community[patch]: Release 0.0.2 (#14610)

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Bagatur 2023-12-12 09:58:04 -08:00 committed by GitHub
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commit d388863a3b
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6 changed files with 85 additions and 45 deletions

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@ -1,4 +1,38 @@
from langchain_community.tools.render import format_tool_to_openai_function
from langchain_core.tools import BaseTool
# For backwards compatibility
__all__ = ["format_tool_to_openai_function"]
from langchain_community.utils.openai_functions import (
FunctionDescription,
ToolDescription,
convert_pydantic_to_openai_function,
)
def format_tool_to_openai_function(tool: BaseTool) -> FunctionDescription:
"""Format tool into the OpenAI function API."""
if tool.args_schema:
return convert_pydantic_to_openai_function(
tool.args_schema, name=tool.name, description=tool.description
)
else:
return {
"name": tool.name,
"description": tool.description,
"parameters": {
# This is a hack to get around the fact that some tools
# do not expose an args_schema, and expect an argument
# which is a string.
# And Open AI does not support an array type for the
# parameters.
"properties": {
"__arg1": {"title": "__arg1", "type": "string"},
},
"required": ["__arg1"],
"type": "object",
},
}
def format_tool_to_openai_tool(tool: BaseTool) -> ToolDescription:
"""Format tool into the OpenAI function API."""
function = format_tool_to_openai_function(tool)
return {"type": "function", "function": function}

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@ -4,8 +4,6 @@ Depending on the LLM you are using and the prompting strategy you are using,
you may want Tools to be rendered in a different way.
This module contains various ways to render tools.
"""
from typing import List
from langchain_core.tools import BaseTool
from langchain_community.utils.openai_functions import (
@ -15,37 +13,6 @@ from langchain_community.utils.openai_functions import (
)
def render_text_description(tools: List[BaseTool]) -> str:
"""Render the tool name and description in plain text.
Output will be in the format of:
.. code-block:: markdown
search: This tool is used for search
calculator: This tool is used for math
"""
return "\n".join([f"{tool.name}: {tool.description}" for tool in tools])
def render_text_description_and_args(tools: List[BaseTool]) -> str:
"""Render the tool name, description, and args in plain text.
Output will be in the format of:
.. code-block:: markdown
search: This tool is used for search, args: {"query": {"type": "string"}}
calculator: This tool is used for math, \
args: {"expression": {"type": "string"}}
"""
tool_strings = []
for tool in tools:
args_schema = str(tool.args)
tool_strings.append(f"{tool.name}: {tool.description}, args: {args_schema}")
return "\n".join(tool_strings)
def format_tool_to_openai_function(tool: BaseTool) -> FunctionDescription:
"""Format tool into the OpenAI function API."""
if tool.args_schema:

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@ -3421,7 +3421,7 @@ files = [
[[package]]
name = "langchain-core"
version = "0.0.13"
version = "0.1.0"
description = "Building applications with LLMs through composability"
optional = false
python-versions = ">=3.8.1,<4.0"
@ -8485,4 +8485,4 @@ extended-testing = ["aiosqlite", "aleph-alpha-client", "anthropic", "arxiv", "as
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "a77af01e299fdeb0849f20f2ae8a49030bd38993ff603f464c1c1f6a170d1d9b"
content-hash = "e3bacf389a13d283c4dd29e3a673e1863826b4e98785c666fefc10cf714c2f6f"

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@ -1,6 +1,6 @@
[tool.poetry]
name = "langchain-community"
version = "0.0.1"
version = "0.0.2"
description = "Community contributed LangChain integrations."
authors = []
license = "MIT"
@ -9,7 +9,7 @@ repository = "https://github.com/langchain-ai/langchain"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain-core = ">=0.0.13,<0.1"
langchain-core = "^0.1"
SQLAlchemy = ">=1.4,<3"
requests = "^2"
PyYAML = ">=5.3"

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@ -1,13 +1,52 @@
from langchain_community.tools.render import (
"""Different methods for rendering Tools to be passed to LLMs.
Depending on the LLM you are using and the prompting strategy you are using,
you may want Tools to be rendered in a different way.
This module contains various ways to render tools.
"""
from typing import List
# For backwards compatibility
from langchain_community.tools.convert_to_openai import (
format_tool_to_openai_function,
format_tool_to_openai_tool,
render_text_description,
render_text_description_and_args,
)
from langchain_core.tools import BaseTool
__all__ = [
"render_text_description",
"render_text_description_and_args",
"format_tool_to_openai_function",
"format_tool_to_openai_tool",
"format_tool_to_openai_function",
]
def render_text_description(tools: List[BaseTool]) -> str:
"""Render the tool name and description in plain text.
Output will be in the format of:
.. code-block:: markdown
search: This tool is used for search
calculator: This tool is used for math
"""
return "\n".join([f"{tool.name}: {tool.description}" for tool in tools])
def render_text_description_and_args(tools: List[BaseTool]) -> str:
"""Render the tool name, description, and args in plain text.
Output will be in the format of:
.. code-block:: markdown
search: This tool is used for search, args: {"query": {"type": "string"}}
calculator: This tool is used for math, \
args: {"expression": {"type": "string"}}
"""
tool_strings = []
for tool in tools:
args_schema = str(tool.args)
tool_strings.append(f"{tool.name}: {tool.description}, args: {args_schema}")
return "\n".join(tool_strings)

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@ -3,7 +3,7 @@ from typing import List
import pytest
from langchain_core.tools import BaseTool, tool
from langchain_community.tools.render import (
from langchain.tools.render import (
render_text_description,
render_text_description_and_args,
)