mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
community: Add stock market tools from financialdatasets.ai (#25025)
**Description:** In this PR, I am adding three stock market tools from financialdatasets.ai (my API!): - get balance sheets - get cash flow statements - get income statements Twitter handle: [@virattt](https://twitter.com/virattt) --------- Co-authored-by: Erick Friis <erick@langchain.dev>
This commit is contained in:
Virat Singh
GitHub
parent
267855b3c1
commit
264ab96980
313
docs/docs/integrations/toolkits/financial_datasets.ipynb
Normal file
313
docs/docs/integrations/toolkits/financial_datasets.ipynb
Normal file
@ -0,0 +1,313 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "raw",
|
||||
"id": "afaf8039",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"---\n",
|
||||
"sidebar_label: financial datasets\n",
|
||||
"---"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"# FinancialDatasetsToolkit\n",
|
||||
"\n",
|
||||
"The [financial datasets](https://financialdatasets.ai/) stock market API provides REST endpoints that let you get financial data for 16,000+ tickers spanning 30+ years.\n",
|
||||
"\n",
|
||||
"## Setup\n",
|
||||
"\n",
|
||||
"To use this toolkit, you need two API keys:\n",
|
||||
"\n",
|
||||
"`FINANCIAL_DATASETS_API_KEY`: Get it from [financialdatasets.ai](https://financialdatasets.ai/).\n",
|
||||
"`OPENAI_API_KEY`: Get it from [OpenAI](https://platform.openai.com/)."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"import getpass\n",
|
||||
"import os\n",
|
||||
"\n",
|
||||
"os.environ[\"FINANCIAL_DATASETS_API_KEY\"] = getpass.getpass()"
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"os.environ[\"OPENAI_API_KEY\"] = getpass.getpass()"
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"### Installation\n",
|
||||
"\n",
|
||||
"This toolkit lives in the `langchain-community` package."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "652d6238-1f87-422a-b135-f5abbb8652fc",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%pip install -qU langchain-community"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "a38cde65-254d-4219-a441-068766c0d4b5",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Instantiation\n",
|
||||
"\n",
|
||||
"Now we can instantiate our toolkit:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_community.agent_toolkits.financial_datasets.toolkit import (\n",
|
||||
" FinancialDatasetsToolkit,\n",
|
||||
")\n",
|
||||
"from langchain_community.utilities.financial_datasets import FinancialDatasetsAPIWrapper\n",
|
||||
"\n",
|
||||
"api_wrapper = FinancialDatasetsAPIWrapper(\n",
|
||||
" financial_datasets_api_key=os.environ[\"FINANCIAL_DATASETS_API_KEY\"]\n",
|
||||
")\n",
|
||||
"toolkit = FinancialDatasetsToolkit(api_wrapper=api_wrapper)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "5c5f2839-4020-424e-9fc9-07777eede442",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Tools\n",
|
||||
"\n",
|
||||
"View available tools:"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "51a60dbe-9f2e-4e04-bb62-23968f17164a",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"tools = toolkit.get_tools()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"## Use within an agent\n",
|
||||
"\n",
|
||||
"Let's equip our agent with the FinancialDatasetsToolkit and ask financial questions."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"system_prompt = \"\"\"\n",
|
||||
"You are an advanced financial analysis AI assistant equipped with specialized tools\n",
|
||||
"to access and analyze financial data. Your primary function is to help users with\n",
|
||||
"financial analysis by retrieving and interpreting income statements, balance sheets,\n",
|
||||
"and cash flow statements for publicly traded companies.\n",
|
||||
"\n",
|
||||
"You have access to the following tools from the FinancialDatasetsToolkit:\n",
|
||||
"\n",
|
||||
"1. Balance Sheets: Retrieves balance sheet data for a given ticker symbol.\n",
|
||||
"2. Income Statements: Fetches income statement data for a specified company.\n",
|
||||
"3. Cash Flow Statements: Accesses cash flow statement information for a particular ticker.\n",
|
||||
"\n",
|
||||
"Your capabilities include:\n",
|
||||
"\n",
|
||||
"1. Retrieving financial statements for any publicly traded company using its ticker symbol.\n",
