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chore: import upstream snapshot with attribution
2026-07-13 13:24:08 +08:00

45 lines
1.3 KiB
Python

from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
def call_api(prompt, options, context):
"""
A LangChain-based customer service agent for Acme Corp.
"""
# Initialize the LLM
llm = ChatOpenAI(model_name="gpt-5-nano")
# Load system message
import os
script_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(script_dir, "system_message.txt"), "r") as f:
system_message = f.read()
# Create the prompt template using ChatPromptTemplate
prompt_template = ChatPromptTemplate.from_messages(
[("system", system_message), ("user", "{question}")]
)
# Create the chain using LCEL
chain = prompt_template | llm
try:
# Execute the chain
result = chain.invoke({"question": prompt})
# Extract text output
output_text = result.content if hasattr(result, "content") else str(result)
# Calculate token usage
return {
"output": output_text,
"tokenUsage": {
"total": llm.get_num_tokens(prompt + output_text),
"prompt": llm.get_num_tokens(prompt),
"completion": llm.get_num_tokens(output_text),
},
}
except Exception as e:
return {"error": str(e), "output": None}