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2 weeks ago @Royisaboy Hey there! I'm here to help you with any bugs, questions, or contributions you might have. Let's get to the bottom of this together.
To resolve the ValueError: Single '}' encountered in format string when using pydantic response with the chat engine in LlamaIndex version 0.10.36, you need to ensure that any braces in your strings are properly escaped. The provided code already includes a utility function _escape_braces that handles this.
You should use the _escape_braces function to escape braces in your chat messages before they are processed. This function is already being used in the _escape_json function, which is applied to the messages in the chat and astream_chat methods.
Here is the relevant part of the code that shows how _escape_braces is used:
def _escape_braces(text: str) -> str:
"""
Escape braces in text.
Only captures template variables, skips already escaped braces.
"""
def replace(match):
if match.group(0).startswith("{{") and match.group(0).endswith("}}"):
return match.group(0) # Already escaped, return as is
return "{{" + match.group(1) + "}}"
pattern = r"(?<!\{)\{([^{}]+?)\}(?!\})"
return re.sub(pattern, replace, text)
def _escape_json(messages: Sequence[ChatMessage]) -> Sequence[ChatMessage]:
"""Escape JSON in messages."""
new_messages = []
for message in messages:
if isinstance(message.content, str):
escaped_msg = _escape_braces(message.content)
new_messages.append(
ChatMessage(
role=message.role,
content=escaped_msg,
additional_kwargs=message.additional_kwargs,
)
)
else:
new_messages.append(message)
return new_messagesIn the chat method, _escape_json is called to escape the braces in the messages:
@llm_chat_callback()
def chat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> ChatResponse:
"""Chat endpoint for LLM."""
chat_prompt = ChatPromptTemplate(message_templates=_escape_json(messages))
output = self.llm.structured_predict(
output_cls=self.output_cls, prompt=chat_prompt
)
return ChatResponse(
message=ChatMessage(
role=MessageRole.ASSISTANT, content=output.model_dump_json()
),
raw=output,
)Ensure that your messages are passed through _escape_json before being used in the chat engine to avoid the ValueError [1].
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nerdai
Royisaboy
Hkllopp
Bug Description
I'm trying to get pydantic response with chat engine but it threw errors. i tried different versions of llamaindex but none of them worked.
Version
0.10.36
Steps to Reproduce
!pip install llama-index-vector-stores-pinecone==0.1.7 pinecone-client==3.2.2 llama-index-embeddings-openai !pip install llama-index==0.10.36
from llama_index.llms.openai import OpenAI as llama_index_openai import openai from llama_index.embeddings.openai import OpenAIEmbedding from pinecone import Pinecone from llama_index.vector_stores.pinecone import PineconeVectorStore from llama_index.core import ( VectorStoreIndex ) from typing import List from pydantic.v1 import BaseModel, Field
class Movie(BaseModel): """Object representing a single movie."""
name: str = Field(..., description="Name of the movie.") year: int = Field(..., description="Year of the movie.")
class Movies(BaseModel): """Object representing a list of movies."""
movies: List[Movie] = Field(..., description="List of movies.")
openai.api_key = "XXX" embed_model = OpenAIEmbedding(model="text-embedding-3-small")
llm = llama_index_openai(temperature=0.1, model="gpt-4o") pc = Pinecone(api_key="XXX") pinecone_index = pc.Index("quick_start") vector_store = PineconeVectorStore(pinecone_index=pinecone_index) loaded_index = VectorStoreIndex.from_vector_store(vector_store=vector_store, embed_model=embed_model) sllm = llm.as_structured_llm(Movies) query_engine = loaded_index.as_chat_engine( chat_mode="context", similarity_top_k=5, llm=sllm ) prompt = ''' Please generate related movies to Titanic ''' response = query_engine.chat(prompt)
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