35.5,T,S
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341,1,2,"Navratil, Master. Edmond Roger",male,2,1,1,230080,26,F2,S
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342,1,1,"Fortune, Miss. Alice Elizabeth",female,24,3,2,19950,263,C23 C25 C27,S
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343,0,2,"Collander, Mr. Erik Gustaf",male,28,0,0,248740,13,,S
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344,0,2,"Sedgwick, Mr. Charles Frederick Waddington",male,25,0,0,244361,13,,S
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345,0,2,"Fox, Mr. Stanley Hubert",male,36,0,0,229236,13,,S
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346,1,2,"Brown, Miss. Amelia ""Mildred""",female,24,0,0,248733,13,F33,S
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347,1,2,"Smith, Miss. Marion Elsie",female,40,0,0,31418,13,,S
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348,1,3,"Davison, Mrs. Thomas Henry (Mary E Finck)",female,,1,0,386525,16.1,,S
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349,1,3,"Coutts, Master. William Loch ""William""",male,3,1,1,C.A. 37671,15.9,,S
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350,0,3,"Dimic, Mr. Jovan",male,42,0,0,315088,8.6625,,S
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351,0,3,"Odahl, Mr. Nils Martin",male,23,0,0,7267,9.225,,S
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352,0,1,"Williams-Lambert, Mr. Fletcher Fellows",male,,0,0,113510,35,C128,S
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353,0,3,"Elias, Mr. Tannous",male,15,1,1,2695,7.2292,,C
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354,0,3,"Arnold-Franchi, Mr. Josef",male,25,1,0,349237,17.8,,S
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355,0,3,"Yousif, Mr. Wazli",male,,0,0,2647,7.225,,C
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356,0,3,"Vanden Steen, Mr. Leo Peter",male,28,0,0,345783,9.5,,S
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357,1,1,"Bowerman, Miss. Elsie Edith",female,22,0,1,113505,55,E33,S
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358,0,2,"Funk, Miss. Annie Clemmer",female,38,0,0,237671,13,,S
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359,1,3,"McGovern, Miss. Mary",female,,0,0,330931,7.8792,,Q
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360,1,3,"Mockler, Miss. Helen Mary ""Ellie""",female,,0,0,330980,7.8792,,Q
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361,0,3,"Skoog, Mr. Wilhelm",male,40,1,4,347088,27.9,,S
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362,0,2,"del Carlo, Mr. Sebastiano",male,29,1,0,SC/PARIS 2167,27.7208,,C
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363,0,3,"Barbara, Mrs. (Catherine David)",female,45,0,1,2691,14.4542,,C
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364,0,3,"Asim, Mr. Adola",male,35,0,0,SOTON/O.Q. 3101310,7.05,,S
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365,0,3,"O'Brien, Mr. Thomas",male,,1,0,370365,15.5,,Q
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366,0,3,"Adahl, Mr. Mauritz Nils Martin",male,30,0,0,C 7076,7.25,,S
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367,1,1,"Warren, Mrs. Frank Manley (Anna Sophia Atkinson)",female,60,1,0,110813,75.25,D37,C
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368,1,3,"Moussa, Mrs. (Mantoura Boulos)",female,,0,0,2626,7.2292,,C
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369,1,3,"Jermyn, Miss. Annie",female,,0,0,14313,7.75,,Q
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370,1,1,"Aubart, Mme. Leontine Pauline",female,24,0,0,PC 17477,69.3,B35,C
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371,1,1,"Harder, Mr. George Achilles",male,25,1,0,11765,55.4417,E50,C
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372,0,3,"Wiklund, Mr. Jakob Alfred",male,18,1,0,3101267,6.4958,,S
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373,0,3,"Beavan, Mr. William Thomas",male,19,0,0,323951,8.05,,S
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374,0,1,"Ringhini, Mr. Sante",male,22,0,0,PC 17760,135.6333,,C
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375,0,3,"Palsson, Miss. Stina Viola",female,3,3,1,349909,21.075,,S
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376,1,1,"Meyer, Mrs. Edgar Joseph (Leila Saks)",female,,1,0,PC 17604,82.1708,,C
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377,1,3,"Landergren, Miss. Aurora Adelia",female,22,0,0,C 7077,7.25,,S
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378,0,1,"Widener, Mr. Harry Elkins",male,27,0,2,113503,211.5,C82,C
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379,0,3,"Betros, Mr. Tannous",male,20,0,0,2648,4.0125,,C
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380,0,3,"Gustafsson, Mr. Karl Gideon",male,19,0,0,347069,7.775,,S
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381,1,1,"Bidois, Miss. Rosalie",female,42,0,0,PC 17757,227.525,,C
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382,1,3,"Nakid, Miss. Maria (""Mary"")",female,1,0,2,2653,15.7417,,C
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383,0,3,"Tikkanen, Mr. Juho",male,32,0,0,STON/O 2. 3101293,7.925,,S
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384,1,1,"Holverson, Mrs. Alexander Oskar (Mary Aline Towner)",female,35,1,0,113789,52,,S
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385,0,3,"Plotcharsky, Mr. Vasil",male,,0,0,349227,7.8958,,S
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386,0,2,"Davies, Mr. Charles Henry",male,18,0,0,S.O.C. 14879,73.5,,S
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387,0,3,"Goodwin, Master. Sidney Leonard",male,1,5,2,CA 2144,46.9,,S
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388,1,2,"Buss, Miss. Kate",female,36,0,0,27849,13,,S
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389,0,3,"Sadlier, Mr. Matthew",male,,0,0,367655,7.7292,,Q
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390,1,2,"Lehmann, Miss. Bertha",female,17,0,0,SC 1748,12,,C
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391,1,1,"Carter, Mr. William Ernest",male,36,1,2,113760,120,B96 B98,S
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392,1,3,"Jansson, Mr. Carl Olof",male,21,0,0,350034,7.7958,,S
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393,0,3,"Gustafsson, Mr. Johan Birger",male,28,2,0,3101277,7.925,,S
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394,1,1,"Newell, Miss. Marjorie",female,23,1,0,35273,113.275,D36,C
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395,1,3,"Sandstrom, Mrs. Hjalmar (Agnes Charlotta Bengtsson)",female,24,0,2,PP 9549,16.7,G6,S
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396,0,3,"Johansson, Mr. Erik",male,22,0,0,350052,7.7958,,S
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397,0,3,"Olsson, Miss. Elina",female,31,0,0,350407,7.8542,,S
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398,0,2,"McKane, Mr. Peter David",male,46,0,0,28403,26,,S
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399,0,2,"Pain, Dr. Alfred",male,23,0,0,244278,10.5,,S
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400,1,2,"Trout, Mrs. William H (Jessie L)",female,28,0,0,240929,12.65,,S
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401,1,3,"Niskanen, Mr. Juha",male,39,0,0,STON/O 2. 3101289,7.925,,S
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402,0,3,"Adams, Mr. John",male,26,0,0,341826,8.05,,S
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403,0,3,"Jussila, Miss. Mari Aina",female,21,1,0,4137,9.825,,S
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404,0,3,"Hakkarainen, Mr. Pekka Pietari",male,28,1,0,STON/O2. 3101279,15.85,,S
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405,0,3,"Oreskovic, Miss. Marija",female,20,0,0,315096,8.6625,,S
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406,0,2,"Gale, Mr. Shadrach",male,34,1,0,28664,21,,S
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407,0,3,"Widegren, Mr. Carl/Charles Peter",male,51,0,0,347064,7.75,,S
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408,1,2,"Richards, Master. William Rowe",male,3,1,1,29106,18.75,,S
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409,0,3,"Birkeland, Mr. Hans Martin Monsen",male,21,0,0,312992,7.775,,S
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410,0,3,"Lefebre, Miss. Ida",female,,3,1,4133,25.4667,,S
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411,0,3,"Sdycoff, Mr. Todor",male,,0,0,349222,7.8958,,S
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412,0,3,"Hart, Mr. Henry",male,,0,0,394140,6.8583,,Q
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413,1,1,"Minahan, Miss. Daisy E",female,33,1,0,19928,90,C78,Q
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414,0,2,"Cunningham, Mr. Alfred Fleming",male,,0,0,239853,0,,S
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415,1,3,"Sundman, Mr. Johan Julian",male,44,0,0,STON/O 2. 3101269,7.925,,S
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416,0,3,"Meek, Mrs. Thomas (Annie Louise Rowley)",female,,0,0,343095,8.05,,S
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417,1,2,"Drew, Mrs. James Vivian (Lulu Thorne Christian)",female,34,1,1,28220,32.5,,S
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418,1,2,"Silven, Miss. Lyyli Karoliina",female,18,0,2,250652,13,,S
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419,0,2,"Matthews, Mr. William John",male,30,0,0,28228,13,,S
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420,0,3,"Van Impe, Miss. Catharina",female,10,0,2,345773,24.15,,S
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421,0,3,"Gheorgheff, Mr. Stanio",male,,0,0,349254,7.8958,,C
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422,0,3,"Charters, Mr. David",male,21,0,0,A/5. 13032,7.7333,,Q
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423,0,3,"Zimmerman, Mr. Leo",male,29,0,0,315082,7.875,,S
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424,0,3,"Danbom, Mrs. Ernst Gilbert (Anna Sigrid Maria Brogren)",female,28,1,1,347080,14.4,,S
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425,0,3,"Rosblom, Mr. Viktor Richard",male,18,1,1,370129,20.2125,,S
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426,0,3,"Wiseman, Mr. Phillippe",male,,0,0,A/4. 34244,7.25,,S
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427,1,2,"Clarke, Mrs. Charles V (Ada Maria Winfield)",female,28,1,0,2003,26,,S
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428,1,2,"Phillips, Miss. Kate Florence (""Mrs Kate Louise Phillips Marshall"")",female,19,0,0,250655,26,,S
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429,0,3,"Flynn, Mr. James",male,,0,0,364851,7.75,,Q
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430,1,3,"Pickard, Mr. Berk (Berk Trembisky)",male,32,0,0,SOTON/O.Q. 392078,8.05,E10,S
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431,1,1,"Bjornstrom-Steffansson, Mr. Mauritz Hakan",male,28,0,0,110564,26.55,C52,S
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432,1,3,"Thorneycroft, Mrs. Percival (Florence Kate White)",female,,1,0,376564,16.1,,S
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433,1,2,"Louch, Mrs. Charles Alexander (Alice Adelaide Slow)",female,42,1,0,SC/AH 3085,26,,S
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434,0,3,"Kallio, Mr. Nikolai Erland",male,17,0,0,STON/O 2. 3101274,7.125,,S
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435,0,1,"Silvey, Mr. William Baird",male,50,1,0,13507,55.9,E44,S
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436,1,1,"Carter, Miss. Lucile Polk",female,14,1,2,113760,120,B96 B98,S
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437,0,3,"Ford, Miss. Doolina Margaret ""Daisy""",female,21,2,2,W./C. 6608,34.375,,S
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438,1,2,"Richards, Mrs. Sidney (Emily Hocking)",female,24,2,3,29106,18.75,,S
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439,0,1,"Fortune, Mr. Mark",male,64,1,4,19950,263,C23 C25 C27,S
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440,0,2,"Kvillner, Mr. Johan Henrik Johannesson",male,31,0,0,C.A. 18723,10.5,,S
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441,1,2,"Hart, Mrs. Benjamin (Esther Ada Bloomfield)",female,45,1,1,F.C.C. 13529,26.25,,S
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442,0,3,"Hampe, Mr. Leon",male,20,0,0,345769,9.5,,S
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443,0,3,"Petterson, Mr. Johan Emil",male,25,1,0,347076,7.775,,S
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444,1,2,"Reynaldo, Ms. Encarnacion",female,28,0,0,230434,13,,S
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445,1,3,"Johannesen-Bratthammer, Mr. Bernt",male,,0,0,65306,8.1125,,S
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446,1,1,"Dodge, Master. Washington",male,4,0,2,33638,81.8583,A34,S
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447,1,2,"Mellinger, Miss. Madeleine Violet",female,13,0,1,250644,19.5,,S
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448,1,1,"Seward, Mr. Frederic Kimber",male,34,0,0,113794,26.55,,S
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449,1,3,"Baclini, Miss. Marie Catherine",female,5,2,1,2666,19.2583,,C
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450,1,1,"Peuchen, Major. Arthur Godfrey",male,52,0,0,113786,30.5,C104,S
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451,0,2,"West, Mr. Edwy Arthur",male,36,1,2,C.A. 34651,27.75,,S
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452,0,3,"Hagland, Mr. Ingvald Olai Olsen",male,,1,0,65303,19.9667,,S
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453,0,1,"Foreman, Mr. Benjamin Laventall",male,30,0,0,113051,27.75,C111,C
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454,1,1,"Goldenberg, Mr. Samuel L",male,49,1,0,17453,89.1042,C92,C
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455,0,3,"Peduzzi, Mr. Joseph",male,,0,0,A/5 2817,8.05,,S
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456,1,3,"Jalsevac, Mr. Ivan",male,29,0,0,349240,7.8958,,C
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457,0,1,"Millet, Mr. Francis Davis",male,65,0,0,13509,26.55,E38,S
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458,1,1,"Kenyon, Mrs. Frederick R (Marion)",female,,1,0,17464,51.8625,D21,S
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459,1,2,"Toomey, Miss. Ellen",female,50,0,0,F.C.C. 13531,10.5,,S
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460,0,3,"O'Connor, Mr. Maurice",male,,0,0,371060,7.75,,Q
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461,1,1,"Anderson, Mr. Harry",male,48,0,0,19952,26.55,E12,S
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462,0,3,"Morley, Mr. William",male,34,0,0,364506,8.05,,S
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463,0,1,"Gee, Mr. Arthur H",male,47,0,0,111320,38.5,E63,S
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464,0,2,"Milling, Mr. Jacob Christian",male,48,0,0,234360,13,,S
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465,0,3,"Maisner, Mr. Simon",male,,0,0,A/S 2816,8.05,,S
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466,0,3,"Goncalves, Mr. Manuel Estanslas",male,38,0,0,SOTON/O.Q. 3101306,7.05,,S
