[update]

Agent/utils.py

@@ -11,12 +11,12 @@ from langchain_core.messages import SystemMessage, HumanMessage, AIMessage
 
 def config():
     load_dotenv()
-
+    
     # Set up Neo4J & Gemini API
     os.environ["NEO4J_URI"] = os.getenv("NEO4J_URI")
     os.environ["NEO4J_USERNAME"] = os.getenv("NEO4J_USERNAME")
     os.environ["NEO4J_PASSWORD"] = os.getenv("NEO4J_PASSWORD")
-    os.environ["GOOGLE_API_KEY"] = os.getenv("GEMINI_API_KEY")
+    os.environ["GEMINI_API_KEY"] = os.getenv("GEMINI_API_KEY")
 
 def load_prompt(filepath):
     with open(filepath, "r") as file:

utils.py

@@ -0,0 +1,67 @@
+import os
+import yaml
+from dotenv import load_dotenv
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_community.graphs import Neo4jGraph
+from langchain_core.prompts.prompt import PromptTemplate
+from langchain.chains import GraphCypherQAChain
+from langchain_core.messages import SystemMessage, HumanMessage, AIMessage
+
+def config():
+    load_dotenv()
+
+    # Set up Neo4J & Gemini API
+    os.environ["NEO4J_URI"] = os.getenv("NEO4J_URI")
+    os.environ["NEO4J_USERNAME"] = os.getenv("NEO4J_USERNAME")
+    os.environ["NEO4J_PASSWORD"] = os.getenv("NEO4J_PASSWORD")
+    os.environ["GOOGLE_API_KEY"] = os.getenv("GEMINI_API_KEY")
+
+def load_prompt(filepath):
+    with open(filepath, "r") as file:
+        prompt = yaml.safe_load(file)
+
+    return prompt
+
+def init_():
+    config()
+    graph = Neo4jGraph(enhanced_schema= True)
+    llm = ChatGoogleGenerativeAI(
+        model= "gemini-1.5-flash-latest",
+        temperature = 0
+    )
+
+    return graph, llm
+
+def get_llm_response(query):
+    # Connect to Neo4J Knowledge Graph
+    knowledge_graph, llm_chat = init_()
+    cypher_prompt = load_prompt("prompts/cypher_prompt.yaml")
+    qa_prompt = load_prompt("prompts/qa_prompt.yaml")
+
+    CYPHER_GENERATION_PROMPT = PromptTemplate(**cypher_prompt)
+    QA_GENERATION_PROMPT = PromptTemplate(**qa_prompt)
+
+    chain = GraphCypherQAChain.from_llm(
+        llm_chat, graph=knowledge_graph, verbose=True,
+        cypher_prompt= CYPHER_GENERATION_PROMPT,
+        qa_prompt= QA_GENERATION_PROMPT
+    )
+
+    return chain.invoke({"query": query})["result"]
+
+def llm_answer(message, history):
+
+
+    try:
+        response = get_llm_response(message["text"])
+    except Exception:
+        response = "Exception"
+    except Error:
+        response = "Error"
+    return response
+
+# if __name__ == "__main__":
+#     message = "Have any company recruiting jobs about Machine Learning and coresponding job titles?"
+#     history = [("What's your name?", "My name is Gemini")]
+#     resp = llm_answer(message, history)
+#     print(resp)