|
||||
"2. Analyzing financial ratios and metrics based on the data from these statements.\n",
|
||||
"3. Comparing financial performance across different time periods (e.g., year-over-year or quarter-over-quarter).\n",
|
||||
"4. Identifying trends in a company's financial health and performance.\n",
|
||||
"5. Providing insights on a company's liquidity, solvency, profitability, and efficiency.\n",
|
||||
"6. Explaining complex financial concepts in simple terms.\n",
|
||||
"\n",
|
||||
"When responding to queries:\n",
|
||||
"\n",
|
||||
"1. Always specify which financial statement(s) you're using for your analysis.\n",
|
||||
"2. Provide context for the numbers you're referencing (e.g., fiscal year, quarter).\n",
|
||||
"3. Explain your reasoning and calculations clearly.\n",
|
||||
"4. If you need more information to provide a complete answer, ask for clarification.\n",
|
||||
"5. When appropriate, suggest additional analyses that might be helpful.\n",
|
||||
"\n",
|
||||
"Remember, your goal is to provide accurate, insightful financial analysis to\n",
|
||||
"help users make informed decisions. Always maintain a professional and objective tone in your responses.\n",
|
||||
"\"\"\""
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"Instantiate the LLM."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "310bf18e-6c9a-4072-b86e-47bc1fcca29d",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_core.tools import tool\n",
|
||||
"from langchain_openai import ChatOpenAI\n",
|
||||
"\n",
|
||||
"model = ChatOpenAI(model=\"gpt-4o\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"Define a user query."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "23e11cc9-abd6-4855-a7eb-799f45ca01ae",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"query = \"What was AAPL's revenue in 2023? What about it's total debt in Q1 2024?\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"Create the agent."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.agents import AgentExecutor, create_tool_calling_agent\n",
|
||||
"from langchain_core.prompts import ChatPromptTemplate\n",
|
||||
"\n",
|
||||
"prompt = ChatPromptTemplate.from_messages(\n",
|
||||
" [\n",
|
||||
" (\"system\", system_prompt),\n",
|
||||
" (\"human\", \"{input}\"),\n",
|
||||
" # Placeholders fill up a **list** of messages\n",
|
||||
" (\"placeholder\", \"{agent_scratchpad}\"),\n",
|
||||
" ]\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"agent = create_tool_calling_agent(model, tools, prompt)\n",
|
||||
"agent_executor = AgentExecutor(agent=agent, tools=tools)"
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"Query the agent."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"agent_executor.invoke({\"input\": query})"
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"## API reference\n",
|
||||
"\n",
|
||||
"For detailed documentation of all `FinancialDatasetsToolkit` features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/agent_toolkits/langchain_community.agent_toolkits.financial_datasets.toolkit.FinancialDatasetsToolkit.html)."
|
||||
],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [],
|
||||
"metadata": {
|
||||
"collapsed": false
|
||||
}
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.4"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@ -0,0 +1 @@
|
||||
"""financial datasets toolkit."""
|
||||
@ -0,0 +1,45 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import List
|
||||
|
||||
from langchain_core.pydantic_v1 import Field
|
||||
from langchain_core.tools import BaseToolkit
|
||||
|
||||
from langchain_community.tools import BaseTool
|
||||
from langchain_community.tools.financial_datasets.balance_sheets import BalanceSheets
|
||||
from langchain_community.tools.financial_datasets.cash_flow_statements import (
|
||||
CashFlowStatements,
|
||||
)
|
||||
from langchain_community.tools.financial_datasets.income_statements import (
|
||||
IncomeStatements,
|
||||
)
|
||||
from langchain_community.utilities.financial_datasets import FinancialDatasetsAPIWrapper
|
||||
|
||||
|
||||
class FinancialDatasetsToolkit(BaseToolkit):
|
||||
"""Toolkit for interacting with financialdatasets.ai.
|
||||
|
||||
Parameters:
|
||||
api_wrapper: The FinancialDatasets API Wrapper.
