Here is the schematic of the architecture:
Architecture diagram#
Sales conversation stages.#
The agent employs an assistant who keeps it in check as in what stage of the conversation it is in. These stages were generated by ChatGPT and can be easily modified to fit other use cases or modes of conversation.
Introduction: Start the conversation by introducing yourself and your company. Be polite and respectful while keeping the tone of the conversation professional.
Qualification: Qualify the prospect by confirming if they are the right person to talk to regarding your product/service. Ensure that they have the authority to make purchasing decisions.
Value proposition: Briefly explain how your product/service can benefit the prospect. Focus on the unique selling points and value proposition of your product/service that sets it apart from competitors.
Needs analysis: Ask open-ended questions to uncover the prospect’s needs and pain points. Listen carefully to their responses and take notes.
Solution presentation: Based on the prospect’s needs, present your product/service as the solution that can address their pain points.
Objection handling: Address any objections that the prospect may have regarding your product/service. Be prepared to provide evidence or testimonials to support your claims.
Close: Ask for the sale by proposing a next step. This could be a demo, a trial or a meeting with decision-makers. Ensure to summarize what has been discussed and reiterate the benefits.
class StageAnalyzerChain(LLMChain):
    """Chain to analyze which conversation stage should the conversation move into."""
    @classmethod
    def from_llm(cls, llm: BaseLLM, verbose: bool = True) -> LLMChain:
        """Get the response parser."""
        stage_analyzer_inception_prompt_template = (
            """You are a sales assistant helping your sales agent to determine which stage of a sales conversation should the agent move to, or stay at.
            Following '===' is the conversation history.
rtdocs_stable/api.python.langchain.com/en/stable/use_cases/agents/sales_agent_with_context.html