app.py

import os
import gradio as gr 
from crewai import Agent, Task, Crew, Process 
from huggingface_hub import login
from langchain_community.llms import HuggingFaceEndpoint
from pydantic import BaseModel  # Using Pydantic v2
from typing import Dict, Any

# Set all required environment variables explicitly
os.environ["AZURE_API_TYPE"] = "azure"
os.environ["AZURE_API_BASE"] = os.getenv("AZURE_OPENAI_ENDPOINT")
os.environ["AZURE_API_KEY"] = os.getenv("AZURE_OPENAI_API_KEY")
os.environ["AZURE_API_VERSION"] = os.getenv("OPENAI_API_VERSION")
os.environ["AZURE_DEPLOYMENT_NAME"] = os.getenv("AZURE_DEPLOYMENT_NAME")

AZURE_API_BASE = os.getenv("AZURE_OPENAI_ENDPOINT")
AZURE_API_KEY = os.getenv("AZURE_OPENAI_API_KEY")
AZURE_API_VERSION = os.getenv("OPENAI_API_VERSION")
AZURE_DEPLOYMENT_NAME = os.getenv("AZURE_DEPLOYMENT_NAME")


if not AZURE_API_KEY or not AZURE_API_BASE or not AZURE_API_VERSION or not AZURE_DEPLOYMENT_NAME:
    raise ValueError("Missing Azure OpenAI environment variables. Check your Hugging Face Space settings.")


# Configuring AzureChatOpenAI client...
from langchain_openai import AzureChatOpenAI
llm = AzureChatOpenAI(
    azure_deployment=os.getenv("AZURE_DEPLOYMENT_NAME"),
    azure_endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),
    api_version=os.getenv("OPENAI_API_VERSION") ,
    model=f"azure/{os.getenv('AZURE_DEPLOYMENT_NAME')}",
    max_retries=3,
    timeout=30,
  #  max_tokens=2000  # max possible..
    temperature=0.3,  # Adjust based on requirements
)

# ================= AGENTS =================
proposal_writer = Agent(
    role="Humanitarian Proposal Writer",
    llm=llm,
    goal="Write compelling funding proposals for humanitarian projects",
    backstory="You are an expert in humanitarian aid and grant writing.",
    verbose=True,
    allow_delegation=False
)

proposal_reviewer = Agent(
    role="Proposal Quality Assurance Specialist",
    llm=llm,
    goal="Ensure proposals meet funding criteria and formatting requirements",
    backstory="You are a grant evaluator for major humanitarian organizations.",
    verbose=True,
    allow_delegation=False
)

# ================= TASKS =================
def create_proposal_task(idea: str, budget: str, duration: str, scope: str):
    return Task(
        description=(
            f"Write a detailed project proposal. Project: {idea}, Budget: {budget}, Duration: {duration}, Scope: {scope}"
        ),
        expected_output="A well-structured proposal document.",
        agent=proposal_writer,
        output_file="proposal_draft.md"
    )

def review_task():
    return Task(
        description="Review the proposal for formatting, compliance, and logical flow.",
        expected_output="Reviewed proposal with feedback.",
        agent=proposal_reviewer,
        output_file="proposal_review.md"
    )

# ================= CREW =================
def generate_proposal(description: str, org: str, duration: str, budget: str, region: str):
    inputs = {
        "idea": description,
        "budget": budget,
        "duration": duration,
        "scope": f"Target region: {region}, Funding organization: {org}"
    }

    crew = Crew(
        agents=[proposal_writer, proposal_reviewer],
        tasks=[create_proposal_task(**inputs), review_task()],
        process=Process.sequential,
        verbose=2,
        memory=True
    )
    
    return crew.kickoff()


# ================= GRADIO INTERFACE =================
with gr.Blocks() as demo:
    gr.Markdown("# 📄 Humanitarian Proposal Generator")

    description = gr.Textbox(label="Project Description", placeholder="Describe your project...")
    org = gr.Dropdown(["UN", "EU", "USAID", "IOM"], label="Funding Organization")
    duration = gr.Dropdown(["6 months", "1 year", "2 years"], label="Project Duration")
    budget = gr.Dropdown(["$50,000 - $100,000", "$100,000 - $150,000", "$200,000 - $300,000"], label="Budget Range")
    region = gr.Textbox(label="Target Region", placeholder="Enter project region (e.g., Africa, Asia)")

    generate_button = gr.Button("Generate", visible=True)
    output = gr.Markdown()
    debug_output = gr.Textbox(label="Debug Console", interactive=False)

    def process_proposal(desc, org, duration, budget, region):
        debug_logs = "🔍 Debug Log:\n"
        try:
            if not desc:
                raise ValueError("⚠️ Error: Project description cannot be empty.")

            debug_logs += f"✅ Inputs: {desc[:50]}..., {org}, {duration}, {budget}, {region}\n"
            result = generate_proposal(desc, org, duration, budget, region)
            
            debug_logs += "✅ Proposal successfully generated!\n"
            return result, debug_logs
        
        except Exception as e:
            debug_logs += f"❌ Error: {str(e)}\n"
            return f"<div style='color:red;'>❌ {str(e)}</div>", debug_logs

    generate_button.click(
        process_proposal,
        inputs=[description, org, duration, budget, region],
        outputs=[output, debug_output]
    )

if __name__ == "__main__":
    print("🚀 Starting Gradio app...")
    demo.launch(server_name="0.0.0.0", share=False, debug=True, show_error=True)