Agent Executor Error code: 404

[shamussim-ai]

System Info

Python 3.10.10

langchain 0.0.350
langchain-community 0.0.3
langchain-core 0.1.1

Windows Machine
VSCode

Who can help?

No response

Information

• The official example notebooks/scripts
• My own modified scripts

Related Components

• LLMs/Chat Models
• Embedding Models
• Prompts / Prompt Templates / Prompt Selectors
• Output Parsers
• Document Loaders
• Vector Stores / Retrievers
• Memory
• Agents / Agent Executors
• Tools / Toolkits
• Chains
• Callbacks/Tracing
• Async

Reproduction

Here I am pretty much following the official tutorial with a modification where I used Pinecone Vector DB instead of Chroma.
Tutorial link- https://python.langchain.com/docs/use_cases/question_answering/conversational_retrieval_agents#the-prompt-template
Code

loader = DirectoryLoader('/home/azureuser/cloudfiles/code/Users/shamus/Chat With Your Data /docs/CPG', glob="./*.pdf", loader_cls=PyPDFLoader)

documents = loader.load()

text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
texts = text_splitter.split_documents(documents)
pinecone.init(
        api_key = PINECONE_API_KEY,
        environment = PINECONE_ENV
)

#Use Pinecone
index_name = 'openai-ada'

from langchain.embeddings import AzureOpenAIEmbeddings

embeddings = AzureOpenAIEmbeddings(
    azure_deployment="embedding",
    openai_api_version="2023-05-15", #or 2023-12-01-preview
)

docsearch = Pinecone.from_documents(texts, embeddings, index_name = index_name)
retriever = docsearch.as_retriever(include_metadata=True, metadata_key = 'source', search_type="mmr")
from langchain.agents.agent_toolkits.conversational_retrieval.tool import create_retriever_tool
tool = create_retriever_tool(
    retriever,
    name="Cardiology_CPG", #has some naming convention:1 to 64 characters long,only contain alphanumeric characters, (_), (-)
    description="Searches and returns documents regarding CPG Cardiology in Malaysia.",
)
tools = [tool]
from langchain.agents.agent_toolkits import create_conversational_retrieval_agent

chat_llm = AzureChatOpenAI(
    openai_api_version="2023-12-01-preview",
    azure_deployment="Test1",
    temperature=0
)

agent_executor = create_conversational_retrieval_agent(chat_llm, tools=tools, verbose=True)
result = agent_executor({"input": "Hi, what are the key latest updates of Clinical Practice Guidelines in Cardiology this year?"})

As part of my sanity check. I ran the following which all returned intelligible outputs.

docs = retriever.get_relevant_documents("What are the latest guidelines in CPG Cardiology in Malaysia?")
print(docs)
# Check the properties of the first tool (assuming only one tool is added)
if tools:
    first_tool = tools[0]
    print(f"Tool Name: {first_tool.name}")
    print(f"Tool Description: {first_tool.description}")

chat_llm.predict("Hello world!")

Error

> Entering new AgentExecutor chain...
---------------------------------------------------------------------------
NotFoundError                             Traceback (most recent call last)
Cell In[129], [line 1](vscode-notebook-cell:?execution_count=129&line=1)
----> [1](vscode-notebook-cell:?execution_count=129&line=1) result = agent_executor({"input": "Hi, what are the key latest updates of Clinical Practice Guidelines in Cardiology this year?"})

File /anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:312, in Chain.__call__(self, inputs, return_only_outputs, callbacks, tags, metadata, run_name, include_run_info)
    [310](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:310) except BaseException as e:
    [311](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:311)     run_manager.on_chain_error(e)
--> [312](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:312)     raise e
    [313](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:313) run_manager.on_chain_end(outputs)
    [314](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:314) final_outputs: Dict[str, Any] = self.prep_outputs(
    [315](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:315)     inputs, outputs, return_only_outputs
    [316](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:316) )

File /anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:306, in Chain.__call__(self, inputs, return_only_outputs, callbacks, tags, metadata, run_name, include_run_info)
    [299](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:299) run_manager = callback_manager.on_chain_start(
    [300](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:300)     dumpd(self),
    [301](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:301)     inputs,
    [302](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:302)     name=run_name,
    [303](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:303) )
    [304](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:304) try:
    [305](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:305)     outputs = (
--> [306](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:306)         self._call(inputs, run_manager=run_manager)
    [307](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:307)         if new_arg_supported
    [308](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/langchain/chains/base.py:308)         else self._call(inputs)
...
   (...)
    [937](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/openai/_base_client.py:937)     stream_cls=stream_cls,
    [938](https://vscode-remote+amlext-002b2f737562736372697074696f6e732f31653065376137362d306236362d343632622d613831352d3733363863633464363832312f7265736f7572636547726f7570732f47656e657261746976655f41492f70726f7669646572732f4d6963726f736f66742e4d616368696e654c6561726e696e6753657276696365732f776f726b7370616365732f6c6c616d612f636f6d70757465732f7368616d75732d637075.vscode-resource.vscode-cdn.net/anaconda/envs/langchain/lib/python3.10/site-packages/openai/_base_client.py:938) )

NotFoundError: Error code: 404 - {'error': {'message': 'Unrecognized request argument supplied: functions', 'type': 'invalid_request_error', 'param': None, 'code': None}}

My understanding of the error is that something is not working with the 'tools'. Although I cant work out why because the retriever is working just fine. Appreciate any advise on this.

Expected behavior

Expect 'normal' chatbot output

[dosubot]

🤖

Hey @shamussim-ai! 👋

I'm Dosu, a friendly bot here to assist you with your LangChain concerns. While we're waiting for a human maintainer, feel free to ask me anything regarding bugs, questions, or even becoming a contributor. Looking forward to helping you out! 😊

Based on the error message you provided, it seems like the issue might be related to the agent_executor function. The error message indicates that an unrecognized request argument 'functions' was supplied. However, according to the LangChain codebase, the agent_executor function does not take a parameter named 'functions'.

The agent_executor function expects the following parameters:

def load_agent_executor(
    llm: BaseLanguageModel,
    tools: List[BaseTool],
    verbose: bool = False,
    include_task_in_prompt: bool = False,
) -> ChainExecutor:

Here, llm is an instance of BaseLanguageModel, tools is a list of BaseTool instances, verbose is a boolean that defaults to False, and include_task_in_prompt is also a boolean that defaults to False.

Given this, I would recommend checking the arguments you are passing to the agent_executor function. Make sure that you are not passing an argument named 'functions', and that the arguments you are passing match the expected parameters.

If the issue persists, could you please provide more details about the error, such as the line of code causing the error and the full error message? This will help in diagnosing the problem more accurately.

You can find more information about the agent_executor function in the LangChain codebase.

I hope this helps! If you have any more questions, feel free to ask.

-Dosu

Sources

• libs/langchain/langchain/agents/agent_toolkits/python/init.py
• libs/experimental/langchain_experimental/plan_and_execute/executors/agent_executor.py

---

This response is meant to be useful and save you time. It is not meant to be a precise solution, but rather a starting point for your own research.

Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.

If you want to continue the conversation, start your reply with @dosu-bot.

[shamussim-ai]

Seems like tthis was caused by a Azure Chat OpenAI issues.