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467,0,2,"Campbell, Mr. William",male,,0,0,239853,0,,S
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468,0,1,"Smart, Mr. John Montgomery",male,56,0,0,113792,26.55,,S
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469,0,3,"Scanlan, Mr. James",male,,0,0,36209,7.725,,Q
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470,1,3,"Baclini, Miss. Helene Barbara",female,0.75,2,1,2666,19.2583,,C
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471,0,3,"Keefe, Mr. Arthur",male,,0,0,323592,7.25,,S
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472,0,3,"Cacic, Mr. Luka",male,38,0,0,315089,8.6625,,S
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473,1,2,"West, Mrs. Edwy Arthur (Ada Mary Worth)",female,33,1,2,C.A. 34651,27.75,,S
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474,1,2,"Jerwan, Mrs. Amin S (Marie Marthe Thuillard)",female,23,0,0,SC/AH Basle 541,13.7917,D,C
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475,0,3,"Strandberg, Miss. Ida Sofia",female,22,0,0,7553,9.8375,,S
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476,0,1,"Clifford, Mr. George Quincy",male,,0,0,110465,52,A14,S
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477,0,2,"Renouf, Mr. Peter Henry",male,34,1,0,31027,21,,S
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478,0,3,"Braund, Mr. Lewis Richard",male,29,1,0,3460,7.0458,,S
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479,0,3,"Karlsson, Mr. Nils August",male,22,0,0,350060,7.5208,,S
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480,1,3,"Hirvonen, Miss. Hildur E",female,2,0,1,3101298,12.2875,,S
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481,0,3,"Goodwin, Master. Harold Victor",male,9,5,2,CA 2144,46.9,,S
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482,0,2,"Frost, Mr. Anthony Wood ""Archie""",male,,0,0,239854,0,,S
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483,0,3,"Rouse, Mr. Richard Henry",male,50,0,0,A/5 3594,8.05,,S
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484,1,3,"Turkula, Mrs. (Hedwig)",female,63,0,0,4134,9.5875,,S
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485,1,1,"Bishop, Mr. Dickinson H",male,25,1,0,11967,91.0792,B49,C
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486,0,3,"Lefebre, Miss. Jeannie",female,,3,1,4133,25.4667,,S
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487,1,1,"Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)",female,35,1,0,19943,90,C93,S
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488,0,1,"Kent, Mr. Edward Austin",male,58,0,0,11771,29.7,B37,C
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489,0,3,"Somerton, Mr. Francis William",male,30,0,0,A.5. 18509,8.05,,S
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490,1,3,"Coutts, Master. Eden Leslie ""Neville""",male,9,1,1,C.A. 37671,15.9,,S
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491,0,3,"Hagland, Mr. Konrad Mathias Reiersen",male,,1,0,65304,19.9667,,S
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492,0,3,"Windelov, Mr. Einar",male,21,0,0,SOTON/OQ 3101317,7.25,,S
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493,0,1,"Molson, Mr. Harry Markland",male,55,0,0,113787,30.5,C30,S
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494,0,1,"Artagaveytia, Mr. Ramon",male,71,0,0,PC 17609,49.5042,,C
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495,0,3,"Stanley, Mr. Edward Roland",male,21,0,0,A/4 45380,8.05,,S
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496,0,3,"Yousseff, Mr. Gerious",male,,0,0,2627,14.4583,,C
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497,1,1,"Eustis, Miss. Elizabeth Mussey",female,54,1,0,36947,78.2667,D20,C
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498,0,3,"Shellard, Mr. Frederick William",male,,0,0,C.A. 6212,15.1,,S
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499,0,1,"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)",female,25,1,2,113781,151.55,C22 C26,S
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500,0,3,"Svensson, Mr. Olof",male,24,0,0,350035,7.7958,,S
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501,0,3,"Calic, Mr. Petar",male,17,0,0,315086,8.6625,,S
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502,0,3,"Canavan, Miss. Mary",female,21,0,0,364846,7.75,,Q
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503,0,3,"O'Sullivan, Miss. Bridget Mary",female,,0,0,330909,7.6292,,Q
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504,0,3,"Laitinen, Miss. Kristina Sofia",female,37,0,0,4135,9.5875,,S
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505,1,1,"Maioni, Miss. Roberta",female,16,0,0,110152,86.5,B79,S
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506,0,1,"Penasco y Castellana, Mr. Victor de Satode",male,18,1,0,PC 17758,108.9,C65,C
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507,1,2,"Quick, Mrs. Frederick Charles (Jane Richards)",female,33,0,2,26360,26,,S
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508,1,1,"Bradley, Mr. George (""George Arthur Brayton"")",male,,0,0,111427,26.55,,S
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509,0,3,"Olsen, Mr. Henry Margido",male,28,0,0,C 4001,22.525,,S
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510,1,3,"Lang, Mr. Fang",male,26,0,0,1601,56.4958,,S
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511,1,3,"Daly, Mr. Eugene Patrick",male,29,0,0,382651,7.75,,Q
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512,0,3,"Webber, Mr. James",male,,0,0,SOTON/OQ 3101316,8.05,,S
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513,1,1,"McGough, Mr. James Robert",male,36,0,0,PC 17473,26.2875,E25,S
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514,1,1,"Rothschild, Mrs. Martin (Elizabeth L. Barrett)",female,54,1,0,PC 17603,59.4,,C
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515,0,3,"Coleff, Mr. Satio",male,24,0,0,349209,7.4958,,S
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516,0,1,"Walker, Mr. William Anderson",male,47,0,0,36967,34.0208,D46,S
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517,1,2,"Lemore, Mrs. (Amelia Milley)",female,34,0,0,C.A. 34260,10.5,F33,S
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518,0,3,"Ryan, Mr. Patrick",male,,0,0,371110,24.15,,Q
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519,1,2,"Angle, Mrs. William A (Florence ""Mary"" Agnes Hughes)",female,36,1,0,226875,26,,S
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520,0,3,"Pavlovic, Mr. Stefo",male,32,0,0,349242,7.8958,,S
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521,1,1,"Perreault, Miss. Anne",female,30,0,0,12749,93.5,B73,S
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522,0,3,"Vovk, Mr. Janko",male,22,0,0,349252,7.8958,,S
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523,0,3,"Lahoud, Mr. Sarkis",male,,0,0,2624,7.225,,C
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524,1,1,"Hippach, Mrs. Louis Albert (Ida Sophia Fischer)",female,44,0,1,111361,57.9792,B18,C
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525,0,3,"Kassem, Mr. Fared",male,,0,0,2700,7.2292,,C
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526,0,3,"Farrell, Mr. James",male,40.5,0,0,367232,7.75,,Q
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527,1,2,"Ridsdale, Miss. Lucy",female,50,0,0,W./C. 14258,10.5,,S
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528,0,1,"Farthing, Mr. John",male,,0,0,PC 17483,221.7792,C95,S
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529,0,3,"Salonen, Mr. Johan Werner",male,39,0,0,3101296,7.925,,S
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530,0,2,"Hocking, Mr. Richard George",male,23,2,1,29104,11.5,,S
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531,1,2,"Quick, Miss. Phyllis May",female,2,1,1,26360,26,,S
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532,0,3,"Toufik, Mr. Nakli",male,,0,0,2641,7.2292,,C
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533,0,3,"Elias, Mr. Joseph Jr",male,17,1,1,2690,7.2292,,C
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534,1,3,"Peter, Mrs. Catherine (Catherine Rizk)",female,,0,2,2668,22.3583,,C
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535,0,3,"Cacic, Miss. Marija",female,30,0,0,315084,8.6625,,S
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536,1,2,"Hart, Miss. Eva Miriam",female,7,0,2,F.C.C. 13529,26.25,,S
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537,0,1,"Butt, Major. Archibald Willingham",male,45,0,0,113050,26.55,B38,S
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538,1,1,"LeRoy, Miss. Bertha",female,30,0,0,PC 17761,106.425,,C
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539,0,3,"Risien, Mr. Samuel Beard",male,,0,0,364498,14.5,,S
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540,1,1,"Frolicher, Miss. Hedwig Margaritha",female,22,0,2,13568,49.5,B39,C
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541,1,1,"Crosby, Miss. Harriet R",female,36,0,2,WE/P 5735,71,B22,S
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542,0,3,"Andersson, Miss. Ingeborg Constanzia",female,9,4,2,347082,31.275,,S
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543,0,3,"Andersson, Miss. Sigrid Elisabeth",female,11,4,2,347082,31.275,,S
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544,1,2,"Beane, Mr. Edward",male,32,1,0,2908,26,,S
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545,0,1,"Douglas, Mr. Walter Donald",male,50,1,0,PC 17761,106.425,C86,C
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546,0,1,"Nicholson, Mr. Arthur Ernest",male,64,0,0,693,26,,S
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547,1,2,"Beane, Mrs. Edward (Ethel Clarke)",female,19,1,0,2908,26,,S
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548,1,2,"Padro y Manent, Mr. Julian",male,,0,0,SC/PARIS 2146,13.8625,,C
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549,0,3,"Goldsmith, Mr. Frank John",male,33,1,1,363291,20.525,,S
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550,1,2,"Davies, Master. John Morgan Jr",male,8,1,1,C.A. 33112,36.75,,S
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551,1,1,"Thayer, Mr. John Borland Jr",male,17,0,2,17421,110.8833,C70,C
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552,0,2,"Sharp, Mr. Percival James R",male,27,0,0,244358,26,,S
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553,0,3,"O'Brien, Mr. Timothy",male,,0,0,330979,7.8292,,Q
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554,1,3,"Leeni, Mr. Fahim (""Philip Zenni"")",male,22,0,0,2620,7.225,,C
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555,1,3,"Ohman, Miss. Velin",female,22,0,0,347085,7.775,,S
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556,0,1,"Wright, Mr. George",male,62,0,0,113807,26.55,,S
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557,1,1,"Duff Gordon, Lady. (Lucille Christiana Sutherland) (""Mrs Morgan"")",female,48,1,0,11755,39.6,A16,C
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558,0,1,"Robbins, Mr. Victor",male,,0,0,PC 17757,227.525,,C
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559,1,1,"Taussig, Mrs. Emil (Tillie Mandelbaum)",female,39,1,1,110413,79.65,E67,S
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560,1,3,"de Messemaeker, Mrs. Guillaume Joseph (Emma)",female,36,1,0,345572,17.4,,S
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561,0,3,"Morrow, Mr. Thomas Rowan",male,,0,0,372622,7.75,,Q
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562,0,3,"Sivic, Mr. Husein",male,40,0,0,349251,7.8958,,S
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563,0,2,"Norman, Mr. Robert Douglas",male,28,0,0,218629,13.5,,S
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564,0,3,"Simmons, Mr. John",male,,0,0,SOTON/OQ 392082,8.05,,S
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565,0,3,"Meanwell, Miss. (Marion Ogden)",female,,0,0,SOTON/O.Q. 392087,8.05,,S
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566,0,3,"Davies, Mr. Alfred J",male,24,2,0,A/4 48871,24.15,,S
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567,0,3,"Stoytcheff, Mr. Ilia",male,19,0,0,349205,7.8958,,S
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568,0,3,"Palsson, Mrs. Nils (Alma Cornelia Berglund)",female,29,0,4,349909,21.075,,S
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569,0,3,"Doharr, Mr. Tannous",male,,0,0,2686,7.2292,,C
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570,1,3,"Jonsson, Mr. Carl",male,32,0,0,350417,7.8542,,S
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571,1,2,"Harris, Mr. George",male,62,0,0,S.W./PP 752,10.5,,S
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572,1,1,"Appleton, Mrs. Edward Dale (Charlotte Lamson)",female,53,2,0,11769,51.4792,C101,S
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573,1,1,"Flynn, Mr. John Irwin (""Irving"")",male,36,0,0,PC 17474,26.3875,E25,S
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574,1,3,"Kelly, Miss. Mary",female,,0,0,14312,7.75,,Q
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575,0,3,"Rush, Mr. Alfred George John",male,16,0,0,A/4. 20589,8.05,,S
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576,0,3,"Patchett, Mr. George",male,19,0,0,358585,14.5,,S
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577,1,2,"Garside, Miss. Ethel",female,34,0,0,243880,13,,S
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578,1,1,"Silvey, Mrs. William Baird (Alice Munger)",female,39,1,0,13507,55.9,E44,S
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579,0,3,"Caram, Mrs. Joseph (Maria Elias)",female,,1,0,2689,14.4583,,C
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580,1,3,"Jussila, Mr. Eiriik",male,32,0,0,STON/O 2. 3101286,7.925,,S
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581,1,2,"Christy, Miss. Julie Rachel",female,25,1,1,237789,30,,S
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582,1,1,"Thayer, Mrs. John Borland (Marian Longstreth Morris)",female,39,1,1,17421,110.8833,C68,C
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583,0,2,"Downton, Mr. William James",male,54,0,0,28403,26,,S
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584,0,1,"Ross, Mr. John Hugo",male,36,0,0,13049,40.125,A10,C
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585,0,3,"Paulner, Mr. Uscher",male,,0,0,3411,8.7125,,C
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586,1,1,"Taussig, Miss. Ruth",female,18,0,2,110413,79.65,E68,S
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587,0,2,"Jarvis, Mr. John Denzil",male,47,0,0,237565,15,,S
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588,1,1,"Frolicher-Stehli, Mr. Maxmillian",male,60,1,1,13567,79.2,B41,C
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589,0,3,"Gilinski, Mr. Eliezer",male,22,0,0,14973,8.05,,S
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590,0,3,"Murdlin, Mr. Joseph",male,,0,0,A./5. 3235,8.05,,S
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591,0,3,"Rintamaki, Mr. Matti",male,35,0,0,STON/O 2. 3101273,7.125,,S
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592,1,1,"Stephenson, Mrs. Walter Bertram (Martha Eustis)",female,52,1,0,36947,78.2667,D20,C
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593,0,3,"Elsbury, Mr. William James",male,47,0,0,A/5 3902,7.25,,S
