tests.py

from mcp.server.fastmcp import FastMCP
import time
from litellm import completion
import os
import glob
import http.client
import json
import openpyxl
import shutil
from google import genai
import pexpect

client = genai.Client(api_key="AIzaSyDtP05TyoIy9j0uPL7_wLEhgQEE75AZQSc")
source_dir = "/app/uploads/temp"
destination_dir = "/app/code_interpreter"
files_list=[]
downloaded_files=[]

from openai import OpenAI
clienty = OpenAI(api_key="xyz", base_url="https://akiko19191-backend.hf.space/")

mcp = FastMCP("code_sandbox")
data={}
result=""
import requests
import os
from bs4 import BeautifulSoup  # For parsing HTML

Parent=pexpect.spawn('bash')



def transfer_files():
    try:
        for item in os.listdir(source_dir):
            item_path = os.path.join(source_dir, item)
            if os.path.isdir(item_path): # Check if it's a directory
                for filename in os.listdir(item_path):
                    source_file_path = os.path.join(item_path, filename)
                    destination_file_path = os.path.join(destination_dir, filename)
                    if not os.path.exists(destination_file_path):
                        shutil.move(source_file_path, destination_file_path)
    except:
        pass
def transfer_files2():
    try:
        for item in os.listdir("/app/uploads"):
            if "temp" not in item:
                item_path = os.path.join(source_dir, item)
                if os.path.isdir(item_path): # Check if it's a directory
                    for filename in os.listdir(item_path):
                        source_file_path = os.path.join(item_path, filename)
                        destination_file_path = os.path.join(destination_dir, filename.split("__")[1])
                        if not os.path.exists(destination_file_path):
                            shutil.move(source_file_path, destination_file_path)
    except:
        pass
def upload_file(file_path, upload_url):
    """Uploads a file to the specified server endpoint."""

    try:
        # Check if the file exists
        if not os.path.exists(file_path):
            raise FileNotFoundError(f"File not found: {file_path}")

        # Prepare the file for upload
        with open(file_path, "rb") as file:
            files = {"file": (os.path.basename(file_path), file)}  #  Important: Provide filename

            # Send the POST request
            response = requests.post(upload_url, files=files)

            # Check the response status code
            response.raise_for_status()  # Raise an exception for bad status codes (4xx or 5xx)

            # Parse and print the response
            if response.status_code == 200:
                print(f"File uploaded successfully.  Filename returned by server: {response.text}")
                return response.text # Return the filename returned by the server
            else:
                print(f"Upload failed. Status code: {response.status_code}, Response: {response.text}")
                return None

    except FileNotFoundError as e:
        print(e)
        return None  # or re-raise the exception if you want the program to halt
    except requests.exceptions.RequestException as e:
        print(f"Upload failed. Network error: {e}")
        return None


TOKEN = "5182224145:AAEjkSlPqV-Q3rH8A9X8HfCDYYEQ44v_qy0"
chat_id = "5075390513"
from requests_futures.sessions import FuturesSession
session = FuturesSession()

def run(cmd, timeout_sec,forever_cmd):
    global Parent
    if forever_cmd == 'true':
        Parent.close()
        Parent = pexpect.spawn("bash")
        command="cd /app/code_interpreter/ && "+cmd

        Parent.sendline(command)
        Parent.readline().decode()
        return str(Parent.readline().decode())    
    t=time.time()
    child = pexpect.spawn("bash")
    output=""
    command="cd /app/code_interpreter/ && "+cmd

    child.sendline('PROMPT_COMMAND="echo END"')
    child.readline().decode()
    child.readline().decode()

    child.sendline(command)

    while (not child.eof() ) and (time.time()-t<300):
        x=child.readline().decode()
        output=output+x
        print(x)
        if "END" in x :
            output=output.replace("END","")
            child.close()
            break
        if "true" in forever_cmd:
            break
    return output

@mcp.tool()
def analyse_audio(audiopath,query) -> dict:
    """Ask another AI model about audios.The AI model can listen to the audio and give answers.Eg-query:Generate detailed minutes of meeting from the audio clip,audiopath='/app/code_interpreter/<audioname>'.Note:The audios are automatically present  in the /app/code_interpreter directory."""
    transfer_files2()
    myfile = client.files.upload(file=audiopath)

    response = client.models.generate_content(
    model='gemini-2.0-flash',
    contents=[query, myfile]
    )
    return {"Output":str(response.text)}

