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openai can give multiple tool calls, current implementation assumes only one function call at a time. Fixed this to handle multiple function calls.

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This commit is contained in:
JeevanReddy
2024-08-07 13:07:18 +05:30
committed by Kwindla Hultman Kramer
parent 5d63615b1b
commit def04ac0ce
1 changed files with 27 additions and 6 deletions
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33
src/pipecat/services/openai.py
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@@ -205,6 +205,10 @@ class BaseOpenAILLMService(LLMService):
return chunks return chunks
async def _process_context(self, context: OpenAILLMContext): async def _process_context(self, context: OpenAILLMContext):
functions_list = []
arguments_list = []
tool_id_list = []
func_idx = 0
function_name = "" function_name = ""
arguments = "" arguments = ""
tool_call_id = "" tool_call_id = ""
@@ -242,6 +246,14 @@ class BaseOpenAILLMService(LLMService):
# yield a frame containing the function name and the arguments. # yield a frame containing the function name and the arguments.
tool_call = chunk.choices[0].delta.tool_calls[0] tool_call = chunk.choices[0].delta.tool_calls[0]
if tool_call.index != func_idx:
functions_list.append(function_name)
arguments_list.append(arguments)
tool_id_list.append(tool_call_id)
function_name = ""
arguments = ""
tool_call_id = ""
func_idx += 1
if tool_call.function and tool_call.function.name: if tool_call.function and tool_call.function.name:
function_name += tool_call.function.name function_name += tool_call.function.name
tool_call_id = tool_call.id tool_call_id = tool_call.id
@@ -257,12 +269,21 @@ class BaseOpenAILLMService(LLMService):
# the context, and re-prompt to get a chat answer. If we don't have a registered # the context, and re-prompt to get a chat answer. If we don't have a registered
# handler, raise an exception. # handler, raise an exception.
if function_name and arguments: if function_name and arguments:
if self.has_function(function_name): # added to the list as last function name and arguments not added to the list
await self._handle_function_call(context, tool_call_id, function_name, arguments) functions_list.append(function_name)
else: arguments_list.append(arguments)
raise OpenAIUnhandledFunctionException( tool_id_list.append(tool_call_id)
f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function." for function_name, arguments, tool_id in zip(
) functions_list, arguments_list, tool_id_list
):
if self.has_function(function_name):
await self._handle_function_call(context, tool_id, function_name, arguments)
else:
raise OpenAIUnhandledFunctionException(
f"The LLM tried to call a function named '{function_name}', but there isn't a callback registered for that function."
)
# re-prompt to get a human answer after all the functions are called
await self._process_context(context)
async def _handle_function_call(self, context, tool_call_id, function_name, arguments): async def _handle_function_call(self, context, tool_call_id, function_name, arguments):
arguments = json.loads(arguments) arguments = json.loads(arguments)