- adding Claude 3.5 haiku

Config_files/message_system_config.json

@@ -21,10 +21,11 @@
   "AI_phrases_singeo": ["your voice deserves more"],
   "header_limit": 30,
   "message_limit": 110,
-  "LLM_models": ["gpt-4o-mini", "gpt-4o", "gpt-4.1-mini", "gpt-3.5-turbo", "o1", "o4-mini", "o1-mini", "o3-mini"],
+  "LLM_models": ["gpt-4o-mini", "gpt-4o", "gpt-4.1-mini", "gpt-3.5-turbo", "o1", "o4-mini", "o1-mini", "o3-mini", "claude-3-5-haiku-latest"],
   "openai_models": ["gpt-4o-mini", "gpt-4o", "gpt-4.1-nano", "gpt-3.5-turbo", "gpt-4.1-mini"],
   "reasoning": ["o1", "o4-mini", "o1-mini", "o3-mini"],
-  "ollama_models": ["deepseek-r1:1.5b", "gemma3:4b", "deepseek-r1:7b", "gemma3:4b"]
+  "ollama_models": ["deepseek-r1:1.5b", "gemma3:4b", "deepseek-r1:7b", "gemma3:4b"],
+  "claude_models": ["claude-3-5-haiku-latest"]
 }
 
 

Messaging_system/LLM.py

@@ -9,6 +9,9 @@ import openai
 import ollama
 import torch
 import re
+import anthropic
+import os
+import streamlit as st
 
 
 
@@ -20,12 +23,17 @@ class LLM:
         self.client = None
         self.connect_to_llm()
 
+    def get_credential(self, key):
+        return os.getenv(key) or st.secrets.get(key)
 
     def get_response(self, prompt, instructions):
         if self.model_type == "openai":
             response = self.get_message_openai(prompt, instructions)
         elif self.model_type == "ollama":
             response = self.get_message_ollama(prompt, instructions)
+
+        elif self.model_type == "claude":
+            response = self.get_message_claude(prompt, instructions)
         else:
             raise f"Invalid model type : {self.model_type}"
 
@@ -40,78 +48,17 @@ class LLM:
         if self.Core.model in self.Core.config_file["openai_models"]:
             self.model_type = "openai"
 
-        if self.Core.model in self.Core.config_file["ollama_models"]:
+        elif self.Core.model in self.Core.config_file["ollama_models"]:
             self.model_type = "ollama"
             self.client = ollama.Client()
 
-        self.model = self.Core.model
-
-
-    # def get_message_openai(self, prompt, instructions, max_retries=4):
-    #
-    #
-    #     openai.api_key = self.Core.api_key
-    #     client = OpenAI(api_key=self.Core.api_key)
-    #
-    #     for attempt in range(max_retries):
-    #         try:
-    #             response = client.chat.completions.create(
-    #                 model=self.Core.model,
-    #                 messages= [{"role": "system", "content": instructions},{"role": "user", "content": prompt}],
-    #                 response_format={"type": "json_object"},
-    #                 reasoning_effort=self.reasoning,
-    #                 max_tokens=1000,
-    #                 temperature=self.Core.temperature,
-    #                 tools=[]
-    #             )
-    #
-    #             tokens = {
-    #                 'prompt_tokens': response.usage.prompt_tokens,
-    #                 'completion_tokens': response.usage.completion_tokens,
-    #                 'total_tokens': response.usage.total_tokens
-    #             }
-    #
-    #             try:
-    #                 content = response.choices[0].message.content
-    #
-    #                 # Extract JSON code block
-    #
-    #                 output = json.loads(content)
-    #
-    #                 if 'message' not in output or 'header' not in output:
-    #                     print(f"'message' or 'header' is missing in response on attempt {attempt + 1}. Retrying...")
-    #                     continue  # Continue to next attempt
-    #
-    #                 else:
-    #                     if len(output["header"].strip()) > self.Core.config_file["header_limit"] or len(
-    #                             output["message"].strip()) > self.Core.config_file["message_limit"]:
-    #                         print(
-    #                             f"'header' or 'message' is more than specified characters in response on attempt {attempt + 1}. Retrying...")
-    #                         continue
-    #
-    #                 # validating the JSON
-    #                 self.Core.total_tokens['prompt_tokens'] += tokens['prompt_tokens']
-    #                 self.Core.total_tokens['completion_tokens'] += tokens['completion_tokens']
-    #                 self.Core.temp_token_counter += tokens['total_tokens']
-    #                 return output
-    #
-    #             except json.JSONDecodeError:
-    #                 print(f"Invalid JSON from LLM on attempt {attempt + 1}. Retrying...")
-    #
-    #         except openai.APIConnectionError as e:
-    #             print("The server could not be reached")
-    #             print(e.__cause__)  # an underlying Exception, likely raised within httpx.
-    #         except openai.RateLimitError as e:
-    #             print("A 429 status code was received; we should back off a bit.")
-    #         except openai.APIStatusError as e:
-    #             print("Another non-200-range status code was received")
-    #             print(e.status_code)
-    #             print(e.response)
-    #
-    #     print("Max retries exceeded. Returning empty response.")
-    #     return None
-
+        elif self.Core.model in self.Core.config_file["claude_models"]:
+            self.model_type = "claude"
+            self.client = anthropic.Anthropic(
+                api_key=self.get_credential('claude_api_key'),
+            )
 
