@ToolParserManager.register_module("hermes")
class Hermes2ProToolParser(ToolParser):
def __init__(self, tokenizer: AnyTokenizer):
super().__init__(tokenizer)
if isinstance(self.model_tokenizer, MistralTokenizer):
logger.error(
"Detected Mistral tokenizer when using a Hermes model")
self.model_tokenizer = self.model_tokenizer.tokenizer
self.current_tool_name_sent: bool = False
self.prev_tool_call_arr: list[dict] = []
self.current_tool_id: int = -1
self.streamed_args_for_tool: list[str] = [
] # map what has been streamed for each tool so far to a list
self.tool_call_start_token: str = "<tool_call>"
self.tool_call_end_token: str = "</tool_call>"
self.tool_call_regex = re.compile(
r"<tool_call>(.*?)</tool_call>|<tool_call>(.*)", re.DOTALL)
self.scratch_pad_regex = re.compile(
r"<scratch_pad>(.*?)</scratch_pad>", re.DOTALL)
if not self.model_tokenizer:
raise ValueError(
"The model tokenizer must be passed to the ToolParser "
"constructor during construction.")
self.tool_call_start_token_id = self.vocab.get(
self.tool_call_start_token)
self.tool_call_end_token_id = self.vocab.get(self.tool_call_end_token)
if (self.tool_call_start_token_id is None
or self.tool_call_end_token_id is None):
raise RuntimeError(
"Hermes 2 Pro Tool parser could not locate tool call start/end "
"tokens in the tokenizer!")
def extract_tool_calls(
self,
model_output: str,
request: ChatCompletionRequest,
) -> ExtractedToolCallInformation:
# sanity check; avoid unnecessary processing
if self.tool_call_start_token not in model_output:
return ExtractedToolCallInformation(tools_called=False,
tool_calls=[],
content=model_output)
else:
try:
# there are two possible captures - between tags, or between a
# tag and end-of-string so the result of
# findall is an array of tuples where one is a function call and
# the other is None
function_call_tuples = (
self.tool_call_regex.findall(model_output))
# load the JSON, and then use it to build the Function and
# Tool Call
raw_function_calls = [
json.loads(match[0] if match[0] else match[1])
for match in function_call_tuples
]
tool_calls = [
ToolCall(
type="function",
function=FunctionCall(
name=function_call["name"],
# function call args are JSON but as a string
arguments=json.dumps(function_call["arguments"],
ensure_ascii=False)))
for function_call in raw_function_calls
]
content = model_output[:model_output.
find(self.tool_call_start_token)]
return ExtractedToolCallInformation(
tools_called=True,
tool_calls=tool_calls,
content=content if content else None)
except Exception:
logger.exception(
"Error in extracting tool call from response.")
return ExtractedToolCallInformation(tools_called=False,
tool_calls=[],
content=model_output)
def extract_tool_calls_streaming(
self,
previous_text: str,
current_text: str,
delta_text: str,
previous_token_ids: Sequence[int],
current_token_ids: Sequence[int],
delta_token_ids: Sequence[int],
request: ChatCompletionRequest,
) -> Union[DeltaMessage, None]:
logger.debug("delta_text: %s", delta_text)
logger.debug("delta_token_ids: %s", delta_token_ids)
# check to see if we should be streaming a tool call - is there a
if self.tool_call_start_token_id not in current_token_ids:
logger.debug("No tool call tokens found!")
return DeltaMessage(content=delta_text)
try:
# figure out where we are in the parsing by counting tool call
# start & end tags
prev_tool_start_count = previous_token_ids.count(
self.tool_call_start_token_id)
prev_tool_end_count = previous_token_ids.count(
self.tool_call_end_token_id)
cur_tool_start_count = current_token_ids.count(
self.tool_call_start_token_id)
cur_tool_end_count = current_token_ids.count(
self.tool_call_end_token_id)
tool_call_portion = None
text_portion = None
# case: if we're generating text, OR rounding out a tool call
if (cur_tool_start_count == cur_tool_end_count
and prev_tool_end_count == cur_tool_end_count
and self.tool_call_end_token not in delta_text):
logger.debug("Generating text content! skipping tool parsing.")
return DeltaMessage(content=delta_text)
if self.tool_call_end_token in delta_text:
logger.debug("tool_call_end_token in delta_text")
full_text = current_text + delta_text
tool_call_portion = full_text.split(
self.tool_call_start_token)[-1].split(
self.tool_call_end_token)[0].rstrip()
delta_text = delta_text.split(
self.tool_call_end_token)[0].rstrip()
text_portion = delta_text.split(
self.tool_call_end_token)[-1].lstrip()
# case: if tool open & close tag counts don't match, we're doing
# imaginary "else" block here
# something with tools with this diff.
# flags for partial JSON parting. exported constants from
# "Allow" are handled via BIT MASK
flags = Allow.ALL if self.current_tool_name_sent \
else Allow.ALL & ~Allow.STR
# case -- we're starting a new tool call
if (cur_tool_start_count > cur_tool_end_count
and cur_tool_start_count > prev_tool_start_count):
if len(delta_token_ids) > 1:
tool_call_portion = current_text.split(
self.tool_call_start_token)[-1]
else:
tool_call_portion = None
delta = None
text_portion = None
# set cursors and state appropriately
self.current_tool_id += 1
self.current_tool_name_sent = False
self.streamed_args_for_tool.append("")
logger.debug("Starting on a new tool %s", self.current_tool_id)
# case -- we're updating an existing tool call
elif (cur_tool_start_count > cur_tool_end_count
and cur_tool_start_count == prev_tool_start_count):
# get the portion of the text that's the tool call
tool_call_portion = current_text.split(
self.tool_call_start_token)[-1]
