Update Cypher QA prompt (#5173)

# 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)

langchain/chains/graph_qa/cypher.py

@@ -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:

langchain/chains/graph_qa/prompts.py

@@ -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
+)