readding nserver backend code

nostr_dvm/backends/nova_server/utils.py

@@ -0,0 +1,112 @@
+import io
+import json
+import os
+import time
+import zipfile
+import pandas as pd
+import requests
+import PIL.Image as Image
+
+from nostr_dvm.utils.output_utils import upload_media_to_hoster
+
+"""
+This file contains basic calling functions for ML tasks that are outsourced to nova server. It is an Open-Source backend
+that enables running models locally based on preefined modules, by accepting a request form.
+Modules are deployed in in separate virtual environments so dependencies won't conflict. 
+"""
+
+"""
+send_request_to_n_server(request_form, address)
+Function to send a request_form to the server, containing all the information we parsed from the Nostr event and added
+in the module that is calling the server
+
+"""
+
+def send_request_to_server(request_form, address):
+    print("Sending job to Server")
+    url = ('http://' + address + '/process')
+    headers = {'Content-type': 'application/x-www-form-urlencoded'}
+    response = requests.post(url, headers=headers, data=request_form)
+    return response.text
+
+
+def send_file_to_server(filepath, address):
+    print("Sending file to Server")
+    url = ('http://' + address + '/upload')
+    try:
+        fp = open(filepath, 'rb')
+        response = requests.post(url, files={'file': fp})
+        result = response.content.decode('utf-8')
+    except Exception as e:
+        print(e)
+        print(response.content.decode('utf-8'))
+
+    return result
+
+    # headers = {'Content-type': 'application/x-www-form-urlencoded'}
+
+
+"""
+check_n_server_status(request_form, address)
+Function that requests the status of the current process with the jobID (we use the Nostr event as jobID).
+When the Job is successfully finished we grab the result and depending on the type return the output
+We throw an exception on error
+"""
+
+
+def check_server_status(jobID, address) -> str | pd.DataFrame:
+    headers = {'Content-type': 'application/x-www-form-urlencoded'}
+    url_status = 'http://' + address + '/job_status'
+    url_log = 'http://' + address + '/log'
+
+    print("Sending Status Request to Server")
+    data = {"jobID": jobID}
+
+    status = 0
+    length = 0
+    while status != 2 and status != 3:
+        response_status = requests.post(url_status, headers=headers, data=data)
+        response_log = requests.post(url_log, headers=headers, data=data)
+        status = int(json.loads(response_status.text)['status'])
+        log_content = str(json.loads(response_log.text)['message']).replace("ERROR", "").replace("INFO", "")
+        log = log_content[length:]
+        length = len(log_content)
+        if log != "":
+            print(log)
+        # WAITING = 0, RUNNING = 1, FINISHED = 2, ERROR = 3
+        time.sleep(1.0)
+
+    if status == 2:
+        try:
+            url_fetch = 'http://' + address + '/fetch_result'
+            print("Fetching Results from Server...")
+            data = {"jobID": jobID, "delete_after_download": True}
+            response = requests.post(url_fetch, headers=headers, data=data)
+            content_type = response.headers['content-type']
+            print("Content-type: " + str(content_type))
+            if content_type == "image/jpeg":
+                image = Image.open(io.BytesIO(response.content))
+                image.save("./outputs/image.jpg")
+                result = upload_media_to_hoster("./outputs/image.jpg")
+                os.remove("./outputs/image.jpg")
+                return result
+            elif content_type == 'text/plain; charset=utf-8':
+                return response.content.decode('utf-8')
+            elif content_type == "application/x-zip-compressed":
+                zf = zipfile.ZipFile(io.BytesIO(response.content), "r")
+
+                for fileinfo in zf.infolist():
+                    if fileinfo.filename.endswith(".annotation~"):
+                        try:
+                            anno_string = zf.read(fileinfo).decode('utf-8', errors='replace')
+                            columns = ['from', 'to', 'name', 'conf']
+                            result = pd.DataFrame([row.split(';') for row in anno_string.split('\n')],
+                                                  columns=columns)
+                            return result
+                        except Exception as e:
+                            print(e)
+        except Exception as e:
+            print("Couldn't fetch result: " + str(e))
+
+    elif status == 3:
+        return "error"