Create agent.py

agent.py

@@ -0,0 +1,54 @@
+# agent.py
+
+from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.core.tools import FunctionTool
+from langchain_community.tools import DuckDuckGoSearchRun, WikipediaQueryRun
+from langchain_experimental.tools.python.tool import PythonREPLTool
+from langchain_community.document_loaders import YoutubeLoader
+
+# Define all tool functions with type annotations
+
+def search_duckduckgo(query: str) -> str:
+    """Use DuckDuckGo to search the internet."""
+    return DuckDuckGoSearchRun().run(query)
+
+def search_wikipedia(query: str) -> str:
+    """Use Wikipedia to look up facts."""
+    return WikipediaQueryRun(api_wrapper=None).run(query)
+
+def run_python(code: str) -> str:
+    """Execute Python code and return output."""
+    return PythonREPLTool().run(code)
+
+def get_youtube_transcript(url: str) -> str:
+    """Extract transcript from YouTube video."""
+    loader = YoutubeLoader.from_youtube_url(url, add_video_info=False)
+    docs = loader.load()
+    return " ".join(doc.page_content for doc in docs)
+
+# Build tool wrappers
+TOOLS = [
+    FunctionTool.from_defaults(search_duckduckgo),
+    FunctionTool.from_defaults(search_wikipedia),
+    FunctionTool.from_defaults(run_python),
+    FunctionTool.from_defaults(get_youtube_transcript),
+]
+
+# Load LLM
+llm = HuggingFaceInferenceAPI(model_name="Qwen/Qwen2.5-Coder-32B-Instruct")
+
+# Create LlamaIndex agent
+agent = AgentWorkflow.from_tools_or_functions(
+    TOOLS,
+    llm=llm,
+    system_prompt="You are a helpful and smart AI agent that solves tasks using reasoning and external tools."
+)
+
+# Optional: support context (stateful runs)
+from llama_index.core.workflow import Context
+ctx = Context(agent)
+
+async def answer_question(question: str) -> str:
+    """Run the agent on a single question."""
+    return await agent.arun(question)