[Bug]: NameError: name 'AgentChatResponse' is not defined in Using Meta-Llama-3-70B-Instruct with HuggingFace Inference API about llama_index HOT 6 CLOSED

It looks like the issue you're encountering with the NameError for AgentChatResponse is due to it not being imported in your script. To resolve this, you should import AgentChatResponse from the llama_index.core.chat_engine.types module by adding the following line to your script:

from llama_index.core.chat_engine.types import AgentChatResponse

This class is crucial for handling the response from an agent's chat interaction within the LlamaIndex framework, encapsulating the response text and details about the contributing sources.

Ensure that all necessary dependencies for the LlamaIndex library are installed. If you haven't already, you can install the required packages by running pip install gradio ansi2html in your terminal.

The integration of the HuggingFace Inference API with the LlamaIndex library and the Meta-Llama-3-70B-Instruct model is managed through the HuggingFaceLLM and HuggingFaceInferenceAPI classes. These abstract the details of interfacing with HuggingFace models and their inference API, so no additional steps should be necessary beyond the standard setup for the HuggingFace Inference API.

There are no known issues in the LlamaIndex library version 0.10.34 related to the recognition or functionality of AgentChatResponse. If you continue to experience issues after importing AgentChatResponse and ensuring all dependencies are installed, please provide more details for further assistance.

To continue the conversation, mention @dosu.

from llama_index.

The error message "Messages passed in must be of odd length" indicates that the function you're using expects an odd number of messages in the conversation history to ensure there's a final user message for the model to respond to. This is a specific requirement of the chat_messages_to_conversational_kwargs function within the LlamaIndex library when interfacing with conversational models. To resolve this, adjust your input to ensure that the sequence of messages (including both user and assistant messages) has an odd number, with the last message being from the user.

Regarding the NameError for AgentChatResponse, even after importing it, it's crucial to ensure that your environment is correctly set up and that it has access to the correct version of the llama_index package where AgentChatResponse is defined. Double-check the spelling and case sensitivity of your import statement to ensure it matches the definition in the llama_index package. This error suggests that the environment might not be recognizing the import correctly, possibly due to a mismatch in the installed package version or an issue with the Python environment itself.

If you're still encountering issues after making these adjustments, it might be helpful to verify the version of the LlamaIndex library you're using and ensure it's up to date. Additionally, reviewing the documentation for any updates or changes in method names, especially if you're using a method like predict_and_call, could provide further insights. Libraries and APIs can evolve, leading to changes in how functions and classes are named or how they're expected to be used.

Adjusting the number of messages to meet the odd-length requirement and ensuring your environment correctly recognizes the AgentChatResponse import should help in resolving the issues you're facing. If the problem persists, providing more details about your setup and any changes you've made could be helpful for further troubleshooting.

To continue the conversation, mention @dosu.

from llama_index.

Hey there, @AnandUgale! Fancy seeing you here again, diving into the depths of LLMs and unearthing new mysteries. 🕵️‍♂️ I'm on the case of the elusive 'AgentChatResponse' - will report back with findings shortly. Stay tuned!

from llama_index.

Might be a bug in the llm base class?

(This won't actually do anything besides using a react agent FYI)

from llama_index.

It looks like the issue you're encountering with the NameError for AgentChatResponse is due to it not being imported in your script. To resolve this, you should import AgentChatResponse from the llama_index.core.chat_engine.types module by adding the following line to your script:

from llama_index.core.chat_engine.types import AgentChatResponse

This class is crucial for handling the response from an agent's chat interaction within the LlamaIndex framework, encapsulating the response text and details about the contributing sources.

Ensure that all necessary dependencies for the LlamaIndex library are installed. If you haven't already, you can install the required packages by running pip install gradio ansi2html in your terminal.

The integration of the HuggingFace Inference API with the LlamaIndex library and the Meta-Llama-3-70B-Instruct model is managed through the HuggingFaceLLM and HuggingFaceInferenceAPI classes. These abstract the details of interfacing with HuggingFace models and their inference API, so no additional steps should be necessary beyond the standard setup for the HuggingFace Inference API.

There are no known issues in the LlamaIndex library version 0.10.34 related to the recognition or functionality of AgentChatResponse. If you continue to experience issues after importing AgentChatResponse and ensuring all dependencies are installed, please provide more details for further assistance.

Details

To continue the conversation, mention @dosu.

Nope, by importing AgentChatResponse, it hasn't resolved the issue.

Error is:

NotImplementedError Traceback (most recent call last)
File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\core\llms\llm.py:609, in LLM.predict_and_call(self, tools, user_msg, chat_history, verbose, **kwargs)
608 try:
--> 609 output = worker.run_step(step, task).output
611 # react agent worker inserts a "Observation: " prefix to the response

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\core\callbacks\utils.py:41, in trace_method..decorator..wrapper(self, *args, **kwargs)
40 with callback_manager.as_trace(trace_id):
---> 41 return func(self, *args, **kwargs)

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\core\agent\react\step.py:744, in ReActAgentWorker.run_step(self, step, task, **kwargs)
743 """Run step."""
--> 744 return self._run_step(step, task)

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\core\agent\react\step.py:539, in ReActAgentWorker._run_step(self, step, task)
538 # send prompt
--> 539 chat_response = self._llm.chat(input_chat)
540 # given react prompt outputs, call tools or return response

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\llms\huggingface\base.py:631, in HuggingFaceInferenceAPI.chat(self, messages, **kwargs)
629 if self.task == "conversational" or self.task is None:
630 output: "ConversationalOutput" = self._sync_client.conversational(
--> 631 **{**chat_messages_to_conversational_kwargs(messages), **kwargs}
632 )
633 return ChatResponse(
634 message=ChatMessage(
635 role=MessageRole.ASSISTANT, content=output["generated_text"]
636 )
637 )

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\llms\huggingface\base.py:436, in chat_messages_to_conversational_kwargs(messages)
435 if len(messages) % 2 != 1:
--> 436 raise NotImplementedError("Messages passed in must be of odd length.")
437 last_message = messages[-1]

NotImplementedError: Messages passed in must be of odd length.

During handling of the above exception, another exception occurred:

NameError Traceback (most recent call last)
Cell In[7], line 1
----> 1 response = llm.predict_and_call(
2 [add_tool, mystery_tool],
3 "Tell me the output of the mystery function on 2 and 9",
4 verbose=True
5 )
6 print(str(response))

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\core\instrumentation\dispatcher.py:274, in Dispatcher.span..wrapper(func, instance, args, kwargs)
270 self.span_enter(
271 id_=id_, bound_args=bound_args, instance=instance, parent_id=parent_id
272 )
273 try:
--> 274 result = func(*args, **kwargs)
275 except BaseException as e:
276 self.event(SpanDropEvent(span_id=id_, err_str=str(e)))

File ~\AppData\Local\anaconda3\envs\llm_framework\lib\site-packages\llama_index\core\llms\llm.py:615, in LLM.predict_and_call(self, tools, user_msg, chat_history, verbose, **kwargs)
613 output.response = output.response.replace("Observation: ", "")
614 except Exception as e:
--> 615 output = AgentChatResponse(
616 response="An error occurred while running the tool: " + str(e),
617 sources=[],
618 )
620 return output

NameError: name 'AgentChatResponse' is not defined

from llama_index.

@AnandUgale I meant in the source code of the framework. I made a PR

from llama_index.