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594,0,3,"Bourke, Miss. Mary",female,,0,2,364848,7.75,,Q
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595,0,2,"Chapman, Mr. John Henry",male,37,1,0,SC/AH 29037,26,,S
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596,0,3,"Van Impe, Mr. Jean Baptiste",male,36,1,1,345773,24.15,,S
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597,1,2,"Leitch, Miss. Jessie Wills",female,,0,0,248727,33,,S
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598,0,3,"Johnson, Mr. Alfred",male,49,0,0,LINE,0,,S
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599,0,3,"Boulos, Mr. Hanna",male,,0,0,2664,7.225,,C
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600,1,1,"Duff Gordon, Sir. Cosmo Edmund (""Mr Morgan"")",male,49,1,0,PC 17485,56.9292,A20,C
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605,1,1,"Homer, Mr. Harry (""Mr E Haven"")",male,35,0,0,111426,26.55,,C
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606,0,3,"Lindell, Mr. Edvard Bengtsson",male,36,1,0,349910,15.55,,S
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607,0,3,"Karaic, Mr. Milan",male,30,0,0,349246,7.8958,,S
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608,1,1,"Daniel, Mr. Robert Williams",male,27,0,0,113804,30.5,,S
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609,1,2,"Laroche, Mrs. Joseph (Juliette Marie Louise Lafargue)",female,22,1,2,SC/Paris 2123,41.5792,,C
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610,1,1,"Shutes, Miss. Elizabeth W",female,40,0,0,PC 17582,153.4625,C125,S
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611,0,3,"Andersson, Mrs. Anders Johan (Alfrida Konstantia Brogren)",female,39,1,5,347082,31.275,,S
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612,0,3,"Jardin, Mr. Jose Neto",male,,0,0,SOTON/O.Q. 3101305,7.05,,S
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613,1,3,"Murphy, Miss. Margaret Jane",female,,1,0,367230,15.5,,Q
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614,0,3,"Horgan, Mr. John",male,,0,0,370377,7.75,,Q
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615,0,3,"Brocklebank, Mr. William Alfred",male,35,0,0,364512,8.05,,S
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616,1,2,"Herman, Miss. Alice",female,24,1,2,220845,65,,S
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617,0,3,"Danbom, Mr. Ernst Gilbert",male,34,1,1,347080,14.4,,S
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618,0,3,"Lobb, Mrs. William Arthur (Cordelia K Stanlick)",female,26,1,0,A/5. 3336,16.1,,S
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619,1,2,"Becker, Miss. Marion Louise",female,4,2,1,230136,39,F4,S
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620,0,2,"Gavey, Mr. Lawrence",male,26,0,0,31028,10.5,,S
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621,0,3,"Yasbeck, Mr. Antoni",male,27,1,0,2659,14.4542,,C
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622,1,1,"Kimball, Mr. Edwin Nelson Jr",male,42,1,0,11753,52.5542,D19,S
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623,1,3,"Nakid, Mr. Sahid",male,20,1,1,2653,15.7417,,C
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624,0,3,"Hansen, Mr. Henry Damsgaard",male,21,0,0,350029,7.8542,,S
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625,0,3,"Bowen, Mr. David John ""Dai""",male,21,0,0,54636,16.1,,S
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626,0,1,"Sutton, Mr. Frederick",male,61,0,0,36963,32.3208,D50,S
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627,0,2,"Kirkland, Rev. Charles Leonard",male,57,0,0,219533,12.35,,Q
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628,1,1,"Longley, Miss. Gretchen Fiske",female,21,0,0,13502,77.9583,D9,S
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629,0,3,"Bostandyeff, Mr. Guentcho",male,26,0,0,349224,7.8958,,S
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630,0,3,"O'Connell, Mr. Patrick D",male,,0,0,334912,7.7333,,Q
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631,1,1,"Barkworth, Mr. Algernon Henry Wilson",male,80,0,0,27042,30,A23,S
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632,0,3,"Lundahl, Mr. Johan Svensson",male,51,0,0,347743,7.0542,,S
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633,1,1,"Stahelin-Maeglin, Dr. Max",male,32,0,0,13214,30.5,B50,C
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634,0,1,"Parr, Mr. William Henry Marsh",male,,0,0,112052,0,,S
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635,0,3,"Skoog, Miss. Mabel",female,9,3,2,347088,27.9,,S
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636,1,2,"Davis, Miss. Mary",female,28,0,0,237668,13,,S
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637,0,3,"Leinonen, Mr. Antti Gustaf",male,32,0,0,STON/O 2. 3101292,7.925,,S
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638,0,2,"Collyer, Mr. Harvey",male,31,1,1,C.A. 31921,26.25,,S
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639,0,3,"Panula, Mrs. Juha (Maria Emilia Ojala)",female,41,0,5,3101295,39.6875,,S
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640,0,3,"Thorneycroft, Mr. Percival",male,,1,0,376564,16.1,,S
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641,0,3,"Jensen, Mr. Hans Peder",male,20,0,0,350050,7.8542,,S
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642,1,1,"Sagesser, Mlle. Emma",female,24,0,0,PC 17477,69.3,B35,C
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643,0,3,"Skoog, Miss. Margit Elizabeth",female,2,3,2,347088,27.9,,S
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644,1,3,"Foo, Mr. Choong",male,,0,0,1601,56.4958,,S
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645,1,3,"Baclini, Miss. Eugenie",female,0.75,2,1,2666,19.2583,,C
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646,1,1,"Harper, Mr. Henry Sleeper",male,48,1,0,PC 17572,76.7292,D33,C
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647,0,3,"Cor, Mr. Liudevit",male,19,0,0,349231,7.8958,,S
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648,1,1,"Simonius-Blumer, Col. Oberst Alfons",male,56,0,0,13213,35.5,A26,C
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649,0,3,"Willey, Mr. Edward",male,,0,0,S.O./P.P. 751,7.55,,S
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650,1,3,"Stanley, Miss. Amy Zillah Elsie",female,23,0,0,CA. 2314,7.55,,S
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651,0,3,"Mitkoff, Mr. Mito",male,,0,0,349221,7.8958,,S
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652,1,2,"Doling, Miss. Elsie",female,18,0,1,231919,23,,S
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653,0,3,"Kalvik, Mr. Johannes Halvorsen",male,21,0,0,8475,8.4333,,S
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654,1,3,"O'Leary, Miss. Hanora ""Norah""",female,,0,0,330919,7.8292,,Q
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655,0,3,"Hegarty, Miss. Hanora ""Nora""",female,18,0,0,365226,6.75,,Q
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656,0,2,"Hickman, Mr. Leonard Mark",male,24,2,0,S.O.C. 14879,73.5,,S
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657,0,3,"Radeff, Mr. Alexander",male,,0,0,349223,7.8958,,S
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658,0,3,"Bourke, Mrs. John (Catherine)",female,32,1,1,364849,15.5,,Q
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659,0,2,"Eitemiller, Mr. George Floyd",male,23,0,0,29751,13,,S
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660,0,1,"Newell, Mr. Arthur Webster",male,58,0,2,35273,113.275,D48,C
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661,1,1,"Frauenthal, Dr. Henry William",male,50,2,0,PC 17611,133.65,,S
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662,0,3,"Badt, Mr. Mohamed",male,40,0,0,2623,7.225,,C
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663,0,1,"Colley, Mr. Edward Pomeroy",male,47,0,0,5727,25.5875,E58,S
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664,0,3,"Coleff, Mr. Peju",male,36,0,0,349210,7.4958,,S
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665,1,3,"Lindqvist, Mr. Eino William",male,20,1,0,STON/O 2. 3101285,7.925,,S
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666,0,2,"Hickman, Mr. Lewis",male,32,2,0,S.O.C. 14879,73.5,,S
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667,0,2,"Butler, Mr. Reginald Fenton",male,25,0,0,234686,13,,S
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668,0,3,"Rommetvedt, Mr. Knud Paust",male,,0,0,312993,7.775,,S
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669,0,3,"Cook, Mr. Jacob",male,43,0,0,A/5 3536,8.05,,S
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670,1,1,"Taylor, Mrs. Elmer Zebley (Juliet Cummins Wright)",female,,1,0,19996,52,C126,S
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671,1,2,"Brown, Mrs. Thomas William Solomon (Elizabeth Catherine Ford)",female,40,1,1,29750,39,,S
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672,0,1,"Davidson, Mr. Thornton",male,31,1,0,F.C. 12750,52,B71,S
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673,0,2,"Mitchell, Mr. Henry Michael",male,70,0,0,C.A. 24580,10.5,,S
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674,1,2,"Wilhelms, Mr. Charles",male,31,0,0,244270,13,,S
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675,0,2,"Watson, Mr. Ennis Hastings",male,,0,0,239856,0,,S
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676,0,3,"Edvardsson, Mr. Gustaf Hjalmar",male,18,0,0,349912,7.775,,S
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677,0,3,"Sawyer, Mr. Frederick Charles",male,24.5,0,0,342826,8.05,,S
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678,1,3,"Turja, Miss. Anna Sofia",female,18,0,0,4138,9.8417,,S
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679,0,3,"Goodwin, Mrs. Frederick (Augusta Tyler)",female,43,1,6,CA 2144,46.9,,S
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680,1,1,"Cardeza, Mr. Thomas Drake Martinez",male,36,0,1,PC 17755,512.3292,B51 B53 B55,C
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681,0,3,"Peters, Miss. Katie",female,,0,0,330935,8.1375,,Q
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682,1,1,"Hassab, Mr. Hammad",male,27,0,0,PC 17572,76.7292,D49,C
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683,0,3,"Olsvigen, Mr. Thor Anderson",male,20,0,0,6563,9.225,,S
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684,0,3,"Goodwin, Mr. Charles Edward",male,14,5,2,CA 2144,46.9,,S
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685,0,2,"Brown, Mr. Thomas William Solomon",male,60,1,1,29750,39,,S
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686,0,2,"Laroche, Mr. Joseph Philippe Lemercier",male,25,1,2,SC/Paris 2123,41.5792,,C
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687,0,3,"Panula, Mr. Jaako Arnold",male,14,4,1,3101295,39.6875,,S
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688,0,3,"Dakic, Mr. Branko",male,19,0,0,349228,10.1708,,S
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689,0,3,"Fischer, Mr. Eberhard Thelander",male,18,0,0,350036,7.7958,,S
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690,1,1,"Madill, Miss. Georgette Alexandra",female,15,0,1,24160,211.3375,B5,S
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691,1,1,"Dick, Mr. Albert Adrian",male,31,1,0,17474,57,B20,S
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692,1,3,"Karun, Miss. Manca",female,4,0,1,349256,13.4167,,C
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693,1,3,"Lam, Mr. Ali",male,,0,0,1601,56.4958,,S
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694,0,3,"Saad, Mr. Khalil",male,25,0,0,2672,7.225,,C
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695,0,1,"Weir, Col. John",male,60,0,0,113800,26.55,,S
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696,0,2,"Chapman, Mr. Charles Henry",male,52,0,0,248731,13.5,,S
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697,0,3,"Kelly, Mr. James",male,44,0,0,363592,8.05,,S
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698,1,3,"Mullens, Miss. Katherine ""Katie""",female,,0,0,35852,7.7333,,Q
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699,0,1,"Thayer, Mr. John Borland",male,49,1,1,17421,110.8833,C68,C
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700,0,3,"Humblen, Mr. Adolf Mathias Nicolai Olsen",male,42,0,0,348121,7.65,F G63,S
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701,1,1,"Astor, Mrs. John Jacob (Madeleine Talmadge Force)",female,18,1,0,PC 17757,227.525,C62 C64,C
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702,1,1,"Silverthorne, Mr. Spencer Victor",male,35,0,0,PC 17475,26.2875,E24,S
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703,0,3,"Barbara, Miss. Saiide",female,18,0,1,2691,14.4542,,C
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704,0,3,"Gallagher, Mr. Martin",male,25,0,0,36864,7.7417,,Q
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705,0,3,"Hansen, Mr. Henrik Juul",male,26,1,0,350025,7.8542,,S
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706,0,2,"Morley, Mr. Henry Samuel (""Mr Henry Marshall"")",male,39,0,0,250655,26,,S
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707,1,2,"Kelly, Mrs. Florence ""Fannie""",female,45,0,0,223596,13.5,,S
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708,1,1,"Calderhead, Mr. Edward Pennington",male,42,0,0,PC 17476,26.2875,E24,S
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709,1,1,"Cleaver, Miss. Alice",female,22,0,0,113781,151.55,,S
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710,1,3,"Moubarek, Master. Halim Gonios (""William George"")",male,,1,1,2661,15.2458,,C
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711,1,1,"Mayne, Mlle. Berthe Antonine (""Mrs de Villiers"")",female,24,0,0,PC 17482,49.5042,C90,C
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712,0,1,"Klaber, Mr. Herman",male,,0,0,113028,26.55,C124,S
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713,1,1,"Taylor, Mr. Elmer Zebley",male,48,1,0,19996,52,C126,S
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714,0,3,"Larsson, Mr. August Viktor",male,29,0,0,7545,9.4833,,S
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715,0,2,"Greenberg, Mr. Samuel",male,52,0,0,250647,13,,S
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716,0,3,"Soholt, Mr. Peter Andreas Lauritz Andersen",male,19,0,0,348124,7.65,F G73,S
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717,1,1,"Endres, Miss. Caroline Louise",female,38,0,0,PC 17757,227.525,C45,C
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718,1,2,"Troutt, Miss. Edwina Celia ""Winnie""",female,27,0,0,34218,10.5,E101,S
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719,0,3,"McEvoy, Mr. Michael",male,,0,0,36568,15.5,,Q
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720,0,3,"Johnson, Mr. Malkolm Joackim",male,33,0,0,347062,7.775,,S
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721,1,2,"Harper, Miss. Annie Jessie ""Nina""",female,6,0,1,248727,33,,S
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722,0,3,"Jensen, Mr. Svend Lauritz",male,17,1,0,350048,7.0542,,S
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723,0,2,"Gillespie, Mr. William Henry",male,34,0,0,12233,13,,S
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724,0,2,"Hodges, Mr. Henry Price",male,50,0,0,250643,13,,S
