mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
54 lines
1.7 KiB
Python
54 lines
1.7 KiB
Python
"""
|
|
Adapted from https://github.com/venuv/langchain_yt_tools
|
|
|
|
CustomYTSearchTool searches YouTube videos related to a person
|
|
and returns a specified number of video URLs.
|
|
Input to this tool should be a comma separated list,
|
|
- the first part contains a person name
|
|
- and the second(optional) a number that is the
|
|
maximum number of video results to return
|
|
"""
|
|
import json
|
|
from typing import Optional
|
|
|
|
from langchain_core.callbacks import CallbackManagerForToolRun
|
|
|
|
from langchain_community.tools import BaseTool
|
|
|
|
|
|
class YouTubeSearchTool(BaseTool):
|
|
"""Tool that queries YouTube."""
|
|
|
|
name: str = "youtube_search"
|
|
description: str = (
|
|
"search for youtube videos associated with a person. "
|
|
"the input to this tool should be a comma separated list, "
|
|
"the first part contains a person name and the second a "
|
|
"number that is the maximum number of video results "
|
|
"to return aka num_results. the second part is optional"
|
|
)
|
|
|
|
def _search(self, person: str, num_results: int) -> str:
|
|
from youtube_search import YoutubeSearch
|
|
|
|
results = YoutubeSearch(person, num_results).to_json()
|
|
data = json.loads(results)
|
|
url_suffix_list = [
|
|
"https://www.youtube.com" + video["url_suffix"] for video in data["videos"]
|
|
]
|
|
return str(url_suffix_list)
|
|
|
|
def _run(
|
|
self,
|
|
query: str,
|
|
run_manager: Optional[CallbackManagerForToolRun] = None,
|
|
) -> str:
|
|
"""Use the tool."""
|
|
values = query.split(",")
|
|
person = values[0]
|
|
if len(values) > 1:
|
|
num_results = int(values[1])
|
|
else:
|
|
num_results = 2
|
|
return self._search(person, num_results)
|