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| import asyncio | |
| import chainlit as cl | |
| from langchain_openai import ChatOpenAI | |
| from utils_actions import offer_actions,offer_initial_actions | |
| from utils_data import get_company_data, get_opportunities | |
| from utils_prompt import get_chat_prompt | |
| from utils_objections import create_objections | |
| async def prep_start(session_state): | |
| get_company_data(session_state) | |
| chat_prompt = get_chat_prompt() | |
| chat_model = ChatOpenAI(model=session_state.llm_model) | |
| simple_chain = chat_prompt | chat_model | |
| cl.user_session.set("chain", simple_chain) | |
| welcome_message = f"**Welcome to {session_state.company.name} SalesBuddy**\n*Your AI assistant for sales and sales management*" | |
| await cl.Message(content=welcome_message).send() | |
| # await cl.Message(content=session_state.company.product_summary).send() | |
| image = cl.Image(path="images/salesbuddy_logo.jpg", name="salesbuddy_logo", display="inline") | |
| await cl.Message( | |
| content=" ", | |
| elements=[image], | |
| ).send() | |
| await offer_initial_actions() | |
| opportunities = get_opportunities() | |
| cl.user_session.set("opportunities", opportunities) | |
| async def prep_opportunities(session_state): | |
| research_title = "**Upcoming Opportunities**" | |
| await cl.Message(content=research_title).send() | |
| opportunities = cl.user_session.get("opportunities", None) | |
| if opportunities is None: | |
| await cl.Message(content="No scenarios found.").send() | |
| return | |
| opportunity_actions = [] | |
| for idx, row in opportunities.iterrows(): | |
| if row['Opportunity Description'] != "": | |
| customer_name = row['Customer Name'] | |
| opportunity_name = row['Opportunity Name'] | |
| opportunity_stage = row['Opportunity Stage'] | |
| name = f"{customer_name}: {opportunity_name} ({opportunity_stage})" | |
| opportunity_action = cl.Action( | |
| name=name, | |
| value=f"{idx}", # Send the row index as value | |
| description=f"{row['Customer Name']}: {row['Opportunity Name']} ({row['Opportunity Stage']}) " | |
| f"Value: {row['Opportunity Value']}. Meeting with {row['Customer Contact']} " | |
| f"({row['Customer Contact Role']})" | |
| ) | |
| opportunity_actions.append(opportunity_action) | |
| await cl.Message(content="Select an opportunity (hover for details):", actions=opportunity_actions).send() | |
| async def prep_opportunity_analysis(): | |
| session_state = cl.user_session.get("session_state", None) | |
| opportunity_analysis_message = "Retrieving and Reviewing HSBC Opportunitiy - please wait..." | |
| await cl.Message(content=opportunity_analysis_message).send() | |
| if session_state.do_opportunity_analysis: | |
| pass | |
| else: | |
| agent_1_message = "*Retrieving data from SalesForce CRM ...*" | |
| await cl.Message(content=agent_1_message).send() | |
| await asyncio.sleep(2) | |
| if session_state.add_objections_to_analysis: | |
| agent_3_message = "*Evaluating opportunity and identifying risks ...*" | |
| await cl.Message(content=agent_3_message).send() | |
| session_state.objections = await create_objections(session_state) | |
| else: | |
| agent_2_message = "*Evaluating opportunity ...*" | |
| await cl.Message(content=agent_2_message).send() | |
| await asyncio.sleep(1.5) | |
| agent_3_message = "*Determining next steps ...*" | |
| await cl.Message(content=agent_3_message).send() | |
| await asyncio.sleep(1) | |
| output_message = "**Analysis Results**" | |
| await cl.Message(content=output_message).send() | |
| output_messages = get_opportunity_analysis() | |
| for output_message in output_messages: | |
| await cl.Message(content=output_message).send() | |
| await cl.Message(content="").send() | |
| if session_state.add_objections_to_analysis: | |
| output_message = "**Risks**" | |
| await cl.Message(content=output_message).send() | |
| for obj in session_state.objections: | |
| await cl.Message(content=obj).send() | |
| output_message = "**Next Steps**" | |
| await cl.Message(content=output_message).send() | |
| output_messages = get_next_steps() | |
| for output_message in output_messages: | |
| await cl.Message(content=output_message).send() | |
| await cl.Message(content="").send() | |
| await cl.Message(content="\n\n").send() | |
| await offer_actions() | |
| async def prep_research(session_state): | |
| research_title = "**Customer Research**" | |
| await cl.Message(content=research_title).send() | |
| research_message = "Enter customer name to research" | |
| await cl.Message(content=research_message).send() | |
| def get_opportunity_analysis(): | |
| output_1 = "**Summary:** The HSBC opportunity involves replacing the existing analytics engine for their loan origination system, valued at $250,000. The current system is slow and lacks flexibility, creating urgency due to an impending renewal with the existing vendor. Multiple meetings have been conducted, culminating in a proposal review. The decision process is progressing, with a meeting scheduled on October 26 with John Smith to discuss the next steps. Potential for pilot program or final negotiations." | |
| output_2 = "**Score: 75**" | |
| output_3 = "**MEDDIC Evaluation:**" | |
| output_4 = "**Metrics: 70** - The proposal discussed expected performance improvements and ROI, but specific quantitative metrics driving the decision were not detailed." | |
| output_5 = "**Economic Buyer: 65** - There is no direct mention of engagement with the ultimate economic buyer, although the CFO's involvement in the proposal review suggests some level of engagement." | |
| output_6 = "**Decision Criteria: 75** - The decision criteria seem to be partially understood, as there has been discussion about ROI, performance improvements, and contract terms, but further clarity is needed." | |
| output_7 = "**Decision Process: 80** - The decision process appears to be well-understood, with clear next steps and urgency due to the vendor renewal timeline." | |
| output_8 = "**Identify Pain: 85** - The pain points related to the existing system's performance and flexibility are clearly identified, driving the opportunity forward." | |
| output_9 = "**Champion: 75** - John Smith, the VP of IT, appears to be a potential champion, as he is involved in every meeting, but his level of influence and commitment is not fully confirmed." | |
| outputs = [output_1, output_2, output_3, output_4, output_5, output_6, output_7, output_8, output_9] | |
| return outputs | |
| def get_next_steps(): | |
| output_10 = "Engage with the CFO and other key stakeholders to refine the understanding of the decision criteria and ensure alignment with their expectations. Confirm John Smith's role as a champion and clarify his influence on the decision-making process." | |
| output_11 = "**Talking Points:**" | |
| output_12 = " 1. Discuss specific quantitative metrics and performance benchmarks that demonstrate the expected improvements and ROI to solidify the business case" | |
| output_13 = " 2. Address the decision criteria with more clarity, ensuring that all stakeholders, including the CFO, have a shared understanding of what is needed to move forward" | |
| output_14 = " 3. Highlight the urgency of the situation due to the impending vendor renewal and how your solution can address the identified pain points in a timely manner" | |
| outputs = [output_10, output_11, output_12, output_13, output_14] | |
| return outputs | |
| async def prep_latest_news(): | |
| latest_news_message = "Retrieving latest news on this customer - please wait..." | |
| await cl.Message(content=latest_news_message).send() | |
| await asyncio.sleep(2) | |
| agent_1_message = "Agent 1: Processing data..." | |
| await cl.Message(content=agent_1_message).send() | |
| await asyncio.sleep(1) | |
| agent_2_message = "Agent 2: Evaluating opportunity..." | |
| await cl.Message(content=agent_2_message).send() |