|
||||
"""
|
||||
|
||||
api_wrapper: FinancialDatasetsAPIWrapper = Field(
|
||||
default_factory=FinancialDatasetsAPIWrapper
|
||||
)
|
||||
|
||||
def __init__(self, api_wrapper: FinancialDatasetsAPIWrapper):
|
||||
super().__init__()
|
||||
self.api_wrapper = api_wrapper
|
||||
|
||||
class Config:
|
||||
"""Pydantic config."""
|
||||
|
||||
arbitrary_types_allowed = True
|
||||
|
||||
def get_tools(self) -> List[BaseTool]:
|
||||
"""Get the tools in the toolkit."""
|
||||
return [
|
||||
BalanceSheets(api_wrapper=self.api_wrapper),
|
||||
CashFlowStatements(api_wrapper=self.api_wrapper),
|
||||
IncomeStatements(api_wrapper=self.api_wrapper),
|
||||
]
|
||||
@ -120,6 +120,15 @@ if TYPE_CHECKING:
|
||||
ReadFileTool,
|
||||
WriteFileTool,
|
||||
)
|
||||
from langchain_community.tools.financial_datasets.balance_sheets import (
|
||||
BalanceSheets,
|
||||
)
|
||||
from langchain_community.tools.financial_datasets.cash_flow_statements import (
|
||||
CashFlowStatements,
|
||||
)
|
||||
from langchain_community.tools.financial_datasets.income_statements import (
|
||||
IncomeStatements,
|
||||
)
|
||||
from langchain_community.tools.gmail import (
|
||||
GmailCreateDraft,
|
||||
GmailGetMessage,
|
||||
@ -348,6 +357,7 @@ __all__ = [
|
||||
"AzureCogsSpeech2TextTool",
|
||||
"AzureCogsText2SpeechTool",
|
||||
"AzureCogsTextAnalyticsHealthTool",
|
||||
"BalanceSheets",
|
||||
"BaseGraphQLTool",
|
||||
"BaseRequestsTool",
|
||||
"BaseSQLDatabaseTool",
|
||||
@ -357,6 +367,7 @@ __all__ = [
|
||||
"BingSearchResults",
|
||||
"BingSearchRun",
|
||||
"BraveSearch",
|
||||
"CashFlowStatements",
|
||||
"ClickTool",
|
||||
"CogniswitchKnowledgeRequest",
|
||||
"CogniswitchKnowledgeSourceFile",
|
||||
@ -396,6 +407,7 @@ __all__ = [
|
||||
"GoogleSerperRun",
|
||||
"HumanInputRun",
|
||||
"IFTTTWebhook",
|
||||
"IncomeStatements",
|
||||
"InfoPowerBITool",
|
||||
"InfoSQLDatabaseTool",
|
||||
"InfoSparkSQLTool",
|
||||
@ -498,6 +510,7 @@ _module_lookup = {
|
||||
"AzureCogsSpeech2TextTool": "langchain_community.tools.azure_cognitive_services",
|
||||
"AzureCogsText2SpeechTool": "langchain_community.tools.azure_cognitive_services",
|
||||
"AzureCogsTextAnalyticsHealthTool": "langchain_community.tools.azure_cognitive_services", # noqa: E501
|
||||
"BalanceSheets": "langchain_community.tools.financial_datasets.balance_sheets",
|
||||
"BaseGraphQLTool": "langchain_community.tools.graphql.tool",
|
||||
"BaseRequestsTool": "langchain_community.tools.requests.tool",
|
||||
"BaseSQLDatabaseTool": "langchain_community.tools.sql_database.tool",
|
||||
@ -507,6 +520,7 @@ _module_lookup = {
|
||||
"BingSearchResults": "langchain_community.tools.bing_search.tool",
|
||||
"BingSearchRun": "langchain_community.tools.bing_search.tool",
|
||||
"BraveSearch": "langchain_community.tools.brave_search.tool",
|
||||
"CashFlowStatements": "langchain_community.tools.financial_datasets.cash_flow_statements", # noqa: E501
|
||||
"ClickTool": "langchain_community.tools.playwright",
|
||||
"CogniswitchKnowledgeRequest": "langchain_community.tools.cogniswitch.tool",
|
||||
"CogniswitchKnowledgeSourceFile": "langchain_community.tools.cogniswitch.tool",
|
||||
@ -547,6 +561,7 @@ _module_lookup = {
|
||||
"GoogleSerperRun": "langchain_community.tools.google_serper.tool",
|
||||
"HumanInputRun": "langchain_community.tools.human.tool",
|
||||
"IFTTTWebhook": "langchain_community.tools.ifttt",
|
||||
"IncomeStatements": "langchain_community.tools.financial_datasets.income_statements", # noqa: E501
|
||||
"InfoPowerBITool": "langchain_community.tools.powerbi.tool",
|
||||
"InfoSQLDatabaseTool": "langchain_community.tools.sql_database.tool",
|
||||
"InfoSparkSQLTool": "langchain_community.tools.spark_sql.tool",
|
||||
|
||||
@ -0,0 +1,17 @@
|
||||
"""financial datasets tools."""
