import gradio as gr
import json
import os

# Load source_connectors and destination_connectors from JSON files
with open('source_connectors.json', 'r') as f:
    source_connectors = json.load(f)

with open('destination_connectors.json', 'r') as f:
    destination_connectors = json.load(f)

def generate_documentation_link(source, destination):
    return f"[{source['source_connector']} documentation]({source['docs']}) | [{destination['destination_connector']} documentation]({destination['docs']})"

def generate_code(source, destination, chunking, embedding):
    source_connector = source_connectors[source]
    destination_connector = destination_connectors[destination]

    # Ensure proper indentation for source and destination configs
    indented_source_configs = '\n'.join(
        '        ' + line
        for line in source_connector['configs'].strip().split('\n'))
    indented_destination_configs = '\n'.join(
        '        ' + line
        for line in destination_connector['configs'].strip().split('\n'))

    code = f'''
import os
from unstructured_ingest.v2.pipeline.pipeline import Pipeline
from unstructured_ingest.v2.interfaces import ProcessorConfig
from unstructured_ingest.v2.processes.partitioner import PartitionerConfig
{source_connector['imports']}
{destination_connector['imports']}
from unstructured_ingest.v2.processes.chunker import ChunkerConfig
from unstructured_ingest.v2.processes.embedder import EmbedderConfig

if __name__ == "__main__":
    Pipeline.from_configs(
        context=ProcessorConfig(),
{indented_source_configs}
        partitioner_config=PartitionerConfig(
            partition_by_api=True,
            api_key=os.getenv("UNSTRUCTURED_API_KEY"),
            partition_endpoint=os.getenv("UNSTRUCTURED_API_URL"),
            strategy="hi_res",
        ),
        {'chunker_config=ChunkerConfig(chunking_strategy="by_title"),' if chunking else '# Chunking is disabled'}
        {'embedder_config=EmbedderConfig(embedding_provider="' + embedding + '")' if embedding else '# Embedding is disabled'}
{indented_destination_configs}
    ).run()
'''
    doc_link = generate_documentation_link(source_connector, destination_connector)
    return code, doc_link

demo = gr.Interface(
    fn=generate_code,
    inputs=[
        gr.Dropdown(list(source_connectors.keys()),
                    label="Get unstructured documents from:"),
        gr.Dropdown(list(destination_connectors.keys()),
                    label="Upload RAG-ready documents to:"),
        gr.Checkbox(label="Check to enable chunking"),
        gr.Dropdown(["langchain-openai", "langchain-huggingface"],
                    label="Embedding provider:")
    ],
    outputs=[
        gr.Code(language="python", label="Generated Code"),
        gr.Markdown(label="Documentation Links")
    ],
    title="Unstructured-Ingest Code Generator",
    description="Generate code for the unstructured-ingest library based on your inputs.")


demo.launch()