Refactor/react agent (#3355)
Yeuoly
2 years ago
committed by
GitHub
parent
509c640a80
commit
cea107b165
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import json
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from core.agent.cot_agent_runner import CotAgentRunner
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from core.model_runtime.entities.message_entities import (
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AssistantPromptMessage,
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PromptMessage,
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SystemPromptMessage,
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UserPromptMessage,
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)
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from core.model_runtime.utils.encoders import jsonable_encoder
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class CotChatAgentRunner(CotAgentRunner):
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def _organize_system_prompt(self) -> SystemPromptMessage:
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"""
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Organize system prompt
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"""
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prompt_entity = self.app_config.agent.prompt
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first_prompt = prompt_entity.first_prompt
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system_prompt = first_prompt \
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.replace("{{instruction}}", self._instruction) \
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.replace("{{tools}}", json.dumps(jsonable_encoder(self._prompt_messages_tools))) \
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.replace("{{tool_names}}", ', '.join([tool.name for tool in self._prompt_messages_tools]))
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return SystemPromptMessage(content=system_prompt)
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def _organize_prompt_messages(self) -> list[PromptMessage]:
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"""
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Organize
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"""
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# organize system prompt
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system_message = self._organize_system_prompt()
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# organize historic prompt messages
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historic_messages = self._historic_prompt_messages
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# organize current assistant messages
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agent_scratchpad = self._agent_scratchpad
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if not agent_scratchpad:
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assistant_messages = []
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else:
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assistant_message = AssistantPromptMessage(content='')
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for unit in agent_scratchpad:
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if unit.is_final():
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assistant_message.content += f"Final Answer: {unit.agent_response}"
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else:
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assistant_message.content += f"Thought: {unit.thought}\n\n"
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if unit.action_str:
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assistant_message.content += f"Action: {unit.action_str}\n\n"
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if unit.observation:
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assistant_message.content += f"Observation: {unit.observation}\n\n"
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assistant_messages = [assistant_message]
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# query messages
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query_messages = UserPromptMessage(content=self._query)
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if assistant_messages:
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messages = [
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system_message,
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*historic_messages,
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query_messages,
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*assistant_messages,
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UserPromptMessage(content='continue')
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]
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else:
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messages = [system_message, *historic_messages, query_messages]
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# join all messages
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return messages
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import json
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from core.agent.cot_agent_runner import CotAgentRunner
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from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, UserPromptMessage
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from core.model_runtime.utils.encoders import jsonable_encoder
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class CotCompletionAgentRunner(CotAgentRunner):
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def _organize_instruction_prompt(self) -> str:
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"""
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Organize instruction prompt
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"""
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prompt_entity = self.app_config.agent.prompt
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first_prompt = prompt_entity.first_prompt
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system_prompt = first_prompt.replace("{{instruction}}", self._instruction) \
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.replace("{{tools}}", json.dumps(jsonable_encoder(self._prompt_messages_tools))) \
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.replace("{{tool_names}}", ', '.join([tool.name for tool in self._prompt_messages_tools]))
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return system_prompt
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def _organize_historic_prompt(self) -> str:
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"""
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Organize historic prompt
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"""
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historic_prompt_messages = self._historic_prompt_messages
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historic_prompt = ""
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for message in historic_prompt_messages:
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if isinstance(message, UserPromptMessage):
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historic_prompt += f"Question: {message.content}\n\n"
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elif isinstance(message, AssistantPromptMessage):
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historic_prompt += message.content + "\n\n"
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return historic_prompt
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def _organize_prompt_messages(self) -> list[PromptMessage]:
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"""
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Organize prompt messages
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"""
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# organize system prompt
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system_prompt = self._organize_instruction_prompt()
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# organize historic prompt messages
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historic_prompt = self._organize_historic_prompt()
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# organize current assistant messages
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agent_scratchpad = self._agent_scratchpad
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assistant_prompt = ''
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for unit in agent_scratchpad:
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if unit.is_final():
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assistant_prompt += f"Final Answer: {unit.agent_response}"
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else:
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assistant_prompt += f"Thought: {unit.thought}\n\n"
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if unit.action_str:
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assistant_prompt += f"Action: {unit.action_str}\n\n"
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if unit.observation:
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assistant_prompt += f"Observation: {unit.observation}\n\n"
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# query messages
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query_prompt = f"Question: {self._query}"
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# join all messages
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prompt = system_prompt \
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.replace("{{historic_messages}}", historic_prompt) \
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.replace("{{agent_scratchpad}}", assistant_prompt) \
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.replace("{{query}}", query_prompt)
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return [UserPromptMessage(content=prompt)]
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@ -0,0 +1,183 @@
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import json
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import re
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from collections.abc import Generator
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from typing import Union
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from core.agent.entities import AgentScratchpadUnit
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from core.model_runtime.entities.llm_entities import LLMResultChunk
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class CotAgentOutputParser:
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@classmethod
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def handle_react_stream_output(cls, llm_response: Generator[LLMResultChunk, None, None]) -> \
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Generator[Union[str, AgentScratchpadUnit.Action], None, None]:
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def parse_action(json_str):
