feat: Enable Anthropic streaming on new agent loop (#1550)
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Matthew Zhou
323
letta/interfaces/anthropic_streaming_interface.py
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323
letta/interfaces/anthropic_streaming_interface.py
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from datetime import datetime, timezone
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from enum import Enum
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from typing import AsyncGenerator, List, Union
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from anthropic import AsyncStream
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from anthropic.types.beta import (
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BetaInputJSONDelta,
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BetaRawContentBlockDeltaEvent,
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BetaRawContentBlockStartEvent,
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BetaRawContentBlockStopEvent,
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BetaRawMessageDeltaEvent,
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BetaRawMessageStartEvent,
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BetaRawMessageStopEvent,
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BetaRawMessageStreamEvent,
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BetaRedactedThinkingBlock,
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BetaSignatureDelta,
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BetaTextBlock,
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BetaTextDelta,
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BetaThinkingBlock,
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BetaThinkingDelta,
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BetaToolUseBlock,
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)
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from letta.constants import DEFAULT_MESSAGE_TOOL, DEFAULT_MESSAGE_TOOL_KWARG
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from letta.local_llm.constants import INNER_THOUGHTS_KWARG
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from letta.log import get_logger
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from letta.schemas.letta_message import (
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AssistantMessage,
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HiddenReasoningMessage,
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LettaMessage,
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ReasoningMessage,
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ToolCallDelta,
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ToolCallMessage,
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)
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from letta.schemas.letta_message_content import ReasoningContent, RedactedReasoningContent, TextContent
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from letta.schemas.message import Message
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from letta.schemas.openai.chat_completion_response import FunctionCall, ToolCall
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from letta.server.rest_api.optimistic_json_parser import OptimisticJSONParser
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logger = get_logger(__name__)
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# TODO: These modes aren't used right now - but can be useful we do multiple sequential tool calling within one Claude message
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class EventMode(Enum):
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TEXT = "TEXT"
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TOOL_USE = "TOOL_USE"
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THINKING = "THINKING"
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REDACTED_THINKING = "REDACTED_THINKING"
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class AnthropicStreamingInterface:
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"""
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Encapsulates the logic for streaming responses from Anthropic.
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This class handles parsing of partial tokens, pre-execution messages,
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and detection of tool call events.
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"""
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def __init__(self, use_assistant_message: bool = False, put_inner_thoughts_in_kwarg: bool = False):
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self.optimistic_json_parser: OptimisticJSONParser = OptimisticJSONParser()
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self.use_assistant_message = use_assistant_message
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# Premake IDs for database writes
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self.letta_assistant_message_id = Message.generate_id()
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self.letta_tool_message_id = Message.generate_id()
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self.anthropic_mode = None
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self.message_id = None
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self.accumulated_inner_thoughts = []
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self.tool_call_id = None
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self.tool_call_name = None
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self.accumulated_tool_call_args = []
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self.previous_parse = {}
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# usage trackers
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self.input_tokens = 0
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self.output_tokens = 0
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# reasoning object trackers
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self.reasoning_messages = []
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# Buffer to hold tool call messages until inner thoughts are complete
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self.tool_call_buffer = []
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self.inner_thoughts_complete = False
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self.put_inner_thoughts_in_kwarg = put_inner_thoughts_in_kwarg
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def get_tool_call_object(self) -> ToolCall:
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"""Useful for agent loop"""
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return ToolCall(
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id=self.tool_call_id, function=FunctionCall(arguments="".join(self.accumulated_tool_call_args), name=self.tool_call_name)
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)
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def _check_inner_thoughts_complete(self, combined_args: str) -> bool:
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"""
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Check if inner thoughts are complete in the current tool call arguments
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by looking for a closing quote after the inner_thoughts field
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"""
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if not self.put_inner_thoughts_in_kwarg:
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# None of the things should have inner thoughts in kwargs
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return True
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else:
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parsed = self.optimistic_json_parser.parse(combined_args)
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# TODO: This will break on tools with 0 input
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return len(parsed.keys()) > 1 and INNER_THOUGHTS_KWARG in parsed.keys()
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async def process(self, stream: AsyncStream[BetaRawMessageStreamEvent]) -> AsyncGenerator[LettaMessage, None]:
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async with stream:
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async for event in stream:
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# TODO: Support BetaThinkingBlock, BetaRedactedThinkingBlock
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if isinstance(event, BetaRawContentBlockStartEvent):
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content = event.content_block
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if isinstance(content, BetaTextBlock):
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self.anthropic_mode = EventMode.TEXT
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# TODO: Can capture citations, etc.
