from fastapi import Request, HTTPException
from pydantic import BaseModel, BaseModel, HttpUrl
from modal import Secret, App, web_endpoint, Image
from typing import Optional, List
from example import proposal
import os

app = App(name="circleback", image=Image.debian_slim().pip_install("openai", "pydantic", "fastapi"))

class Attendee(BaseModel):
    name: Optional[str]
    email: Optional[str]

    def markdown(self) -> str:
        if self.name:
            return f"- {self.name} ({self.email})"
        return f"- {self.email}"

class Assignee(BaseModel):
    name: Optional[str]
    email: Optional[str]

    def markdown(self) -> str:
        if self.name:
            return f"{self.name} ({self.email})"
        return f"{self.email}"

class ActionItem(BaseModel):
    id: int
    title: str
    description: str
    assignee: Optional[Assignee]
    status: str

    def markdown(self) -> str:
        assignee_info = self.assignee.markdown() if self.assignee else "Unassigned"
        return f"**{self.title}** (Status: {self.status})\n" \
               f"- Description: {self.description}\n" \
               f"- Assignee: {assignee_info}\n"

class MeetingNotes(BaseModel):
    id: int
    name: str
    createdAt: str
    duration: int
    url: Optional[HttpUrl]
    recordingUrl: Optional[HttpUrl]
    attendees: List[Attendee]
    notes: str
    actionItems: List[ActionItem]

    def to_markdown(self) -> str:
        attendees_md = "\n".join([attendee.markdown() for attendee in self.attendees])
        action_items_md = "\n".join([item.markdown() for item in self.actionItems])
        return f"# Meeting: {self.name}\n\n" \
               f"**Created At:** {self.createdAt}\n" \
               f"**Duration:** {self.duration} seconds\n" \
               f"**URL:** {self.url if self.url else 'N/A'}\n\n" \
               f"**Attendees:**\n{attendees_md}\n\n" \
               f"# Notes\n\n{self.notes}\n\n" \
               f"# Action Items\n\n{action_items_md}\n"

@app.function(secrets=[Secret.from_name("OPENAI_API_KEY")])
@web_endpoint(method="POST")
async def f(request: Request):
    body = await request.json()
    try:
        webhook_data = MeetingNotes(**body)
    except Exception as e:
        raise HTTPException(status_code=400, detail=str(e)) from e
    
    transcript = webhook_data.to_markdown()
    print('PROMPT:\n', '==='*10, '\n', prompt(transcript), '\n', '==='*10)
    proposal = gen_proposal(transcript)
    print('\n\nAI GENERATED PROPOSAL:\n\n', '==='*10, '\n', proposal, '\n', '==='*10)

def prompt(transcript: str):
    return f"""
Here is an example consulting proposal:

<example>
{proposal}
</example>

Here is a transcript of a recent call with a potential client (the client name is in the transcript):

<transcript>
{transcript}
</transcript>

Write a detailed project proposal, but do not worry about the pricing or the rate. Focus on fleshing out the different tasks we would do that is compelling and convincing for a founder.

Flesh out these ideas and add more as necessary. Do not anchor too much on the given examples, instead write a convincing proposal.
"""

def gen_proposal(transcript: str):
        from openai import OpenAI
        client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
        response = client.chat.completions.create(
            model="gpt-4-turbo",
            messages=[
                {"role": "system", "content": "You are an expert AI consultant. Your task is to write a project proposal for a potential client. The client is interested in your services and wants to know more about your approach to solving their problems. Write a detailed proposal that outlines the tasks you would do to help them grow their business. Focus on the value you can provide and how you can help them achieve their goals. Be persuasive and convincing."},
                {"role": "user", "content": prompt(transcript)}
            ]
        )
        return response.choices[0].message.content