Griptape is a versatile Python framework designed for building AI agents and workflows, featuring chain-of-thought reasoning, integrated tools, and memory capabilities. It helps developers to create intelligent applications with ease.
claude install griptape-ai/griptapehttps://docs.griptape.ai/
["1. Identify the specific task you want the Griptape agent to perform. Be as detailed as possible about the goal and the steps needed to achieve it.","2. Choose the appropriate tools for the task. Griptape supports a variety of tools, including web search, database queries, and API calls.","3. Write the Python code to create the agent. Include the tools and any necessary memory or reasoning capabilities.","4. Define the task for the agent. This should be a clear, concise statement of what you want the agent to accomplish.","5. Run the agent and review the results. Use the output to refine the agent's task or tools as needed."]
Build custom AI workflows that automate repetitive tasks and improve efficiency.
Integrate memory capabilities into AI applications to enhance user interactions and personalization.
Implement chain-of-thought reasoning in AI agents to improve decision-making processes.
Create modular AI solutions that can be easily adapted and extended for various applications.
claude install griptape-ai/griptapegit clone https://github.com/griptape-ai/griptapeCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Create a Griptape agent that can [SPECIFIC TASK]. The agent should use [TOOLS] to accomplish this. Include a chain-of-thought reasoning process and memory to track progress. Provide the Python code to implement this agent.
Here's a Griptape agent that automates market research for a new product launch. This agent uses web search tools to gather information, analyzes competitor pricing, and suggests optimal pricing strategies based on the data. The agent includes memory to track previous searches and reasoning to justify its recommendations.
```python
from griptape.artifacts import TextArtifact
from griptape.drivers import WebDriver
from griptape.agents import Agent
from griptape.memory import Memory
# Initialize memory
memory = Memory()
# Initialize web driver
web_driver = WebDriver()
# Create agent
agent = Agent(
name="Market Research Agent",
tools=[web_driver],
memory=memory
)
# Define the task
agent.task(
"Research the market for [PRODUCT]. Find competitor pricing and suggest optimal pricing strategies."
)
# Run the agent
agent.run()
# Output the results
results = agent.get_results()
for result in results:
print(result)
```
The agent will output a detailed market analysis, including competitor pricing and suggested strategies for optimal pricing.Simplify sustainable farming
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