import streamlit as st
import requests
import subprocess
import re
import sys
import urllib.request
import json
import os
import ssl
import time

PROMPT_TEMPLATE = """### Instruction:\n{instruction}\n\n### Input:\n{input}\n### Question:\n{question}\n\n### Response (use duckdb shorthand if possible):\n"""
INSTRUCTION_TEMPLATE = """Your task is to generate valid duckdb SQL to answer the following question{has_schema}"""  # noqa: E501
ERROR_MESSAGE = ":red[ Quack! Much to our regret, SQL generation has gone a tad duck-side-down.\nThe model is currently not able to craft a correct SQL query for this request. \nSorry my duck friend. ]\n\n:red[If the question is about your own database, make sure to set the correct schema. Otherwise, try to rephrase your request. ]\n\n```sql\n{sql_query}\n```\n\n```sql\n{error_msg}\n```"
STOP_TOKENS = ["###", ";", "--", "```"]

def allowSelfSignedHttps(allowed):
    # bypass the server certificate verification on client side
    if allowed and not os.environ.get('PYTHONHTTPSVERIFY', '') and getattr(ssl, '_create_unverified_context', None):
        ssl._create_default_https_context = ssl._create_unverified_context

allowSelfSignedHttps(True) # this line is needed if you use self-signed certificate in your scoring service.


def generate_prompt(question, schema):
    input = ""
    if schema:
        # Lowercase types inside each CREATE TABLE (...) statement
        for create_table in re.findall(
                r"CREATE TABLE [^(]+\((.*?)\);", schema, flags=re.DOTALL | re.MULTILINE
        ):
            for create_col in re.findall(r"(\w+) (\w+)", create_table):
                schema = schema.replace(
                    f"{create_col[0]} {create_col[1]}",
                    f"{create_col[0]} {create_col[1].lower()}",
                )
        input = """Here is the database schema that the SQL query will run on:\n{schema}\n""".format(  # noqa: E501
            schema=schema
        )
    prompt = PROMPT_TEMPLATE.format(
        instruction=INSTRUCTION_TEMPLATE.format(
            has_schema="." if schema == "" else ", given a duckdb database schema."
        ),
        input=input,
        question=question,
    )
    return prompt


def generate_sql_azure(question, schema):
    prompt = generate_prompt(question, schema)
    start = time.time()

    data={
        "input_data": {
            "input_string": [prompt],
            "parameters":{
                "top_p": 0.9,
                "temperature": 0.1,
                "max_new_tokens": 200,
                "do_sample": True
            }
        }
    }
    body = str.encode(json.dumps(data))

    url = 'https://motherduck-eu-west2-xbdfd.westeurope.inference.ml.azure.com/score'
    headers = {'Content-Type':'application/json', 'Authorization':('Bearer '+ st.secrets['azure_ai_token']), 'azureml-model-deployment': 'motherduckdb-duckdb-nsql-7b-v-1' }
    req = urllib.request.Request(url, body, headers)
    raw_resp = urllib.request.urlopen(req)
    resp = json.loads(raw_resp.read().decode("utf-8"))[0]["0"]
    sql_query = resp[len(prompt):]
    print(time.time()-start)
    return sql_query

def generate_sql(question, schema):
    prompt = generate_prompt(question, schema)
    start = time.time()
    s = requests.Session()
    api_base = "https://text-motherduck-sql-fp16-4vycuix6qcp2.octoai.run"
    url = f"{api_base}/v1/completions"
    body = {
        "model": "motherduck-sql-fp16",
        "prompt": prompt,
        "temperature": 0.1,
        "max_tokens": 200,
        "stop": "<s>",
        "n": 1,
    }
    headers = {"Authorization": f"Bearer {st.secrets['octoml_token']}"}
    with s.post(url, json=body, headers=headers) as resp:
        sql_query = resp.json()["choices"][0]["text"]
    print(time.time()-start)
    return sql_query


def validate_sql(query, schema):
    try:
        # Define subprocess
        process = subprocess.Popen(
            [sys.executable, './validate_sql.py', query, schema],
            stdout=subprocess.PIPE,
            stderr=subprocess.PIPE
        )
        # Get output and potential parser, and binder error message
        stdout, stderr = process.communicate(timeout=0.5)
        if stderr:
            error_message = stderr.decode('utf8').split("\n")
            # skip traceback
            if len(error_message) > 3:
                error_message = "\n".join(error_message[3:])
            return False, error_message
        return True, ""
    except subprocess.TimeoutExpired:
        process.kill()
        # timeout reached, so parsing and binding was very likely successful
        return True, ""


st.title("DuckDB-NSQL-7B Demo")

expander = st.expander("Customize Schema (Optional)")
expander.markdown(
    "If you DuckDB database is `database.duckdb`, execute this query in your terminal to get your current schema:"
)
expander.markdown(
    """```bash\necho ".schema" | duckdb database.duckdb | sed 's/(/(\\n    /g' | sed 's/, /,\\n    /g' | sed 's/);/\\n);\\n/g'\n```""",
)