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725,1,1,"Chambers, Mr. Norman Campbell",male,27,1,0,113806,53.1,E8,S
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726,0,3,"Oreskovic, Mr. Luka",male,20,0,0,315094,8.6625,,S
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727,1,2,"Renouf, Mrs. Peter Henry (Lillian Jefferys)",female,30,3,0,31027,21,,S
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728,1,3,"Mannion, Miss. Margareth",female,,0,0,36866,7.7375,,Q
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729,0,2,"Bryhl, Mr. Kurt Arnold Gottfrid",male,25,1,0,236853,26,,S
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730,0,3,"Ilmakangas, Miss. Pieta Sofia",female,25,1,0,STON/O2. 3101271,7.925,,S
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731,1,1,"Allen, Miss. Elisabeth Walton",female,29,0,0,24160,211.3375,B5,S
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732,0,3,"Hassan, Mr. Houssein G N",male,11,0,0,2699,18.7875,,C
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733,0,2,"Knight, Mr. Robert J",male,,0,0,239855,0,,S
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734,0,2,"Berriman, Mr. William John",male,23,0,0,28425,13,,S
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735,0,2,"Troupiansky, Mr. Moses Aaron",male,23,0,0,233639,13,,S
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736,0,3,"Williams, Mr. Leslie",male,28.5,0,0,54636,16.1,,S
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737,0,3,"Ford, Mrs. Edward (Margaret Ann Watson)",female,48,1,3,W./C. 6608,34.375,,S
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738,1,1,"Lesurer, Mr. Gustave J",male,35,0,0,PC 17755,512.3292,B101,C
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739,0,3,"Ivanoff, Mr. Kanio",male,,0,0,349201,7.8958,,S
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740,0,3,"Nankoff, Mr. Minko",male,,0,0,349218,7.8958,,S
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741,1,1,"Hawksford, Mr. Walter James",male,,0,0,16988,30,D45,S
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742,0,1,"Cavendish, Mr. Tyrell William",male,36,1,0,19877,78.85,C46,S
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743,1,1,"Ryerson, Miss. Susan Parker ""Suzette""",female,21,2,2,PC 17608,262.375,B57 B59 B63 B66,C
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744,0,3,"McNamee, Mr. Neal",male,24,1,0,376566,16.1,,S
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745,1,3,"Stranden, Mr. Juho",male,31,0,0,STON/O 2. 3101288,7.925,,S
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746,0,1,"Crosby, Capt. Edward Gifford",male,70,1,1,WE/P 5735,71,B22,S
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747,0,3,"Abbott, Mr. Rossmore Edward",male,16,1,1,C.A. 2673,20.25,,S
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748,1,2,"Sinkkonen, Miss. Anna",female,30,0,0,250648,13,,S
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749,0,1,"Marvin, Mr. Daniel Warner",male,19,1,0,113773,53.1,D30,S
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750,0,3,"Connaghton, Mr. Michael",male,31,0,0,335097,7.75,,Q
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751,1,2,"Wells, Miss. Joan",female,4,1,1,29103,23,,S
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752,1,3,"Moor, Master. Meier",male,6,0,1,392096,12.475,E121,S
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753,0,3,"Vande Velde, Mr. Johannes Joseph",male,33,0,0,345780,9.5,,S
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754,0,3,"Jonkoff, Mr. Lalio",male,23,0,0,349204,7.8958,,S
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755,1,2,"Herman, Mrs. Samuel (Jane Laver)",female,48,1,2,220845,65,,S
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756,1,2,"Hamalainen, Master. Viljo",male,0.67,1,1,250649,14.5,,S
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757,0,3,"Carlsson, Mr. August Sigfrid",male,28,0,0,350042,7.7958,,S
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758,0,2,"Bailey, Mr. Percy Andrew",male,18,0,0,29108,11.5,,S
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759,0,3,"Theobald, Mr. Thomas Leonard",male,34,0,0,363294,8.05,,S
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760,1,1,"Rothes, the Countess. of (Lucy Noel Martha Dyer-Edwards)",female,33,0,0,110152,86.5,B77,S
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761,0,3,"Garfirth, Mr. John",male,,0,0,358585,14.5,,S
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762,0,3,"Nirva, Mr. Iisakki Antino Aijo",male,41,0,0,SOTON/O2 3101272,7.125,,S
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763,1,3,"Barah, Mr. Hanna Assi",male,20,0,0,2663,7.2292,,C
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764,1,1,"Carter, Mrs. William Ernest (Lucile Polk)",female,36,1,2,113760,120,B96 B98,S
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765,0,3,"Eklund, Mr. Hans Linus",male,16,0,0,347074,7.775,,S
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766,1,1,"Hogeboom, Mrs. John C (Anna Andrews)",female,51,1,0,13502,77.9583,D11,S
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767,0,1,"Brewe, Dr. Arthur Jackson",male,,0,0,112379,39.6,,C
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768,0,3,"Mangan, Miss. Mary",female,30.5,0,0,364850,7.75,,Q
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769,0,3,"Moran, Mr. Daniel J",male,,1,0,371110,24.15,,Q
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770,0,3,"Gronnestad, Mr. Daniel Danielsen",male,32,0,0,8471,8.3625,,S
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771,0,3,"Lievens, Mr. Rene Aime",male,24,0,0,345781,9.5,,S
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772,0,3,"Jensen, Mr. Niels Peder",male,48,0,0,350047,7.8542,,S
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773,0,2,"Mack, Mrs. (Mary)",female,57,0,0,S.O./P.P. 3,10.5,E77,S
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774,0,3,"Elias, Mr. Dibo",male,,0,0,2674,7.225,,C
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775,1,2,"Hocking, Mrs. Elizabeth (Eliza Needs)",female,54,1,3,29105,23,,S
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776,0,3,"Myhrman, Mr. Pehr Fabian Oliver Malkolm",male,18,0,0,347078,7.75,,S
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777,0,3,"Tobin, Mr. Roger",male,,0,0,383121,7.75,F38,Q
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778,1,3,"Emanuel, Miss. Virginia Ethel",female,5,0,0,364516,12.475,,S
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779,0,3,"Kilgannon, Mr. Thomas J",male,,0,0,36865,7.7375,,Q
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780,1,1,"Robert, Mrs. Edward Scott (Elisabeth Walton McMillan)",female,43,0,1,24160,211.3375,B3,S
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781,1,3,"Ayoub, Miss. Banoura",female,13,0,0,2687,7.2292,,C
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782,1,1,"Dick, Mrs. Albert Adrian (Vera Gillespie)",female,17,1,0,17474,57,B20,S
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783,0,1,"Long, Mr. Milton Clyde",male,29,0,0,113501,30,D6,S
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784,0,3,"Johnston, Mr. Andrew G",male,,1,2,W./C. 6607,23.45,,S
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785,0,3,"Ali, Mr. William",male,25,0,0,SOTON/O.Q. 3101312,7.05,,S
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786,0,3,"Harmer, Mr. Abraham (David Lishin)",male,25,0,0,374887,7.25,,S
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787,1,3,"Sjoblom, Miss. Anna Sofia",female,18,0,0,3101265,7.4958,,S
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788,0,3,"Rice, Master. George Hugh",male,8,4,1,382652,29.125,,Q
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789,1,3,"Dean, Master. Bertram Vere",male,1,1,2,C.A. 2315,20.575,,S
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790,0,1,"Guggenheim, Mr. Benjamin",male,46,0,0,PC 17593,79.2,B82 B84,C
|
||||
791,0,3,"Keane, Mr. Andrew ""Andy""",male,,0,0,12460,7.75,,Q
|
||||
792,0,2,"Gaskell, Mr. Alfred",male,16,0,0,239865,26,,S
|
||||
793,0,3,"Sage, Miss. Stella Anna",female,,8,2,CA. 2343,69.55,,S
|
||||
794,0,1,"Hoyt, Mr. William Fisher",male,,0,0,PC 17600,30.6958,,C
|
||||
795,0,3,"Dantcheff, Mr. Ristiu",male,25,0,0,349203,7.8958,,S
|
||||
796,0,2,"Otter, Mr. Richard",male,39,0,0,28213,13,,S
|
||||
797,1,1,"Leader, Dr. Alice (Farnham)",female,49,0,0,17465,25.9292,D17,S
|
||||
798,1,3,"Osman, Mrs. Mara",female,31,0,0,349244,8.6833,,S
|
||||
799,0,3,"Ibrahim Shawah, Mr. Yousseff",male,30,0,0,2685,7.2292,,C
|
||||
800,0,3,"Van Impe, Mrs. Jean Baptiste (Rosalie Paula Govaert)",female,30,1,1,345773,24.15,,S
|
||||
801,0,2,"Ponesell, Mr. Martin",male,34,0,0,250647,13,,S
|
||||
802,1,2,"Collyer, Mrs. Harvey (Charlotte Annie Tate)",female,31,1,1,C.A. 31921,26.25,,S
|
||||
803,1,1,"Carter, Master. William Thornton II",male,11,1,2,113760,120,B96 B98,S
|
||||
804,1,3,"Thomas, Master. Assad Alexander",male,0.42,0,1,2625,8.5167,,C
|
||||
805,1,3,"Hedman, Mr. Oskar Arvid",male,27,0,0,347089,6.975,,S
|
||||
806,0,3,"Johansson, Mr. Karl Johan",male,31,0,0,347063,7.775,,S
|
||||
807,0,1,"Andrews, Mr. Thomas Jr",male,39,0,0,112050,0,A36,S
|
||||
808,0,3,"Pettersson, Miss. Ellen Natalia",female,18,0,0,347087,7.775,,S
|
||||
809,0,2,"Meyer, Mr. August",male,39,0,0,248723,13,,S
|
||||
810,1,1,"Chambers, Mrs. Norman Campbell (Bertha Griggs)",female,33,1,0,113806,53.1,E8,S
|
||||
811,0,3,"Alexander, Mr. William",male,26,0,0,3474,7.8875,,S
|
||||
812,0,3,"Lester, Mr. James",male,39,0,0,A/4 48871,24.15,,S
|
||||
813,0,2,"Slemen, Mr. Richard James",male,35,0,0,28206,10.5,,S
|
||||
814,0,3,"Andersson, Miss. Ebba Iris Alfrida",female,6,4,2,347082,31.275,,S
|
||||
815,0,3,"Tomlin, Mr. Ernest Portage",male,30.5,0,0,364499,8.05,,S
|
||||
816,0,1,"Fry, Mr. Richard",male,,0,0,112058,0,B102,S
|
||||
817,0,3,"Heininen, Miss. Wendla Maria",female,23,0,0,STON/O2. 3101290,7.925,,S
|
||||
818,0,2,"Mallet, Mr. Albert",male,31,1,1,S.C./PARIS 2079,37.0042,,C
|
||||
819,0,3,"Holm, Mr. John Fredrik Alexander",male,43,0,0,C 7075,6.45,,S
|
||||
820,0,3,"Skoog, Master. Karl Thorsten",male,10,3,2,347088,27.9,,S
|
||||
821,1,1,"Hays, Mrs. Charles Melville (Clara Jennings Gregg)",female,52,1,1,12749,93.5,B69,S
|
||||
822,1,3,"Lulic, Mr. Nikola",male,27,0,0,315098,8.6625,,S
|
||||
823,0,1,"Reuchlin, Jonkheer. John George",male,38,0,0,19972,0,,S
|
||||
824,1,3,"Moor, Mrs. (Beila)",female,27,0,1,392096,12.475,E121,S
|
||||
825,0,3,"Panula, Master. Urho Abraham",male,2,4,1,3101295,39.6875,,S
|
||||
826,0,3,"Flynn, Mr. John",male,,0,0,368323,6.95,,Q
|
||||
827,0,3,"Lam, Mr. Len",male,,0,0,1601,56.4958,,S
|
||||
828,1,2,"Mallet, Master. Andre",male,1,0,2,S.C./PARIS 2079,37.0042,,C
|
||||
829,1,3,"McCormack, Mr. Thomas Joseph",male,,0,0,367228,7.75,,Q
|
||||
830,1,1,"Stone, Mrs. George Nelson (Martha Evelyn)",female,62,0,0,113572,80,B28,
|
||||
831,1,3,"Yasbeck, Mrs. Antoni (Selini Alexander)",female,15,1,0,2659,14.4542,,C
|
||||
832,1,2,"Richards, Master. George Sibley",male,0.83,1,1,29106,18.75,,S
|
||||
833,0,3,"Saad, Mr. Amin",male,,0,0,2671,7.2292,,C
|
||||
834,0,3,"Augustsson, Mr. Albert",male,23,0,0,347468,7.8542,,S
|
||||
835,0,3,"Allum, Mr. Owen George",male,18,0,0,2223,8.3,,S
|
||||
836,1,1,"Compton, Miss. Sara Rebecca",female,39,1,1,PC 17756,83.1583,E49,C
|
||||
837,0,3,"Pasic, Mr. Jakob",male,21,0,0,315097,8.6625,,S
|
||||
838,0,3,"Sirota, Mr. Maurice",male,,0,0,392092,8.05,,S
|
||||
839,1,3,"Chip, Mr. Chang",male,32,0,0,1601,56.4958,,S
|
||||
840,1,1,"Marechal, Mr. Pierre",male,,0,0,11774,29.7,C47,C
|
||||
841,0,3,"Alhomaki, Mr. Ilmari Rudolf",male,20,0,0,SOTON/O2 3101287,7.925,,S
|
||||
842,0,2,"Mudd, Mr. Thomas Charles",male,16,0,0,S.O./P.P. 3,10.5,,S
|
||||
843,1,1,"Serepeca, Miss. Augusta",female,30,0,0,113798,31,,C
|
||||
844,0,3,"Lemberopolous, Mr. Peter L",male,34.5,0,0,2683,6.4375,,C
|
||||
845,0,3,"Culumovic, Mr. Jeso",male,17,0,0,315090,8.6625,,S
|
||||
846,0,3,"Abbing, Mr. Anthony",male,42,0,0,C.A. 5547,7.55,,S
|
||||
847,0,3,"Sage, Mr. Douglas Bullen",male,,8,2,CA. 2343,69.55,,S
|
||||
848,0,3,"Markoff, Mr. Marin",male,35,0,0,349213,7.8958,,C
|
||||
849,0,2,"Harper, Rev. John",male,28,0,1,248727,33,,S
|
||||
850,1,1,"Goldenberg, Mrs. Samuel L (Edwiga Grabowska)",female,,1,0,17453,89.1042,C92,C
|
||||
851,0,3,"Andersson, Master. Sigvard Harald Elias",male,4,4,2,347082,31.275,,S
|
||||
852,0,3,"Svensson, Mr. Johan",male,74,0,0,347060,7.775,,S
|
||||
853,0,3,"Boulos, Miss. Nourelain",female,9,1,1,2678,15.2458,,C
|
||||
854,1,1,"Lines, Miss. Mary Conover",female,16,0,1,PC 17592,39.4,D28,S
|
||||
855,0,2,"Carter, Mrs. Ernest Courtenay (Lilian Hughes)",female,44,1,0,244252,26,,S
|
||||
856,1,3,"Aks, Mrs. Sam (Leah Rosen)",female,18,0,1,392091,9.35,,S
|
||||
857,1,1,"Wick, Mrs. George Dennick (Mary Hitchcock)",female,45,1,1,36928,164.8667,,S
|
||||
858,1,1,"Daly, Mr. Peter Denis ",male,51,0,0,113055,26.55,E17,S
|
||||
859,1,3,"Baclini, Mrs. Solomon (Latifa Qurban)",female,24,0,3,2666,19.2583,,C
|
||||
860,0,3,"Razi, Mr. Raihed",male,,0,0,2629,7.2292,,C
|
||||
861,0,3,"Hansen, Mr. Claus Peter",male,41,2,0,350026,14.1083,,S
|
||||
862,0,2,"Giles, Mr. Frederick Edward",male,21,1,0,28134,11.5,,S
|
||||
863,1,1,"Swift, Mrs. Frederick Joel (Margaret Welles Barron)",female,48,0,0,17466,25.9292,D17,S
|
||||
864,0,3,"Sage, Miss. Dorothy Edith ""Dolly""",female,,8,2,CA. 2343,69.55,,S
|
||||
865,0,2,"Gill, Mr. John William",male,24,0,0,233866,13,,S
|
||||
866,1,2,"Bystrom, Mrs. (Karolina)",female,42,0,0,236852,13,,S
|
||||
867,1,2,"Duran y More, Miss. Asuncion",female,27,1,0,SC/PARIS 2149,13.8583,,C
|
||||
868,0,1,"Roebling, Mr. Washington Augustus II",male,31,0,0,PC 17590,50.4958,A24,S
|
||||
869,0,3,"van Melkebeke, Mr. Philemon",male,,0,0,345777,9.5,,S
|
||||
870,1,3,"Johnson, Master. Harold Theodor",male,4,1,1,347742,11.1333,,S
|
||||
871,0,3,"Balkic, Mr. Cerin",male,26,0,0,349248,7.8958,,S
|
||||
872,1,1,"Beckwith, Mrs. Richard Leonard (Sallie Monypeny)",female,47,1,1,11751,52.5542,D35,S
|
||||
873,0,1,"Carlsson, Mr. Frans Olof",male,33,0,0,695,5,B51 B53 B55,S
|
||||
874,0,3,"Vander Cruyssen, Mr. Victor",male,47,0,0,345765,9,,S
|
||||
875,1,2,"Abelson, Mrs. Samuel (Hannah Wizosky)",female,28,1,0,P/PP 3381,24,,C
|
||||
876,1,3,"Najib, Miss. Adele Kiamie ""Jane""",female,15,0,0,2667,7.225,,C
|
||||
877,0,3,"Gustafsson, Mr. Alfred Ossian",male,20,0,0,7534,9.8458,,S
|
||||
878,0,3,"Petroff, Mr. Nedelio",male,19,0,0,349212,7.8958,,S
|
||||
879,0,3,"Laleff, Mr. Kristo",male,,0,0,349217,7.8958,,S
|
||||
880,1,1,"Potter, Mrs. Thomas Jr (Lily Alexenia Wilson)",female,56,0,1,11767,83.1583,C50,C
|
||||
881,1,2,"Shelley, Mrs. William (Imanita Parrish Hall)",female,25,0,1,230433,26,,S
|
||||
882,0,3,"Markun, Mr. Johann",male,33,0,0,349257,7.8958,,S
|
||||
883,0,3,"Dahlberg, Miss. Gerda Ulrika",female,22,0,0,7552,10.5167,,S
|
||||
884,0,2,"Banfield, Mr. Frederick James",male,28,0,0,C.A./SOTON 34068,10.5,,S
|
||||
885,0,3,"Sutehall, Mr. Henry Jr",male,25,0,0,SOTON/OQ 392076,7.05,,S
|
||||
886,0,3,"Rice, Mrs. William (Margaret Norton)",female,39,0,5,382652,29.125,,Q
|
||||
887,0,2,"Montvila, Rev. Juozas",male,27,0,0,211536,13,,S
|
||||
888,1,1,"Graham, Miss. Margaret Edith",female,19,0,0,112053,30,B42,S
|
||||
