├── .gitignore ├── .python-version ├── CODE_OF_CONDUCT.md ├── CONTRIBUTING.md ├── LICENSE ├── NOTICE ├── README.md ├── main.py ├── pkg ├── __init__.py └── ask.py ├── requirements.txt └── tools ├── __init__.py ├── currency.py └── ticker.py /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/latest/usage/project/#working-with-version-control 110 | .pdm.toml 111 | .pdm-python 112 | .pdm-build/ 113 | 114 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 115 | __pypackages__/ 116 | 117 | # Celery stuff 118 | celerybeat-schedule 119 | celerybeat.pid 120 | 121 | # SageMath parsed files 122 | *.sage.py 123 | 124 | # Environments 125 | .env 126 | .venv 127 | env/ 128 | venv/ 129 | ENV/ 130 | env.bak/ 131 | venv.bak/ 132 | 133 | # Spyder project settings 134 | .spyderproject 135 | .spyproject 136 | 137 | # Rope project settings 138 | .ropeproject 139 | 140 | # mkdocs documentation 141 | /site 142 | 143 | # mypy 144 | .mypy_cache/ 145 | .dmypy.json 146 | dmypy.json 147 | 148 | # Pyre type checker 149 | .pyre/ 150 | 151 | # pytype static type analyzer 152 | .pytype/ 153 | 154 | # Cython debug symbols 155 | cython_debug/ 156 | 157 | # PyCharm 158 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 159 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 160 | # and can be added to the global gitignore or merged into this file. For a more nuclear 161 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 162 | #.idea/ -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.12 2 | -------------------------------------------------------------------------------- /CODE_OF_CONDUCT.md: -------------------------------------------------------------------------------- 1 | ## Code of Conduct 2 | This project has adopted the [Amazon Open Source Code of Conduct](https://aws.github.io/code-of-conduct). 3 | For more information see the [Code of Conduct FAQ](https://aws.github.io/code-of-conduct-faq) or contact 4 | opensource-codeofconduct@amazon.com with any additional questions or comments. 5 | -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # Contributing Guidelines 2 | 3 | Thank you for your interest in contributing to our project. 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All Rights Reserved. 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Function calling using Amazon Bedrock with Anthropic Claude 3 2 | 3 | Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies and a set of capabilities to build generative AI applications. 4 | 5 | This sample repo provide an example for using function calling using the [Converse API](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/bedrock-runtime/client/converse.html) with [Anthropic Claude 3 Sonnet](https://aws.amazon.com/about-aws/whats-new/2024/03/anthropics-claude-3-sonnet-model-amazon-bedrock/), using multiple tools. This repo is a sample only code, that demonstrate how to use function calling as tools for a model to use to fetch results using plain function code. 6 | 7 | The `Converse` API provides a consistent interface that works with all models that support messages. This allows you to write code once and use it with different models. Should a model have unique inference parameters, you can also pass those unique parameters to the model. 8 | 9 | ## Overview 10 | 11 | Function calling (also known as tools), is a way to provide the model, with a descriptive guidance for a function that is available to the model to use for answering the user input. 12 | 13 | In this sample, we will ask a Claude 3 to answer, what is a stock ticker value, and with option to convert the default ticker currency to any currency that was provided in the user input. 14 | 15 | ## Tools 16 | 17 | There are 2 tools available to the models to use: 18 | 19 | * get_stock_price - given a ticker string, the open source library [yfinance](https://pypi.org/project/yfinance/) will get the current stock value, and currency that its being traded. 20 | * convert_currency - given an amount, source and target currency, the open source library [CurrencyConverter](https://pypi.org/project/CurrencyConverter/) will convert the amount given from source currency to target currency. 