Ollama Fails When Tools Use Optional Args
Introduction
Ollama is a powerful tool for generating text based on user input. However, when using Ollama with the model llama3.1, users may encounter an error related to optional arguments. In this article, we will explore the issue and provide a solution to resolve the problem.
Understanding the Error
The error message indicates that there is a KeyError
when trying to access the 'type'
key in the prop_schema
dictionary. This error occurs in the _process_create_args
method of the _ollama_client
class.
create_params = self._process_create_args(
# ...
)
The _process_create_args
method calls the convert_tools
function to convert the tools
argument into a format that can be used by Ollama.
converted_tools = convert_tools(tools)
The convert_tools
function is responsible for converting the tools
argument into a format that can be used by Ollama. However, when the tools
argument contains optional arguments, the convert_tools
function fails to convert them correctly, resulting in a KeyError
.
The Root Cause of the Issue
The root cause of the issue is related to the way Ollama handles optional arguments. When using Ollama with the model llama3.1, the tools
argument may contain optional arguments that are not present in the prop_schema
dictionary. In this case, the convert_tools
function fails to convert the optional arguments correctly, resulting in a KeyError
.
The Solution
To resolve the issue, we need to modify the convert_tools
function to handle optional arguments correctly. We can do this by adding a check to see if the optional argument is present in the prop_schema
dictionary before trying to access it.
def convert_tools(tools):
converted_tools = []
for tool in tools:
if 'type' in tool:
converted_tools.append(tool)
elif 'optional' in tool and tool['optional']:
# Handle optional arguments correctly
if 'type' in tool['optional']:
converted_tools.append(tool)
return converted_tools
Modifying the Ollama Client
To apply the solution, we need to modify the Ollama client to use the modified convert_tools
function. We can do this by updating the _process_create_args
method to use the modified convert_tools
function.
def _process_create_args(self, tools):
converted_tools = convert_tools(tools)
# ...
Conclusion
In conclusion, the issue with Ollama failing when tools use optional args is related to the way Ollama handles optional arguments. By modifying the convert_tools
function to handle optional arguments correctly, we can resolve the issue and use Ollama with the model llama3.1 without encountering errors.
Additional Information
For more information on the issue, please refer to the following GitHub pull request:
Related Issues
Commit Message
- "Modify convert_tools function to handle optional arguments correctly"
API Documentation
Troubleshooting
- If you encounter the same issue, please check the
prop_schema
dictionary to ensure that it contains the required keys. - If the issue persists, please try modifying the
convert_tools
function to handle optional arguments correctly. - If you are still experiencing issues, please refer to the GitHub pull request for more information.
Ollama Fails When Tools Use Optional Args: Q&A =====================================================
Introduction
In our previous article, we explored the issue of Ollama failing when tools use optional args. We discussed the root cause of the issue and provided a solution to resolve the problem. In this article, we will answer some frequently asked questions related to the issue.
Q: What is the root cause of the issue?
A: The root cause of the issue is related to the way Ollama handles optional arguments. When using Ollama with the model llama3.1, the tools
argument may contain optional arguments that are not present in the prop_schema
dictionary. In this case, the convert_tools
function fails to convert the optional arguments correctly, resulting in a KeyError
.
Q: How can I resolve the issue?
A: To resolve the issue, you need to modify the convert_tools
function to handle optional arguments correctly. You can do this by adding a check to see if the optional argument is present in the prop_schema
dictionary before trying to access it.
Q: What is the modified convert_tools
function?
A: The modified convert_tools
function is as follows:
def convert_tools(tools):
converted_tools = []
for tool in tools:
if 'type' in tool:
converted_tools.append(tool)
elif 'optional' in tool and tool['optional']:
# Handle optional arguments correctly
if 'type' in tool['optional']:
converted_tools.append(tool)
return converted_tools
Q: How can I apply the solution?
A: To apply the solution, you need to modify the Ollama client to use the modified convert_tools
function. You can do this by updating the _process_create_args
method to use the modified convert_tools
function.
Q: What are the benefits of the solution?
A: The benefits of the solution are:
- Resolves the issue of Ollama failing when tools use optional args
- Improves the reliability of the Ollama client
- Enhances the overall user experience
Q: Are there any related issues?
A: Yes, there are related issues that you may encounter. Please refer to the following GitHub issues:
Q: How can I troubleshoot the issue?
A: To troubleshoot the issue, please follow these steps:
- Check the
prop_schema
dictionary to ensure that it contains the required keys. - If the issue persists, please try modifying the
convert_tools
function to handle optional arguments correctly. - If you are still experiencing issues, please refer to the GitHub pull request for more information.
Q: What is the commit message for the solution?
A: The commit message for the solution is:
- "Modify convert_tools function to handle optional arguments correctly"
Q: Where can I find more information on the issue?
A: You can find more information on the by referring to the following resources:
- https://github.com/microsoft/autogen/pull/6343/files
- https://docs.microsoft.com/en-us/autogen/api/ollama
Conclusion
In conclusion, the issue of Ollama failing when tools use optional args is a common problem that can be resolved by modifying the convert_tools
function to handle optional arguments correctly. We hope that this Q&A article has provided you with the information you need to resolve the issue and improve the reliability of the Ollama client.