dendrebeden
commented
3 months ago Same here. Tried to run code from this notebook and got the same problem with serialization https://github.com/langchain-ai/langgraph/blob/main/examples/reflexion/reflexion.ipynb?ref=blog.langchain.dev
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[37], line 2
1 example_question = "Why is reflection useful in AI?"
----> 2 initial = first_responder.respond([HumanMessage(content=example_question)])
Cell In[34], line 30, in ResponderWithRetries.respond(self, state)
28 response = []
29 for attempt in range(3):
---> 30 response = self.runnable.invoke(
31 {"messages": state}, {"tags": [f"attempt:{attempt}"]}
32 )
33 try:
34 self.validator.invoke(response)
...
File /opt/conda/lib/python3.10/json/encoder.py:257, in JSONEncoder.iterencode(self, o, _one_shot)
252 else:
253 _iterencode = _make_iterencode(
254 markers, self.default, _encoder, self.indent, floatstr,
255 self.key_separator, self.item_separator, self.sort_keys,
256 self.skipkeys, _one_shot)
--> 257 return _iterencode(o, 0)
TypeError: Object of type ModelMetaclass is not JSON serializablePackages: langchain 0.1.20 langchain-anthropic 0.1.11 langchain-core 0.1.52 pydantic 2.7.1 pydantic_core 2.18.2
MacOS as well.
JonZeolla
lalanikarim
Checked other resources
Example Code
I'm using this simple code and its returning an error. I cheked the documentation and the example is something similar to what I'm trying to do.
Error Message and Stack Trace (if applicable)
Description
I'm trying to run an example from langgraph using local Ollama. The only way I've found to use with structured output is by using Ollama Functions but it trows an error.
System Info
langchain==0.1.17 langchain-community==0.0.37 langchain-core==0.1.52 langchain-experimental==0.0.58 langchain-groq==0.1.3 langchain-openai==0.1.6 langchain-text-splitters==0.0.1 langchainhub==0.1.15
platform: macOS