185 lines
6.4 KiB
Python
185 lines
6.4 KiB
Python
"""
|
|
A2A Streaming Iterator with token tracking and logging support.
|
|
"""
|
|
|
|
import asyncio
|
|
from datetime import datetime
|
|
from typing import TYPE_CHECKING, Any, AsyncIterator, Dict, List, Optional
|
|
|
|
import litellm
|
|
from litellm._logging import verbose_logger
|
|
from litellm.a2a_protocol.cost_calculator import A2ACostCalculator
|
|
from litellm.a2a_protocol.utils import A2ARequestUtils
|
|
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
|
|
from litellm.litellm_core_utils.thread_pool_executor import executor
|
|
|
|
if TYPE_CHECKING:
|
|
from a2a.types import SendStreamingMessageRequest, SendStreamingMessageResponse
|
|
|
|
|
|
class A2AStreamingIterator:
|
|
"""
|
|
Async iterator for A2A streaming responses with token tracking.
|
|
|
|
Collects chunks, extracts text, and logs usage on completion.
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
stream: AsyncIterator["SendStreamingMessageResponse"],
|
|
request: "SendStreamingMessageRequest",
|
|
logging_obj: LiteLLMLoggingObj,
|
|
agent_name: str = "unknown",
|
|
):
|
|
self.stream = stream
|
|
self.request = request
|
|
self.logging_obj = logging_obj
|
|
self.agent_name = agent_name
|
|
self.start_time = datetime.now()
|
|
|
|
# Collect chunks for token counting
|
|
self.chunks: List[Any] = []
|
|
self.collected_text_parts: List[str] = []
|
|
self.final_chunk: Optional[Any] = None
|
|
|
|
def __aiter__(self):
|
|
return self
|
|
|
|
async def __anext__(self) -> "SendStreamingMessageResponse":
|
|
try:
|
|
chunk = await self.stream.__anext__()
|
|
|
|
# Store chunk
|
|
self.chunks.append(chunk)
|
|
|
|
# Extract text from chunk for token counting
|
|
self._collect_text_from_chunk(chunk)
|
|
|
|
# Check if this is the final chunk (completed status)
|
|
if self._is_completed_chunk(chunk):
|
|
self.final_chunk = chunk
|
|
|
|
return chunk
|
|
|
|
except StopAsyncIteration:
|
|
# Stream ended - handle logging
|
|
if self.final_chunk is None and self.chunks:
|
|
self.final_chunk = self.chunks[-1]
|
|
await self._handle_stream_complete()
|
|
raise
|
|
|
|
def _collect_text_from_chunk(self, chunk: Any) -> None:
|
|
"""Extract text from a streaming chunk and add to collected parts."""
|
|
try:
|
|
chunk_dict = (
|
|
chunk.model_dump(mode="json", exclude_none=True)
|
|
if hasattr(chunk, "model_dump")
|
|
else {}
|
|
)
|
|
text = A2ARequestUtils.extract_text_from_response(chunk_dict)
|
|
if text:
|
|
self.collected_text_parts.append(text)
|
|
except Exception:
|
|
verbose_logger.debug("Failed to extract text from A2A streaming chunk")
|
|
|
|
def _is_completed_chunk(self, chunk: Any) -> bool:
|
|
"""Check if chunk indicates stream completion."""
|
|
try:
|
|
chunk_dict = (
|
|
chunk.model_dump(mode="json", exclude_none=True)
|
|
if hasattr(chunk, "model_dump")
|
|
else {}
|
|
)
|
|
result = chunk_dict.get("result", {})
|
|
if isinstance(result, dict):
|
|
status = result.get("status", {})
|
|
if isinstance(status, dict):
|
|
return status.get("state") == "completed"
|
|
except Exception:
|
|
pass
|
|
return False
|
|
|
|
async def _handle_stream_complete(self) -> None:
|
|
"""Handle logging and token counting when stream completes."""
|
|
try:
|
|
end_time = datetime.now()
|
|
|
|
# Calculate tokens from collected text
|
|
input_message = A2ARequestUtils.get_input_message_from_request(self.request)
|
|
input_text = A2ARequestUtils.extract_text_from_message(input_message)
|
|
prompt_tokens = A2ARequestUtils.count_tokens(input_text)
|
|
|
|
# Use the last (most complete) text from chunks
|
|
output_text = (
|
|
self.collected_text_parts[-1] if self.collected_text_parts else ""
|
|
)
|
|
completion_tokens = A2ARequestUtils.count_tokens(output_text)
|
|
|
|
total_tokens = prompt_tokens + completion_tokens
|
|
|
|
# Create usage object
|
|
usage = litellm.Usage(
|
|
prompt_tokens=prompt_tokens,
|
|
completion_tokens=completion_tokens,
|
|
total_tokens=total_tokens,
|
|
)
|
|
|
|
# Set usage on logging obj
|
|
self.logging_obj.model_call_details["usage"] = usage
|
|
# Mark stream flag for downstream callbacks
|
|
self.logging_obj.model_call_details["stream"] = False
|
|
|
|
# Calculate cost using A2ACostCalculator
|
|
response_cost = A2ACostCalculator.calculate_a2a_cost(self.logging_obj)
|
|
self.logging_obj.model_call_details["response_cost"] = response_cost
|
|
|
|
# Build result for logging
|
|
result = self._build_logging_result(usage)
|
|
|
|
# Call success handlers - they will build standard_logging_object
|
|
asyncio.create_task(
|
|
self.logging_obj.async_success_handler(
|
|
result=result,
|
|
start_time=self.start_time,
|
|
end_time=end_time,
|
|
cache_hit=None,
|
|
)
|
|
)
|
|
|
|
executor.submit(
|
|
self.logging_obj.success_handler,
|
|
result=result,
|
|
cache_hit=None,
|
|
start_time=self.start_time,
|
|
end_time=end_time,
|
|
)
|
|
|
|
verbose_logger.info(
|
|
f"A2A streaming completed: prompt_tokens={prompt_tokens}, "
|
|
f"completion_tokens={completion_tokens}, total_tokens={total_tokens}, "
|
|
f"response_cost={response_cost}"
|
|
)
|
|
|
|
except Exception as e:
|
|
verbose_logger.debug(f"Error in A2A streaming completion handler: {e}")
|
|
|
|
def _build_logging_result(self, usage: litellm.Usage) -> Dict[str, Any]:
|
|
"""Build a result dict for logging."""
|
|
result: Dict[str, Any] = {
|
|
"id": getattr(self.request, "id", "unknown"),
|
|
"jsonrpc": "2.0",
|
|
"usage": usage.model_dump()
|
|
if hasattr(usage, "model_dump")
|
|
else dict(usage),
|
|
}
|
|
|
|
# Add final chunk result if available
|
|
if self.final_chunk:
|
|
try:
|
|
chunk_dict = self.final_chunk.model_dump(mode="json", exclude_none=True)
|
|
result["result"] = chunk_dict.get("result", {})
|
|
except Exception:
|
|
pass
|
|
|
|
return result
|