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| @@ -1,3 +1,91 @@ | ||
| # Source code | ||
| *.bash text eol=lf | ||
| *.bat text eol=crlf | ||
| *.cmd text eol=crlf | ||
| *.coffee text | ||
| *.css text diff=css eol=lf | ||
| *.htm text diff=html eol=lf | ||
| *.html text diff=html eol=lf | ||
| *.inc text | ||
| *.ini text | ||
| *.js text | ||
| *.json text eol=lf | ||
| *.jsx text | ||
| *.less text | ||
| *.ls text | ||
| *.map text -diff | ||
| *.od text | ||
| *.onlydata text | ||
| *.php text diff=php | ||
| *.pl text | ||
| *.ps1 text eol=crlf | ||
| *.py text diff=python eol=lf | ||
| *.rb text diff=ruby eol=lf | ||
| *.sass text | ||
| *.scm text | ||
| *.scss text diff=css | ||
| *.sh text eol=lf | ||
| .husky/* text eol=lf | ||
| *.sql text | ||
| *.styl text | ||
| *.tag text | ||
| *.ts text | ||
| *.tsx text | ||
| *.xml text | ||
| *.xhtml text diff=html | ||
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| # Docker | ||
| Dockerfile text eol=lf | ||
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| # Documentation | ||
| *.ipynb text | ||
| *.markdown text diff=markdown eol=lf | ||
| *.md text diff=markdown eol=lf | ||
| *.mdwn text diff=markdown eol=lf | ||
| *.mdown text diff=markdown eol=lf | ||
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| NEWS text eol=lf | ||
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| # Configs | ||
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| # Images | ||
| *.png filter=lfs diff=lfs merge=lfs -text | ||
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109 changes: 109 additions & 0 deletions
109
autogen/agentchat/contrib/llamaindex_conversable_agent.py
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,109 @@ | ||
| from typing import Dict, List, Optional, Tuple, Union | ||
|
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| from autogen import OpenAIWrapper | ||
| from autogen.agentchat import Agent, ConversableAgent | ||
| from autogen.agentchat.contrib.vectordb.utils import get_logger | ||
|
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| logger = get_logger(__name__) | ||
|
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| try: | ||
| from llama_index.core.agent.runner.base import AgentRunner | ||
| from llama_index.core.chat_engine.types import AgentChatResponse | ||
| from llama_index_client import ChatMessage | ||
| except ImportError as e: | ||
| logger.fatal("Failed to import llama-index. Try running 'pip install llama-index'") | ||
| raise e | ||
|
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|
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| class LLamaIndexConversableAgent(ConversableAgent): | ||
|
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| def __init__( | ||
| self, | ||
| name: str, | ||
| llama_index_agent: AgentRunner, | ||
| description: Optional[str] = None, | ||
| **kwargs, | ||
| ): | ||
| """ | ||
| Args: | ||
| name (str): agent name. | ||
| llama_index_agent (AgentRunner): llama index agent. | ||
| Please override this attribute if you want to reprogram the agent. | ||
| description (str): a short description of the agent. This description is used by other agents | ||
| (e.g. the GroupChatManager) to decide when to call upon this agent. | ||
| **kwargs (dict): Please refer to other kwargs in | ||
| [ConversableAgent](../conversable_agent#__init__). | ||
| """ | ||
|
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| if llama_index_agent is None: | ||
| raise ValueError("llama_index_agent must be provided") | ||
|
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| if description is None or description.isspace(): | ||
| raise ValueError("description must be provided") | ||
|
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| super().__init__( | ||
| name, | ||
| description=description, | ||
| **kwargs, | ||
| ) | ||
|
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| self._llama_index_agent = llama_index_agent | ||
|
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| # Override the `generate_oai_reply` | ||
| self.replace_reply_func(ConversableAgent.generate_oai_reply, LLamaIndexConversableAgent._generate_oai_reply) | ||
|
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| self.replace_reply_func(ConversableAgent.a_generate_oai_reply, LLamaIndexConversableAgent._a_generate_oai_reply) | ||
|
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| def _generate_oai_reply( | ||
| self, | ||
| messages: Optional[List[Dict]] = None, | ||
| sender: Optional[Agent] = None, | ||
| config: Optional[OpenAIWrapper] = None, | ||
| ) -> Tuple[bool, Union[str, Dict, None]]: | ||
| """Generate a reply using autogen.oai.""" | ||
| user_message, history = self._extract_message_and_history(messages=messages, sender=sender) | ||
|
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| chatResponse: AgentChatResponse = self._llama_index_agent.chat(message=user_message, chat_history=history) | ||
|
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| extracted_response = chatResponse.response | ||
|
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| return (True, extracted_response) | ||
|
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| async def _a_generate_oai_reply( | ||
| self, | ||
| messages: Optional[List[Dict]] = None, | ||
| sender: Optional[Agent] = None, | ||
| config: Optional[OpenAIWrapper] = None, | ||
| ) -> Tuple[bool, Union[str, Dict, None]]: | ||
| """Generate a reply using autogen.oai.""" | ||
| user_message, history = self._extract_message_and_history(messages=messages, sender=sender) | ||
|
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| chatResponse: AgentChatResponse = await self._llama_index_agent.achat( | ||
| message=user_message, chat_history=history | ||
| ) | ||
|
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| extracted_response = chatResponse.response | ||
|
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| return (True, extracted_response) | ||
|
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| def _extract_message_and_history( | ||
| self, messages: Optional[List[Dict]] = None, sender: Optional[Agent] = None | ||
| ) -> Tuple[str, List[ChatMessage]]: | ||
| """Extract the message and history from the messages.""" | ||
| if not messages: | ||
| messages = self._oai_messages[sender] | ||
|
|
||
| if not messages: | ||
| return "", [] | ||
|
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| message = messages[-1].get("content", "") | ||
|
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| history = messages[:-1] | ||
| history_messages: List[ChatMessage] = [] | ||
| for history_message in history: | ||
| content = history_message.get("content", "") | ||
| role = history_message.get("role", "user") | ||
| if role: | ||
| if role == "user" or role == "assistant": | ||
| history_messages.append(ChatMessage(content=content, role=role, additional_kwargs={})) | ||
| return message, history_messages |
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