|
||||
|
||||
from langchain_community.tools.financial_datasets.balance_sheets import (
|
||||
BalanceSheets,
|
||||
)
|
||||
from langchain_community.tools.financial_datasets.cash_flow_statements import (
|
||||
CashFlowStatements,
|
||||
)
|
||||
from langchain_community.tools.financial_datasets.income_statements import (
|
||||
IncomeStatements,
|
||||
)
|
||||
|
||||
__all__ = [
|
||||
"BalanceSheets",
|
||||
"CashFlowStatements",
|
||||
"IncomeStatements",
|
||||
]
|
||||
@ -0,0 +1,62 @@
|
||||
from typing import Optional, Type
|
||||
|
||||
from langchain_core.callbacks import CallbackManagerForToolRun
|
||||
from langchain_core.pydantic_v1 import BaseModel, Field
|
||||
from langchain_core.tools import BaseTool
|
||||
|
||||
from langchain_community.utilities.financial_datasets import FinancialDatasetsAPIWrapper
|
||||
|
||||
|
||||
class BalanceSheetsSchema(BaseModel):
|
||||
"""Input for BalanceSheets."""
|
||||
|
||||
ticker: str = Field(
|
||||
description="The ticker symbol to fetch balance sheets for.",
|
||||
)
|
||||
period: str = Field(
|
||||
description="The period of the balance sheets. "
|
||||
"Possible values are: "
|
||||
"annual, quarterly, ttm. "
|
||||
"Default is 'annual'.",
|
||||
)
|
||||
limit: int = Field(
|
||||
description="The number of balance sheets to return. " "Default is 10.",
|
||||
)
|
||||
|
||||
|
||||
class BalanceSheets(BaseTool):
|
||||
"""
|
||||
Tool that gets balance sheets for a given ticker over a given period.
|
||||
"""
|
||||
|
||||
mode: str = "get_balance_sheets"
|
||||
name: str = "balance_sheets"
|
||||
description: str = (
|
||||
"A wrapper around financial datasets's Balance Sheets API. "
|
||||
"This tool is useful for fetching balance sheets for a given ticker."
|
||||
"The tool fetches balance sheets for a given ticker over a given period."
|
||||
"The period can be annual, quarterly, or trailing twelve months (ttm)."
|
||||
"The number of balance sheets to return can also be "
|
||||
"specified using the limit parameter."
|
||||
)
|
||||
args_schema: Type[BalanceSheetsSchema] = BalanceSheetsSchema
|
||||
|
||||
api_wrapper: FinancialDatasetsAPIWrapper = Field(..., exclude=True)
|
||||
|
||||
def __init__(self, api_wrapper: FinancialDatasetsAPIWrapper):
|
||||
super().__init__(api_wrapper=api_wrapper)
|
||||
|
||||
def _run(
|
||||
self,
|
||||
ticker: str,
|
||||
period: str,
|
||||
limit: Optional[int],
|
||||
run_manager: Optional[CallbackManagerForToolRun] = None,
|
||||
) -> str:
|
||||
"""Use the Balance Sheets API tool."""
