mirror of https://github.com/hwchase17/langchain
add youtube tools (#4320)
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1d1166ded6
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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": "acb64858",
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"metadata": {},
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"source": [
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"# YouTubeSearchTool\n",
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"\n",
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"This notebook shows how to use a tool to search YouTube\n",
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"\n",
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"Adapted from [https://github.com/venuv/langchain_yt_tools](https://github.com/venuv/langchain_yt_tools)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "9bb15d4a",
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"metadata": {},
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"outputs": [],
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"source": [
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"#! pip install youtube_search"
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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": "cc1c83e2",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.tools import YouTubeSearchTool"
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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": "becb262b",
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"metadata": {},
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"outputs": [],
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"source": [
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"tool = YouTubeSearchTool()"
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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": "6bbc4211",
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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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"\"['/watch?v=VcVfceTsD0A&pp=ygUMbGV4IGZyaWVkbWFu', '/watch?v=gPfriiHBBek&pp=ygUMbGV4IGZyaWVkbWFu']\""
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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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"tool.run(\"lex friedman\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "7f772147",
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"metadata": {},
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"source": [
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"You can also specify the number of results that are returned"
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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": "682fdb33",
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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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"\"['/watch?v=VcVfceTsD0A&pp=ygUMbGV4IGZyaWVkbWFu', '/watch?v=YVJ8gTnDC4Y&pp=ygUMbGV4IGZyaWVkbWFu', '/watch?v=Udh22kuLebg&pp=ygUMbGV4IGZyaWVkbWFu', '/watch?v=gPfriiHBBek&pp=ygUMbGV4IGZyaWVkbWFu', '/watch?v=L_Guz73e6fw&pp=ygUMbGV4IGZyaWVkbWFu']\""
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]
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},
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"execution_count": 7,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"tool.run(\"lex friedman,5\")"
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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": "bb5e1659",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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@ -0,0 +1,59 @@
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"""
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Adapted from https://github.com/venuv/langchain_yt_tools
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CustomYTSearchTool searches YouTube videos related to a person
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and returns a specified number of video URLs.
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Input to this tool should be a comma separated list,
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- the first part contains a person name
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- and the second(optional) a number that is the
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maximum number of video results to return
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"""
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import json
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from typing import Optional
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from langchain.callbacks.manager import (
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AsyncCallbackManagerForToolRun,
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CallbackManagerForToolRun,
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)
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from langchain.tools import BaseTool
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class YouTubeSearchTool(BaseTool):
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name = "YouTubeSearch"
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description = (
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"search for youtube videos associated with a person. "
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"the input to this tool should be a comma separated list, "
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"the first part contains a person name and the second a "
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"number that is the maximum number of video results "
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"to return aka num_results. the second part is optional"
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)
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def _search(self, person: str, num_results: int) -> str:
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from youtube_search import YoutubeSearch
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results = YoutubeSearch(person, num_results).to_json()
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data = json.loads(results)
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url_suffix_list = [video["url_suffix"] for video in data["videos"]]
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return str(url_suffix_list)
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def _run(
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self,
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query: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the tool."""
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values = query.split(",")
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person = values[0]
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if len(values) > 1:
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num_results = int(values[1])
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else:
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num_results = 2
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return self._search(person, num_results)
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async def _arun(
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self,
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query: str,
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run_manager: Optional[AsyncCallbackManagerForToolRun] = None,
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) -> str:
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"""Use the tool asynchronously."""
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raise NotImplementedError("YouTubeSearchTool does not yet support async")
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