Skip to content

feat: Add 10 new agents to Kimi2_Intelligent_Agents (aerospace, bioinformatics, blockchain, energy, IoT, metaverse, nanotechnology, quantum AI, quantum computing, robotics) #948

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

feat: Add 10 new agents to Kimi2_Intelligent_Agents (aerospace, bioinformatics, blockchain, energy, IoT, metaverse, nanotechnology, quantum AI, quantum computing, robotics) #948

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/aerospace_engineering_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are an aerospace engineering AI agent. "
"Help users understand aerospace engineering concepts, "
"aircraft design, and space technology. Provide guidance on "
"aerodynamics, propulsion systems, materials science, "
"and satellite technology.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your aerospace engineering assistant. "
"How can I help you with aerospace engineering "
"and space technology today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are an aerospace engineering AI agent. "
"Help users understand aerospace engineering concepts, "
"aircraft design, and space technology. Provide guidance on "
"aerodynamics, propulsion systems, materials science, "
"and satellite technology.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your aerospace engineering assistant. "
"How can I help you with aerospace engineering "
"and space technology today?")
def main():
agent = Agent(
instructions="You are an aerospace engineering AI agent. "
"Help users understand aerospace engineering concepts, "
"aircraft design, and space technology. Provide guidance on "
"aerodynamics, propulsion systems, materials science, "
"and satellite technology.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your aerospace engineering assistant. "
"How can I help you with aerospace engineering "
"and space technology today?")
print(response)
if __name__ == "__main__":
main()

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/bioinformatics_genomics_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a bioinformatics and genomics AI agent. "
"Help users understand bioinformatics, genomics, "
"and computational biology. Provide guidance on "
"DNA sequence analysis, protein structure prediction, "
"genetic algorithms, and biological data mining.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your bioinformatics and genomics assistant. "
"How can I help you with bioinformatics "
"and genomics research today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a bioinformatics and genomics AI agent. "
"Help users understand bioinformatics, genomics, "
"and computational biology. Provide guidance on "
"DNA sequence analysis, protein structure prediction, "
"genetic algorithms, and biological data mining.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your bioinformatics and genomics assistant. "
"How can I help you with bioinformatics "
"and genomics research today?")
def main():
agent = Agent(
instructions="You are a bioinformatics and genomics AI agent. "
"Help users understand bioinformatics, genomics, "
"and computational biology. Provide guidance on "
"DNA sequence analysis, protein structure prediction, "
"genetic algorithms, and biological data mining.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your bioinformatics and genomics assistant. "
"How can I help you with bioinformatics "
"and genomics research today?")
print(response)
if __name__ == "__main__":
main()

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/blockchain_defi_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a blockchain and DeFi AI agent. "
"Help users understand blockchain technology, "
"decentralized finance, and cryptocurrency. Provide guidance on "
"smart contract development, DeFi protocols, "
"tokenomics, and blockchain security.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your blockchain and DeFi assistant. "
"How can I help you explore blockchain technology "
"and decentralized finance today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a blockchain and DeFi AI agent. "
"Help users understand blockchain technology, "
"decentralized finance, and cryptocurrency. Provide guidance on "
"smart contract development, DeFi protocols, "
"tokenomics, and blockchain security.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your blockchain and DeFi assistant. "
"How can I help you explore blockchain technology "
"and decentralized finance today?")
def main():
agent = Agent(
instructions="You are a blockchain and DeFi AI agent. "
"Help users understand blockchain technology, "
"decentralized finance, and cryptocurrency. Provide guidance on "
"smart contract development, DeFi protocols, "
"tokenomics, and blockchain security.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your blockchain and DeFi assistant. "
"How can I help you explore blockchain technology "
"and decentralized finance today?")
print(response)
if __name__ == "__main__":
main()

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/energy_renewables_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are an energy and renewables AI agent. "
"Help users understand renewable energy technologies, "
"energy systems, and sustainability. Provide guidance on "
"solar power, wind energy, energy storage, "
"and green technology solutions.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your energy and renewables assistant. "
"How can I help you with renewable energy "
"and sustainability today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are an energy and renewables AI agent. "
"Help users understand renewable energy technologies, "
"energy systems, and sustainability. Provide guidance on "
"solar power, wind energy, energy storage, "
"and green technology solutions.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your energy and renewables assistant. "
"How can I help you with renewable energy "
"and sustainability today?")
def main():
agent = Agent(
instructions="You are an energy and renewables AI agent. "
"Help users understand renewable energy technologies, "
"energy systems, and sustainability. Provide guidance on "
"solar power, wind energy, energy storage, "
"and green technology solutions.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your energy and renewables assistant. "
"How can I help you with renewable energy "
"and sustainability today?")
print(response)
if __name__ == "__main__":
main()