|
||||
return self.api_wrapper.run(
|
||||
mode=self.mode,
|
||||
ticker=ticker,
|
||||
period=period,
|
||||
limit=limit,
|
||||
)
|
||||
@ -0,0 +1,62 @@
|
||||
from typing import Optional, Type
|
||||
|
||||
from langchain_core.callbacks import CallbackManagerForToolRun
|
||||
from langchain_core.pydantic_v1 import BaseModel, Field
|
||||
from langchain_core.tools import BaseTool
|
||||
|
||||
from langchain_community.utilities.financial_datasets import FinancialDatasetsAPIWrapper
|
||||
|
||||
|
||||
class CashFlowStatementsSchema(BaseModel):
|
||||
"""Input for CashFlowStatements."""
|
||||
|
||||
ticker: str = Field(
|
||||
description="The ticker symbol to fetch cash flow statements for.",
|
||||
)
|
||||
period: str = Field(
|
||||
description="The period of the cash flow statement. "
|
||||
"Possible values are: "
|
||||
"annual, quarterly, ttm. "
|
||||
"Default is 'annual'.",
|
||||
)
|
||||
limit: int = Field(
|
||||
description="The number of cash flow statements to return. " "Default is 10.",
|
||||
)
|
||||
|
||||
|
||||
class CashFlowStatements(BaseTool):
|
||||
"""
|
||||
Tool that gets cash flow statements for a given ticker over a given period.
|
||||
"""
|
||||
|
||||
mode: str = "get_cash_flow_statements"
|
||||
name: str = "cash_flow_statements"
|
||||
description: str = (
|
||||
"A wrapper around financial datasets's Cash Flow Statements API. "
|
||||
"This tool is useful for fetching cash flow statements for a given ticker."
|
||||
"The tool fetches cash flow statements for a given ticker over a given period."
|
||||
"The period can be annual, quarterly, or trailing twelve months (ttm)."
|
||||
"The number of cash flow statements to return can also be "
|
||||
"specified using the limit parameter."
|
||||
)
|
||||
args_schema: Type[CashFlowStatementsSchema] = CashFlowStatementsSchema
|
||||
|
||||
api_wrapper: FinancialDatasetsAPIWrapper = Field(..., exclude=True)
|
||||
|
||||
def __init__(self, api_wrapper: FinancialDatasetsAPIWrapper):
|
||||
super().__init__(api_wrapper=api_wrapper)
|
||||
|
||||
def _run(
|
||||
self,
|
||||
ticker: str,
|
||||
period: str,
|
||||
limit: Optional[int],
|
||||
run_manager: Optional[CallbackManagerForToolRun] = None,
|
||||
) -> str:
|
||||
"""Use the Cash Flow Statements API tool."""
|
||||
return self.api_wrapper.run(
|
||||
mode=self.mode,
|
||||
ticker=ticker,
|
||||
period=period,
|
||||
limit=limit,
|
||||
)
|
||||
@ -0,0 +1,62 @@
|
||||
from typing import Optional, Type
|
||||
|
||||
from langchain_core.callbacks import CallbackManagerForToolRun
|
||||
from langchain_core.pydantic_v1 import BaseModel, Field
|
||||
from langchain_core.tools import BaseTool
|
||||
|
||||
from langchain_community.utilities.financial_datasets import FinancialDatasetsAPIWrapper
|
||||
|
||||
|
||||
class IncomeStatementsSchema(BaseModel):
|
||||
"""Input for IncomeStatements."""
|
||||
|
||||
ticker: str = Field(
|
||||
description="The ticker symbol to fetch income statements for.",
|
||||
)
|
||||
period: str = Field(
|
||||
description="The period of the income statement. "
|
||||
"Possible values are: "
|
||||
"annual, quarterly, ttm. "
|
||||
"Default is 'annual'.",
|
||||
)
|
||||
limit: int = Field(
|
||||
description="The number of income statements to return. " "Default is 10.",
|
||||
)
|
||||
|
||||
|
||||
class IncomeStatements(BaseTool):
|
||||
"""
|
||||
Tool that gets income statements for a given ticker over a given period.
|
||||
"""
|
||||
|
||||
mode: str = "get_income_statements"
|
||||
name: str = "income_statements"
|
||||
description: str = (
|
||||
"A wrapper around financial datasets's Income Statements API. "
|
||||
"This tool is useful for fetching income statements for a given ticker."