889,0,3,"Johnston, Miss. Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S
|
||||
890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C
|
||||
891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q
|
|
@ -0,0 +1,417 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "18ada398-dce6-4049-9b56-fc0ede63da9c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Vectorstore Agent\n",
|
||||
"\n",
|
||||
"This notebook showcases an agent designed to retrieve information from one or more vectorstores, either with or without sources."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "eecb683b-3a46-4b9d-81a3-7caefbfec1a1",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Create the Vectorstores"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "9bfd0ed8-a5eb-443e-8e92-90be8cabb0a7",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.embeddings.openai import OpenAIEmbeddings\n",
|
||||
"from langchain.vectorstores import Chroma\n",
|
||||
"from langchain.text_splitter import CharacterTextSplitter\n",
|
||||
"from langchain import OpenAI, VectorDBQA\n",
|
||||
"llm = OpenAI(temperature=0)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "345bb078-4ec1-4e3a-827b-cd238c49054d",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Running Chroma using direct local API.\n",
|
||||
"Using DuckDB in-memory for database. Data will be transient.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain.document_loaders import TextLoader\n",
|
||||
"loader = TextLoader('../../state_of_the_union.txt')\n",
|
||||
"documents = loader.load()\n",
|
||||
"text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)\n",
|
||||
"texts = text_splitter.split_documents(documents)\n",
|
||||
"\n",
|
||||
"embeddings = OpenAIEmbeddings()\n",
|
||||
"state_of_union_store = Chroma.from_documents(texts, embeddings, collection_name=\"state-of-union\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "5f50eb82-e1a5-4252-8306-8ec1b478d9b4",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Running Chroma using direct local API.\n",
|
||||
"Using DuckDB in-memory for database. Data will be transient.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from langchain.document_loaders import WebBaseLoader\n",
|
||||
"loader = WebBaseLoader(\"https://beta.ruff.rs/docs/faq/\")\n",
|
||||
"docs = loader.load()\n",
|
||||
"ruff_texts = text_splitter.split_documents(docs)\n",
|
||||
"ruff_store = Chroma.from_documents(ruff_texts, embeddings, collection_name=\"ruff\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f4814175-964d-42f1-aa9d-22801ce1e912",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Initalize Toolkit and Agent\n",
|
||||
"\n",
|
||||
"First, we'll create an agent with a single vectorstore."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "5b3b3206",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.agents.agent_toolkits import (\n",
|
||||
" create_vectorstore_agent,\n",
|
||||
" VectorStoreToolkit,\n",
|
||||
" VectorStoreInfo,\n",
|
||||
")\n",
|
||||
"vectorstore_info = VectorStoreInfo(\n",
|
||||
" name=\"state_of_union_address\",\n",
|
||||
" description=\"the most recent state of the Union adress\",\n",
|
||||
" vectorstore=state_of_union_store\n",
|
||||
")\n",
|
||||
"toolkit = VectorStoreToolkit(vectorstore_info=vectorstore_info)\n",
|
||||
"agent_executor = create_vectorstore_agent(\n",
|
||||
" llm=llm,\n",
|
||||
" toolkit=toolkit,\n",
|
||||
" verbose=True\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "8a38ad10",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Examples"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "3f2f455c",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to find the answer in the state of the union address\n",
|
||||
"Action: state_of_union_address\n",
|
||||
"Action Input: What did biden say about ketanji brown jackson\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m Biden said that Ketanji Brown Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: Biden said that Ketanji Brown Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"Biden said that Ketanji Brown Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\""
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"What did biden say about ketanji brown jackson is the state of the union address?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "d61e1e63",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to use the state_of_union_address_with_sources tool to answer this question.\n",
|
||||
"Action: state_of_union_address_with_sources\n",
|
||||
"Action Input: What did biden say about ketanji brown jackson\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m{\"answer\": \" Biden said that he nominated Circuit Court of Appeals Judge Ketanji Brown Jackson to the United States Supreme Court, and that she is one of the nation's top legal minds who will continue Justice Breyer's legacy of excellence.\\n\", \"sources\": \"../../state_of_the_union.txt\"}\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: Biden said that he nominated Circuit Court of Appeals Judge Ketanji Brown Jackson to the United States Supreme Court, and that she is one of the nation's top legal minds who will continue Justice Breyer's legacy of excellence. Sources: ../../state_of_the_union.txt\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"Biden said that he nominated Circuit Court of Appeals Judge Ketanji Brown Jackson to the United States Supreme Court, and that she is one of the nation's top legal minds who will continue Justice Breyer's legacy of excellence. Sources: ../../state_of_the_union.txt\""
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"What did biden say about ketanji brown jackson is the state of the union address? List the source.\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "7ca07707",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Multiple Vectorstores\n",
|
||||
"We can also easily use this initialize an agent with multiple vectorstores and use the agent to route between them. To do this. This agent is optimized for routing, so it is a different toolkit and initializer."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "c3209fd3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.agents.agent_toolkits import (\n",
|
||||
" create_vectorstore_router_agent,\n",
|
||||
" VectorStoreRouterToolkit,\n",
|
||||
" VectorStoreInfo,\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "815c4f39-308d-4949-b992-1361036e6e09",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"ruff_vectorstore_info = VectorStoreInfo(\n",
|
||||
" name=\"ruff\",\n",
|
||||
" description=\"Information about the Ruff python linting library\",\n",
|
||||
" vectorstore=ruff_store\n",
|
||||
")\n",
|
||||
"router_toolkit = VectorStoreRouterToolkit(\n",
|
||||
" vectorstores=[vectorstore_info, ruff_vectorstore_info],\n",
|
||||
" llm=llm\n",
|
||||
")\n",
|
||||
"agent_executor = create_vectorstore_agent(\n",
|
||||
" llm=llm,\n",
|
||||
" toolkit=router_toolkit,\n",
|
||||
" verbose=True\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "71680984-edaf-4a63-90f5-94edbd263550",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Examples"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "3cd1bf3e-e3df-4e69-bbe1-71c64b1af947",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to use the state_of_union_address tool to answer this question.\n",
|
||||
"Action: state_of_union_address\n",
|
||||
"Action Input: What did biden say about ketanji brown jackson\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m Biden said that Ketanji Brown Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: Biden said that Ketanji Brown Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"\"Biden said that Ketanji Brown Jackson is one of the nation's top legal minds and that she will continue Justice Breyer's legacy of excellence.\""
|
||||
]
|
||||
},
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"What did biden say about ketanji brown jackson is the state of the union address?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"id": "c5998b8d",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to find out what tool ruff uses to run over Jupyter Notebooks\n",
|
||||
"Action: ruff\n",
|
||||
"Action Input: What tool does ruff use to run over Jupyter Notebooks?\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m Ruff is integrated into nbQA, a tool for running linters and code formatters over Jupyter Notebooks. After installing ruff and nbqa, you can run Ruff over a notebook like so: > nbqa ruff Untitled.ipynb\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n",
|
||||
"Final Answer: Ruff is integrated into nbQA, a tool for running linters and code formatters over Jupyter Notebooks. After installing ruff and nbqa, you can run Ruff over a notebook like so: > nbqa ruff Untitled.ipynb\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Ruff is integrated into nbQA, a tool for running linters and code formatters over Jupyter Notebooks. After installing ruff and nbqa, you can run Ruff over a notebook like so: > nbqa ruff Untitled.ipynb'"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"What tool does ruff use to run over Jupyter Notebooks?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "744e9b51-fbd9-4778-b594-ea957d0f3467",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
|
||||
"\u001b[32;1m\u001b[1;3m I need to find out what tool ruff uses and if the president mentioned it in the state of the union.\n",
|
||||
"Action: ruff\n",
|
||||
"Action Input: What tool does ruff use to run over Jupyter Notebooks?\u001b[0m\n",
|
||||
"Observation: \u001b[33;1m\u001b[1;3m Ruff is integrated into nbQA, a tool for running linters and code formatters over Jupyter Notebooks. After installing ruff and nbqa, you can run Ruff over a notebook like so: > nbqa ruff Untitled.ipynb\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I need to find out if the president mentioned nbQA in the state of the union.\n",
|
||||
"Action: state_of_union_address\n",
|
||||
"Action Input: Did the president mention nbQA in the state of the union?\u001b[0m\n",
|
||||
"Observation: \u001b[36;1m\u001b[1;3m No, the president did not mention nbQA in the state of the union.\u001b[0m\n",
|
||||
"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n",
|
||||
"Final Answer: No, the president did not mention nbQA in the state of the union.\u001b[0m\n",
|
||||
"\n",
|
||||
"\u001b[1m> Finished chain.\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'No, the president did not mention nbQA in the state of the union.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 11,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"agent_executor.run(\"What tool does ruff use to run over Jupyter Notebooks? Did the president mention that tool in the state of the union?\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "92203aa9-f63a-4ce1-b562-fadf4474ad9d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.9"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
File diff suppressed because it is too large
Load Diff
File diff suppressed because one or more lines are too long
@ -0,0 +1,245 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e49f1e0d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# OpenAIChat\n",
|
||||
"\n",
|
||||
"OpenAI also has a [chat model](https://platform.openai.com/docs/guides/chat) you can use. The interface is very similar to the normal OpenAI model."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "522686de",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.llms import OpenAIChat\n",
|
||||
"from langchain import PromptTemplate, LLMChain"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "62e0dbc3",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llm = OpenAIChat(temperature=0)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "fbb043e6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"template = \"\"\"Question: {question}\n",
|
||||
"\n",
|
||||
"Answer: Let's think step by step.\"\"\"\n",
|
||||
"\n",
|
||||
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "3f945b76",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llm_chain = LLMChain(prompt=prompt, llm=llm)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "25260808",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'\\n\\nJustin Bieber was born on March 1, 1994. \\n\\nThe Super Bowl is played in February of each year. \\n\\nTherefore, the Super Bowl that was played in the year Justin Bieber was born was Super Bowl XXVIII, which was played on January 30, 1994. \\n\\nThe Dallas Cowboys won Super Bowl XXVIII by defeating the Buffalo Bills with a score of 30-13.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
|
||||
"\n",
|
||||
"llm_chain.run(question)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "75a05b79",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Prefix Messages\n",
|
||||
"\n",
|
||||
"OpenAI Chat also supports the idea of [prefix messages](https://platform.openai.com/docs/guides/chat/chat-vs-completions), eg messages that would appear before the user input. These can be used as system messages to give more context/purpose the LLM."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "c27a1501",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"prefix_messages = [{\"role\": \"system\", \"content\": \"You are a helpful assistant that is very good at problem solving who thinks step by step.\"}]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"id": "e46a914e",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llm = OpenAIChat(temperature=0, prefix_messages=prefix_messages)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"id": "d683d9f2",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"llm_chain = LLMChain(prompt=prompt, llm=llm)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"id": "6f5b8e78",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Step 1: Justin Bieber was born on March 1, 1994.\\nStep 2: The Super Bowl is played in February of each year.\\nStep 3: Therefore, the Super Bowl that was played in the year Justin Bieber was born was Super Bowl XXVIII, which was played on January 30, 1994.\\nStep 4: The team that won Super Bowl XXVIII was the Dallas Cowboys.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 9,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"question = \"What NFL team won the Super Bowl in the year Justin Beiber was born?\"\n",
|
||||
"\n",
|
||||
"llm_chain.run(question)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "f6d5dda8",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Async"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 11,
|
||||
"id": "1973b9bb",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"result = await llm_chain.arun(question)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 12,
|
||||
"id": "5815178f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'Step 1: Justin Bieber was born on March 1, 1994.\\nStep 2: The Super Bowl is played in February of each year.\\nStep 3: Therefore, the Super Bowl that was played in the year Justin Bieber was born was Super Bowl XXVIII, which was played on January 30, 1994.\\nStep 4: The team that won Super Bowl XXVIII was the Dallas Cowboys.'"
