agents.py modified

agents.py

@@ -5,7 +5,9 @@ from langgraph.graph import START, StateGraph, MessagesState
 from langgraph.prebuilt import tools_condition
 from langgraph.prebuilt import ToolNode
 from langchain_google_genai import ChatGoogleGenerativeAI
+# from langchain_openai import ChatOpenAI
 from langchain.agents import initialize_agent, Tool
+from langchain_groq import ChatGroq
 from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint, HuggingFaceEmbeddings
 from langchain_community.tools.tavily_search import TavilySearchResults
 from langchain_community.document_loaders import WikipediaLoader
@@ -108,7 +110,26 @@ def arvix_search(query: str) -> str:
 
 # load the system prompt from the file
 with open("system_prompt.txt", "r", encoding="utf-8") as f:
-    system_prompt = f.read()
+    # system_prompt = f.read()
+    system_prompt='''
+You are a helpful assistant tasked with answering questions using a set of tools.
+
+Your final answer must strictly follow this format:
+FINAL ANSWER: [ANSWER]
+
+Only write the answer in that exact format. Do not explain anything. Do not include any other text.
+
+If you are provided with a similar question and its final answer, and the current question is **exactly the same**, then simply return the same final answer without using any tools.
+
+Only use tools if the current question is different from the similar one.
+
+Examples:
+- FINAL ANSWER: FunkMonk
+- FINAL ANSWER: Paris
+- FINAL ANSWER: 128
+
+If you do not follow this format exactly, your response will be considered incorrect.
+'''
 
 # System message
 sys_msg = SystemMessage(content=system_prompt)
@@ -146,10 +167,25 @@ tools = [
 # Build graph function
 def build_graph(provider: str = "groq"):
     """Build the graph"""
-
-    # Google Gemini
-    llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
-
+    # Load environment variables from .env file
+    if provider == "google":
+        # Google Gemini
+        llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
+    elif provider == "groq":
+        # Groq https://console.groq.com/docs/models
+        llm = ChatGroq(model="qwen-qwq-32b", temperature=0) # optional : qwen-qwq-32b gemma2-9b-it
+    # elif provider == "openai":
+    #     # OpenAI
+    #     llm = ChatOpenAI(model="gpt-4", temperature=0)
+    elif provider == "huggingface":
+        llm = ChatHuggingFace(
+            llm=HuggingFaceEndpoint(
+                url="https://api-inference.huggingface.co/models/Meta-DeepLearning/llama-2-7b-chat-hf",
+                temperature=0,
+            ),
+        )
+    else:
+        raise ValueError("Invalid provider. Choose 'google', 'groq' or 'huggingface'.")
     # Bind tools to LLM
     llm_with_tools = llm.bind_tools(tools)