Upload 3 files

conversations.py

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+#!/usr/bin/python3
+import requests
+import json
+import sys
+import psycopg2
+from datetime import datetime
+from sentence_transformers import SentenceTransformer
+import numpy as np
+
+MAX_WORDS=1024
+
+model = SentenceTransformer("all-MiniLM-L6-v2")
+
+def last_n_words(text: str, n: int) -> str:
+    words = text.split()
+    return " ".join(words[-n:])
+
+def get_chat_completion(content: str, port: int) -> str:
+    url = f"http://localhost:{port}/v1/chat/completions"
+    headers = {"Content-Type": "application/json"}
+    data = {
+        "model": "Default",
+        "messages": [{"role": "user", "content": content}],
+        "max_tokens": 2048,
+        "temperature": 0.28
+    }
+    
+    response = requests.post(url, headers=headers, data=json.dumps(data))
+    
+    if response.status_code == 200:
+        response_json = response.json()
+        return response_json.get("choices", [{}])[0].get("message", {}).get("content", "No response content")
+    else:
+        return f"Request failed with status code {response.status_code}"
+
+
+
+
+# database connection
+def get_db_connection():
+    try:
+        connection = psycopg2.connect(
+            dbname="d_conversations",
+            user="postgres",
+            password="********",
+            host="pg-db",
+            port="5432"
+        )
+        return connection
+    except Exception as e:
+        print(f"Error in connection to database: {e}")
+        return None
+
+def save_message(db_connection, message, chatbot_id, model_id):
+    # save a message in conversation table
+
+    embeds = model.encode(message).tolist()
+
+    try:
+        with db_connection.cursor() as cursor:
+            query = """
+                INSERT INTO conversation (id, chatbot_id, message, create_dt, model_id, embeds)
+                VALUES (nextval('conversation_seq'), %s, %s, %s, %s, %s)
+                RETURNING id;
+            """
+            create_dt = datetime.utcnow()
+            cursor.execute(query, (chatbot_id, message, create_dt, model_id, embeds))
+            conversation_id = cursor.fetchone()[0]
+            db_connection.commit()
+            return conversation_id
+    except Exception as e:
+        db_connection.rollback()
+        print(f"Error while inserting: {e}")
+        return None
+
+
+def get_last_n_messages(db_connection, n):
+    """
+    Retrieves the last n messages from the conversation table and formats them as a chat log.
+    
+    :param db_connection: Database connection object
+    :return: Formatted string with the last n messages
+    """
+    try:
+        with db_connection.cursor() as cursor:
+            query = """
+                SELECT cb.name, c.message 
+                FROM conversation c,  chatbot cb WHERE c.chatbot_id=cb.id
+                ORDER BY c.id DESC 
+                LIMIT %s;
+            """
+            cursor.execute(query, (n,))
+            rows = cursor.fetchall()
+
+            if len(rows)==3:
+                formatted_messages = f"<{rows[2][0]}> - {rows[2][1]}\n\n<{rows[1][0]}> - {rows[1][1]}\n\n<{rows[0][0]}> - {rows[0][1]}"
+
+            if len(rows)==2:
+                formatted_messages = f"<{rows[1][0]}> - {rows[1][1]}\n\n<{rows[0][0]}> - {rows[0][1]}"
+
+            if len(rows)==1:
+                formatted_messages = f"<{rows[0][0]}> - {rows[0][1]}"
+            
+            if len(rows)==0:
+                formatted_messages = "\n"
+
+            return formatted_messages
+    except Exception as e:
+        print(f"Error while retrieving messages: {e}")
+        return None
+
+
+
+
+def get_chatbot_model_port(db_connection, chatbot_id):
+    """
+    Retrieves model_id and port from the chatbot table for a given chatbot ID.
+    
+    :param db_connection: Database connection object
+    :param chatbot_id: ID of the chatbot
+    :return: Tuple (model_id, port) or None if not found
+    """
+    try:
+        with db_connection.cursor() as cursor:
+            query = "SELECT model_id, port FROM chatbot WHERE id = %s;"
+            cursor.execute(query, (chatbot_id,))
+            result = cursor.fetchone()
+            
+            if result:
+                return result  # (model_id, port)
+            else:
+                print(f"No chatbot found with ID {chatbot_id}")
+                return None
+    except Exception as e:
+        print(f"Error retrieving chatbot info: {e}")
+        return None
+
+
+
+# Example usage
+if len(sys.argv) < 2:
+        print("Usage: python3 conversations.py '<your question here>'")
+        sys.exit(1)
+
+conn = get_db_connection()
+if conn is None:
+    print("Connection to database failed")
+    exit(1)
+
+user_input = sys.argv[1]
+save_message(conn, user_input, 1, 0)
+
+
+chatbot_a = 4
+chatbot_b = 7
+current_chatbot = chatbot_a  
+
+
+try:
+    while True:
+        # Recovers last message from conversation
+        last_messages = get_last_n_messages(conn, 1)  
+        
+        print("last messages: "+last_messages)
+        # Change chatbot
+        current_chatbot = chatbot_a if current_chatbot == chatbot_b else chatbot_b
+ 
+        print(f"asking chatbot {current_chatbot}")
+        # Retrieve model and port of current chatbot
+        model_port_info = get_chatbot_model_port(conn, current_chatbot)
+        if not model_port_info:
+            print(f"Could not retrieve info from {current_chatbot}")
+            break
+
+        model_id, port = model_port_info
+        print("retrieved model and port")
+
+        # Retrieves answer
+        if (current_chatbot == chatbot_a):
+            print("ask for question")
+            last_messages = last_messages + "\n\nSuggest one very short factual follow-up question that has not been answered yet or cannot be found inspired by the previous conversation and excerpts.\n"
+        response = get_chat_completion(last_n_words(last_messages, MAX_WORDS), port)
+
+        # Saves answer in database
+        save_message(conn, response, current_chatbot, model_id)
+
+        # Print last answer
+        print("answer was:")
+        print(get_last_n_messages(conn,1))
+
+except KeyboardInterrupt:
+    print("\nConversation interrupted by human.")
+finally:
+    conn.close()

gpt4all-relay.sh

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+#!/bin/bash
+ssh -g -L 4891:localhost:4891 -f -N dm@gpt4all
+ssh -g -L 4892:localhost:4891 -f -N dm@chatbot1 
+ssh -g -L 4893:localhost:4891 -f -N dm@chatbot2
+ssh -g -L 4894:localhost:4891 -f -N dm@area51