|
||||
]
|
||||
},
|
||||
"execution_count": 12,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"result"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "eb779f3f",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Streaming"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 14,
|
||||
"id": "509181be",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"\n",
|
||||
"Justin Bieber was born on March 1, 1994. The NFL team that won the Super Bowl in the same year was the Dallas Cowboys. They defeated the Buffalo Bills 30-13 in Super Bowl XXVIII on January 30, 1994."
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"\n",
|
||||
"from langchain.callbacks.base import CallbackManager\n",
|
||||
"from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler\n",
|
||||
"llm = OpenAIChat(streaming=True, callback_manager=CallbackManager([StreamingStdOutCallbackHandler()]), verbose=True, temperature=0)\n",
|
||||
"resp = llm(question)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "c095285d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
@ -1,4 +1,5 @@
|
||||
{
|
||||
"_type": "prompt",
|
||||
"input_variables": ["input", "output"],
|
||||
"template": "Input: {input}\nOutput: {output}"
|
||||
}
|
||||
|
@ -0,0 +1,184 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "9355a547",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Partial Prompt Templates\n",
|
||||
"\n",
|
||||
"A prompt template is a class with a `.format` method which takes in a key-value map and returns a string (a prompt) to pass to the language model. Like other methods, it can make sense to \"partial\" a prompt template - eg pass in a subset of the required values, as to create a new prompt template which expects only the remaining subset of values.\n",
|
||||
"\n",
|
||||
"LangChain supports this in two ways: we allow for partially formatted prompts (1) with string values, (2) with functions that return string values. These two different ways support different use cases. In the documentation below we go over the motivations for both use cases as well as how to do it in LangChain.\n",
|
||||
"\n",
|
||||
"## Partial With Strings\n",
|
||||
"\n",
|
||||
"One common use case for wanting to partial a prompt template is if you get some of the variables before others. For example, suppose you have a prompt template that requires two variables, `foo` and `baz`. If you get the `foo` value early on in the chain, but the `baz` value later, it can be annoying to wait until you have both variables in the same place to pass them to the prompt template. Instead, you can partial the prompt template with the `foo` value, and then pass the partialed prompt template along and just use that. Below is an example of doing this:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"id": "643af5da",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.prompts import PromptTemplate"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"id": "4080d8d7",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"foobaz\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = PromptTemplate(template=\"{foo}{bar}\", input_variables=[\"foo\", \"bar\"])\n",
|
||||
"partial_prompt = prompt.partial(foo=\"foo\");\n",
|
||||
"print(partial_prompt.format(bar=\"baz\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "9986766e",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"You can also just initialize the prompt with the partialed variables."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"id": "e2ce95b3",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"foobaz\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = PromptTemplate(template=\"{foo}{bar}\", input_variables=[\"bar\"], partial_variables={\"foo\": \"foo\"})\n",
|
||||
"print(prompt.format(bar=\"baz\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a9c66f83",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Partial With Functions\n",
|
||||
"\n",
|
||||
"The other common use is to partial with a function. The use case for this is when you have a variable you know that you always want to fetch in a common way. A prime example of this is with date or time. Imagine you have a prompt which you always want to have the current date. You can't hard code it in the prompt, and passing it along with the other input variables is a bit annoying. In this case, it's very handy to be able to partial the prompt with a function that always returns the current date."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "d0712d8a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from datetime import datetime\n",
|
||||
"\n",
|
||||
"def _get_datetime():\n",
|
||||
" now = datetime.now()\n",
|
||||
" return now.strftime(\"%m/%d/%Y, %H:%M:%S\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"id": "4cbcb666",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tell me a funny joke about the day 02/27/2023, 22:15:16\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = PromptTemplate(\n",
|
||||
" template=\"Tell me a {adjective} joke about the day {date}\", \n",
|
||||
" input_variables=[\"adjective\", \"date\"]\n",
|
||||
");\n",
|
||||
"partial_prompt = prompt.partial(date=_get_datetime)\n",
|
||||
"print(partial_prompt.format(adjective=\"funny\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ffed6811",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"You can also just initialize the prompt with the partialed variables, which often makes more sense in this workflow."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"id": "96285b25",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Tell me a funny joke about the day 02/27/2023, 22:15:16\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"prompt = PromptTemplate(\n",
|
||||
" template=\"Tell me a {adjective} joke about the day {date}\", \n",
|
||||
" input_variables=[\"adjective\"],\n",
|
||||
" partial_variables={\"date\": _get_datetime}\n",
|
||||
");\n",
|
||||
"print(prompt.format(adjective=\"funny\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4bff16f7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.1"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
@ -1,4 +1,5 @@
|
||||
{
|
||||
"_type": "prompt",
|
||||
"input_variables": ["adjective", "content"],
|
||||
"template": "Tell me a {adjective} joke about {content}."
|
||||
}
|
||||
|
@ -1,4 +1,5 @@
|
||||
{
|
||||
"_type": "prompt",
|
||||
"input_variables": ["adjective", "content"],
|
||||
"template_path": "simple_template.txt"
|
||||
}
|
||||
|
@ -0,0 +1,37 @@
|
||||
"""Agent toolkits."""
|
||||
|
||||
from langchain.agents.agent_toolkits.csv.base import create_csv_agent
|
||||
from langchain.agents.agent_toolkits.json.base import create_json_agent
|
||||
from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
|
||||
from langchain.agents.agent_toolkits.openapi.base import create_openapi_agent
|
||||
from langchain.agents.agent_toolkits.openapi.toolkit import OpenAPIToolkit
|
||||
from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent
|
||||
from langchain.agents.agent_toolkits.python.base import create_python_agent
|
||||
from langchain.agents.agent_toolkits.sql.base import create_sql_agent
|
||||
from langchain.agents.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
|
||||
from langchain.agents.agent_toolkits.vectorstore.base import (
|
||||
create_vectorstore_agent,
|
||||
create_vectorstore_router_agent,
|
||||
)
|
||||
from langchain.agents.agent_toolkits.vectorstore.toolkit import (
|
||||
VectorStoreInfo,
|
||||
VectorStoreRouterToolkit,
|
||||
VectorStoreToolkit,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
"create_json_agent",
|
||||
"create_sql_agent",
|
||||
"create_openapi_agent",
|
||||
"create_python_agent",
|
||||
"create_vectorstore_agent",
|
||||
"JsonToolkit",
|
||||
"SQLDatabaseToolkit",
|
||||
"OpenAPIToolkit",
|
||||
"VectorStoreToolkit",
|
||||
"create_vectorstore_router_agent",
|
||||
"VectorStoreInfo",
|
||||
"VectorStoreRouterToolkit",
|
||||
"create_pandas_dataframe_agent",
|
||||
"create_csv_agent",
|
||||
]
|
@ -0,0 +1,15 @@
|
||||
"""Toolkits for agents."""
|
||||
from abc import abstractmethod
|
||||
from typing import List
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from langchain.tools import BaseTool
|
||||
|
||||
|
||||
class BaseToolkit(BaseModel):
|
||||
"""Class responsible for defining a collection of related tools."""
|
||||
|
||||
@abstractmethod
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
@ -0,0 +1 @@
|
||||
"""CSV toolkit."""
|
@ -0,0 +1,17 @@
|
||||
"""Agent for working with csvs."""
|
||||
from typing import Any, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent
|
||||
from langchain.llms.base import BaseLLM
|
||||
|
||||
|
||||
def create_csv_agent(
|
||||
llm: BaseLLM, path: str, pandas_kwargs: Optional[dict] = None, **kwargs: Any
|
||||
) -> AgentExecutor:
|
||||
"""Create csv agent by loading to a dataframe and using pandas agent."""
|
||||
import pandas as pd
|
||||
|
||||
_kwargs = pandas_kwargs or {}
|
||||
df = pd.read_csv(path, **_kwargs)
|
||||
return create_pandas_dataframe_agent(llm, df, **kwargs)
|
@ -0,0 +1 @@
|
||||
"""Json agent."""
|
@ -0,0 +1,43 @@
|
||||
"""Json agent."""
|
||||
from typing import Any, List, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
|
||||
from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
|
||||
from langchain.agents.mrkl.base import ZeroShotAgent
|
||||
from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
|
||||
from langchain.callbacks.base import BaseCallbackManager
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
|
||||
|
||||
def create_json_agent(
|
||||
llm: BaseLLM,
|
||||
toolkit: JsonToolkit,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
prefix: str = JSON_PREFIX,
|
||||
suffix: str = JSON_SUFFIX,
|
||||
format_instructions: str = FORMAT_INSTRUCTIONS,
|
||||
input_variables: Optional[List[str]] = None,
|
||||
verbose: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a json agent from an LLM and tools."""
|
||||
tools = toolkit.get_tools()
|
||||
prompt = ZeroShotAgent.create_prompt(
|
||||
tools,
|
||||
prefix=prefix,
|
||||
suffix=suffix,
|
||||
format_instructions=format_instructions,
|
||||
input_variables=input_variables,
|
||||
)
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(
|
||||
agent=agent, tools=toolkit.get_tools(), verbose=verbose
|
||||
)
|
@ -0,0 +1,25 @@
|
||||
# flake8: noqa
|
||||
|
||||
JSON_PREFIX = """You are an agent designed to interact with JSON.
|
||||
Your goal is to return a final answer by interacting with the JSON.
|
||||
You have access to the following tools which help you learn more about the JSON you are interacting with.
|
||||
Only use the below tools. Only use the information returned by the below tools to construct your final answer.
|
||||
Do not make up any information that is not contained in the JSON.
|
||||
Your input to the tools should be in the form of `data["key"][0]` where `data` is the JSON blob you are interacting with, and the syntax used is Python.
|
||||
You should only use keys that you know for a fact exist. You must validate that a key exists by seeing it previously when calling `json_spec_list_keys`.
|
||||
If you have not seen a key in one of those responses, you cannot use it.
|
||||
You should only add one key at a time to the path. You cannot add multiple keys at once.
|
||||
If you encounter a "KeyError", go back to the previous key, look at the available keys, and try again.
|
||||
|
||||
If the question does not seem to be related to the JSON, just return "I don't know" as the answer.
|
||||
Always begin your interaction with the `json_spec_list_keys` tool with input "data" to see what keys exist in the JSON.
|
||||
|
||||
Note that sometimes the value at a given path is large. In this case, you will get an error "Value is a large dictionary, should explore its keys directly".
|
||||
In this case, you should ALWAYS follow up by using the `json_spec_list_keys` tool to see what keys exist at that path.
|
||||
Do not simply refer the user to the JSON or a section of the JSON, as this is not a valid answer. Keep digging until you find the answer and explicitly return it.
|
||||
"""
|
||||
JSON_SUFFIX = """Begin!"
|
||||
|
||||
Question: {input}
|
||||
Thought: I should look at the keys that exist in data to see what I have access to
|
||||
{agent_scratchpad}"""
|
@ -0,0 +1,21 @@
|
||||
"""Toolkit for interacting with a JSON spec."""
