chore: added pre-commit-hooks and ruff formatting for commit-hooks

lightrag/prompt.py

@@ -9,9 +9,7 @@ PROMPTS["process_tickers"] = ["⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "
 
 PROMPTS["DEFAULT_ENTITY_TYPES"] = ["organization", "person", "geo", "event"]
 
-PROMPTS[
-    "entity_extraction"
-] = """-Goal-
+PROMPTS["entity_extraction"] = """-Goal-
 Given a text document that is potentially relevant to this activity and a list of entity types, identify all entities of those types from the text and all relationships among the identified entities.
 
 -Steps-
@@ -32,7 +30,7 @@ Format each relationship as ("relationship"{tuple_delimiter}<source_entity>{tupl
 
 3. Identify high-level key words that summarize the main concepts, themes, or topics of the entire text. These should capture the overarching ideas present in the document.
 Format the content-level key words as ("content_keywords"{tuple_delimiter}<high_level_keywords>)
- 
+
 4. Return output in English as a single list of all the entities and relationships identified in steps 1 and 2. Use **{record_delimiter}** as the list delimiter.
 
 5. When finished, output {completion_delimiter}
@@ -146,9 +144,7 @@ PROMPTS[
 
 PROMPTS["fail_response"] = "Sorry, I'm not able to provide an answer to that question."
 
-PROMPTS[
-    "rag_response"
-] = """---Role---
+PROMPTS["rag_response"] = """---Role---
 
 You are a helpful assistant responding to questions about data in the tables provided.
 
@@ -241,9 +237,7 @@ Output:
 
 """
 
-PROMPTS[
-    "naive_rag_response"
-] = """You're a helpful assistant
+PROMPTS["naive_rag_response"] = """You're a helpful assistant
 Below are the knowledge you know:
 {content_data}
 ---