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elif isinstance(content, BetaToolUseBlock):
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self.anthropic_mode = EventMode.TOOL_USE
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self.tool_call_id = content.id
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self.tool_call_name = content.name
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self.inner_thoughts_complete = False
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if not self.use_assistant_message:
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# Buffer the initial tool call message instead of yielding immediately
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tool_call_msg = ToolCallMessage(
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id=self.letta_tool_message_id,
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tool_call=ToolCallDelta(name=self.tool_call_name, tool_call_id=self.tool_call_id),
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date=datetime.now(timezone.utc).isoformat(),
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)
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self.tool_call_buffer.append(tool_call_msg)
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elif isinstance(content, BetaThinkingBlock):
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self.anthropic_mode = EventMode.THINKING
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# TODO: Can capture signature, etc.
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elif isinstance(content, BetaRedactedThinkingBlock):
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self.anthropic_mode = EventMode.REDACTED_THINKING
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hidden_reasoning_message = HiddenReasoningMessage(
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id=self.letta_assistant_message_id,
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state="redacted",
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hidden_reasoning=content.data,
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date=datetime.now(timezone.utc).isoformat(),
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)
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self.reasoning_messages.append(hidden_reasoning_message)
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yield hidden_reasoning_message
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elif isinstance(event, BetaRawContentBlockDeltaEvent):
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delta = event.delta
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if isinstance(delta, BetaTextDelta):
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# Safety check
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if not self.anthropic_mode == EventMode.TEXT:
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raise RuntimeError(
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f"Streaming integrity failed - received BetaTextDelta object while not in TEXT EventMode: {delta}"
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)
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# TODO: Strip out </thinking> more robustly, this is pretty hacky lol
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delta.text = delta.text.replace("</thinking>", "")
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self.accumulated_inner_thoughts.append(delta.text)
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reasoning_message = ReasoningMessage(
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id=self.letta_assistant_message_id,
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reasoning=self.accumulated_inner_thoughts[-1],
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date=datetime.now(timezone.utc).isoformat(),
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)
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self.reasoning_messages.append(reasoning_message)
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yield reasoning_message
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elif isinstance(delta, BetaInputJSONDelta):
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if not self.anthropic_mode == EventMode.TOOL_USE:
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raise RuntimeError(
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f"Streaming integrity failed - received BetaInputJSONDelta object while not in TOOL_USE EventMode: {delta}"
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)
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self.accumulated_tool_call_args.append(delta.partial_json)
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combined_args = "".join(self.accumulated_tool_call_args)
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current_parsed = self.optimistic_json_parser.parse(combined_args)
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# Start detecting a difference in inner thoughts
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previous_inner_thoughts = self.previous_parse.get(INNER_THOUGHTS_KWARG, "")
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current_inner_thoughts = current_parsed.get(INNER_THOUGHTS_KWARG, "")
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inner_thoughts_diff = current_inner_thoughts[len(previous_inner_thoughts) :]
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if inner_thoughts_diff:
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reasoning_message = ReasoningMessage(
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id=self.letta_assistant_message_id,
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reasoning=inner_thoughts_diff,
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date=datetime.now(timezone.utc).isoformat(),
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)
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self.reasoning_messages.append(reasoning_message)
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yield reasoning_message
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# Check if inner thoughts are complete - if so, flush the buffer
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if not self.inner_thoughts_complete and self._check_inner_thoughts_complete(combined_args):
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self.inner_thoughts_complete = True
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# Flush all buffered tool call messages
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for buffered_msg in self.tool_call_buffer:
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yield buffered_msg
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self.tool_call_buffer = []
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# Start detecting special case of "send_message"
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if self.tool_call_name == DEFAULT_MESSAGE_TOOL and self.use_assistant_message:
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previous_send_message = self.previous_parse.get(DEFAULT_MESSAGE_TOOL_KWARG, "")
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current_send_message = current_parsed.get(DEFAULT_MESSAGE_TOOL_KWARG, "")
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send_message_diff = current_send_message[len(previous_send_message) :]
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# Only stream out if it's not an empty string
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if send_message_diff:
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yield AssistantMessage(
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id=self.letta_assistant_message_id,
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content=[TextContent(text=send_message_diff)],
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date=datetime.now(timezone.utc).isoformat(),
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)
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else:
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# Otherwise, it is a normal tool call - buffer or yield based on inner thoughts status
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tool_call_msg = ToolCallMessage(
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id=self.letta_tool_message_id,
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tool_call=ToolCallDelta(arguments=delta.partial_json),
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date=datetime.now(timezone.utc).isoformat(),
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)