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import List
|
||||
|
||||
from langchain.agents.agent_toolkits.base import BaseToolkit
|
||||
from langchain.tools import BaseTool
|
||||
from langchain.tools.json.tool import JsonGetValueTool, JsonListKeysTool, JsonSpec
|
||||
|
||||
|
||||
class JsonToolkit(BaseToolkit):
|
||||
"""Toolkit for interacting with a JSON spec."""
|
||||
|
||||
spec: JsonSpec
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
||||
return [
|
||||
JsonListKeysTool(spec=self.spec),
|
||||
JsonGetValueTool(spec=self.spec),
|
||||
]
|
@ -0,0 +1 @@
|
||||
"""OpenAPI spec agent."""
|
@ -0,0 +1,46 @@
|
||||
"""OpenAPI spec agent."""
|
||||
from typing import Any, List, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.openapi.prompt import (
|
||||
OPENAPI_PREFIX,
|
||||
OPENAPI_SUFFIX,
|
||||
)
|
||||
from langchain.agents.agent_toolkits.openapi.toolkit import OpenAPIToolkit
|
||||
from langchain.agents.mrkl.base import ZeroShotAgent
|
||||
from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
|
||||
from langchain.callbacks.base import BaseCallbackManager
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
|
||||
|
||||
def create_openapi_agent(
|
||||
llm: BaseLLM,
|
||||
toolkit: OpenAPIToolkit,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
prefix: str = OPENAPI_PREFIX,
|
||||
suffix: str = OPENAPI_SUFFIX,
|
||||
format_instructions: str = FORMAT_INSTRUCTIONS,
|
||||
input_variables: Optional[List[str]] = None,
|
||||
verbose: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a json agent from an LLM and tools."""
|
||||
tools = toolkit.get_tools()
|
||||
prompt = ZeroShotAgent.create_prompt(
|
||||
tools,
|
||||
prefix=prefix,
|
||||
suffix=suffix,
|
||||
format_instructions=format_instructions,
|
||||
input_variables=input_variables,
|
||||
)
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(
|
||||
agent=agent, tools=toolkit.get_tools(), verbose=verbose
|
||||
)
|
@ -0,0 +1,29 @@
|
||||
# flake8: noqa
|
||||
|
||||
OPENAPI_PREFIX = """You are an agent designed to answer questions by making web requests to an API given the openapi spec.
|
||||
|
||||
If the question does not seem related to the API, return I don't know. Do not make up an answer.
|
||||
Only use information provided by the tools to construct your response.
|
||||
|
||||
First, find the base URL needed to make the request.
|
||||
|
||||
Second, find the relevant paths needed to answer the question. Take note that, sometimes, you might need to make more than one request to more than one path to answer the question.
|
||||
|
||||
Third, find the required parameters needed to make the request. For GET requests, these are usually URL parameters and for POST requests, these are request body parameters.
|
||||
|
||||
Fourth, make the requests needed to answer the question. Ensure that you are sending the correct parameters to the request by checking which parameters are required. For parameters with a fixed set of values, please use the spec to look at which values are allowed.
|
||||
|
||||
Use the exact parameter names as listed in the spec, do not make up any names or abbreviate the names of parameters.
|
||||
If you get a not found error, ensure that you are using a path that actually exists in the spec.
|
||||
"""
|
||||
OPENAPI_SUFFIX = """Begin!"
|
||||
|
||||
Question: {input}
|
||||
Thought: I should explore the spec to find the base url for the API.
|
||||
{agent_scratchpad}"""
|
||||
|
||||
DESCRIPTION = """Can be used to answer questions about the openapi spec for the API. Always use this tool before trying to make a request.
|
||||
Example inputs to this tool:
|
||||
'What are the required query parameters for a GET request to the /bar endpoint?`
|
||||
'What are the required parameters in the request body for a POST request to the /foo endpoint?'
|
||||
Always give this tool a specific question."""
|
@ -0,0 +1,67 @@
|
||||
"""Requests toolkit."""
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any, List
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.base import BaseToolkit
|
||||
from langchain.agents.agent_toolkits.json.base import create_json_agent
|
||||
from langchain.agents.agent_toolkits.json.toolkit import JsonToolkit
|
||||
from langchain.agents.agent_toolkits.openapi.prompt import DESCRIPTION
|
||||
from langchain.agents.tools import Tool
|
||||
from langchain.llms.base import BaseLLM
|
||||
from langchain.requests import RequestsWrapper
|
||||
from langchain.tools import BaseTool
|
||||
from langchain.tools.json.tool import JsonSpec
|
||||
from langchain.tools.requests.tool import (
|
||||
RequestsDeleteTool,
|
||||
RequestsGetTool,
|
||||
RequestsPatchTool,
|
||||
RequestsPostTool,
|
||||
RequestsPutTool,
|
||||
)
|
||||
|
||||
|
||||
class RequestsToolkit(BaseToolkit):
|
||||
"""Toolkit for making requests."""
|
||||
|
||||
requests_wrapper: RequestsWrapper
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Return a list of tools."""
|
||||
return [
|
||||
RequestsGetTool(requests_wrapper=self.requests_wrapper),
|
||||
RequestsPostTool(requests_wrapper=self.requests_wrapper),
|
||||
RequestsPatchTool(requests_wrapper=self.requests_wrapper),
|
||||
RequestsPutTool(requests_wrapper=self.requests_wrapper),
|
||||
RequestsDeleteTool(requests_wrapper=self.requests_wrapper),
|
||||
]
|
||||
|
||||
|
||||
class OpenAPIToolkit(BaseToolkit):
|
||||
"""Toolkit for interacting with a OpenAPI api."""
|
||||
|
||||
json_agent: AgentExecutor
|
||||
requests_wrapper: RequestsWrapper
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
||||
json_agent_tool = Tool(
|
||||
name="json_explorer",
|
||||
func=self.json_agent.run,
|
||||
description=DESCRIPTION,
|
||||
)
|
||||
request_toolkit = RequestsToolkit(requests_wrapper=self.requests_wrapper)
|
||||
return [*request_toolkit.get_tools(), json_agent_tool]
|
||||
|
||||
@classmethod
|
||||
def from_llm(
|
||||
cls,
|
||||
llm: BaseLLM,
|
||||
json_spec: JsonSpec,
|
||||
requests_wrapper: RequestsWrapper,
|
||||
**kwargs: Any,
|
||||
) -> OpenAPIToolkit:
|
||||
"""Create json agent from llm, then initialize."""
|
||||
json_agent = create_json_agent(llm, JsonToolkit(spec=json_spec), **kwargs)
|
||||
return cls(json_agent=json_agent, requests_wrapper=requests_wrapper)
|
@ -0,0 +1 @@
|
||||
"""Pandas toolkit."""
|
@ -0,0 +1,42 @@
|
||||
"""Agent for working with pandas objects."""
|
||||
from typing import Any, List, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.pandas.prompt import PREFIX, SUFFIX
|
||||
from langchain.agents.mrkl.base import ZeroShotAgent
|
||||
from langchain.callbacks.base import BaseCallbackManager
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
from langchain.tools.python.tool import PythonAstREPLTool
|
||||
|
||||
|
||||
def create_pandas_dataframe_agent(
|
||||
llm: BaseLLM,
|
||||
df: Any,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
prefix: str = PREFIX,
|
||||
suffix: str = SUFFIX,
|
||||
input_variables: Optional[List[str]] = None,
|
||||
verbose: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a pandas agent from an LLM and dataframe."""
|
||||
import pandas as pd
|
||||
|
||||
if not isinstance(df, pd.DataFrame):
|
||||
raise ValueError(f"Expected pandas object, got {type(df)}")
|
||||
if input_variables is None:
|
||||
input_variables = ["df", "input", "agent_scratchpad"]
|
||||
tools = [PythonAstREPLTool(locals={"df": df})]
|
||||
prompt = ZeroShotAgent.create_prompt(
|
||||
tools, prefix=prefix, suffix=suffix, input_variables=input_variables
|
||||
)
|
||||
partial_prompt = prompt.partial(df=str(df.head()))
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=partial_prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=verbose)
|
@ -0,0 +1,13 @@
|
||||
# flake8: noqa
|
||||
|
||||
PREFIX = """
|
||||
You are working with a pandas dataframe in Python. The name of the dataframe is `df`.
|
||||
You should use the tools below to answer the question posed of you:"""
|
||||
|
||||
SUFFIX = """
|
||||
This is the result of `print(df.head())`:
|
||||
{df}
|
||||
|
||||
Begin!
|
||||
Question: {input}
|
||||
{agent_scratchpad}"""
|
@ -0,0 +1,32 @@
|
||||
"""Python agent."""
|
||||
|
||||
from typing import Any, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.python.prompt import PREFIX
|
||||
from langchain.agents.mrkl.base import ZeroShotAgent
|
||||
from langchain.callbacks.base import BaseCallbackManager
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
from langchain.tools.python.tool import PythonREPLTool
|
||||
|
||||
|
||||
def create_python_agent(
|
||||
llm: BaseLLM,
|
||||
tool: PythonREPLTool,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
verbose: bool = False,
|
||||
prefix: str = PREFIX,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a python agent from an LLM and tool."""
|
||||
tools = [tool]
|
||||
prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix)
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=verbose)
|
@ -0,0 +1,9 @@
|
||||
# flake8: noqa
|
||||
|
||||
PREFIX = """You are an agent designed to write and execute python code to answer questions.
|
||||
You have access to a python REPL, which you can use to execute python code.
|
||||
If you get an error, debug your code and try again.
|
||||
Only use the output of your code to answer the question.
|
||||
You might know the answer without running any code, but you should still run the code to get the answer.
|
||||
If it does not seem like you can write code to answer the question, just return "I don't know" as the answer.
|
||||
"""
|
@ -0,0 +1 @@
|
||||
"""SQL agent."""
|
@ -0,0 +1,45 @@
|
||||
"""SQL agent."""
|
||||
from typing import Any, List, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.sql.prompt import SQL_PREFIX, SQL_SUFFIX
|
||||
from langchain.agents.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
|
||||
from langchain.agents.mrkl.base import ZeroShotAgent
|
||||
from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
|
||||
from langchain.callbacks.base import BaseCallbackManager
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
|
||||
|
||||
def create_sql_agent(
|
||||
llm: BaseLLM,
|
||||
toolkit: SQLDatabaseToolkit,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
prefix: str = SQL_PREFIX,
|
||||
suffix: str = SQL_SUFFIX,
|
||||
format_instructions: str = FORMAT_INSTRUCTIONS,
|
||||
input_variables: Optional[List[str]] = None,
|
||||
top_k: int = 10,
|
||||
verbose: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a sql agent from an LLM and tools."""
|
||||
tools = toolkit.get_tools()
|
||||
prefix = prefix.format(dialect=toolkit.dialect, top_k=top_k)
|
||||
prompt = ZeroShotAgent.create_prompt(
|
||||
tools,
|
||||
prefix=prefix,
|
||||
suffix=suffix,
|
||||
format_instructions=format_instructions,
|
||||
input_variables=input_variables,
|
||||
)
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(
|
||||
agent=agent, tools=toolkit.get_tools(), verbose=verbose
|
||||
)
|
@ -0,0 +1,21 @@
|
||||
# flake8: noqa
|
||||
|
||||
SQL_PREFIX = """You are an agent designed to interact with a SQL database.
|
||||
Given an input question, create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer.
|
||||
Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most {top_k} results.
|
||||
You can order the results by a relevant column to return the most interesting examples in the database.
|
||||
Never query for all the columns from a specific table, only ask for a the few relevant columns given the question.
|
||||
You have access to tools for interacting with the database.
|
||||
Only use the below tools. Only use the information returned by the below tools to construct your final answer.
|
||||
You MUST double check your query before executing it. If you get an error while executing a query, rewrite the query and try again.
|
||||
|
||||
DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.
|
||||
|
||||
If the question does not seem related to the database, just return "I don't know" as the answer.
|
||||
"""
|
||||
|
||||
SQL_SUFFIX = """Begin!
|
||||
|
||||
Question: {input}
|
||||
Thought: I should look at the tables in the database to see what I can query.
|
||||
{agent_scratchpad}"""
|
@ -0,0 +1,39 @@
|
||||
"""Toolkit for interacting with a SQL database."""
|
||||
from typing import List
|
||||
|
||||
from pydantic import Field
|
||||
|
||||
from langchain.agents.agent_toolkits.base import BaseToolkit
|
||||
from langchain.sql_database import SQLDatabase
|
||||
from langchain.tools import BaseTool
|
||||
from langchain.tools.sql_database.tool import (
|
||||
InfoSQLDatabaseTool,
|
||||
ListSQLDatabaseTool,
|
||||
QueryCheckerTool,
|
||||
QuerySQLDataBaseTool,
|
||||
)
|
||||
|
||||
|
||||
class SQLDatabaseToolkit(BaseToolkit):
|
||||
"""Toolkit for interacting with SQL databases."""