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/iot_smart_cities_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are an IoT and smart cities AI agent. "
"Help users understand Internet of Things, smart city "
"technologies, and connected systems. Provide guidance on "
"IoT device integration, smart infrastructure, "
"sensor networks, and urban technology solutions.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your IoT and smart cities assistant. "
"How can I help you with IoT and smart city "
"technologies today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are an IoT and smart cities AI agent. "
"Help users understand Internet of Things, smart city "
"technologies, and connected systems. Provide guidance on "
"IoT device integration, smart infrastructure, "
"sensor networks, and urban technology solutions.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your IoT and smart cities assistant. "
"How can I help you with IoT and smart city "
"technologies today?")
def main():
agent = Agent(
instructions="You are an IoT and smart cities AI agent. "
"Help users understand Internet of Things, smart city "
"technologies, and connected systems. Provide guidance on "
"IoT device integration, smart infrastructure, "
"sensor networks, and urban technology solutions.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your IoT and smart cities assistant. "
"How can I help you with IoT and smart city "
"technologies today?")
print(response)
if __name__ == "__main__":
main()

Comment on lines +1 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

🛠️ Refactor suggestion

Consistent implementation with IoT-specific domain expertise.

The IoT and smart cities instructions effectively cover the domain including device integration, sensor networks, and urban technology solutions. The implementation maintains consistency with the established pattern.

Since all agent files share the same structure and issues, consider implementing a factory pattern or base configuration to reduce code duplication across the entire agent collection.

Consider creating a shared agent factory to reduce duplication:

# agent_factory.py
from praisonaiagents import Agent

def create_domain_agent(domain_name, instructions, greeting_message):
    """Factory function to create domain-specific agents with consistent error handling."""
    try:
        agent = Agent(
            instructions=instructions,
            llm="openrouter/moonshotai/kimi-k2"
        )
        response = agent.start(greeting_message)
        print(response)
        return agent
    except Exception as e:
        print(f"Error initializing {domain_name} agent: {e}")
        return None

Then use it in each agent file:

from agent_factory import create_domain_agent

agent = create_domain_agent(
    "IoT and Smart Cities",
    "You are an IoT and smart cities AI agent. ...",
    "Hello! I'm your IoT and smart cities assistant. ..."
)
🤖 Prompt for AI Agents 
In
examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/iot_smart_cities_agent.py
lines 1 to 14, the agent initialization code duplicates the pattern used across
multiple agent files. To reduce code duplication and improve maintainability,
refactor by creating a shared factory function (e.g., in agent_factory.py) that
accepts domain-specific parameters like instructions and greeting messages,
handles agent creation and error management, and returns the initialized agent.
Then update this file to use that factory function for cleaner, consistent agent
setup.

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/metaverse_vr_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a metaverse and virtual reality AI agent. "
"Help users understand metaverse concepts, VR development, "
"and immersive technologies. Provide guidance on "
"3D modeling, VR programming, digital twins, "
"and virtual world design.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your metaverse and VR assistant. "
"How can I help you explore the metaverse "
"and virtual reality today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a metaverse and virtual reality AI agent. "
"Help users understand metaverse concepts, VR development, "
"and immersive technologies. Provide guidance on "
"3D modeling, VR programming, digital twins, "
"and virtual world design.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your metaverse and VR assistant. "
"How can I help you explore the metaverse "
"and virtual reality today?")
def main():
agent = Agent(
instructions="You are a metaverse and virtual reality AI agent. "
"Help users understand metaverse concepts, VR development, "
"and immersive technologies. Provide guidance on "
"3D modeling, VR programming, digital twins, "
"and virtual world design.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your metaverse and VR assistant. "
"How can I help you explore the metaverse "
"and virtual reality today?")
print(response)
if __name__ == "__main__":
main()

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/nanotechnology_materials_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a nanotechnology and materials AI agent. "
"Help users understand nanotechnology, advanced materials, "
"and material science. Provide guidance on "
"nanomaterials, material properties, fabrication techniques, "
"and applications in various industries.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your nanotechnology and materials assistant. "
"How can I help you with nanotechnology "
"and materials science today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a nanotechnology and materials AI agent. "
"Help users understand nanotechnology, advanced materials, "
"and material science. Provide guidance on "
"nanomaterials, material properties, fabrication techniques, "
"and applications in various industries.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your nanotechnology and materials assistant. "
"How can I help you with nanotechnology "
"and materials science today?")
def main():
agent = Agent(
instructions="You are a nanotechnology and materials AI agent. "
"Help users understand nanotechnology, advanced materials, "
"and material science. Provide guidance on "
"nanomaterials, material properties, fabrication techniques, "
"and applications in various industries.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your nanotechnology and materials assistant. "
"How can I help you with nanotechnology "
"and materials science today?")
print(response)
if __name__ == "__main__":
main()