# Input field for text prompt
default_schema = """CREATE TABLE rideshare(
    hvfhs_license_num VARCHAR,
    dispatching_base_num VARCHAR,
    originating_base_num VARCHAR,
    request_datetime TIMESTAMP,
    on_scene_datetime TIMESTAMP,
    pickup_datetime TIMESTAMP,
    dropoff_datetime TIMESTAMP,
    PULocationID BIGINT,
    DOLocationID BIGINT,
    trip_miles DOUBLE,
    trip_time BIGINT,
    base_passenger_fare DOUBLE,
    tolls DOUBLE,
    bcf DOUBLE,
    sales_tax DOUBLE,
    congestion_surcharge DOUBLE,
    airport_fee DOUBLE,
    tips DOUBLE,
    driver_pay DOUBLE,
    shared_request_flag VARCHAR,
    shared_match_flag VARCHAR,
    access_a_ride_flag VARCHAR,
    wav_request_flag VARCHAR,
    wav_match_flag VARCHAR
);

CREATE TABLE service_requests(
    unique_key BIGINT,
    created_date TIMESTAMP,
    closed_date TIMESTAMP,
    agency VARCHAR,
    agency_name VARCHAR,
    complaint_type VARCHAR,
    descriptor VARCHAR,
    location_type VARCHAR,
    incident_zip VARCHAR,
    incident_address VARCHAR,
    street_name VARCHAR,
    cross_street_1 VARCHAR,
    cross_street_2 VARCHAR,
    intersection_street_1 VARCHAR,
    intersection_street_2 VARCHAR,
    address_type VARCHAR,
    city VARCHAR,
    landmark VARCHAR,
    facility_type VARCHAR,
    status VARCHAR,
    due_date TIMESTAMP,
    resolution_description VARCHAR,
    resolution_action_updated_date TIMESTAMP,
    community_board VARCHAR,
    bbl VARCHAR,
    borough VARCHAR,
    x_coordinate_state_plane VARCHAR,
    y_coordinate_state_plane VARCHAR,
    open_data_channel_type VARCHAR,
    park_facility_name VARCHAR,
    park_borough VARCHAR,
    vehicle_type VARCHAR,
    taxi_company_borough VARCHAR,
    taxi_pick_up_location VARCHAR,
    bridge_highway_name VARCHAR,
    bridge_highway_direction VARCHAR,
    road_ramp VARCHAR,
    bridge_highway_segment VARCHAR,
    latitude DOUBLE,
    longitude DOUBLE
);

CREATE TABLE taxi(
    VendorID BIGINT,
    tpep_pickup_datetime TIMESTAMP,
    tpep_dropoff_datetime TIMESTAMP,
    passenger_count DOUBLE,
    trip_distance DOUBLE,
    RatecodeID DOUBLE,
    store_and_fwd_flag VARCHAR,
    PULocationID BIGINT,
    DOLocationID BIGINT,
    payment_type BIGINT,
    fare_amount DOUBLE,
    extra DOUBLE,
    mta_tax DOUBLE,
    tip_amount DOUBLE,
    tolls_amount DOUBLE,
    improvement_surcharge DOUBLE,
    total_amount DOUBLE,
    congestion_surcharge DOUBLE,
    airport_fee DOUBLE,
    drivers VARCHAR[],
    speeding_tickets STRUCT(date TIMESTAMP, speed VARCHAR)[],
    other_violations JSON
);"""
schema = expander.text_area("Current schema:", value=default_schema, height=500)

# Input field for text prompt
text_prompt = st.text_input(
    "What DuckDB SQL query can I write for you?", value="Read a CSV file from test.csv"
)

if text_prompt:
    sql_query = generate_sql(text_prompt, schema)
    valid, msg = validate_sql(sql_query, schema)
    if not valid:
        st.markdown(ERROR_MESSAGE.format(sql_query=sql_query, error_msg=msg))
    else:
        st.markdown(f"""```sql\n{sql_query}\n```""")