Create Agent.py

Agent.py

@@ -0,0 +1,78 @@
+from langchain.tools import Tool
+from langraph.graph import StateGraph, END
+from langchain.agents import AgentExecutor, initialize_agent
+from langchain.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory
+from langchain_community.tools import DuckDuckGoSearchRun
+
+def calculator_tool(input: str) -> str:
+    try:
+        return str(eval(input))
+    except Exception as e:
+        return f"Error: {e}"
+
+calc_tool = Tool(name="Calculator", func=calculator_tool, description="Perform basic math.")
+search_tool = DuckDuckGoSearchRun()
+
+import wikipedia
+def search_wikipedia(query: str) -> str:
+    try:
+        return wikipedia.summary(query, sentences=3)
+    except Exception as e:
+        return f"Wikipedia Error: {str(e)}"
+
+wikipedia_tool = Tool(
+    name="Wikipedia Search",
+    func=search_wikipedia,
+    description="Use this to search and summarize articles from Wikipedia."
+)
+
+import arxiv
+def search_arxiv(query: str) -> str:
+    try:
+        search = arxiv.Search(
+            query=query,
+            max_results=1,
+            sort_by=arxiv.SortCriterion.Relevance
+        )
+        for result in search.results():
+            return f"{result.title}\n\n{result.summary}\n\nPDF: {result.pdf_url}"
+        return "No relevant arXiv papers found."
+    except Exception as e:
+        return f"arXiv Error: {str(e)}"
+
+arxiv_tool = Tool(
+    name="arXiv Search",
+    func=search_arxiv,
+    description="Search for scientific papers on arXiv.org"
+)
+class GaiaState:
+    input: str
+    intermediate_steps: list = []
+    output: str = ""
+
+# Initialize tools and agent
+llm = ChatOpenAI(temperature=0)
+tools = [calc_tool, search_tool, arxiv_tool, wikipedia_tool]  # Add more tools as needed
+
+agent = initialize_agent(
+    tools=tools,
+    llm=llm,
+    agent_type="openai-functions",
+    verbose=True
+)
+
+def run_agent(state: GaiaState) -> GaiaState:
+    result = agent.run(state.input)
+    state.output = result
+    state.intermediate_steps.append(result)
+    return state
+    
+graph = StateGraph(GaiaState)
+
+graph.add_node("run_agent", run_agent)
+graph.set_entry_point("run_agent")
+graph.add_edge("run_agent", END)
+
+# Compile the graph
+app = graph.compile()