text_portion = None
# case -- the current tool call is being closed.
elif (cur_tool_start_count == cur_tool_end_count
and cur_tool_end_count >= prev_tool_end_count):
if (self.prev_tool_call_arr is None
or len(self.prev_tool_call_arr) == 0):
logger.debug(
"attempting to close tool call, but no tool call")
return None
diff = self.prev_tool_call_arr[self.current_tool_id].get(
"arguments")
if diff:
diff = diff.encode('utf-8').decode(
'unicode_escape') if diff is str else diff
if ('"}' not in delta_text):
return None
end_loc = delta_text.rindex('"}')
diff = delta_text[:end_loc] + '"}'
logger.debug(
"Finishing tool and found diff that had not "
"been streamed yet: %s", diff)
self.streamed_args_for_tool[self.current_tool_id] \
+= diff
return DeltaMessage(tool_calls=[
DeltaToolCall(index=self.current_tool_id,
function=DeltaFunctionCall(
arguments=diff).model_dump(
exclude_none=True))
])
# case -- otherwise we're just generating text
else:
text = delta_text.replace(self.tool_call_start_token, "")
text = text.replace(self.tool_call_end_token, "")
delta = DeltaMessage(tool_calls=[], content=text)
return delta
try:
current_tool_call = partial_json_parser.loads(
tool_call_portion or "{}",
flags) if tool_call_portion else None
logger.debug("Parsed tool call %s", current_tool_call)
except partial_json_parser.core.exceptions.MalformedJSON:
logger.debug('not enough tokens to parse into JSON yet')
return None
except json.decoder.JSONDecodeError:
logger.debug("unable to parse JSON")
return None
# case - we haven't sent the tool name yet. If it's available, send
# it. otherwise, wait until it's available.
if not self.current_tool_name_sent:
if (current_tool_call is None):
return None
function_name: Union[str, None] = current_tool_call.get("name")
if function_name:
self.current_tool_name_sent = True
return DeltaMessage(tool_calls=[
DeltaToolCall(index=self.current_tool_id,
type="function",
id=random_tool_call_id(),
function=DeltaFunctionCall(
name=function_name).model_dump(
exclude_none=True))
])
else:
return None
# case -- otherwise, send the tool call delta
# if the tool call portion is None, send the delta as text
if tool_call_portion is None:
# if there's text but not tool calls, send that -
# otherwise None to skip chunk
delta = DeltaMessage(content=delta_text) \
if text_portion is not None else None
return delta
# now, the nitty-gritty of tool calls
# now we have the portion to parse as tool call.
logger.debug("Trying to parse current tool call with ID %s",
self.current_tool_id)
# if we're starting a new tool call, push an empty object in as
# a placeholder for the arguments
if len(self.prev_tool_call_arr) <= self.current_tool_id:
self.prev_tool_call_arr.append({})
# main logic for tool parsing here - compare prev. partially-parsed
# JSON to the current partially-parsed JSON
prev_arguments = (
self.prev_tool_call_arr[self.current_tool_id].get("arguments"))
cur_arguments = current_tool_call.get("arguments")
logger.debug("diffing old arguments: %s", prev_arguments)
logger.debug("against new ones: %s", cur_arguments)
# case -- no arguments have been created yet. skip sending a delta.
if not cur_arguments and not prev_arguments:
logger.debug("Skipping text %s - no arguments", delta_text)
delta = None
# case -- prev arguments are defined, but non are now.
# probably impossible, but not a fatal error - just keep going
elif not cur_arguments and prev_arguments:
logger.error("should be impossible to have arguments reset "
"mid-call. skipping streaming anything.")
delta = None
# case -- we now have the first info about arguments available from
# autocompleting the JSON
elif cur_arguments and not prev_arguments:
cur_arguments_json = json.dumps(cur_arguments,
ensure_ascii=False)
logger.debug("finding %s in %s", delta_text,
cur_arguments_json)
# get the location where previous args differ from current
if (delta_text not in cur_arguments_json[:-2]):
return None
args_delta_start_loc = cur_arguments_json[:-2]. \
rindex(delta_text) + \
len(delta_text)
# use that to find the actual delta
arguments_delta = cur_arguments_json[:args_delta_start_loc]
logger.debug("First tokens in arguments received: %s",
arguments_delta)
delta = DeltaMessage(tool_calls=[
DeltaToolCall(index=self.current_tool_id,
function=DeltaFunctionCall(
arguments=arguments_delta).model_dump(
exclude_none=True))
])
self.streamed_args_for_tool[self.current_tool_id] \
+= arguments_delta
# last case -- we have an update to existing arguments.
elif cur_arguments and prev_arguments:
if isinstance(delta_text, str) and len(delta_text.rstrip(
)) >= 1 and delta_text.rstrip()[-1] == '}':
delta_text = delta_text.rstrip()[:-1]
logger.debug("got diff %s", delta_text)
delta = DeltaMessage(tool_calls=[
DeltaToolCall(index=self.current_tool_id,
function=DeltaFunctionCall(
arguments=delta_text).model_dump(
exclude_none=True))
])
self.streamed_args_for_tool[self.current_tool_id] \
+= delta_text
# handle saving the state for the current tool into
# the "prev" list for use in diffing for the next iteration
if self.current_tool_id == len(self.prev_tool_call_arr) - 1:
self.prev_tool_call_arr[self.current_tool_id] = \
current_tool_call
else:
self.prev_tool_call_arr.append(current_tool_call)
return delta
except Exception:
logger.exception("Error trying to handle streaming tool call.")
return None # do not stream a delta. skip this token ID.