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"""Question answering over a graph.""" | |
from __future__ import annotations | |
import re | |
from typing import Any, Dict, List, Optional | |
from langchain_core.prompts import BasePromptTemplate | |
from langchain_core.pydantic_v1 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 ( | |
AQL_FIX_PROMPT, | |
AQL_GENERATION_PROMPT, | |
AQL_QA_PROMPT, | |
) | |
from langchain.chains.llm import LLMChain | |
from langchain.graphs.arangodb_graph import ArangoGraph | |
class ArangoGraphQAChain(Chain): | |
"""Chain for question-answering against a graph by generating AQL statements. | |
*Security note*: Make sure that the database connection uses credentials | |
that are narrowly-scoped to only include necessary permissions. | |
Failure to do so may result in data corruption or loss, since the calling | |
code may attempt commands that would result in deletion, mutation | |
of data if appropriately prompted or reading sensitive data if such | |
data is present in the database. | |
The best way to guard against such negative outcomes is to (as appropriate) | |
limit the permissions granted to the credentials used with this tool. | |
See https://python.langchain.com/docs/security for more information. | |
""" | |
graph: ArangoGraph = Field(exclude=True) | |
aql_generation_chain: LLMChain | |
aql_fix_chain: LLMChain | |
qa_chain: LLMChain | |
input_key: str = "query" #: :meta private: | |
output_key: str = "result" #: :meta private: | |
# Specifies the maximum number of AQL Query Results to return | |
top_k: int = 10 | |
# Specifies the set of AQL Query Examples that promote few-shot-learning | |
aql_examples: str = "" | |
# Specify whether to return the AQL Query in the output dictionary | |
return_aql_query: bool = False | |
# Specify whether to return the AQL JSON Result in the output dictionary | |
return_aql_result: bool = False | |
# Specify the maximum amount of AQL Generation attempts that should be made | |
max_aql_generation_attempts: int = 3 | |
def input_keys(self) -> List[str]: | |
return [self.input_key] | |
def output_keys(self) -> List[str]: | |
return [self.output_key] | |
def _chain_type(self) -> str: | |
return "graph_aql_chain" | |
def from_llm( | |
cls, | |
llm: BaseLanguageModel, | |
*, | |
qa_prompt: BasePromptTemplate = AQL_QA_PROMPT, | |
aql_generation_prompt: BasePromptTemplate = AQL_GENERATION_PROMPT, | |
aql_fix_prompt: BasePromptTemplate = AQL_FIX_PROMPT, | |
**kwargs: Any, | |
) -> ArangoGraphQAChain: | |
"""Initialize from LLM.""" | |
qa_chain = LLMChain(llm=llm, prompt=qa_prompt) | |
aql_generation_chain = LLMChain(llm=llm, prompt=aql_generation_prompt) | |
aql_fix_chain = LLMChain(llm=llm, prompt=aql_fix_prompt) | |
return cls( | |
qa_chain=qa_chain, | |
aql_generation_chain=aql_generation_chain, | |
aql_fix_chain=aql_fix_chain, | |
**kwargs, | |
) | |
def _call( | |
self, | |
inputs: Dict[str, Any], | |
run_manager: Optional[CallbackManagerForChainRun] = None, | |
) -> Dict[str, Any]: | |
""" | |
Generate an AQL statement from user input, use it retrieve a response | |
from an ArangoDB Database instance, and respond to the user input | |
in natural language. | |
Users can modify the following ArangoGraphQAChain Class Variables: | |
:var top_k: The maximum number of AQL Query Results to return | |
:type top_k: int | |
:var aql_examples: A set of AQL Query Examples that are passed to | |
the AQL Generation Prompt Template to promote few-shot-learning. | |
Defaults to an empty string. | |
:type aql_examples: str | |
:var return_aql_query: Whether to return the AQL Query in the | |
output dictionary. Defaults to False. | |
:type return_aql_query: bool | |
:var return_aql_result: Whether to return the AQL Query in the | |
output dictionary. Defaults to False | |
:type return_aql_result: bool | |
:var max_aql_generation_attempts: The maximum amount of AQL | |
Generation attempts to be made prior to raising the last | |
AQL Query Execution Error. Defaults to 3. | |
:type max_aql_generation_attempts: int | |
""" | |
_run_manager = run_manager or CallbackManagerForChainRun.get_noop_manager() | |
callbacks = _run_manager.get_child() | |
user_input = inputs[self.input_key] | |
######################### | |
# Generate AQL Query # | |
aql_generation_output = self.aql_generation_chain.run( | |
{ | |
"adb_schema": self.graph.schema, | |
"aql_examples": self.aql_examples, | |
"user_input": user_input, | |
}, | |
callbacks=callbacks, | |
) | |
######################### | |
aql_query = "" | |
aql_error = "" | |
aql_result = None | |
aql_generation_attempt = 1 | |
while ( | |
aql_result is None | |
and aql_generation_attempt < self.max_aql_generation_attempts + 1 | |
): | |
##################### | |
# Extract AQL Query # | |
pattern = r"```(?i:aql)?(.*?)```" | |
matches = re.findall(pattern, aql_generation_output, re.DOTALL) | |
if not matches: | |
_run_manager.on_text( | |
"Invalid Response: ", end="\n", verbose=self.verbose | |
) | |
_run_manager.on_text( | |
aql_generation_output, color="red", end="\n", verbose=self.verbose | |
) | |
raise ValueError(f"Response is Invalid: {aql_generation_output}") | |
aql_query = matches[0] | |
##################### | |
_run_manager.on_text( | |
f"AQL Query ({aql_generation_attempt}):", verbose=self.verbose | |
) | |
_run_manager.on_text( | |
aql_query, color="green", end="\n", verbose=self.verbose | |
) | |
##################### | |
# Execute AQL Query # | |
from arango import AQLQueryExecuteError | |
try: | |
aql_result = self.graph.query(aql_query, self.top_k) | |
except AQLQueryExecuteError as e: | |
aql_error = e.error_message | |
_run_manager.on_text( | |
"AQL Query Execution Error: ", end="\n", verbose=self.verbose | |
) | |
_run_manager.on_text( | |
aql_error, color="yellow", end="\n\n", verbose=self.verbose | |
) | |
######################## | |
# Retry AQL Generation # | |
aql_generation_output = self.aql_fix_chain.run( | |
{ | |
"adb_schema": self.graph.schema, | |
"aql_query": aql_query, | |
"aql_error": aql_error, | |
}, | |
callbacks=callbacks, | |
) | |
######################## | |
##################### | |
aql_generation_attempt += 1 | |
if aql_result is None: | |
m = f""" | |
Maximum amount of AQL Query Generation attempts reached. | |
Unable to execute the AQL Query due to the following error: | |
{aql_error} | |
""" | |
raise ValueError(m) | |
_run_manager.on_text("AQL Result:", end="\n", verbose=self.verbose) | |
_run_manager.on_text( | |
str(aql_result), color="green", end="\n", verbose=self.verbose | |
) | |
######################## | |
# Interpret AQL Result # | |
result = self.qa_chain( | |
{ | |
"adb_schema": self.graph.schema, | |
"user_input": user_input, | |
"aql_query": aql_query, | |
"aql_result": aql_result, | |
}, | |
callbacks=callbacks, | |
) | |
######################## | |
# Return results # | |
result = {self.output_key: result[self.qa_chain.output_key]} | |
if self.return_aql_query: | |
result["aql_query"] = aql_query | |
if self.return_aql_result: | |
result["aql_result"] = aql_result | |
return result | |