21 | 22 | The model each turn will review the prompt given, will decide if it can answer properly the question provided in the user input, each turn according to the response from Bedrock `end_turn` or `tool_use`. `end_turn` means that the final answer was provided, and `tool_use` will parse the appropriate data per the tool description that will be used to execute the tool function, and build a proper result back to the model. 23 | 24 | >This sample code was tested using [pyenv](https://github.com/pyenv/pyenv) with python 3.12, and set in [.python-version](.python-version) 25 | 26 | ## Setup 27 | 28 | 1. **AWS Configuration**: 29 | - Ensure you have an AWS account and the AWS CLI installed and configured. 30 | - AWS region for this sample uses `us-west-2`, and be configured in [ask.py](pkg/ask.py) 31 | 32 | 2. **Bedrock Access**: 33 | - If its the first time using Bedrock, please review [Manage access to Amazon Bedrock foundation models](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access.html) 34 | - To add model access, ensure that the user logged in has the minimum permissions for adding an AWS marketplace subscription: 35 | - aws-marketplace:Subscribe 36 | - aws-marketplace:Unsubscribe 37 | - aws-marketplace:ViewSubscriptions 38 | - In AWS Console under Amazon Bedrock service, go to [model access](https://us-west-2.console.aws.amazon.com/bedrock/home?region=us-west-2#/modelaccess), click on **Modify model access** and enable **Claude 3 Sonnet**, the model id is shown in [ask.py](ask.py) `anthropic.claude-3-sonnet-20240229-v1:0` 39 | 40 | 3. **IAM permissions**: 41 | - Make sure that the IAM user that runs this project, make sure that he as the permissions to invoke Claude 3 models. 42 | For this sample, you can use: 43 | 44 | ```json 45 | { 46 | "Version": "2012-10-17", 47 | "Statement": [ 48 | { 49 | "Sid": "LeastPrivilege4BRClient", 50 | "Effect": "Allow", 51 | "Action": [ 52 | "bedrock:InvokeModel" 53 | ], 54 | "Resource": "arn:aws:bedrock:us-west-2::foundation-model/*" 55 | }] 56 | } 57 | ``` 58 | 59 | >This can be more restricted using least privileges with the specific model id. 60 | 61 | ## Usage 62 | 63 | To run this sample code follow these steps: 64 | 65 | 1. **Install dependency** - run `pip install -r requirements.txt` 66 | 2. **Run the script** - run the `python main.py` 67 | 3. **Command line argument** - Optionally you can add `--input "new input here"` to overide the default user input text. 68 | 69 | ### Example 70 | 71 | **Default prompt**: "What is the current stock price of amazon stock in pounds? 72 | 73 | For example Anthropic Claude 3 Sonnet will know the Amazon Ticker is AMZN, will use the tool get the ticker value, and then will convert the source currency of the stock price to the destination currency. 74 | 75 | Each iteration of inference, when a `tool_use` is returned, the returned messages will be appended to build a conversation like for the model, due to the nature of LLM's being stateless. 76 | 77 | The final prompt, before the final answer from the Claude 3 will look similar to this: 78 | 79 | ```json 80 | [ 81 | { 82 | "role": "user", 83 | "content": [ 84 | { 85 | "text": "What is the current stock price of amazon stock in pounds?" 86 | } 87 | ] 88 | }, 89 | { 90 | "role": "assistant", 91 | "content": [ 92 | { 93 | "text": "Okay, let me get the current Amazon (AMZN) stock price and convert it to British pounds for you:" 94 | }, 95 | { 96 | "toolUse": { 97 | "toolUseId": "tooluse_7ofuIPr8T3uBsK2xy1GZBw", 98 | "name": "get_stock_price", 99 | "input": { 100 | "ticker": "AMZN" 101 | } 102 | } 103 | } 104 | ] 105 | }, 106 | { 107 | "role": "user", 108 | "content": [ 109 | { 110 | "toolResult": { 111 | "toolUseId": "tooluse_7ofuIPr8T3uBsK2xy1GZBw", 112 | "content": [ 113 | { 114 | "json": { 115 | "ticker": "AMZN", 116 | "price": 200, 117 | "currency": "USD" 118 | } 119 | } 120 | ] 121 | } 122 | } 123 | ] 124 | }, 125 | { 126 | "role": "assistant", 127 | "content": [ 128 | { 129 | "text": "The current Amazon stock price is $200.00 USD. To convert that to British pounds:" 130 | }, 131 | { 132 | "toolUse": { 133 | "toolUseId": "tooluse_lyTta3oMSfik5EhsCnnkGg", 134 | "name": "convert_currency", 135 | "input": { 136 | "amount": 200, 137 | "source_currency": "USD", 138 | "target_currency": "GBP" 139 | } 140 | } 141 | } 142 | ] 143 | }, 144 | { 145 | "role": "user", 146 | "content": [ 147 | { 148 | "toolResult": { 149 | "toolUseId": "tooluse_lyTta3oMSfik5EhsCnnkGg", 150 | "content": [ 151 | { 152 | "json": { 153 | "converted_currency": 158.0185237159697 154 | } 155 | } 156 | ] 157 | } 158 | } 159 | ] 160 | } 161 | ] 162 | ``` 163 | 164 | And the final answer should be similar to this: `So the current Amazon (AMZN) stock price of $200.00 USD converts to £158.02 GBP.