mirror of
https://github.com/hwchase17/langchain
synced 2024-11-04 06:00:26 +00:00
ecf8042a10
A template with JSON-based agent using Mixtral via Ollama. --------- Co-authored-by: Erick Friis <erick@langchain.dev>
85 lines
2.4 KiB
Python
85 lines
2.4 KiB
Python
from typing import Dict, List
|
|
|
|
from langchain_community.graphs import Neo4jGraph
|
|
|
|
graph = Neo4jGraph()
|
|
|
|
|
|
def get_user_id() -> int:
|
|
"""
|
|
Placeholder for a function that would normally retrieve
|
|
a user's ID
|
|
"""
|
|
return 1
|
|
|
|
|
|
def remove_lucene_chars(text: str) -> str:
|
|
"""Remove Lucene special characters"""
|
|
special_chars = [
|
|
"+",
|
|
"-",
|
|
"&",
|
|
"|",
|
|
"!",
|
|
"(",
|
|
")",
|
|
"{",
|
|
"}",
|
|
"[",
|
|
"]",
|
|
"^",
|
|
'"',
|
|
"~",
|
|
"*",
|
|
"?",
|
|
":",
|
|
"\\",
|
|
]
|
|
for char in special_chars:
|
|
if char in text:
|
|
text = text.replace(char, " ")
|
|
return text.strip()
|
|
|
|
|
|
def generate_full_text_query(input: str) -> str:
|
|
"""
|
|
Generate a full-text search query for a given input string.
|
|
|
|
This function constructs a query string suitable for a full-text search.
|
|
It processes the input string by splitting it into words and appending a
|
|
similarity threshold (~0.8) to each word, then combines them using the AND
|
|
operator. Useful for mapping movies and people from user questions
|
|
to database values, and allows for some misspelings.
|
|
"""
|
|
full_text_query = ""
|
|
words = [el for el in remove_lucene_chars(input).split() if el]
|
|
for word in words[:-1]:
|
|
full_text_query += f" {word}~0.8 AND"
|
|
full_text_query += f" {words[-1]}~0.8"
|
|
return full_text_query.strip()
|
|
|
|
|
|
candidate_query = """
|
|
CALL db.index.fulltext.queryNodes($index, $fulltextQuery, {limit: $limit})
|
|
YIELD node
|
|
RETURN coalesce(node.name, node.title) AS candidate,
|
|
[el in labels(node) WHERE el IN ['Person', 'Movie'] | el][0] AS label
|
|
"""
|
|
|
|
|
|
def get_candidates(input: str, type: str, limit: int = 3) -> List[Dict[str, str]]:
|
|
"""
|
|
Retrieve a list of candidate entities from database based on the input string.
|
|
|
|
This function queries the Neo4j database using a full-text search. It takes the
|
|
input string, generates a full-text query, and executes this query against the
|
|
specified index in the database. The function returns a list of candidates
|
|
matching the query, with each candidate being a dictionary containing their name
|
|
(or title) and label (either 'Person' or 'Movie').
|
|
"""
|
|
ft_query = generate_full_text_query(input)
|
|
candidates = graph.query(
|
|
candidate_query, {"fulltextQuery": ft_query, "index": type, "limit": limit}
|
|
)
|
|
return candidates
|