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try:
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action = json.loads(json_str)
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action_name = None
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action_input = None
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for key, value in action.items():
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if 'input' in key.lower():
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action_input = value
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else:
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action_name = value
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if action_name is not None and action_input is not None:
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return AgentScratchpadUnit.Action(
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action_name=action_name,
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action_input=action_input,
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)
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else:
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return json_str or ''
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except:
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return json_str or ''
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def extra_json_from_code_block(code_block) -> Generator[Union[dict, str], None, None]:
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code_blocks = re.findall(r'```(.*?)```', code_block, re.DOTALL)
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if not code_blocks:
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return
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for block in code_blocks:
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json_text = re.sub(r'^[a-zA-Z]+\n', '', block.strip(), flags=re.MULTILINE)
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yield parse_action(json_text)
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code_block_cache = ''
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code_block_delimiter_count = 0
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in_code_block = False
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json_cache = ''
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json_quote_count = 0
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in_json = False
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got_json = False
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action_cache = ''
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action_str = 'action:'
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action_idx = 0
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thought_cache = ''
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thought_str = 'thought:'
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thought_idx = 0
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for response in llm_response:
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response = response.delta.message.content
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if not isinstance(response, str):
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continue
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# stream
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index = 0
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while index < len(response):
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steps = 1
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delta = response[index:index+steps]
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last_character = response[index-1] if index > 0 else ''
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if delta == '`':
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code_block_cache += delta
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code_block_delimiter_count += 1
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else:
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if not in_code_block:
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if code_block_delimiter_count > 0:
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yield code_block_cache
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code_block_cache = ''
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else:
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code_block_cache += delta
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code_block_delimiter_count = 0
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if not in_code_block and not in_json:
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if delta.lower() == action_str[action_idx] and action_idx == 0:
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if last_character not in ['\n', ' ', '']:
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index += steps
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yield delta
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continue
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action_cache += delta
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action_idx += 1
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if action_idx == len(action_str):
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action_cache = ''
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action_idx = 0
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index += steps
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continue
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elif delta.lower() == action_str[action_idx] and action_idx > 0:
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action_cache += delta
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action_idx += 1
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if action_idx == len(action_str):
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action_cache = ''
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action_idx = 0
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index += steps
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continue
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else:
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if action_cache:
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yield action_cache
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action_cache = ''
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action_idx = 0
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if delta.lower() == thought_str[thought_idx] and thought_idx == 0:
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if last_character not in ['\n', ' ', '']:
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index += steps
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yield delta
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continue
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thought_cache += delta
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thought_idx += 1
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if thought_idx == len(thought_str):
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thought_cache = ''
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thought_idx = 0
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index += steps
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continue
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elif delta.lower() == thought_str[thought_idx] and thought_idx > 0:
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thought_cache += delta
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thought_idx += 1
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if thought_idx == len(thought_str):
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thought_cache = ''
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thought_idx = 0
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index += steps
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continue
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else:
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if thought_cache:
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yield thought_cache
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thought_cache = ''
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thought_idx = 0
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if code_block_delimiter_count == 3:
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if in_code_block:
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yield from extra_json_from_code_block(code_block_cache)
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code_block_cache = ''
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in_code_block = not in_code_block
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code_block_delimiter_count = 0
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if not in_code_block:
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# handle single json
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if delta == '{':
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json_quote_count += 1
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in_json = True
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json_cache += delta
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elif delta == '}':
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json_cache += delta
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if json_quote_count > 0:
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json_quote_count -= 1
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if json_quote_count == 0:
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in_json = False
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got_json = True
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index += steps
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continue
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else:
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if in_json:
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json_cache += delta
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if got_json:
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got_json = False
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yield parse_action(json_cache)
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json_cache = ''
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json_quote_count = 0
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in_json = False
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if not in_code_block and not in_json:
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yield delta.replace('`', '')
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index += steps
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if code_block_cache:
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yield code_block_cache
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if json_cache:
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yield parse_action(json_cache)
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