` 165 | 166 | >**Note:** Stock prices and currency exchange rates are highly volatile and can change rapidly. The example output shown in this README may not reflect current market values. When running the code, you'll get real-time data which may differ from the examples provided. 167 | 168 | ## Security 169 | 170 | See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information. 171 | 172 | ## Contributing 173 | 174 | See [CONTRIBUTING](CONTRIBUTING.md) for more information. 175 | 176 | 177 | ## License 178 | 179 | This project is licensed under the Apache-2.0 License. 180 | 181 | -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | from pkg.ask import generate_text 2 | from loguru import logger 3 | from tools.ticker import parse_and_run_get_stock_price 4 | from tools.currency import parse_and_run_convert_currency 5 | import argparse 6 | import json 7 | 8 | 9 | def parse_args(): 10 | parser = argparse.ArgumentParser() 11 | parser.add_argument('--input', type=str, required=False, help='Input text for the LLM', default="What is the current stock price of amazon stock in pounds?") 12 | return parser.parse_known_args() 13 | 14 | 15 | def build_message(input_text:str) -> list[dict]: 16 | """ 17 | Build the message to send to the LLM from the input test 18 | :param input_text: the input text to send to the LLM 19 | :return: a list containing containing the role, content and user input as text 20 | """ 21 | return [{"role": "user", "content": [{"text": input_text}]}] 22 | 23 | 24 | def main(): 25 | logger.info("Starting") 26 | args, _ = parse_args() 27 | input_text = args.input 28 | msg = build_message(input_text) 29 | logger.info(f"input text: {input_text}") 30 | 31 | stop_reason: str = None 32 | answer: str = None 33 | 34 | # Run until the model end_turn 35 | while stop_reason != 'end_turn': 36 | stop_reason, tools_requested, messages = generate_text(msg) 37 | logger.debug(f"stop reason is {stop_reason}, continue work till final answer") 38 | 39 | # Amazon Bedrock LLM ended turn and responded the final answer 40 | if stop_reason == 'end_turn': 41 | logger.info("The question asked the LLM ended turn and this is the answer") 42 | answers = messages.get("content", {}) 43 | # itterate over the returned answers from Amazon Bedrock LLM 44 | answers_text = [a.get('text', '\n') for a in answers] 45 | answer = ''.join(answers_text) 46 | break 47 | 48 | if stop_reason == 'tool_use': 49 | # find from the content returned form tools_requested the tool to use 50 | for content in tools_requested: 51 | if 'toolUse' in content: 52 | tool_use_id = content.get('toolUse', {}).get('toolUseId') 53 | tool_use_name = content.get('toolUse', {}).get('name') 54 | tool_use_input = content.get('toolUse', {}).get('input') 55 | logger.info(f"tool use id is {tool_use_id}, tool use name is {tool_use_name}") 56 | # stock price tool 57 | if tool_use_name == 'get_stock_price': 58 | message = parse_and_run_get_stock_price(tool_use_id, tool_use_input) 59 | messages.append(message) 60 | 61 | # currency conversion tool 62 | if tool_use_name == 'convert_currency': 63 | message = parse_and_run_convert_currency(tool_use_id, tool_use_input) 64 | messages.append(message) 65 | 66 | # See the messages appended that are being built for the LLM, this will allow the Bedrock LLM to provide the final answer. 67 | logger.debug(f"messages:\n{json.dumps(messages)}") 68 | 69 | else: 70 | # Stop reasons can be: 'end_turn'|'tool_use'|'max_tokens'|'stop_sequence'|'guardrail_intervened'|'content_filtered' 71 | # This code sample only covers end_turn, and tool_use, you may need to implement additional code to cover all the rest of the responses. 