|
||||
"The tool fetches income statements for a given ticker over a given period."
|
||||
"The period can be annual, quarterly, or trailing twelve months (ttm)."
|
||||
"The number of income statements to return can also be "
|
||||
"specified using the limit parameter."
|
||||
)
|
||||
args_schema: Type[IncomeStatementsSchema] = IncomeStatementsSchema
|
||||
|
||||
api_wrapper: FinancialDatasetsAPIWrapper = Field(..., exclude=True)
|
||||
|
||||
def __init__(self, api_wrapper: FinancialDatasetsAPIWrapper):
|
||||
super().__init__(api_wrapper=api_wrapper)
|
||||
|
||||
def _run(
|
||||
self,
|
||||
ticker: str,
|
||||
period: str,
|
||||
limit: Optional[int],
|
||||
run_manager: Optional[CallbackManagerForToolRun] = None,
|
||||
) -> str:
|
||||
"""Use the Income Statements API tool."""
|
||||
return self.api_wrapper.run(
|
||||
mode=self.mode,
|
||||
ticker=ticker,
|
||||
period=period,
|
||||
limit=limit,
|
||||
)
|
||||
@ -0,0 +1,135 @@
|
||||
"""
|
||||
Util that calls several of financial datasets stock market REST APIs.
|
||||
Docs: https://docs.financialdatasets.ai/
|
||||
"""
|
||||
|
||||
import json
|
||||
from typing import Any, List, Optional
|
||||
|
||||
import requests
|
||||
from langchain_core.pydantic_v1 import BaseModel
|
||||
from langchain_core.utils import get_from_dict_or_env
|
||||
|
||||
FINANCIAL_DATASETS_BASE_URL = "https://api.financialdatasets.ai/"
|
||||
|
||||
|
||||
class FinancialDatasetsAPIWrapper(BaseModel):
|
||||
"""Wrapper for financial datasets API."""
|
||||
|
||||
financial_datasets_api_key: Optional[str] = None
|
||||
|
||||
def __init__(self, **data: Any):
|
||||
super().__init__(**data)
|
||||
self.financial_datasets_api_key = get_from_dict_or_env(
|
||||
data, "financial_datasets_api_key", "FINANCIAL_DATASETS_API_KEY"
|
||||
)
|
||||
|
||||
def get_income_statements(
|
||||
self,
|
||||
ticker: str,
|
||||
period: str,
|
||||
limit: Optional[int],
|
||||
) -> Optional[dict]:
|
||||
"""
|
||||
Get the income statements for a stock `ticker` over a `period` of time.
|
||||
|
||||
:param ticker: the stock ticker
|
||||
:param period: the period of time to get the balance sheets for.
|
||||
Possible values are: annual, quarterly, ttm.
|
||||
:param limit: the number of results to return, default is 10
|
||||
:return: a list of income statements
|
||||
"""
|
||||
url = (
|
||||
f"{FINANCIAL_DATASETS_BASE_URL}financials/income-statements/"
|
||||
f"?ticker={ticker}"
|
||||
f"&period={period}"
|
||||
f"&limit={limit if limit else 10}"
|
||||
)
|
||||
|
||||
# Add the api key to the headers
|
||||
headers = {"X-API-KEY": self.financial_datasets_api_key}
|
||||
|
||||
# Execute the request
|
||||
response = requests.get(url, headers=headers)
|
||||
data = response.json()
|
||||
|
||||
return data.get("income_statements", None)
|
||||
|
||||
def get_balance_sheets(
|
||||
self,
|
||||
ticker: str,
|
||||
period: str,
|
||||
limit: Optional[int],
|
||||
) -> List[dict]:
|
||||
"""
|
||||
Get the balance sheets for a stock `ticker` over a `period` of time.
|
||||
|
||||
:param ticker: the stock ticker
|
||||
:param period: the period of time to get the balance sheets for.
|
||||
Possible values are: annual, quarterly, ttm.
