mirror of
https://github.com/hwchase17/langchain
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985496f4be
Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
87 lines
1.8 KiB
Plaintext
87 lines
1.8 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "984a8fca",
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"metadata": {},
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"source": [
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"# Python REPL\n",
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"\n",
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"Sometimes, for complex calculations, rather than have an LLM generate the answer directly, it can be better to have the LLM generate code to calculate the answer, and then run that code to get the answer. In order to easily do that, we provide a simple Python REPL to execute commands in.\n",
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"\n",
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"This interface will only return things that are printed - therefor, if you want to use it to calculate an answer, make sure to have it print out the answer."
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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": "f6593089",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.utilities import PythonREPL"
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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": "6f21f0a4",
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"metadata": {},
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"outputs": [],
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"source": [
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"python_repl = PythonREPL()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "7ebbbaea",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'2\\n'"
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]
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},
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"execution_count": 3,
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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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"python_repl.run(\"print(1+1)\")"
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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": "54fc1f03",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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