72 | logger.warning(f"llm didn't end_turn, or asked to use a tool, he asked to {stop_reason}") 73 | return 74 | 75 | # Printing the final reponse from the model 76 | logger.info(answer) 77 | 78 | 79 | if __name__ == "__main__": 80 | main() 81 | 82 | -------------------------------------------------------------------------------- /pkg/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aws-samples/function-calling-using-amazon-bedrock-anthropic-claude-3/78e24750781cb5a3d7ad654a73ed889d196d96b4/pkg/__init__.py -------------------------------------------------------------------------------- /pkg/ask.py: -------------------------------------------------------------------------------- 1 | import boto3 2 | from tools.ticker import ticker_tool_description 3 | from tools.currency import currency_converter_tool_description 4 | from typing import Union 5 | 6 | 7 | bedrock_client = boto3.client("bedrock-runtime", region_name="us-west-2") 8 | 9 | # Bedrock model selected 10 | # See supported models: 11 | # https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html#conversation-inference-supported-models-features 12 | modelId = "anthropic.claude-3-sonnet-20240229-v1:0" # Claude Sonnet 3 13 | # modelId = "anthropic.claude-3-5-sonnet-20240620-v1:0" # Claude Sonnet 3.5 14 | # modelId = "cohere.command-r-v1:0" # Command R 15 | # modelId = "cohere.command-r-plus-v1:0" # Command R+ 16 | # modelId = "mistral.mistral-large-2407-v1:0" # Mistral Large 17 | # modelId = "meta.llama3-1-70b-instruct-v1:0" # Meta LLAMA3.1 70B 18 | 19 | # Converse API inferense parameters 20 | kwargs = { 21 | "temperature": 0, 22 | "maxTokens": 2048, 23 | "topP": 0, 24 | } 25 | 26 | 27 | system_text_promot = """you are a stock market bot, that provides accurate ticker prices at any currency. 28 | use your tools to get stock price, and covert to another currency when asked. 29 | You answer only questions on companies ticker value and currency. 30 | """ 31 | 32 | 33 | def generate_text(messages) -> Union[str, list[str], list[dict[str, any]]]: 34 | """ 35 | Generate the Amazon Bedrock model response for a given input text, and return the response of each turn 36 | :param messages: list of message dicts from the user 37 | :return: stop reason, list of the tools requested, and the output messages from the model 38 | """ 39 | 40 | system_prompt = [{"text": system_text_promot}] 41 | 42 | # Using Amazon Bedrock converse API 43 | # https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html 44 | response = bedrock_client.converse( 45 | modelId=modelId, 46 | messages=messages, 47 | system=system_prompt, 48 | toolConfig={ 49 | "tools": [ticker_tool_description, currency_converter_tool_description] 50 | }, 51 | inferenceConfig=kwargs, 52 | ) 53 | 54 | output_message = response.get("output", {}).get("message", {}) 55 | stop_reason = response.get("stopReason") 56 | tools_requested = [] 57 | # Only if a tools should be used, send the tool to use, and append the messages for the user and assistant to build a conversation 58 | if stop_reason == "tool_use": 59 | tools_requested = ( 60 | response.get("output", {}).get("message", {}).get("content", {}) 61 | ) 62 | messages.append(output_message) 63 | return stop_reason, tools_requested, messages 64 | 65 | return stop_reason, tools_requested, output_message 66 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | boto3>=1.34.141 2 | loguru>=0.7.2 3 | yfinance==0.2.40 4 | currencyconverter==0.17.25 -------------------------------------------------------------------------------- /tools/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/aws-samples/function-calling-using-amazon-bedrock-anthropic-claude-3/78e24750781cb5a3d7ad654a73ed889d196d96b4/tools/__init__.py -------------------------------------------------------------------------------- /tools/currency.py: -------------------------------------------------------------------------------- 1 | from currency_converter import CurrencyConverter 2 | 3 | # Tool description to pass the LLM to learn about which tool he may use each turn 4 | currency_converter_tool_description = { 5 | "toolSpec": { 6 | "name": "convert_currency", 7 | "description": "Converts a given amount from one currency to another. The user should provide the amount, the source currency, and the target currency. The tool will return the converted amount in the target currency. It should be used when the user needs to convert one currency to another, such as when purchasing a currency pair or converting cash into a different currency.", 8 | "inputSchema": { 9 | "json": { 10 | "type": "object", 11 | "properties": { 12 | "amount": { 13 | "type": "number", 14 | "description": "The amount of the source currency to be converted.", 15 | }, 16 | "source_currency": { 17 | "type": "string", 18 | "description": "The currency of the amount provided. e.g USD for US Dollars.", 19 | }, 20 | "target_currency": { 21 | "type": "string", 22 | "description": "The currency to convert the amount to. e.g EUR for Euros.", 23 | }, 24 | }, 25 | "required": ["amount", "source_currency", "target_currency"], 26 | }, 27 | }, 28 | } 29 | } 30 | 31 | 32 | def parse_and_run_convert_currency(tool_use_id, input): 33 | """ 34 | Parses the given tool inputs, to pass to the tool, and return the tool result formatted for Bedrock Converse API 35 | :param tool_use_id: The tool use id to uniquely identify the tool use 36 | :param input: The tool inputs, {amount: float, source_currency: str, target_currency: str} 37 | :return: The tool result formatted for Bedrock Converse API 38 | """ 39 | amount = input.get("amount", {}) 40 | source_currency = input.get("source_currency", {}) 41 | target_currency = input.get("target_currency", {}) 42 | converted_currency = convert_currency(amount, source_currency, target_currency) 43 | tool_result = { 44 | "toolUseId": tool_use_id, 45 | "content": [ 46 | { 47 | "json": { 48 | "converted_currency": converted_currency 49 | } 50 | } 51 | ] 52 | } 53 | tool_result_message = { 54 | "role": "user", 55 | "content": [{"toolResult": tool_result}], 56 | } 57 | return tool_result_message 58 | 59 | 60 | 61 | def convert_currency(amount: float, source_currency: str, target_currency: str) -> float: 62 | """ 63 | Convert the given amount from the source currency to the target currency. 64 | :param amount: The amount of the source currency. 65 | :param source_currency: The currency of the amount provided. 66 | :param target_currency: The currency to convert the amount to. 67 | :return: The converted amount in the target currency. 68 | """ 69 | c = CurrencyConverter() 70 | converted_amount = c.convert(amount, source_currency, target_currency) 71 | return float(converted_amount) -------------------------------------------------------------------------------- /tools/ticker.py: -------------------------------------------------------------------------------- 1 | import yfinance as yf 2 | from typing import Union 3 | 4 | 5 | ticker_tool_description = { 6 | "toolSpec": { 7 | "name": "get_stock_price", 8 | "description": "Retrieves the current stock price for a given ticker symbol, and the currency that its being traded. The ticker symbol must be a valid symbol for a publicly traded company on a major US stock exchange like NYSE or NASDAQ. The tool will return the latest trade price in USD. It should be used when the user asks about the current or most recent price of a specific stock. It will not provide any other information about the stock or company.", 9 | "inputSchema": { 10 | "json": { 11 | "type": "object", 12 | "properties": { 13 | "ticker": { 14 | "type": "string", 15 | "description": "The ticker symbol of the company. e.g AAPL for Apple Inc.", 16 | } 17 | }, 18 | "required": ["ticker"], 19 | }, 20 | }, 21 | } 22 | } 23 | 24 | 25 | def parse_and_run_get_stock_price(tool_use_id, input): 26 | """ 27 | Parses the given tool inputs, to pass to the tool, and return the tool result formatted for Bedrock Converse API 28 | :param tool_use_id: the id of the tool use 29 | :param input: the tool input { ticker: str } 30 | :return: The tool result formatted for Bedrock Converse API 31 | """ 32 | ticker = input.get("ticker", {}) 33 | if ticker: 34 | price, currency = get_stock_price(ticker) 35 | tool_result = { 36 | "toolUseId": tool_use_id, 37 | "content": [ 38 | { 39 | "json": { 40 | "ticker": ticker, 41 | "price": price, 42 | "currency": currency, 43 | } 44 | } 45 | ], 46 | } 47 | tool_result_message = {"role": "user", "content": [{"toolResult": tool_result}]} 48 | 49 | return tool_result_message 50 | 51 | 52 | def get_stock_price(ticker: str) -> Union[float, str]: 53 | """ 54 | Retrieves the current stock price for the given ticker symbol. 55 | :param ticker: The ticker symbol of the company. 56 | :return: A tuple containing the current stock price and the currency code. 57 | """ 58 | stock = yf.Ticker(ticker) 59 | info = stock.basic_info 60 | hist = stock.history(period="1d") 61 | current_price = hist["Close"].iloc[0] 62 | return float(current_price), info["currency"] 63 | --------------------------------------------------------------------------------