Update agent.py

agent.py

@@ -0,0 +1,100 @@
+import os
+from langchain.agents import AgentExecutor, create_react_agent
+from langchain.tools import tool
+from langchain.prompts import PromptTemplate
+from langchain_openai import ChatOpenAI  # OpenAI-compatible for Groq API
+from ddgs import DDGS  # Updated DuckDuckGo Search
+from dotenv import load_dotenv
+import re
+import json
+
+# Load environment variables
+load_dotenv()
+
+# --- Define Tools ---
+@tool
+def python_code_executor(code: str) -> str:
+    """Execute Python code and return the result as a string. Use for calculations or data processing."""
+    try:
+        local_vars = {}
+        exec(code, {}, local_vars)
+        return str(local_vars.get("result", "No result defined. Set 'result' variable."))
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+@tool
+def download_file(url: str) -> str:
+    """Download a file from URL and return its content (text if possible)."""
+    try:
+        response = requests.get(url, timeout=10)
+        response.raise_for_status()
+        return response.text[:1000]  # Truncate for brevity
+    except Exception as e:
+        return f"Error downloading: {str(e)}"
+
+@tool
+def duckduckgo_search(query: str) -> str:
+    """Perform a DuckDuckGo search and return top results as a short summary."""
+    try:
+        with DDGS() as ddgs:
+            results = list(ddgs.text(query, max_results=3))
+        if not results:
+            return "No good results found."
+        return json.dumps([{"title": r["title"], "snippet": r["body"]} for r in results])
+    except Exception as e:
+        return f"Search error: {str(e)}"
+
+
+# load the system prompt from the file
+with open("system_prompt.txt", "r", encoding="utf-8") as f:
+    system_prompt = f.read()
+
+# System message
+sys_msg = SystemMessage(content=system_prompt)
+
+tools = [
+    python_code_executor,
+    download_file,
+    duckduckgo_search,
+]
+
+# Build graph function
+#def build_graph(provider: str = "huggingface"):
+def build_graph(provider: str = "google"):
+    """Build the graph"""
+    # 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 == "huggingface":
+        llm = ChatHuggingFace(
+            llm=HuggingFaceEndpoint(
+                repo_id = "Qwen/Qwen2.5-Coder-32B-Instruct"
+            ),
+        )
+    else:
+        raise ValueError("Invalid provider. Choose 'google', 'groq' or 'huggingface'.")
+    
+# Bind tools to LLM
+llm_with_tools = llm.bind_tools(tools)
+
+        # Node
+def assistant(state: MessagesState):
+    """Assistant node"""
+    return {"messages": [llm_with_tools.invoke([sys_msg] + state["messages"])]}
+
+builder = StateGraph(MessagesState)
+builder.add_node("assistant", assistant)
+builder.add_node("tools", ToolNode(tools))
+builder.add_edge(START, "assistant")
+builder.add_conditional_edges(
+    "assistant",
+    tools_condition,
+)
+builder.add_edge("tools", "assistant")
+
+# Compile graph
+return builder.compile()