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/quantum_ai_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a quantum AI agent. "
"Help users understand quantum artificial intelligence, "
"quantum machine learning, and quantum neural networks. "
"Provide guidance on quantum algorithms for AI, "
"quantum optimization, and hybrid quantum-classical systems.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your quantum AI assistant. "
"How can I help you explore quantum artificial "
"intelligence today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a quantum AI agent. "
"Help users understand quantum artificial intelligence, "
"quantum machine learning, and quantum neural networks. "
"Provide guidance on quantum algorithms for AI, "
"quantum optimization, and hybrid quantum-classical systems.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your quantum AI assistant. "
"How can I help you explore quantum artificial "
"intelligence today?")
def main():
agent = Agent(
instructions="You are a quantum AI agent. "
"Help users understand quantum artificial intelligence, "
"quantum machine learning, and quantum neural networks. "
"Provide guidance on quantum algorithms for AI, "
"quantum optimization, and hybrid quantum-classical systems.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your quantum AI assistant. "
"How can I help you explore quantum artificial "
"intelligence today?")
print(response)
if __name__ == "__main__":
main()

Comment on lines +1 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

💡 Verification agent

🧩 Analysis chain

Verify LLM model availability and consider improvements.

The implementation follows the correct pattern using the Agent class from praisonaiagents. However, there are several areas for improvement:

  1. Model validation: Ensure the LLM model "openrouter/moonshotai/kimi-k2" is valid and accessible
  2. Unused response: The response variable is assigned but never used
  3. Missing error handling: No exception handling around agent creation or startup

Consider these improvements:

 from praisonaiagents import Agent

-agent = Agent(
-    instructions="You are a quantum AI agent. "
-                "Help users understand quantum artificial intelligence, "
-                "quantum machine learning, and quantum neural networks. "
-                "Provide guidance on quantum algorithms for AI, "
-                "quantum optimization, and hybrid quantum-classical systems.",
-    llm="openrouter/moonshotai/kimi-k2"
-)
+try:
+    agent = Agent(
+        instructions="You are a quantum AI agent. "
+                    "Help users understand quantum artificial intelligence, "
+                    "quantum machine learning, and quantum neural networks. "
+                    "Provide guidance on quantum algorithms for AI, "
+                    "quantum optimization, and hybrid quantum-classical systems.",
+        llm="openrouter/moonshotai/kimi-k2"
+    )
+    
+    response = agent.start("Hello! I'm your quantum AI assistant. "
+                          "How can I help you explore quantum artificial "
+                          "intelligence today?")
+    print(response)  # Actually use the response
+except Exception as e:
+    print(f"Error initializing quantum AI agent: {e}")
-
-response = agent.start("Hello! I'm your quantum AI assistant. "
-                      "How can I help you explore quantum artificial "
-                      "intelligence today?")

🌐 Web query:

Is "openrouter/moonshotai/kimi-k2" a valid LLM model available through the OpenRouter API?

💡 Result:

Yes, "openrouter/moonshotai/kimi-k2" is a valid LLM model available through the OpenRouter API. The correct model identifier you should use in your API calls is moonshotai/kimi-k2 (not "openrouter/moonshotai/kimi-k2"; drop the "openrouter/" prefix when specifying the model name in requests)[1][4][10].

Key details:

  • moonshotai/kimi-k2 refers specifically to the Kimi K2 model provided by Moonshot AI, a state-of-the-art 1 trillion parameter Mixture-of-Experts language model[1][6][10].
  • Available on OpenRouter: You can access this model via OpenRouter’s API endpoint (https://openrouter.ai/api/v1/chat/completions), specifying "model": "moonshotai/kimi-k2" in your OpenAI-compatible request body[1][4][10].
  • Documentation and guides, including third-party integrations, reference this exact model name and endpoint, and provide working code examples[1][4][8][10].

For example, an API request targeting Kimi K2 would look like this in Python (using the OpenAI SDK, with a custom API base URL):

import openai

client = openai.OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_OPENROUTER_API_KEY",
)

response = client.chat.completions.create(
    model="moonshotai/kimi-k2",
    messages=[
        {"role": "system", "content": "You are Kimi, an AI assistant created by Moonshot AI."},
        {"role": "user", "content": "Write a short story about a robot who discovers music."},
    ],
)

print(response.choices[0].message.content)

[1][4][10]

Summary:

  • The model is correctly specified as moonshotai/kimi-k2 on OpenRouter, not "openrouter/moonshotai/kimi-k2"[1][4][10].
  • It is a live, officially supported model accessible by developers for chat/completion tasks using the standard OpenAI-compatible API.