@mcp.tool()
def analyse_video(videopath,query) -> dict:
    """Ask another AI model about videos.The AI model can see the videos and give answers.Eg-query:Create a very detailed transcript and summary of the video,videopath='/app/code_interpreter/<videoname>'Note:The videos are automatically present  in the /app/code_interpreter directory."""
    transfer_files2()
    video_file = client.files.upload(file=videopath)

    while video_file.state.name == "PROCESSING":
        print('.', end='')
        time.sleep(1)
        video_file = client.files.get(name=video_file.name)

    if video_file.state.name == "FAILED":
        raise ValueError(video_file.state.name)

    response = client.models.generate_content(
    model='gemini-2.0-flash',
    contents=[query, video_file]
    )
    return {"Output":str(response.text)}


@mcp.tool()
def analyse_images(imagepath,query) -> dict:
    """Ask another AI model about images.The AI model can see the images and give answers.Eg-query:Who is the person in this image?,imagepath='/app/code_interpreter/<imagename>'.Note:The images are automatically present  in the /app/code_interpreter directory."""
    transfer_files2()
    video_file = client.files.upload(file=imagepath)


    response = client.models.generate_content(
    model='gemini-2.0-flash',
    contents=[query, video_file]
    )
    return {"Output":str(response.text)}


# @mcp.tool()
# def generate_images(imagepath,query) -> dict:
#     """Ask another AI model to generate images based on the query and the image path.Set image path as an empty string , if you dont want to edit images , but rather generate images.Eg-query:Generate a cartoon version of this image,imagepath='/app/code_interpreter/<imagename>'.Note:The images are automatically present  in the /app/code_interpreter directory."""
#     transfer_files2()
#     video_file = client.files.upload(file=imagepath)


#     response = client.models.generate_content(
#     model='gemini-2.0-flash',
#     contents=[query, video_file]
#     )
#     return {"Output":str(response.text)}

@mcp.tool()
def create_code_files(filename: str, code) -> dict:
    """Create code files by passing the the filename as well the entire code to write.The file is created by default in the /app/code_interpreter directory.Note:All user uploaded files that you might need to work upon are stored in the /app/code_interpreter directory."""
    global destination_dir
    transfer_files()
    transfer_files2()
    if not os.path.exists(os.path.join(destination_dir, filename)):
        
        if isinstance(code, dict):
            with open(os.path.join(destination_dir, filename), 'w', encoding='utf-8') as f:
                json.dump(code, f, ensure_ascii=False, indent=4)
        else:
            f = open(os.path.join(destination_dir, filename), "w")
            f.write(str(code))
            f.close()
        return {"info":"The referenced code files were created successfully."}

    else:
        if isinstance(code, dict):
            with open(os.path.join(destination_dir, filename), 'w', encoding='utf-8') as f:
                json.dump(code, f, ensure_ascii=False, indent=4)
        else:
            f = open(os.path.join(destination_dir, filename), "w")
            f.write(str(code))
            f.close()
        return {"info":"The referenced code files were created successfully."}
        # return {"info":"The referenced code files already exist. Please rename the file or delete the existing one."}

    
@mcp.tool()
def run_code(python_packages:str,filename: str, code: str,start_cmd:str,forever_cmd:str) -> dict:
    """  
    Execute code in a controlled environment with package installation and file handling.
    Args:
        python_packages[Output an empty string ,if using any other language.]: Space-separated list of packages to install (e.g., "numpy matplotlib").
                        Preinstalled packages: gradio, XlsxWriter, openpyxl.
        filename:        Name of the file to create (stored in /app/code_interpreter/).
        code:           Full code to write to the file.
        start_cmd:      Command to execute the file (e.g., "python /app/code_interpreter/app.py" 
                        or "bash /app/code_interpreter/app.py").
        forever_cmd:    If 'true', the command will run indefinitely.Set to 'true', when runnig a website/server.Run all servers/website on port 1337. If 'false', the command will time out after 300 second and the result will be returned.
    Notes:
        - All user-uploaded files are in /app/code_interpreter/.
        - After execution, embed a download link (or display images/gifs/videos directly in markdown format) in your response.
    """
    global destination_dir
    package_names = python_packages.strip()
    command="pip install"
    if  package_names != "" or package_names != " ":
        stdot=run(
            f"{command} --break-system-packages {package_names}", timeout_sec=300,forever_cmd= 'false' 
        )
    transfer_files2()
    transfer_files()
    f = open(os.path.join(destination_dir, filename), "w")
    f.write(code)
    f.close()
    global files_list
    stdot=run(start_cmd, 300,forever_cmd)
    onlyfiles = glob.glob("/app/code_interpreter/*")
    onlyfiles=list(set(onlyfiles)-set(files_list))
    uploaded_filenames=[]
    for files in onlyfiles:
        try:
            uploaded_filename = upload_file(files, "https://opengpt-4ik5.onrender.com/upload")
            uploaded_filenames.append(f"https://opengpt-4ik5.onrender.com/static/{uploaded_filename}")
        except:
            pass
    files_list=onlyfiles
    return {"output":stdot,"Files_download_link":uploaded_filenames}


