import os
from google import genai

# --- 1. Set up the Google Generative AI client ---

# Initialize the genai client from the environment variable
client = genai.Client()

# --- 2. Run the program ---

# Create a sample text file for testing
sample_file_path = "sample_document.txt"
with open(sample_file_path, "w") as f:
    f.write("The annual company picnic will be held on December 15th at the Central Park Pavilion. "
            "All employees and their families are invited to attend.")

# Upload the file using the genai client
uploaded_file = client.files.upload(file=sample_file_path)
print(f"uploaded_file details: {uploaded_file.mime_type}, {uploaded_file.size_bytes}, {uploaded_file.state}")

# Define the question
my_question = "When is the annual company picnic scheduled?"

response = client.models.generate_content(
    model="gemini-flash-latest", contents=[uploaded_file, my_question]
)

# Print the final answer
print(f"Question: {my_question}")
print(f"Answer: {response.text}")

# Remove the local sample file
os.remove(sample_file_path)

import dspy
from google import genai
import os

# --- 1. Set up the Google Generative AI client and DSPy LM ---

# Initialize the genai client from the environment variable
client = genai.Client()

# Configure DSPy to use the Gemini model
GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')
gemini_lm = dspy.LM("gemini/gemini-flash-latest", api_key=GOOGLE_API_KEY)
dspy.configure(lm=gemini_lm)


# --- 2. Define the DSPy Signature ---

class AnswerWithFile(dspy.Signature):
    """Answer a question based on the contents of an uploaded file."""
    question = dspy.InputField()
    file = dspy.InputField()
    answer = dspy.OutputField(desc="A concise answer based on the file content.")


# --- 3. Create the DSPy Module ---

class FileQA(dspy.Module):
    def __init__(self):
        super().__init__()
        # Use a Predict module with the AnswerWithFile signature
        self.predict = dspy.Predict(AnswerWithFile)

    def forward(self, question, file_path):
        # Upload the file using the genai client
        uploaded_file = client.files.upload(file=file_path)
        print(f"uploaded_file details: {uploaded_file.mime_type}, {uploaded_file.size_bytes}, {uploaded_file.state}")

        # Call the DSPy Predict module, passing the question and the uploaded file object
        result = self.predict(question=question, file=uploaded_file)

        return result

# --- 4. Run the program ---

# Create a sample text file for testing
sample_file_path = "sample_document.txt"
with open(sample_file_path, "w") as f:
    f.write("The annual company picnic will be held on December 15th at the Central Park Pavilion."
            "All employees and their families are invited to attend.")

# Create an instance of our module
file_qa_program = FileQA()

# Define the question
my_question = "When is the annual company picnic scheduled?"

# Execute the program
response = file_qa_program(question=my_question, file_path=sample_file_path)

# Print the final answer
print(f"Question: {my_question}")
print(f"Answer: {response.answer}")

# Remove the local sample file
os.remove(sample_file_path)