Fir changes after version was increased to 0.5

ai_model.py

@@ -0,0 +1,145 @@
+from abc import ABC, abstractmethod
+from openai import OpenAI
+from groq import Groq
+from ollama import Client
+from openai import AzureOpenAI 
+from anthropic import Anthropic
+import os
+
+class AIModel(ABC):
+    @abstractmethod
+    def chat(self, model, messages):
+        pass
+
+    @abstractmethod
+    def moderate(self, message):
+        pass
+
+    @staticmethod
+    def get_model_client(config):
+        api_provider=config["api"]
+
+        if api_provider == "" or api_provider==None:
+            api_provider = "groq"
+        
+        if api_provider == "groq":
+            return GroqModel(api_key=os.environ.get("GROQ_API_KEY"))
+        
+        elif api_provider == "openai":
+            api_key = os.getenv("OPENAI_API_KEY")
+            if not api_key:  
+                api_key=config["openai_api_key"]       
+            if not api_key:  #If statement to avoid "invalid filepath" error
+                home_path = os.path.expanduser("~")   
+                api_key=open(os.path.join(home_path,".openai.apikey"), "r").readline().strip()
+                api_key = api_key
+
+            return OpenAIModel(api_key=api_key)
+        
+        elif api_provider == "azure":
+            api_key = os.getenv("AZURE_OPENAI_API_KEY")
+            if not api_key:  
+                api_key=config["azure_openai_api_key"]
+            if not api_key: 
+                home_path = os.path.expanduser("~")   
+                api_key=open(os.path.join(home_path,".azureopenai.apikey"), "r").readline().strip()
+
+            return AzureOpenAIModel(
+                    api_key=api_key,
+                    azure_endpoint=config["azure_endpoint"], 
+                    api_version=config["azure_api_version"])
+        
+        elif api_provider == "ollama":
+            ollama_api   = os.environ.get("OLLAMA_ENDPOINT", "http://localhost:11434")
+            #ollama_model = os.environ.get("OLLAMA_MODEL", "llama3-8b-8192")
+            return OllamaModel(ollama_api)
+
+        if api_provider == "anthropic":
+            api_key = os.getenv("ANTHROPIC_API_KEY")
+            if not api_key: 
+                api_key=config["anthropic_api_key"]
+            return AnthropicModel(api_key=api_key) 
+        else:
+            raise ValueError(f"Invalid AI model provider: {api_provider}")
+
+class GroqModel(AIModel):
+    def __init__(self, api_key):
+        self.client = Groq(api_key=api_key)
+
+    def chat(self, messages, model, temperature, max_tokens):
+        resp = self.client.chat.completions.create(model=model, 
+                                                   messages=messages, 
+                                                   temperature=temperature, 
+                                                   max_tokens=max_tokens)
+        return resp.choices[0].message.content
+    
+    def moderate(self, message):
+        pass
+
+class OpenAIModel(AIModel):
+    def __init__(self, api_key):
+        self.client = OpenAI(api_key=api_key)
+
+    def chat(self, messages, model, temperature, max_tokens):
+        resp = self.client.chat.completions.create(model=model, 
+                                                   messages=messages, 
+                                                   temperature=temperature,
+                                                   max_tokens=max_tokens)
+        
+        return resp.choices[0].message.content
+    
+    def moderate(self, message):
+        return self.client.moderations.create(input=message)
+
+class OllamaModel(AIModel):
+    def __init__(self, host):
+        self.client = Client(host=host)
+    
+    def chat(self, messages, model, temperature, max_tokens):
+        resp = self.client.chat(model=model, 
+                                messages=messages)
+        return resp["message"]["content"]
+    
+    def moderate(self, message):
+        pass
+
+
+class AzureOpenAIModel(AIModel):
+    def __init__(self, azure_endpoint, api_key, api_version):
+        self.client = AzureOpenAI(azure_endpoint=azure_endpoint, api_key=api_key, api_version=api_version)
+
+    def chat(self, messages, model, temperature, max_tokens):
+
+        resp = self.client.chat.completions.create(model=model, 
+                        messages=messages, 
+                        temperature=temperature, 
+                        max_tokens=max_tokens)
+        
+        return resp.choices[0].message.content
+    
+    def moderate(self, message):
+        return self.client.moderations.create(input=message)
+
+class AnthropicModel(AIModel):
+    def __init__(self, api_key):
+        self.client = Anthropic(api_key=api_key)
+
+    def chat(self, messages, model, temperature, max_tokens):
+        ## Anthropic requires the system prompt to be passed separately
+        ## Hence extracting system prompt role from the messages
+        ## and then passing the messages without the system role 
+        ## messages is not subscriptable, so we need to convert it to a list
+        system_prompt = next((m.get("content", "") for m in messages if m.get("role") == "system"), "")
+
+        # Remove system messages from the list
+        user_messages = [m for m in messages if m.get("role") != "system"]
+        resp = self.client.messages.create(model=model, 
+                                    system=system_prompt,
+                                    messages=user_messages,
+                                    temperature=temperature, 
+                                    max_tokens=max_tokens)
+        
+        return resp.content[0].text
+    
+    def moderate(self, message):
+        pass