@mcp.tool()
def run_code_files(start_cmd:str,forever_cmd:str) -> dict:
    """Executes a shell command to run code files from /app/code_interpreter.
    Runs the given `start_cmd`. The execution behavior depends on `forever_cmd`.
    Any server/website started should use port 1337.
    Args:
        start_cmd (str): The shell command to execute the code.
                         (e.g., ``python /app/code_interpreter/app.py`` or ``node /app/code_interpreter/server.js``).
                         Files must be in ``/app/code_interpreter``.
        forever_cmd (str): Execution mode.
                           - ``'true'``: Runs indefinitely (for servers/websites).
                           - ``'false'``: Runs up to 300s, captures output.
    Returns:
        dict: A dictionary containing:
              - ``'output'`` (str): Captured stdout (mainly when forever_cmd='false').
              - ``'Files_download_link'`` (Any): Links/identifiers for downloadable files.
    Notes:
        - After execution, embed a download link (or display images/gifs/videos directly in markdown format) in your response.
        - When editing and subsequently re-executing the server with the forever_cmd='true' setting, the previous server instance will be automatically terminated, and the updated server will commence operation. This functionality negates the requirement for manual process termination commands such as pkill node.    
        - The opened ports can be externally accessed at https://suitable-liked-ibex.ngrok-free.app/ (ONLY if the website is running successfully)
    """    
    global files_list

    stdot=run(start_cmd, 300,forever_cmd)
    onlyfiles = glob.glob("/app/code_interpreter/*")
    onlyfiles=list(set(onlyfiles)-set(files_list))
    uploaded_filenames=[]
    for files in onlyfiles:
        try:
            uploaded_filename = upload_file(files, "https://opengpt-4ik5.onrender.com/upload")
            uploaded_filenames.append(f"https://opengpt-4ik5.onrender.com/static/{uploaded_filename}")
        except:
            pass
    files_list=onlyfiles
    return {"output":stdot,"Files_download_link":uploaded_filenames}


@mcp.tool()
def run_shell_command(cmd:str,forever_cmd:str) -> dict:
    """Executes a shell command in a sandboxed Alpine Linux environment.
    Runs the provided `cmd` string within a bash shell. Commands are executed
    relative to the `/app/code_interpreter/` working directory by default.
    The execution behavior (indefinite run vs. timeout) is controlled by
    the `forever_cmd` parameter.
    Important Environment Notes:
        - The execution environment is **Alpine Linux**. Commands should be
          compatible .
        - `sudo` commands are restricted for security reasons.Hence commands which require elevated privelages like `apk add` CANNOT be executed.Instead try to use `pip install` or `npm install` commands. 
        - Standard bash features like `&&`, `||`, pipes (`|`), etc., are supported.
        - When installing python packages , add an argument --break-system-packages to the pip install command.
        - The following npm packages are preinstalled:  express ejs chart.js .Any additional packages can be installed with npm install command.
    Args:
        cmd (str): The shell command to execute.
                   Example: ``mkdir test_dir && ls -l``
        forever_cmd (str): Determines the execution mode.
                           - ``'true'``: Runs the command indefinitely. Suitable
                             for starting servers or long-running processes.
                             Output capture might be limited.
                           - ``'false'``: Runs the command until completion or
                             a 300-second timeout, whichever comes first.
                             Captures standard output.
    Returns:
        dict: A dictionary containing the execution results:
              - ``'output'`` (str): The captured standard output (stdout) and potentially
                standard error (stderr) from the command.
    """    
    transfer_files()
    transfer_files2()
    output=run(cmd, 300,forever_cmd)
    return {"output":output}



