题意：基于代理的LLM检索增强生成
问题背景：
I was trying the application code in the link.
我正在尝试链接中的应用程序代码。
I am using the following Llang Chain version
我正在使用以下Llang Chain版本
langchain 0.0.327 langchain-community 0.0.2 langchain-core 0.1.0
Getting the following error: 得到以下的错误
Entering new AgentExecutor chain...
Traceback (most recent call last):
File "RAGWithAgent.py", line 54, in <module>
result = agent_executor({"input": "hi, im bob"})
File "\lib\site-packages\langchain\chains\base.py", line 310, in __call__
raise e
File "\lib\site-packages\langchain\chains\base.py", line 304, in __call__
self._call(inputs, run_manager=run_manager)
File "\lib\site-packages\langchain\agents\agent.py", line 1146, in _call
next_step_output = self._take_next_step(
File "\lib\site-packages\langchain\agents\agent.py", line 933, in _take_next_step
output = self.agent.plan(
File "\lib\site-packages\langchain\agents\openai_functions_agent\base.py", line 104, in plan
predicted_message = self.llm.predict_messages(
File "\lib\site-packages\langchain\chat_models\base.py", line 650, in predict_messages
return self(messages, stop=_stop, **kwargs)
File "\lib\site-packages\langchain\chat_models\base.py", line 600, in __call__
generation = self.generate(
File "\lib\site-packages\langchain\chat_models\base.py", line 349, in generate
raise e
File "\lib\site-packages\langchain\chat_models\base.py", line 339, in generate
self._generate_with_cache(
File "\lib\site-packages\langchain\chat_models\base.py", line 492, in _generate_with_cache
return self._generate(
File "\lib\site-packages\langchain\chat_models\openai.py", line 357, in _generate
return _generate_from_stream(stream_iter)
File "\lib\site-packages\langchain\chat_models\base.py", line 57, in _generate_from_stream
for chunk in stream:
File "\lib\site-packages\langchain\chat_models\openai.py", line 326, in _stream
for chunk in self.completion_with_retry(
File "\lib\site-packages\langchain\chat_models\openai.py", line 299, in completion_with_retry
return _completion_with_retry(**kwargs)
File "\lib\site-packages\tenacity\__init__.py", line 289, in wrapped_f
return self(f, *args, **kw)
File "\lib\site-packages\tenacity\__init__.py", line 379, in __call__
do = self.iter(retry_state=retry_state)
File "\lib\site-packages\tenacity\__init__.py", line 314, in iter
return fut.result()
File "D:\Program Files\Python38\lib\concurrent\futures\_base.py", line 432, in result
return self.__get_result()
File "D:\Program Files\Python38\lib\concurrent\futures\_base.py", line 388, in __get_result
raise self._exception
File "\lib\site-packages\tenacity\__init__.py", line 382, in __call__
result = fn(*args, **kwargs)
File "\lib\site-packages\langchain\chat_models\openai.py", line 297, in _completion_with_retry
return self.client.create(**kwargs)
File "\lib\site-packages\openai\api_resources\chat_completion.py", line 25, in create
return super().create(*args, **kwargs)
File "\lib\site-packages\openai\api_resources\abstract\engine_api_resource.py", line 155, in create
response, _, api_key = requestor.request(
File "\lib\site-packages\openai\api_requestor.py", line 299, in request
resp, got_stream = self._interpret_response(result, stream)
File "\lib\site-packages\openai\api_requestor.py", line 710, in _interpret_response
self._interpret_response_line(
File "\lib\site-packages\openai\api_requestor.py", line 775, in _interpret_response_line
raise self.handle_error_response(
openai.error.InvalidRequestError: Unrecognized request argument supplied: functions
Process finished with exit code 1I used Azure LLM instead openAI. FAISS was not working for me so used Chroma Vector Store.
我使用了Azure的LLM，而不是OpenAI。FAISS对我不起作用，所以我使用了Chroma Vector Store。
Following is my code: 下面是我的代码
from langchain.text_splitter import CharacterTextSplitter
from langchain.document_loaders import TextLoader
from langchain.agents.agent_toolkits import create_retriever_tool
from langchain.agents.agent_toolkits import create_conversational_retrieval_agent
from langchain.chat_models import AzureChatOpenAI
from langchain.vectorstores import Chroma
from langchain.embeddings.sentence_transformer import SentenceTransformerEmbeddings
import os
AZURE_OPENAI_API_KEY = ""
os.environ["OPENAI_API_KEY"] = AZURE_OPENAI_API_KEY
loader = TextLoader(r"Toward a Knowledge Graph of Cybersecurity Countermeasures.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
chunks = text_splitter.split_documents(documents)
# create the open-source embedding function
embedding_function = SentenceTransformerEmbeddings(model_name="all-mpnet-base-v2")
current_directory = os.path.dirname("__file__")
# load it into Chroma and save it to disk
db = Chroma.from_documents(chunks, embedding_function, collection_name="groups_collection",
persist_directory=r"\rag_with_agent_chroma_db")
retriever = db.as_retriever(search_kwargs={"k": 5})
tool = create_retriever_tool(
retriever,
"search_state_of_union",
"Searches and returns documents regarding the state-of-the-union.",
)
tools = [tool]
llm = AzureChatOpenAI(
deployment_name='gtp35turbo',
model_name='gpt-35-turbo',
openai_api_key=AZURE_OPENAI_API_KEY,
openai_api_version='2023-03-15-preview',
openai_api_base='https://azureft.openai.azure.com/',
openai_api_type='azure',
streaming=True,
verbose=True
)
agent_executor = create_conversational_retrieval_agent(llm, tools, verbose=True, remember_intermediate_steps=True,
memory_key="chat_history")
result = agent_executor({"input": "hi, im bob"})
print(result["output"])问题解决：
I tried multiple including the answers mentioned above. But did not work. I even tried to degrade, and upgrade llm version.
我尝试了包括上面提到的多种方法，但都没有成功。我甚至尝试降级和升级LLM（大型语言模型）的版本。
Finally, the following code to initialize the agent worked for me with the current version of llm
最后，以下代码使用当前版本的LLM（大型语言模型）来初始化代理对我起作用了。
conversational_agent = initialize_agent(
agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
tools=tools,
llm=llm,
max_iterations=10,
handle_parsing_errors=True,
early_stopping_method="generate",
memory=memory,
verbose=True,
)
