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import asyncio
import json
import chainlit as cl
from datetime import datetime
from utils_chain_parameters import prepare_chain_parameters
from utils_output import display_evaluation_results
from utils_voice import reply_with_voice
async def do_simulation(client, session_state, message):
if session_state.status == "active":
chain = cl.user_session.get("chain")
history = cl.user_session.get("history", [])
history.append({"role": "user", "content": message})
session_state.previous_answer = message.content
prompt_parm = prepare_chain_parameters(session_state, message, history)
session_state.queries.append(prompt_parm)
response_content = chain.invoke(prompt_parm)
json_str = response_content.content.strip('```json\n').strip('```')
try:
this_response = json.loads(json_str)
except json.JSONDecodeError as e:
print(f"JSON Decode Error: {e}")
print(response_content.content)
print(f"Error at position {e.pos}: {json_str[max(0, e.pos-10):e.pos+10]}")
this_response = {"Response": "Error receiving response from LLM"}
llm_response = this_response.get("Response", "No response from LLM")
print("LLM Response:")
print(llm_response)
session_state.llm_responses.append(this_response)
print("Next question:")
print(this_response.get("Question", "No question"))
if session_state.question != "":
session_state.responses.append({
"question_number": session_state.current_question_index,
"question": session_state.question,
"response": session_state.rep_answer,
"ground_truth": session_state.ground_truth,
"response_score": this_response.get("Score", "No score"),
"response_evaluation": this_response.get("Evaluation", "No evaluation"),
"mood_score": this_response.get("Mood Score", "No mood score"),
"overall_score": this_response.get("Overall Score", "No overall score"),
"overall_evaluation": this_response.get("Overall Evaluation", "No overall evaluation"),
})
message_to_rep = llm_response + "\n\n" + this_response.get("Question", "No question")
print("Checking to continue")
print(session_state.current_question_index)
print(len(session_state.questions))
if session_state.current_question_index < len(session_state.questions):
if session_state.do_voice:
await reply_with_voice(cl, client, message_to_rep)
else:
await cl.Message(message_to_rep).send()
# await cl.Message(this_response).send()
history.append({"role": "assistant", "content": response_content})
cl.user_session.set("history", history)
session_state.current_question_index += 1
else:
final_message = message_to_rep
conclusion = this_response.get("Conclusion", "")
if conclusion != "":
final_message = final_message + "\n\n" + conclusion
if session_state.do_voice:
await reply_with_voice(cl, client, final_message)
else:
await cl.Message(message_to_rep).send()
session_state.status = "complete"
end_time = datetime.now()
duration = end_time - session_state.start_time
duration_minutes = round(duration.total_seconds() / 60)
session_state.end_time = end_time
session_state.duration_minutes = duration_minutes
if session_state.do_evaluation:
await display_evaluation_results(cl, session_state)
else:
evaluate_actions = [
cl.Action(name="Evaluate Performance", value="evaluate", description="Evaluate Performance"),
cl.Action(name="Display Queries and Responses", value="display_llm_responses", description="Display LLM Responses")
]
await cl.Message(content="Click to evaluate", actions=evaluate_actions).send() |