Citations:

Update LLM identifier, use the response, and add error handling

The model "openrouter/moonshotai/kimi-k2" is valid on OpenRouter, but when calling the API you should drop the "openrouter/" prefix and use "moonshotai/kimi-k2". Also, the response is never used and there’s no error handling around your agent calls.

File: examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/quantum_ai_agent.py

Changes needed:

  • Correct the model name to "moonshotai/kimi-k2"
  • Wrap agent creation and startup in a try/except
  • Actually use (e.g. print) the response
 from praisonaiagents import Agent

- agent = Agent(
-     instructions="You are a quantum AI agent. "
-                 "Help users understand quantum artificial intelligence, "
-                 "quantum machine learning, and quantum neural networks. "
-                 "Provide guidance on quantum algorithms for AI, "
-                 "quantum optimization, and hybrid quantum-classical systems.",
-     llm="openrouter/moonshotai/kimi-k2"
- )
-
- response = agent.start("Hello! I'm your quantum AI assistant. "
-                       "How can I help you explore quantum artificial "
-                       "intelligence today?")
+try:
+    agent = Agent(
+        instructions="You are a quantum AI agent. "
+                    "Help users understand quantum artificial intelligence, "
+                    "quantum machine learning, and quantum neural networks. "
+                    "Provide guidance on quantum algorithms for AI, "
+                    "quantum optimization, and hybrid quantum-classical systems.",
+        llm="moonshotai/kimi-k2"
+    )
+
+    response = agent.start(
+        "Hello! I'm your quantum AI assistant. "
+        "How can I help you explore quantum artificial intelligence today?"
+    )
+    print(response)  # Use the agent’s response
+except Exception as e:
+    print(f"Error initializing quantum AI agent: {e}")
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
from praisonaiagents import Agent
agent = Agent(
instructions="You are a quantum AI agent. "
"Help users understand quantum artificial intelligence, "
"quantum machine learning, and quantum neural networks. "
"Provide guidance on quantum algorithms for AI, "
"quantum optimization, and hybrid quantum-classical systems.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your quantum AI assistant. "
"How can I help you explore quantum artificial "
"intelligence today?")
from praisonaiagents import Agent
try:
agent = Agent(
instructions="You are a quantum AI agent. "
"Help users understand quantum artificial intelligence, "
"quantum machine learning, and quantum neural networks. "
"Provide guidance on quantum algorithms for AI, "
"quantum optimization, and hybrid quantum-classical systems.",
llm="moonshotai/kimi-k2"
)
response = agent.start(
"Hello! I'm your quantum AI assistant. "
"How can I help you explore quantum artificial intelligence today?"
)
print(response) # Use the agent’s response
except Exception as e:
print(f"Error initializing quantum AI agent: {e}")
🤖 Prompt for AI Agents 
In examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/quantum_ai_agent.py
lines 1 to 14, update the LLM identifier by removing the "openrouter/" prefix so
it reads "moonshotai/kimi-k2". Wrap the agent creation and the call to
agent.start in a try/except block to handle potential errors gracefully.
Finally, use the response variable by printing it or otherwise outputting it to
ensure the result is utilized.

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/quantum_computing_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a quantum computing AI agent. "
"Help users understand quantum computing concepts, "
"quantum algorithms, and quantum programming. Provide guidance on "
"quantum circuit design, quantum error correction, "
"quantum machine learning, and quantum cryptography.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your quantum computing assistant. "
"How can I help you explore quantum computing "
"and quantum programming today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a quantum computing AI agent. "
"Help users understand quantum computing concepts, "
"quantum algorithms, and quantum programming. Provide guidance on "
"quantum circuit design, quantum error correction, "
"quantum machine learning, and quantum cryptography.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your quantum computing assistant. "
"How can I help you explore quantum computing "
"and quantum programming today?")
def main():
agent = Agent(
instructions="You are a quantum computing AI agent. "
"Help users understand quantum computing concepts, "
"quantum algorithms, and quantum programming. Provide guidance on "
"quantum circuit design, quantum error correction, "
"quantum machine learning, and quantum cryptography.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your quantum computing assistant. "
"How can I help you explore quantum computing "
"and quantum programming today?")
print(response)
if __name__ == "__main__":
main()

Comment on lines +1 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

💡 Verification agent

🧩 Analysis chain

Comprehensive quantum computing agent with advanced topic coverage

The instructions effectively cover sophisticated quantum computing topics including quantum algorithms, circuit design, error correction, machine learning, and cryptography. This completes the consistent pattern across all specialized agents.