|
||||
:param limit: the number of results to return, default is 10
|
||||
:return: a list of balance sheets
|
||||
"""
|
||||
url = (
|
||||
f"{FINANCIAL_DATASETS_BASE_URL}financials/balance-sheets/"
|
||||
f"?ticker={ticker}"
|
||||
f"&period={period}"
|
||||
f"&limit={limit if limit else 10}"
|
||||
)
|
||||
|
||||
# Add the api key to the headers
|
||||
headers = {"X-API-KEY": self.financial_datasets_api_key}
|
||||
|
||||
# Execute the request
|
||||
response = requests.get(url, headers=headers)
|
||||
data = response.json()
|
||||
|
||||
return data.get("balance_sheets", None)
|
||||
|
||||
def get_cash_flow_statements(
|
||||
self,
|
||||
ticker: str,
|
||||
period: str,
|
||||
limit: Optional[int],
|
||||
) -> List[dict]:
|
||||
"""
|
||||
Get the cash flow statements for a stock `ticker` over a `period` of time.
|
||||
|
||||
:param ticker: the stock ticker
|
||||
:param period: the period of time to get the balance sheets for.
|
||||
Possible values are: annual, quarterly, ttm.
|
||||
:param limit: the number of results to return, default is 10
|
||||
:return: a list of cash flow statements
|
||||
"""
|
||||
|
||||
url = (
|
||||
f"{FINANCIAL_DATASETS_BASE_URL}financials/cash-flow-statements/"
|
||||
f"?ticker={ticker}"
|
||||
f"&period={period}"
|
||||
f"&limit={limit if limit else 10}"
|
||||
)
|
||||
|
||||
# Add the api key to the headers
|
||||
headers = {"X-API-KEY": self.financial_datasets_api_key}
|
||||
|
||||
# Execute the request
|
||||
response = requests.get(url, headers=headers)
|
||||
data = response.json()
|
||||
|
||||
return data.get("cash_flow_statements", None)
|
||||
|
||||
def run(self, mode: str, ticker: str, **kwargs: Any) -> str:
|
||||
if mode == "get_income_statements":
|
||||
period = kwargs.get("period", "annual")
|
||||
limit = kwargs.get("limit", 10)
|
||||
return json.dumps(self.get_income_statements(ticker, period, limit))
|
||||
elif mode == "get_balance_sheets":
|
||||
period = kwargs.get("period", "annual")
|
||||
limit = kwargs.get("limit", 10)
|
||||
return json.dumps(self.get_balance_sheets(ticker, period, limit))
|
||||
elif mode == "get_cash_flow_statements":
|
||||
period = kwargs.get("period", "annual")
|
||||
limit = kwargs.get("limit", 10)
|
||||
return json.dumps(self.get_cash_flow_statements(ticker, period, limit))
|
||||
else:
|
||||
raise ValueError(f"Invalid mode {mode} for financial datasets API.")
|
||||
@ -20,6 +20,7 @@ EXPECTED_ALL = [
|
||||
"AzureCogsSpeech2TextTool",
|
||||
"AzureCogsText2SpeechTool",
|
||||
"AzureCogsTextAnalyticsHealthTool",
|
||||
"BalanceSheets",
|
||||
"BaseGraphQLTool",
|
||||
"BaseRequestsTool",
|
||||
"BaseSQLDatabaseTool",
|
||||
@ -29,6 +30,7 @@ EXPECTED_ALL = [
|
||||
"BingSearchResults",
|
||||
"BingSearchRun",
|
||||
"BraveSearch",
|
||||
"CashFlowStatements",
|
||||
"ClickTool",
|
||||
"CogniswitchKnowledgeSourceFile",
|
||||
"CogniswitchKnowledgeSourceURL",
|
||||
@ -68,6 +70,7 @@ EXPECTED_ALL = [
|
||||
"GoogleSerperRun",
|
||||
"HumanInputRun",
|
||||
"IFTTTWebhook",
|
||||
"IncomeStatements",
|
||||
"InfoPowerBITool",
|
||||
"InfoSQLDatabaseTool",
|
||||
"InfoSparkSQLTool",
|
||||
|
||||
Loading…
Reference in New Issue
Block a user