|
||||
|
||||
db: SQLDatabase = Field(exclude=True)
|
||||
|
||||
@property
|
||||
def dialect(self) -> str:
|
||||
"""Return string representation of dialect to use."""
|
||||
return self.db.dialect
|
||||
|
||||
class Config:
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
||||
return [
|
||||
QuerySQLDataBaseTool(db=self.db),
|
||||
InfoSQLDatabaseTool(db=self.db),
|
||||
ListSQLDatabaseTool(db=self.db),
|
||||
QueryCheckerTool(db=self.db),
|
||||
]
|
@ -0,0 +1 @@
|
||||
"""Agent toolkit for interacting with vector stores."""
|
@ -0,0 +1,55 @@
|
||||
"""VectorStore agent."""
|
||||
from typing import Any, Optional
|
||||
|
||||
from langchain.agents.agent import AgentExecutor
|
||||
from langchain.agents.agent_toolkits.vectorstore.prompt import PREFIX, ROUTER_PREFIX
|
||||
from langchain.agents.agent_toolkits.vectorstore.toolkit import (
|
||||
VectorStoreRouterToolkit,
|
||||
VectorStoreToolkit,
|
||||
)
|
||||
from langchain.agents.mrkl.base import ZeroShotAgent
|
||||
from langchain.callbacks.base import BaseCallbackManager
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
|
||||
|
||||
def create_vectorstore_agent(
|
||||
llm: BaseLLM,
|
||||
toolkit: VectorStoreToolkit,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
prefix: str = PREFIX,
|
||||
verbose: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a vectorstore agent from an LLM and tools."""
|
||||
tools = toolkit.get_tools()
|
||||
prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix)
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=verbose)
|
||||
|
||||
|
||||
def create_vectorstore_router_agent(
|
||||
llm: BaseLLM,
|
||||
toolkit: VectorStoreRouterToolkit,
|
||||
callback_manager: Optional[BaseCallbackManager] = None,
|
||||
prefix: str = ROUTER_PREFIX,
|
||||
verbose: bool = False,
|
||||
**kwargs: Any,
|
||||
) -> AgentExecutor:
|
||||
"""Construct a vectorstore router agent from an LLM and tools."""
|
||||
tools = toolkit.get_tools()
|
||||
prompt = ZeroShotAgent.create_prompt(tools, prefix=prefix)
|
||||
llm_chain = LLMChain(
|
||||
llm=llm,
|
||||
prompt=prompt,
|
||||
callback_manager=callback_manager,
|
||||
)
|
||||
tool_names = [tool.name for tool in tools]
|
||||
agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
|
||||
return AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=verbose)
|
@ -0,0 +1,13 @@
|
||||
# flake8: noqa
|
||||
|
||||
PREFIX = """You are an agent designed to answer questions about sets of documents.
|
||||
You have access to tools for interacting with the documents, and the inputs to the tools are questions.
|
||||
Sometimes, you will be asked to provide sources for your questions, in which case you should use the appropriate tool to do so.
|
||||
If the question does not seem relevant to any of the tools provided, just return "I don't know" as the answer.
|
||||
"""
|
||||
|
||||
ROUTER_PREFIX = """You are an agent designed to answer questions.
|
||||
You have access to tools for interacting with different sources, and the inputs to the tools are questions.
|
||||
Your main task is to decide which of the tools is relevant for answering question at hand.
|
||||
For complex questions, you can break the question down into sub questions and use tools to answers the sub questions.
|
||||
"""
|
@ -0,0 +1,89 @@
|
||||
"""Toolkit for interacting with a vector store."""
|
||||
from typing import List
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from langchain.agents.agent_toolkits.base import BaseToolkit
|
||||
from langchain.llms.base import BaseLLM
|
||||
from langchain.llms.openai import OpenAI
|
||||
from langchain.tools import BaseTool
|
||||
from langchain.tools.vectorstore.tool import (
|
||||
VectorStoreQATool,
|
||||
VectorStoreQAWithSourcesTool,
|
||||
)
|
||||
from langchain.vectorstores.base import VectorStore
|
||||
|
||||
|
||||
class VectorStoreInfo(BaseModel):
|
||||
"""Information about a vectorstore."""
|
||||
|
||||
vectorstore: VectorStore = Field(exclude=True)
|
||||
name: str
|
||||
description: str
|
||||
|
||||
class Config:
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
|
||||
class VectorStoreToolkit(BaseToolkit):
|
||||
"""Toolkit for interacting with a vector store."""
|
||||
|
||||
vectorstore_info: VectorStoreInfo = Field(exclude=True)
|
||||
llm: BaseLLM = Field(default_factory=lambda: OpenAI(temperature=0))
|
||||
|
||||
class Config:
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
||||
description = VectorStoreQATool.get_description(
|
||||
self.vectorstore_info.name, self.vectorstore_info.description
|
||||
)
|
||||
qa_tool = VectorStoreQATool(
|
||||
name=self.vectorstore_info.name,
|
||||
description=description,
|
||||
vectorstore=self.vectorstore_info.vectorstore,
|
||||
llm=self.llm,
|
||||
)
|
||||
description = VectorStoreQAWithSourcesTool.get_description(
|
||||
self.vectorstore_info.name, self.vectorstore_info.description
|
||||
)
|
||||
qa_with_sources_tool = VectorStoreQAWithSourcesTool(
|
||||
name=f"{self.vectorstore_info.name}_with_sources",
|
||||
description=description,
|
||||
vectorstore=self.vectorstore_info.vectorstore,
|
||||
llm=self.llm,
|
||||
)
|
||||
return [qa_tool, qa_with_sources_tool]
|
||||
|
||||
|
||||
class VectorStoreRouterToolkit(BaseToolkit):
|
||||
"""Toolkit for routing between vectorstores."""
|
||||
|
||||
vectorstores: List[VectorStoreInfo] = Field(exclude=True)
|
||||
llm: BaseLLM = Field(default_factory=lambda: OpenAI(temperature=0))
|
||||
|
||||
class Config:
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
||||
tools: List[BaseTool] = []
|
||||
for vectorstore_info in self.vectorstores:
|
||||
description = VectorStoreQATool.get_description(
|
||||
vectorstore_info.name, vectorstore_info.description
|
||||
)
|
||||
qa_tool = VectorStoreQATool(
|
||||
name=vectorstore_info.name,
|
||||
description=description,
|
||||
vectorstore=vectorstore_info.vectorstore,
|
||||
llm=self.llm,
|
||||
)
|
||||
tools.append(qa_tool)
|
||||
return tools
|
@ -0,0 +1,7 @@
|
||||
"""Summarization checker chain for verifying accuracy of text generation.
|
||||
|
||||
Chain that tries to verify the accuracy of text generation by splitting it into a
|
||||
list of facts, then checking if those facts are true or not, and rewriting
|
||||
the text to make it more truth-ful. It will repeat this loop until it hits `max_tries`
|
||||
or gets to a "true" output.
|
||||
"""
|
@ -0,0 +1,133 @@
|
||||
"""Chain for summarization with self-verification."""
|
||||
|
||||
from pathlib import Path
|
||||
from typing import Dict, List
|
||||
|
||||
from pydantic import BaseModel, Extra
|
||||
|
||||
from langchain.chains.base import Chain
|
||||
from langchain.chains.llm import LLMChain
|
||||
from langchain.chains.sequential import SequentialChain
|
||||
from langchain.llms.base import BaseLLM
|
||||
from langchain.prompts.prompt import PromptTemplate
|
||||
|
||||
PROMPTS_DIR = Path(__file__).parent / "prompts"
|
||||
|
||||
CREATE_ASSERTIONS_PROMPT = PromptTemplate.from_file(
|
||||
PROMPTS_DIR / "create_facts.txt", ["summary"]
|
||||
)
|
||||
CHECK_ASSERTIONS_PROMPT = PromptTemplate.from_file(
|
||||
PROMPTS_DIR / "check_facts.txt", ["assertions"]
|
||||
)
|
||||
REVISED_SUMMARY_PROMPT = PromptTemplate.from_file(
|
||||
PROMPTS_DIR / "revise_summary.txt", ["checked_assertions", "summary"]
|
||||
)
|
||||
ARE_ALL_TRUE_PROMPT = PromptTemplate.from_file(
|
||||
PROMPTS_DIR / "are_all_true_prompt.txt", ["checked_assertions"]
|
||||
)
|
||||
|
||||
|
||||
class LLMSummarizationCheckerChain(Chain, BaseModel):
|
||||
"""Chain for question-answering with self-verification.
|
||||
|
||||
Example:
|
||||
.. code-block:: python
|
||||
|
||||
from langchain import OpenAI, LLMSummarizationCheckerChain
|
||||
llm = OpenAI(temperature=0.0)
|
||||
checker_chain = LLMSummarizationCheckerChain(llm=llm)
|
||||
"""
|
||||
|
||||
llm: BaseLLM
|
||||
"""LLM wrapper to use."""
|
||||
|
||||
create_assertions_prompt: PromptTemplate = CREATE_ASSERTIONS_PROMPT
|
||||
check_assertions_prompt: PromptTemplate = CHECK_ASSERTIONS_PROMPT
|
||||
revised_summary_prompt: PromptTemplate = REVISED_SUMMARY_PROMPT
|
||||
are_all_true_prompt: PromptTemplate = ARE_ALL_TRUE_PROMPT
|
||||
|
||||
input_key: str = "query" #: :meta private:
|
||||
output_key: str = "result" #: :meta private:
|
||||
max_checks: int = 2
|
||||
"""Maximum number of times to check the assertions. Default to double-checking."""
|
||||
|
||||
class Config:
|
||||
"""Configuration for this pydantic object."""
|
||||
|
||||
extra = Extra.forbid
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
@property
|
||||
def input_keys(self) -> List[str]:
|
||||
"""Return the singular input key.
|
||||
|
||||
:meta private:
|
||||
"""
|
||||
return [self.input_key]
|
||||
|
||||
@property
|
||||
def output_keys(self) -> List[str]:
|
||||
"""Return the singular output key.
|
||||
|
||||
:meta private:
|
||||
"""
|
||||
return [self.output_key]
|
||||
|
||||
def _call(self, inputs: Dict[str, str]) -> Dict[str, str]:
|
||||
all_true = False
|
||||
count = 0
|
||||
output = None
|
||||
original_input = inputs[self.input_key]
|
||||
chain_input = original_input
|
||||
|
||||
while not all_true and count < self.max_checks:
|
||||
chain = SequentialChain(
|
||||
chains=[
|
||||
LLMChain(
|
||||
llm=self.llm,
|
||||
prompt=self.create_assertions_prompt,
|
||||
output_key="assertions",
|
||||
verbose=self.verbose,
|
||||
),
|
||||
LLMChain(
|
||||
llm=self.llm,
|
||||
prompt=self.check_assertions_prompt,
|
||||
output_key="checked_assertions",
|
||||
verbose=self.verbose,
|
||||
),
|
||||
LLMChain(
|
||||
llm=self.llm,
|
||||
prompt=self.revised_summary_prompt,
|
||||
output_key="revised_summary",
|
||||
verbose=self.verbose,
|
||||
),
|
||||
LLMChain(
|
||||
llm=self.llm,
|
||||
output_key="all_true",
|
||||
prompt=self.are_all_true_prompt,
|
||||
verbose=self.verbose,
|
||||
),
|
||||
],
|
||||
input_variables=["summary"],
|
||||
output_variables=["all_true", "revised_summary"],
|
||||
verbose=True,
|
||||
)
|
||||
output = chain({"summary": chain_input})
|
||||
count += 1
|
||||
|
||||
if output["all_true"].strip() == "True":
|
||||
break
|
||||
|
||||
if self.verbose:
|
||||
print(output["revised_summary"])
|
||||
|
||||
chain_input = output["revised_summary"]
|
||||
|
||||
if not output:
|
||||
raise ValueError("No output from chain")
|
||||
|
||||
return {self.output_key: output["revised_summary"].strip()}
|
||||
|
||||
@property
|
||||
def _chain_type(self) -> str:
|
||||
return "llm_summarization_checker_chain"
|
@ -0,0 +1,38 @@
|
||||
Below are some assertions that have been fact checked and are labeled as true or false.
|
||||
|
||||
If all of the assertions are true, return "True". If any of the assertions are false, return "False".
|
||||
|
||||
Here are some examples:
|
||||
===
|
||||
|
||||
Checked Assertions: """
|
||||
- The sky is red: False
|
||||
- Water is made of lava: False
|
||||
- The sun is a star: True
|
||||
"""
|
||||
Result: False
|
||||
|
||||
===
|
||||
|
||||
Checked Assertions: """
|
||||
- The sky is blue: True
|
||||
- Water is wet: True
|
||||
- The sun is a star: True
|
||||
"""
|
||||
Result: True
|
||||
|
||||
===
|
||||
|
||||
Checked Assertions: """
|
||||
- The sky is blue - True
|
||||
- Water is made of lava- False
|
||||
- The sun is a star - True
|
||||
"""
|
||||
Result: False
|
||||
|
||||
===
|
||||
|
||||
Checked Assertions:"""
|
||||
{checked_assertions}
|
||||
"""
|
||||
Result:
|
@ -0,0 +1,10 @@
|
||||
You are an expert fact checker. You have been hired by a major news organization to fact check a very important story.
|
||||
|
||||
Here is a bullet point list of facts:
|
||||
"""
|
||||
{assertions}
|
||||
"""
|
||||
|
||||
For each fact, determine whether it is true or false about the subject. If you are unable to determine whether the fact is true or false, output "Undetermined".
|
||||
If the fact is false, explain why.
|
||||
|
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Reference in New Issue