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import asyncio |
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import json |
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import chainlit as cl |
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from datetime import datetime |
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from .utils_chain_parameters import prepare_chain_parameters |
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from .utils_output import display_evaluation_results |
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from .utils_voice import reply_with_voice |
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async def do_simulation(client, session_state, message): |
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if session_state.status == "active": |
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chain = cl.user_session.get("chain") |
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history = cl.user_session.get("history", []) |
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history.append({"role": "user", "content": message}) |
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session_state.previous_answer = message.content |
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prompt_parm = prepare_chain_parameters(session_state, message, history) |
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session_state.queries.append(prompt_parm) |
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response_content = chain.invoke(prompt_parm) |
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json_str = response_content.content.strip('```json\n').strip('```') |
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try: |
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this_response = json.loads(json_str) |
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except json.JSONDecodeError as e: |
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print(f"JSON Decode Error: {e}") |
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print(response_content.content) |
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print(f"Error at position {e.pos}: {json_str[max(0, e.pos-10):e.pos+10]}") |
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this_response = {"Response": "Error receiving response from LLM"} |
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llm_response = this_response.get("Response", "No response from LLM") |
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print("LLM Response:") |
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print(llm_response) |
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session_state.llm_responses.append(this_response) |
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print("Next question:") |
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print(this_response.get("Question", "No question")) |
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if session_state.question != "": |
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session_state.responses.append({ |
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"question_number": session_state.current_question_index, |
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"question": session_state.question, |
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"response": session_state.rep_answer, |
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"ground_truth": session_state.ground_truth, |
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"response_score": this_response.get("Score", "No score"), |
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"response_evaluation": this_response.get("Evaluation", "No evaluation"), |
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"mood_score": this_response.get("Mood Score", "No mood score"), |
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"overall_score": this_response.get("Overall Score", "No overall score"), |
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"overall_evaluation": this_response.get("Overall Evaluation", "No overall evaluation"), |
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}) |
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message_to_rep = llm_response + "\n\n" + this_response.get("Question", "No question") |
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print("Checking to continue") |
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print(session_state.current_question_index) |
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print(len(session_state.questions)) |
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if session_state.current_question_index < len(session_state.questions): |
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if session_state.do_voice: |
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await reply_with_voice(cl, client, message_to_rep) |
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else: |
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await cl.Message(content=message_to_rep, author="John Smith").send() |
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history.append({"role": "assistant", "content": response_content}) |
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cl.user_session.set("history", history) |
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session_state.current_question_index += 1 |
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else: |
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final_message = message_to_rep |
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conclusion = this_response.get("Conclusion", "") |
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if conclusion != "": |
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final_message = final_message + "\n\n" + conclusion |
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if session_state.do_voice: |
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await reply_with_voice(cl, client, final_message) |
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else: |
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await cl.Message(message_to_rep).send() |
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session_state.status = "complete" |
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end_time = datetime.now() |
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session_state.end_time = end_time |
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if session_state.start_time: |
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try: |
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duration = end_time - session_state.start_time |
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duration_minutes = round(duration.total_seconds() / 60) |
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except: |
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print("Error calculating duration") |
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duration = 130 |
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duration_minutes = 2 |
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session_state.duration_minutes = duration_minutes |
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if session_state.do_evaluation: |
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await display_evaluation_results(cl, session_state) |
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else: |
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await cl.Message(content="**Simulation Complete**").send() |
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evaluate_actions = [ |
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cl.Action(name="Evaluate Performance", value="evaluate", description="Evaluate Performance"), |
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cl.Action(name="Display Queries and Responses", value="display_llm_responses", description="Display LLM Responses") |
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] |
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await cl.Message(content="Click to evaluate performance", actions=evaluate_actions).send() |
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await cl.Message(content="\n\n").send() |
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