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refactor(ollama): remove the JSON prompt tool-calling emulation

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With ollama/ tool requests going through /api/chat, nothing reaches the
emulation anymore. The removed block in get_optional_params only ever ran for
ollama (the long != chain was dead after its first == check), and it also
flipped the global litellm.add_function_to_prompt on the first tool request.
function_call_prompt mutated the caller's system message in place, so a
reused message list picked up another copy of the prompt on every turn
This commit is contained in:
Meryem Sakin 2026-09-10 20:55:59 +03:00
parent bf438da481
commit 4f7f73b57e
3 changed files with 0 additions and 76 deletions
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21
litellm/litellm_core_utils/prompt_templates/factory.py
View file

@ -5130,27 +5130,6 @@ def _bedrock_tools_pt(tools: list, model: str | None = None) -> list[BedrockTool
return tool_block_list
# Function call template
def function_call_prompt(messages: list, functions: list):
function_prompt = """Produce JSON OUTPUT ONLY! Adhere to this format {"name": "function_name", "arguments":{"argument_name": "argument_value"}} The following functions are available to you:"""
for function in functions:
function_prompt += f"""\n{function}\n"""
function_added_to_prompt = False
for message in messages:
if "system" in message["role"]:
if isinstance(message["content"], str):
message["content"] += f""" {function_prompt}"""
else:
message["content"].append({"type": "text", "text": f""" {function_prompt}"""})
function_added_to_prompt = True
if function_added_to_prompt is False:
messages.append({"role": "system", "content": f"""{function_prompt}"""})
return messages
def response_schema_prompt(model: str, response_schema: dict) -> str:
"""
Decides if a user-defined custom prompt or default needs to be used

7
litellm/main.py
View file

@ -180,7 +180,6 @@ from .litellm_core_utils.prompt_templates.common_utils import (
)
from .litellm_core_utils.prompt_templates.factory import (
custom_prompt,
function_call_prompt,
map_system_message_pt,
ollama_pt,
prompt_factory,
@ -5467,12 +5466,6 @@ def completion(
provider_config=provider_config,
)
if litellm.add_function_to_prompt and optional_params.get(
"functions_unsupported_model", None
): # if user opts to add it to prompt, when API doesn't support function calling
functions_unsupported_model: Final = optional_params.pop("functions_unsupported_model")
messages = function_call_prompt(messages=messages, functions=functions_unsupported_model)
# For logging - save the values of the litellm-specific params passed in
litellm_params = get_litellm_params(
acompletion=acompletion,

48
litellm/utils.py
View file

@ -4098,54 +4098,6 @@ def pre_process_optional_params(passed_params: dict, non_default_params: dict, c
non_default_params=passed_params, optional_params=optional_params
)
## raise exception if function calling passed in for a provider that doesn't support it
if "functions" in non_default_params or "function_call" in non_default_params or "tools" in non_default_params:
if (
custom_llm_provider == "ollama"
and custom_llm_provider != "text-completion-openai"
and custom_llm_provider != "azure"
and custom_llm_provider != "vertex_ai"
and custom_llm_provider != "anyscale"
and custom_llm_provider != "together_ai"
and custom_llm_provider != "groq"
and custom_llm_provider != "nvidia_nim"
and custom_llm_provider != "cerebras"
and custom_llm_provider != "xai"
and custom_llm_provider != "ai21_chat"
and custom_llm_provider != "volcengine"
and custom_llm_provider != "deepseek"
and custom_llm_provider != "codestral"
and custom_llm_provider != "mistral"
and custom_llm_provider != "anthropic"
and custom_llm_provider != "cohere_chat"
and custom_llm_provider != "cohere"
and custom_llm_provider != "bedrock"
and custom_llm_provider != "ollama_chat"
and custom_llm_provider != "openrouter"
and custom_llm_provider != "vercel_ai_gateway"
and custom_llm_provider != "nebius"
and custom_llm_provider != "wandb"
and custom_llm_provider not in litellm.openai_compatible_providers
):
if custom_llm_provider == "ollama":
# ollama actually supports json output
optional_params["format"] = "json"
litellm.add_function_to_prompt = True # so that main.py adds the function call to the prompt
if "tools" in non_default_params:
optional_params["functions_unsupported_model"] = non_default_params.pop("tools")
non_default_params.pop("tool_choice", None) # causes ollama requests to hang
elif "functions" in non_default_params:
optional_params["functions_unsupported_model"] = non_default_params.pop("functions")
elif litellm.add_function_to_prompt: # if user opts to add it to prompt instead
optional_params["functions_unsupported_model"] = non_default_params.pop(
"tools", non_default_params.pop("functions", None)
)
else:
raise UnsupportedParamsError(
status_code=500,
message=f"Function calling is not supported by {custom_llm_provider}.",
)
return optional_params