+        self.model = self.Core.model
 
     def get_message_openai(self, prompt, instructions, max_retries=4):
         """
@@ -251,6 +198,62 @@ class LLM:
         print("Max retries exceeded. Returning empty response.")
         return [], {}
 
+    def get_message_claude(self, prompt, instructions, max_retries=4):
+        """
+        send prompt to claude LLM and get back the response
+        :param prompt:
+        :param instructions:
+        :return:
+        """
+
+
+        for attempt in range(max_retries):
+            try:
+
+                message = self.client.messages.create(
+                    model=self.model,
+                    max_tokens=4096,
+                    system = instructions,
+                    messages=[
+                        {"role": "user", "content": prompt + "\nHere is the JSON requested:\n"}
+                    ],
+                    temperature=self.Core.temperature
+                )
+                # Try generating the response
+                response = message.content[0].text
+
+                tokens = {
+                    'prompt_tokens': 0,
+                    'completion_tokens': 0,
+                    'total_tokens': 0
+                }
+
+                try:
+                    output = self.preprocess_and_parse_json_claude(response)
+                    if output is None:
+                        continue
+
+                    if 'message' not in output or 'header' not in output:
+                        print(f"'message' or 'header' is missing in response on attempt {attempt + 1}. Retrying...")
+                        continue  # Continue to next attempt
+
+                    else:
+                        if len(output["header"].strip()) > self.Core.config_file["header_limit"] or len(
+                                output["message"].strip()) > self.Core.config_file["message_limit"]:
+                            print(
+                                f"'header' or 'message' is more than specified characters in response on attempt {attempt + 1}. Retrying...")
+                            continue
+                        else:
+                            return output
+
+                except json.JSONDecodeError:
+                    print(f"Invalid JSON from LLM on attempt {attempt + 1}. Retrying...")
+            except Exception as parse_error:
+                print("Error processing output:", parse_error)
+
+        print("Max retries exceeded. Returning empty response.")
+        return [], {}
+
     # ======================================================================
 
     def preprocess_and_parse_json(self, response: str):
@@ -280,6 +283,18 @@ class LLM:
             # print("Offending text:", json_text)
             return None
 
+    # ===============================================================
+    def preprocess_and_parse_json_claude(self, response: str):
+        """
+        process claude response and extract JSON
+        :param response:
+        :return:
+        """
+        json_start = response.index("{")
+        json_end = response.rfind("}")
+        parsed_response = json.loads(response[json_start:json_end + 1])
+        return parsed_response
+
 
 
 

Messaging_system/PromptEng.py

@@ -4,12 +4,13 @@ This is the prompt engineering layer to modifty the prompt for better perfromanc
 import openai
 from fontTools.ttLib.tables.ttProgram import instructions
 from openai import OpenAI
-
+from Messaging_system.LLM import LLM
 
 class PromptEngine:
 
     def __init__(self, coreconfig):
         self.Core=coreconfig
+        self.llm=LLM(self.Core)
 
     # =============================================================
     def prompt_engineering(self, prompt):
@@ -36,8 +37,18 @@ output the new prompt as text without any additional information.
         
