Tool calling issues with vllm

[Navanit-git]

Hi,
Is there a way where we can add the vLLM OpenAI compatibility support.
vllm OpenAI Support

So that anyone can use any llm model calls.

[samuelcolvin]

Should work the same as ollama, see the code here - #112 (comment).

Happy to consider adding vllm as another custom model, but it would need more people to want it before we do the work.

[samuelcolvin]

See #239, that would mean we could add VLLMModel.

[daavoo]

See #239, that would mean we could add VLLMModel.

Ola! I was testing pydantic.ai alongside vLLM and llama.cpp server, which I think both fulfill the rules for adding a new model.

I have looked at the existing Ollama code and I am not sure I understand the value of adding a new VLLMModel.
Looks like there is no custom logic (beyond providing a default api_key value) and provides an ~arbitrary hardcoded list of model names (which don't cover all available models)

I got this same snippet working with both vLLM and llama.cpp server out of the box:

# For example with llama.cpp:
docker run -v ./models:/models -p 8080:8080 \
ghcr.io/ggerganov/llama.cpp:server -m /models/smollm2-360m-instruct-q8_0.gguf

from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIModel

model = OpenAIModel(
    "mymodel", 
    base_url="http://localhost:8080/v1", 
    api_key="foo"
)

agent = Agent(  
    model=model,
    system_prompt='Be concise, reply with one sentence.',  
)

result = agent.run_sync('Where does "hello world" come from?')  
print(result.data)

So, is it better to just send a small documentation patch?

pd. I don't have a problem on contributing a new VLLM/LLAMACPP model myself, just wondering if it makes sense to keep adding those

[sadransh]

@daavoo This wouldnt work with tool calling and non str result type. you can re-use the example from here: to double check #398

[lys791227]

@daavoo This wouldnt work with tool calling and non str result type. you can re-use the example from here: to double check #398

I also same.

[guang11644331]

from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIModel

model = OpenAIModel(
model_name="qwen25",
base_url="http://192.168.xx.xx:8090/v1",
api_key="1"
)

agent = Agent(
model=model,
)

result = agent.run_sync('hello')
print(result.data)

it's work

[lys791227]

from pydantic_ai import Agent from pydantic_ai.models.openai import OpenAIModel

model = OpenAIModel( model_name="qwen25", base_url="http://192.168.xx.xx:8090/v1", api_key="1" )

agent = Agent( model=model, )

result = agent.run_sync('hello') print(result.data)

it's work
Do you call tool try?should not !

[iabgcb]

Does not work with tool calling, excluding which there is no reason for enterprises/retail hosting their own quantized
models to use this framework. so please VLLM compatibility ASAP

[maziyarpanahi]

Obviously, it works for some basic use that doesn't require tool selection, but even a simple code like this fails with vLLM:

from pydantic import BaseModel

from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIModel

model = OpenAIModel(
   model_name="qwen25",
   base_url="http://192.168.xx.xx:8090/v1",
   api_key="1"
)

class CityLocation(BaseModel):
    city: str
    country: str

agent = Agent(model=model, result_type=CityLocation)

result = agent.run_sync('Where were the olympics held in 2012?')
print(result.data)
print(result.usage())

error (tool_choice must either be a named tool, "auto", or "none")

openai.BadRequestError: Error code: 400 - {'object': 'error', 'message': '[{\'type\': \'value_error\', \'loc\': (\'body\',), \'msg\': \'Value error, `tool_choice` must either be a named tool, "auto", or "none".\', \'input\': {\'messages\': [{\'role\': \'user\', \'content\': \'Where were the olympics held in 2012?\'}], \'model\': \'arcee-train/arcee-virtuoso-maz-10b-v2\', \'n\': 1, \'parallel_tool_calls\': True, \'stream\': False, \'tool_choice\': \'required\', \'tools\': [{\'type\': \'function\', \'function\': {\'name\': \'final_result\', \'description\': \'The final response which ends this conversation\', \'parameters\': {\'properties\': {\'city\': {\'title\': \'City\', \'type\': \'string\'}, \'country\': {\'title\': \'Country\', \'type\': \'string\'}}, \'required\': [\'city\', \'country\'], \'title\': \'CityLocation\', \'type\': \'object\'}}}]}, \'ctx\': {\'error\': ValueError(\'`tool_choice` must either be a named tool, "auto", or "none".\')}}]', 'type': 'BadRequestError', 'param': None, 'code': 400}

[iabgcb]

exactly the same error i receive. It simply does not work with vllm.

[nihilimbo]

I can confirm the sample code from @maziyarpanahi comment fails on my dev box with a "tool_choice must either be a named tool, auto, or none" error when run against a vLLM (v0.6.6.post1) instance of meta-llama/Llama-3.3-70B-Instruct.

However, same code works fine against an Ollama instance (on same machine) of llama3.1:8b.

[myyang19770915]

Yes , I use vllm model, and get the same tool calling problems.
please add this work in this project !
thanks