Create agent.py

agent.py

@@ -0,0 +1,30 @@
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain_community.llms import OpenAI as LangOpenAI
+from tools.search import web_search
+
+def load_llm():
+    return LangOpenAI(temperature=0, model_name="gpt-4")
+
+def build_prompt():
+    template = """You are a helpful research assistant. Answer the question using the context provided.
+
+Context:
+{context}
+
+Question: {question}
+Answer:"""
+    return PromptTemplate(template=template, input_variables=["question", "context"])
+
+def answer_question(question, file_context=None, do_search=False):
+    context_parts = []
+    if file_context:
+        context_parts.append(file_context)
+    if do_search:
+        context_parts.append(web_search(question))
+
+    context = "\n\n".join(context_parts) if context_parts else "N/A"
+
+    llm = load_llm()
+    chain = LLMChain(llm=llm, prompt=build_prompt())
+    return chain.run({"question": question, "context": context}).strip()