mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +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
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
"""
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This tool allows agents to interact with the clickup library
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and operate on a Clickup instance.
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To use this tool, you must first set as environment variables:
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client_secret
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client_id
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code
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Below is a sample script that uses the Clickup tool:
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```python
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from langchain_community.agent_toolkits.clickup.toolkit import ClickupToolkit
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from langchain_community.utilities.clickup import ClickupAPIWrapper
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clickup = ClickupAPIWrapper()
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toolkit = ClickupToolkit.from_clickup_api_wrapper(clickup)
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```
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"""
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from typing import Optional
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from langchain_core.callbacks import CallbackManagerForToolRun
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from langchain_core.pydantic_v1 import Field
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from langchain_core.tools import BaseTool
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from langchain_community.utilities.clickup import ClickupAPIWrapper
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class ClickupAction(BaseTool):
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"""Tool that queries the Clickup API."""
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api_wrapper: ClickupAPIWrapper = Field(default_factory=ClickupAPIWrapper)
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mode: str
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name: str = ""
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description: str = ""
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def _run(
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self,
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instructions: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the Clickup API to run an operation."""
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return self.api_wrapper.run(self.mode, instructions)
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