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Update Cypher QA prompt (#5173)

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# Improve Cypher QA prompt

The current QA prompt is optimized for networkX answer generation, which
returns all the possible triples.
However, Cypher search is a bit more focused and doesn't necessary
return all the context information.
Due to that reason, the model sometimes refuses to generate an answer
even though the information is provided:

![Screenshot from 2023-05-24
08-36-23](https://github.com/hwchase17/langchain/assets/19948365/351cf9c1-2567-447c-91fd-284ae3fa1ccf)


To fix this issue, I have updated the prompt. Interestingly, I tried
many variations with less instructions and they didn't work properly.
However, the current fix works nicely.
![Screenshot from 2023-05-24
08-37-25](https://github.com/hwchase17/langchain/assets/19948365/fc830603-e6ec-4a23-8a86-eaf572996014)
This commit is contained in:
Tomaz Bratanic 2023-05-24 17:31:30 +02:00 committed by GitHub
parent aa14e223ee
commit fd866d1801
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2 changed files with 15 additions and 2 deletions
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4
langchain/chains/graph_qa/cypher.py
View File

@ -8,7 +8,7 @@ from pydantic import Field
from langchain.base_language import BaseLanguageModel
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.chains.base import Chain
from langchain.chains.graph_qa.prompts import CYPHER_GENERATION_PROMPT, PROMPT
from langchain.chains.graph_qa.prompts import CYPHER_GENERATION_PROMPT, CYPHER_QA_PROMPT
from langchain.chains.llm import LLMChain
from langchain.graphs.neo4j_graph import Neo4jGraph
from langchain.prompts.base import BasePromptTemplate
@ -45,7 +45,7 @@ class GraphCypherQAChain(Chain):
cls,
llm: BaseLanguageModel,
*,
qa_prompt: BasePromptTemplate = PROMPT,
qa_prompt: BasePromptTemplate = CYPHER_QA_PROMPT,
cypher_prompt: BasePromptTemplate = CYPHER_GENERATION_PROMPT,
**kwargs: Any,
) -> GraphCypherQAChain:

13
langchain/chains/graph_qa/prompts.py
View File

@ -48,3 +48,16 @@ The question is:
CYPHER_GENERATION_PROMPT = PromptTemplate(
input_variables=["schema", "question"], template=CYPHER_GENERATION_TEMPLATE
)
CYPHER_QA_TEMPLATE = """You are an assistant that helps to form nice and human understandable answers.
The information part contains the provided information that you can use to construct an answer.
The provided information is authorative, you must never doubt it or try to use your internal knowledge to correct it.
Make it sound like the information are coming from an AI assistant, but don't add any information.
Information:
{context}
Question: {question}
Helpful Answer:"""
CYPHER_QA_PROMPT = PromptTemplate(
input_variables=["context", "question"], template=CYPHER_QA_TEMPLATE
)