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if self.inner_thoughts_complete:
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yield tool_call_msg
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else:
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self.tool_call_buffer.append(tool_call_msg)
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# Set previous parse
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self.previous_parse = current_parsed
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elif isinstance(delta, BetaThinkingDelta):
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# Safety check
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if not self.anthropic_mode == EventMode.THINKING:
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raise RuntimeError(
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f"Streaming integrity failed - received BetaThinkingBlock object while not in THINKING EventMode: {delta}"
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)
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reasoning_message = ReasoningMessage(
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id=self.letta_assistant_message_id,
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source="reasoner_model",
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reasoning=delta.thinking,
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date=datetime.now(timezone.utc).isoformat(),
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)
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self.reasoning_messages.append(reasoning_message)
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yield reasoning_message
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elif isinstance(delta, BetaSignatureDelta):
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# Safety check
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if not self.anthropic_mode == EventMode.THINKING:
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raise RuntimeError(
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f"Streaming integrity failed - received BetaSignatureDelta object while not in THINKING EventMode: {delta}"
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)
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reasoning_message = ReasoningMessage(
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id=self.letta_assistant_message_id,
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source="reasoner_model",
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reasoning="",
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date=datetime.now(timezone.utc).isoformat(),
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signature=delta.signature,
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)
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self.reasoning_messages.append(reasoning_message)
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yield reasoning_message
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elif isinstance(event, BetaRawMessageStartEvent):
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self.message_id = event.message.id
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self.input_tokens += event.message.usage.input_tokens
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self.output_tokens += event.message.usage.output_tokens
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elif isinstance(event, BetaRawMessageDeltaEvent):
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self.output_tokens += event.usage.output_tokens
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elif isinstance(event, BetaRawMessageStopEvent):
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# Don't do anything here! We don't want to stop the stream.
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pass
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elif isinstance(event, BetaRawContentBlockStopEvent):
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# If we're exiting a tool use block and there are still buffered messages,
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# we should flush them now
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if self.anthropic_mode == EventMode.TOOL_USE and self.tool_call_buffer:
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for buffered_msg in self.tool_call_buffer:
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yield buffered_msg
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self.tool_call_buffer = []
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self.anthropic_mode = None
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def get_reasoning_content(self) -> List[Union[TextContent, ReasoningContent, RedactedReasoningContent]]:
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def _process_group(
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group: List[Union[ReasoningMessage, HiddenReasoningMessage]], group_type: str
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) -> Union[TextContent, ReasoningContent, RedactedReasoningContent]:
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if group_type == "reasoning":
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reasoning_text = "".join(chunk.reasoning for chunk in group)
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is_native = any(chunk.source == "reasoner_model" for chunk in group)
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signature = next((chunk.signature for chunk in group if chunk.signature is not None), None)
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if is_native:
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return ReasoningContent(is_native=is_native, reasoning=reasoning_text, signature=signature)
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else:
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return TextContent(text=reasoning_text)
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elif group_type == "redacted":
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redacted_text = "".join(chunk.hidden_reasoning for chunk in group if chunk.hidden_reasoning is not None)
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return RedactedReasoningContent(data=redacted_text)
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else:
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raise ValueError("Unexpected group type")
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merged = []
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current_group = []
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current_group_type = None # "reasoning" or "redacted"
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for msg in self.reasoning_messages:
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# Determine the type of the current message
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if isinstance(msg, HiddenReasoningMessage):
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msg_type = "redacted"
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elif isinstance(msg, ReasoningMessage):
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msg_type = "reasoning"
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else:
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raise ValueError("Unexpected message type")
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# Initialize group type if not set
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if current_group_type is None:
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current_group_type = msg_type
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# If the type changes, process the current group
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if msg_type != current_group_type:
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merged.append(_process_group(current_group, current_group_type))
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current_group = []
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current_group_type = msg_type
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current_group.append(msg)
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# Process the final group, if any.
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if current_group:
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merged.append(_process_group(current_group, current_group_type))
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return merged
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