@mcp.tool()
def install_python_packages(python_packages:str) -> dict:
    """python_packages to install seperated by space.eg-(python packages:numpy matplotlib).The following python packages are preinstalled:gradio XlsxWriter openpyxl"""
    global sbx
    package_names = python_packages.strip()
    command="pip install"
    if not package_names:
        return

    stdot=run(
        f"{command} --break-system-packages {package_names}", timeout_sec=300, forever_cmd= 'false' 
    )

    return {"stdout":stdot,"info":"Ran package installation command"}

@mcp.tool()
def get_youtube_transcript(videoid:str) -> dict:
    """Get the transcript of a youtube video by passing the video id.Eg videoid=ZacjOVVgoLY"""
    conn = http.client.HTTPSConnection("youtube-transcript3.p.rapidapi.com")
    headers = {
        'x-rapidapi-key': "2a155d4498mshd52b7d6b7a2ff86p10cdd0jsn6252e0f2f529",
        'x-rapidapi-host': "youtube-transcript3.p.rapidapi.com"
    }
    conn.request("GET",f"/api/transcript?videoId={videoid}", headers=headers)

    res = conn.getresponse()
    data = res.read()
    return json.loads(data)

@mcp.tool()
def read_excel_file(filename) -> dict:
    """Reads the contents of an excel file.Returns a dict with key :value pair  = cell location:cell content.Always run this command first , when working with excels.The excel file is automatically present  in the /app/code_interpreter directory. """
    global destination_dir
    transfer_files2()
    transfer_files()

    workbook = openpyxl.load_workbook(os.path.join(destination_dir, filename))

    # Create an empty dictionary to store the data
    excel_data_dict = {}

    # Iterate over all sheets
    for sheet_name in workbook.sheetnames:
        sheet = workbook[sheet_name]
        # Iterate over all rows and columns
        for row in sheet.iter_rows():
            for cell in row:
                # Get cell coordinate (e.g., 'A1') and value
                cell_coordinate = cell.coordinate
                cell_value = cell.value
                if cell_value is not None:
                    excel_data_dict[cell_coordinate] = str(cell_value)
    return excel_data_dict
@mcp.tool()
def scrape_websites(url_list:list,query:str) -> list:
    """Scrapes specific website content.query is the question you want to ask about the content of the website.e.g-query:Give .pptx links in the website,Summarise the content in very  great detail,etc.Maximum 4 urls can be passed at a time."""

    conn = http.client.HTTPSConnection("scrapeninja.p.rapidapi.com")


    headers = {
    'x-rapidapi-key': "2a155d4498mshd52b7d6b7a2ff86p10cdd0jsn6252e0f2f529",
    'x-rapidapi-host': "scrapeninja.p.rapidapi.com",
    'Content-Type': "application/json"
    }
    Output=""
    links=""
    content=""
    for urls in url_list:
        payload = {"url" :urls} 
        payload=json.dumps(payload)
        conn.request("POST", "/scrape", payload, headers)
        res = conn.getresponse()
        data = res.read()
        content=content+str(data.decode("utf-8"))
        
    #Only thing llama 4 is good for.

    response = clienty.chat.completions.create(
        model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
        messages=[
        {"role": "user", "content": f"{query} [CONTENT]:{content}"}
    ],stream=True
    )
    for chunk in response:
        Output = Output +str(chunk.choices[0].delta.content)
    #--------------
    response2 = clienty.chat.completions.create(
        model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
        messages=[
        {"role": "user", "content": f"Give all relevant and different types of links in this content.The links may be relevant image links , file links , video links , website links , etc .You must give Minimum 30 links and maximum 50 links.[CONTENT]:{content}"}
    ],stream=True
    )
    for chunk in response2:
        links = links +str(chunk.choices[0].delta.content)
    return {"website_content":Output,"relevant_links":links}




if __name__ == "__main__":
    # Initialize and run the server
    Ngrok=pexpect.spawn('bash')
    Ngrok.sendline("ngrok http --url=suitable-liked-ibex.ngrok-free.app 1337")
    Ngrok.readline().decode()
    mcp.run(transport='stdio')