https://github.com/thomassuedbroecker/agent_tools_langchain_chatwatsonx
The objective is to get a basic understanding of how to use the tools in AI agents by using the ChatWatsonx class.
https://github.com/thomassuedbroecker/agent_tools_langchain_chatwatsonx
agents ai function-calling langchain watsonx-ai
Last synced: 7 months ago
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The objective is to get a basic understanding of how to use the tools in AI agents by using the ChatWatsonx class.
- Host: GitHub
- URL: https://github.com/thomassuedbroecker/agent_tools_langchain_chatwatsonx
- Owner: thomassuedbroecker
- License: apache-2.0
- Created: 2024-08-16T13:10:44.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-26T16:28:04.000Z (about 1 year ago)
- Last Synced: 2025-01-18T09:52:42.988Z (9 months ago)
- Topics: agents, ai, function-calling, langchain, watsonx-ai
- Language: Python
- Homepage:
- Size: 18.6 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Does it work to use WatsonxChat from langchain_ibm to implement an action that invokes functions?
This repository is an example using the langchain_ibm implementation for action and function calling with ChatWatsonx class.
Related blog post: [Does it work to use WatsonxChat from langchain_ibm to implement an action that invokes functions?](https://wp.me/paelj4-1Sc)
## 0. Clone the repository
```sh
git clone https://github.com/thomassuedbroecker/agent_tools_langchain_chatwatsonx.git
cd agent_tools_langchain_chatwatsonx
```
## 1. Environment Setup
### Step 1: Generate a virtual Python environment
```sh
cd code
python3 -m venv --upgrade-deps venv
source venv/bin/activate
```
### Step 2: Install the needed libraries
```sh
python3 -m pip install -qU langchain-ibm
python3 -m pip install -qU langchain
```
### Step 3: Generate a `.env` file for the needed environment variables
```sh
cat env_example_template > .env
```
Insert the values for the two environment variables:
* `WATSONX_PROJECT_ID=YOUR_WATSONX_PROJECT_ID`
* `IBMCLOUD_APIKEY=YOUR_KEY`
Content of the environment file.
```sh
export IBMCLOUD_APIKEY=YOUR_KEY
export IBMCLOUD_URL="https://iam.cloud.ibm.com/identity/token"
# Watsonx
export WATSONX_URL="https://eu-de.ml.cloud.ibm.com"
export WATSONX_VERSION=2023-05-29
export WATSONX_PROJECT_ID=YOUR_PROJECT_ID
export WATSONX_MIN_NEW_TOKENS=1
export WATSONX_MAX_NEW_TOKENS=300
export WATSONX_LLM_NAME=mistralai/mixtral-8x7b-instruct-v01
export WATSONX_INSTANCE_ID=YOUR_WATSONX_INSTANCE_ID
export WATSONX_USERNAME="exampe_user@exampl.net"
```
## 2. Execution
### Step 5: Run the example
```sh
cd code
bash example_agent_invocation.sh
```
* Output of the invocation:
```sg
======== TOOL ONLY ========
1. Verify the tool schema definition
=============================
1. Tool name:
today_maximal_temperature
2. Tool description:
provides the maximal temperature for today information for the given cities.
Args:
cities: The parameter cities is a list e.g. [ "LA", "NY"].
3. Tool arguments:
{'cities': {'title': 'Cities', 'type': 'array', 'items': {'type': 'string'}}}
4. Tool arguments title:
Cities
=============================
2. Invoke the tool and print invocation result
=============================
Result:
[{'city': 'Berlin', 'temperature_max': '29'}, {'city': 'NY', 'temperature_max': '28'}, {'city': 'Paris', 'temperature_max': '26'}]
======== AGENT ONLY========
Set LangChain Debug: False
1. Load thhe environment variables
{'project_id': 'YOUR_PROJECT', 'url': 'https://eu-de.ml.cloud.ibm.com', 'model_id': 'mistralai/mixtral-8x7b-instruct-v01', 'apikey': 'YOUR_IBMCLOUD_KEY'}
2. Defined tools for langchain.tools.
- The type to the tools:
- The tools list:
[StructuredTool(name='current_temperature', description='provides the current temperature information for given cities. \n Args:\n cities: The parameter cities is a list e.g. ["LA", "NY"].', args_schema=, func=)]
3. Define the model parameters
{'decoding_method': 'greedy', 'max_new_tokens': 400, 'min_new_tokens': 1, 'temperature': 1.0}
4. Create a ChatWatsonx instance for mistralai/mixtral-8x7b-instruct-v01, and not a WatsonxLLM, because to this instance a tool can't be bind.
5. Define a prompt using a ChatPromptTemplate.
-Prompt Template:
input_variables=['input'] optional_variables=['agent_scratchpad', 'chat_history'] input_types={'chat_history': typing.List[typing.Union[langchain_core.messages.ai.AIMessage, langchain_core.messages.human.HumanMessage, langchain_core.messages.chat.ChatMessage, langchain_core.messages.system.SystemMessage, langchain_core.messages.function.FunctionMessage, langchain_core.messages.tool.ToolMessage]], 'agent_scratchpad': typing.List[typing.Union[langchain_core.messages.ai.AIMessage, langchain_core.messages.human.HumanMessage, langchain_core.messages.chat.ChatMessage, langchain_core.messages.system.SystemMessage, langchain_core.messages.function.FunctionMessage, langchain_core.messages.tool.ToolMessage]]} partial_variables={'chat_history': [], 'agent_scratchpad': []} messages=[SystemMessagePromptTemplate(prompt=PromptTemplate(input_variables=[], template="You are a weather expert. If the question is not about the weather, say: I don't know.")), MessagesPlaceholder(variable_name='chat_history', optional=True), HumanMessagePromptTemplate(prompt=PromptTemplate(input_variables=['input'], template='{input}')), MessagesPlaceholder(variable_name='agent_scratchpad', optional=True)]
6. Create a tool calling agent based on parameters: the watsonx_chat_with_tools, the tool, and the prompt.
7. Create an AgentExecutor.
8. Execute the agent using the AgentExecutor by providing a question as input to invoke the model.
> Entering new AgentExecutor chain...
```json
{
"type": "function",
"function": {
"name": "current_temperature",
"arguments": {
"cities": ["LA", "NY"]
}
}
}
```
> Finished chain.
> Entering new AgentExecutor chain...
```json
{
"type": "function",
"function": {
"name": "current_temperature",
"arguments": {
"cities": ["Berlin"]
}
}
}
```
> Finished chain.
> Entering new AgentExecutor chain...
```json
{
"type": "function",
"function": {
"name": "Final Answer",
"arguments": {
"output": "I don't know."
}
}
}
> Finished chain.
> Entering new AgentExecutor chain...
```json
{
"type": "function",
"function": {
"name": "Final Answer",
"arguments": {
"output": "The term 'weather' refers to the state of the atmosphere at a particular place and time, with respect to temperature, humidity, cloudiness, wind, and atmospheric pressure."
}
}
}
```
> Finished chain.
9. Results
| agent question | agent anwser |
|----------------------------------------------------|----------------------------------------------------|
|Which city is hotter today: LA or NY?_______________|function:current_temperature________________________|
|What is the temperature today in Berlin?____________|function:current_temperature________________________|
|How to win a soccer game?___________________________|function:Final Answer_______________________________|
|What is the official definition of the term weather?|function:Final Answer_______________________________|
```