This agent follows the same implementation pattern as the other specialized agents. Given the specialized nature of quantum computing, consider verifying that the chosen LLM model has adequate knowledge in this domain:

The same improvement suggestions apply: handle the unused response variable and add error handling as demonstrated in the aerospace engineering agent review.

🏁 Script executed:

#!/bin/bash
# Check if there are any existing quantum computing examples or tests in the repository
echo "Searching for existing quantum computing references..."
rg -i "quantum" --type py -A 3 -B 3

echo "Searching for LLM model references..."
rg "openrouter/moonshotai/kimi-k2" --type py -A 2 -B 2

Length of output: 32443

Quantum computing agent: verify LLM choice and add response handling

There’s strong quantum‐computing coverage in this agent (and across the repo—tests, use-cases, tools), but we should ensure the LLM has the required domain expertise. Also, the example code currently assigns response without using it and lacks error handling.

Files to update:

  • examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/quantum_computing_agent.py
    • Verify that openrouter/moonshotai/kimi-k2 performs well on quantum topics (see existing quantum references in tests and examples).
    • Handle the response (e.g., print or further process it).
    • Wrap the agent.start(...) call in a try/except block.

Suggested diff:

-agent = Agent(
+agent = Agent(
     instructions="You are a quantum computing AI agent. "
                 "Help users understand quantum computing concepts, "
                 "quantum algorithms, and quantum programming. Provide guidance on "
                 "quantum circuit design, quantum error correction, "
                 "quantum machine learning, and quantum cryptography.",
     llm="openrouter/moonshotai/kimi-k2"
 )
 
-response = agent.start("Hello! I'm your quantum computing assistant. "
-                      "How can I help you explore quantum computing "
-                      "and quantum programming today?")
+try:
+    response = agent.start(
+        "Hello! I'm your quantum computing assistant. "
+        "How can I help you explore quantum computing "
+        "and quantum programming today?"
+    )
+    print(response)
+except Exception as e:
+    print(f"Error during agent execution: {e}")
🤖 Prompt for AI Agents 
In
examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/quantum_computing_agent.py
lines 1 to 14, verify that the LLM "openrouter/moonshotai/kimi-k2" is suitable
for quantum computing topics by checking existing tests or documentation. Then,
wrap the agent.start call in a try/except block to handle potential errors
gracefully. Finally, ensure the response variable is used meaningfully, such as
printing the response or processing it further, instead of just assigning it
without use.

14 changes: 14 additions & 0 deletions examples/python/tools/exa-tool/Kimi2_Intelligent_Agents/robotics_automation_agent.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,14 @@
from praisonaiagents import Agent

agent = Agent(
instructions="You are a robotics and automation AI agent. "
"Help users understand robotics, automation systems, "
"and industrial applications. Provide guidance on "
"robot programming, automation workflows, "
"sensor integration, and robotic process automation.",
llm="openrouter/moonshotai/kimi-k2"
)

response = agent.start("Hello! I'm your robotics and automation assistant. "
"How can I help you with robotics and "
"automation systems today?")
Comment on lines +3 to +14
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

high

This example script can be improved in a few ways to follow Python best practices and be more useful:

  • Show Output: The response from the agent is never printed, so running the script doesn't show any result.
  • Executable Code Scope: It's standard practice to wrap executable script logic in a main function and call it under an if __name__ == "__main__": guard. This prevents code from running when the file is imported by other modules.
  • Missing Final Newline: The file should end with a newline character as per PEP 8.

The suggested change below addresses all these points.

Suggested change
agent = Agent(
instructions="You are a robotics and automation AI agent. "
"Help users understand robotics, automation systems, "
"and industrial applications. Provide guidance on "
"robot programming, automation workflows, "
"sensor integration, and robotic process automation.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your robotics and automation assistant. "
"How can I help you with robotics and "
"automation systems today?")
def main():
agent = Agent(
instructions="You are a robotics and automation AI agent. "
"Help users understand robotics, automation systems, "
"and industrial applications. Provide guidance on "
"robot programming, automation workflows, "
"sensor integration, and robotic process automation.",
llm="openrouter/moonshotai/kimi-k2"
)
response = agent.start("Hello! I'm your robotics and automation assistant. "
"How can I help you with robotics and "
"automation systems today?")
print(response)
if __name__ == "__main__":
main()

Loading