         """
 
-        final_prompt = self.get_llm_response(new_prompt)
+        final_prompt = self.get_final_prompt(new_prompt)
         return final_prompt
+    # ===========================================================
+    def get_final_prompt(self, prompt):
+
+        if self.Core.model in self.Core.config_file["openai_models"]:
+            final_prompt = self.get_openai_response(prompt)
+            return final_prompt
+
+        elif self.Core.model in self.Core.config_file["claude_models"]:
+            final_prompt = self.get_claude_response(prompt, self.llm_instructions())
+            return final_prompt
 
     # ============================================================
     def llm_instructions(self):
@@ -50,7 +61,7 @@ output the new prompt as text without any additional information.
 
     # =============================================================
 
-    def get_llm_response(self, prompt, max_retries=4):
+    def get_openai_response(self, prompt, max_retries=4):
         """
         sending the prompt to openai LLM and get back the response
         """
@@ -115,3 +126,35 @@ output the new prompt as text without any additional information.
         return prompt # returns original prompt if needed
 
     # ==========================================================================
+
+
+    def get_claude_response(self, prompt, instructions, max_retries=4):
+        """
+        send prompt to claude LLM and get back the response
+        :param prompt:
+        :param instructions:
+        :return:
+        """
+
+        for attempt in range(max_retries):
+            try:
+
+                message = self.llm.client.messages.create(
+                    model=self.Core.model,
+                    max_tokens=4096,
+                    system = instructions,
+                    messages=[
+                        {"role": "user", "content": prompt}
+                    ],
+                    temperature=self.Core.temperature
+                )
+                # Try generating the response
+                response = message.content[0].text
+                return response
+            except Exception as e:
+                print(f"Error: {e}")
+
+
+        print("Max retries exceeded. Returning empty response.")
+        return prompt # returns original prompt if needed
+

messaging_main_test.py

@@ -136,18 +136,14 @@ if __name__ == "__main__":
     # number of messages to generate
     number_of_messages = 3
     instructionset = {
-        1: "Talk like a singing coach motivating your student. Don't say things a singer wouldn't say. Make the message quick, concise, and in casual language. Tell them to practice, take a lesson, or warm up today. ",
         2: "Talk like a singing coach motivating your student. Don't say things a singer wouldn't say. Make the message quick, concise, and in casual language. Tell them to practice, take a lesson, or warm up today. ",
-        3: "Talk like a singing coach motivating your student. Don't say things a singer wouldn't say. Make the message quick, concise, and in casual language. Tell them to practice, take a lesson, or warm up today. ",
-    }
+        3: "Talk like a singing coach motivating your student. Don't say things a singer wouldn't say. Make the message quick, concise, and in casual language. Tell them to practice, take a lesson, or warm up today. "}
 
     subsequent_examples = {
-        1: "Header: Sing Your Heart Out!"
+        2: "Header: Sing Your Heart Out!"
            "Message: It’s been a few days. Take a lesson today and start practicing!",
-        2: "header: Here Comes The Sun"
-           "message: A quick practice session will light up your day. Let’s get right back at it. ",
-        3: "header: Ain’t No Mountain High Enough"
-           "message: Daily practice makes you unstoppable. Time to build your skills!"
+        3: "header: Here Comes The Sun"
+           "message: A quick practice session will light up your day. Let’s get right back at it. "
     }
 
     involve_recsys_result = True
@@ -167,7 +163,7 @@ if __name__ == "__main__":
     # o3-mini o1-mini o4-mini o1
 
     users_message = permes.create_personalize_messages(session=session,
-                                                model="o4-mini",
+                                                model="claude-3-5-haiku-latest",
                                                 users=users,
                                                 brand=brand,
                                                 config_file=config_file,