Update LLM.py

LLM.py

@@ -1,8 +1,8 @@
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
 from langchain_groq import ChatGroq
-from langchain_huggingface import ChatHuggingFace
-from langchain_huggingface import HuggingFaceEndpoint
+from langchain_openai import ChatOpenAI
+from langchain_community.chat_models import ChatAnthropic
 from langchain_google_genai import ChatGoogleGenerativeAI
 from dotenv import load_dotenv
 from huggingface_hub import login
@@ -15,28 +15,18 @@ os.environ['CURL_CA_BUNDLE'] = ''
 
 class Bot:
     def __init__(self):
-        # Updated model lists: Remove gated or unsupported IDs        
-        self.groq_models = [
-            'gemma-7b-it',
-            'llama3-70b-8192',
-            'llama3-8b-8192',
-            'mixtral-8x22b'
-        ]
-        self.hf_models = [
-            "01-ai/Yi-1.5-34B-Chat",
-            "google/gemma-1.1-2b-it"
-        ]
-        # Use supported Google GenAI model names
-        self.google_models = [
-            "gemini-pro",
-            "gemini-pro-vision"
-        ]
-        # Master list for sampling (only include accessible models)
-        self.models = self.google_models + self.hf_models + self.groq_models
+        # Verified, stable models
+        self.openai_models = ["gpt-4o", "gpt-4-turbo", "gpt-3.5-turbo"]
+        self.anthropic_models = ["claude-3-opus-20240229", "claude-3-sonnet-20240229"]
+        self.google_models = ["gemini-pro"]
+        self.groq_models = ["llama3-8b-8192", "llama3-70b-8192"]  # Keep only working ones
 
-    def call_groq(self, model, temp=0.7, given_prompt="Hi"):
+        # Final model list
+        self.models = self.openai_models + self.anthropic_models + self.google_models + self.groq_models
+
+    def call_openai(self, model, temp=0.7, given_prompt="Hi"):
         try:
-            llm = ChatGroq(model=model, temperature=temp)
+            llm = ChatOpenAI(model=model, temperature=temp)
             prompt = ChatPromptTemplate.from_messages([
                 ("system", "You are a helpful assistant."),
                 ("human", "{text}")
@@ -44,47 +34,56 @@ class Bot:
             chain = prompt | llm | StrOutputParser()
             return chain.invoke({"text": given_prompt})
         except Exception as e:
-            return f"⚠️ [Groq:{model}] {str(e)}"
+            return f"⚠️ [OpenAI:{model}] {str(e)}"
 
-    def call_hf(self, model, temp=0.7, given_prompt="Hi"):
+    def call_anthropic(self, model, temp=0.7, given_prompt="Hi"):
         try:
-            llm = HuggingFaceEndpoint(repo_id=model, temperature=temp)
-            chat = ChatHuggingFace(llm=llm, verbose=True)
-            template = """
-You are a helpful assistant.
-
-User: {query}
-
-Answer:
-"""
-            prompt = PromptTemplate(template=template, input_variables=["query"])
-            chain = prompt | chat | StrOutputParser()
-            return chain.invoke({"query": given_prompt})
+            llm = ChatAnthropic(model=model, temperature=temp)
+            prompt = ChatPromptTemplate.from_messages([
+                ("system", "You are a helpful assistant."),
+                ("human", "{text}")
+            ])
+            chain = prompt | llm | StrOutputParser()
+            return chain.invoke({"text": given_prompt})
         except Exception as e:
-            return f"⚠️ [HF:{model}] {str(e)}"
+            return f"⚠️ [Anthropic:{model}] {str(e)}"
 
     def call_google(self, model, temp=0.7, given_prompt="Hi"):
         try:
             gm = ChatGoogleGenerativeAI(model=model, temperature=temp)
-            prompt = ChatPromptTemplate.from_messages([("system", "You are a helpful assistant."), ("human", "{text}")])
+            prompt = ChatPromptTemplate.from_messages([
+                ("system", "You are a helpful assistant."),
+                ("human", "{text}")
+            ])
             chain = prompt | gm | StrOutputParser()
             return chain.invoke({"text": given_prompt})
         except Exception as e:
             return f"⚠️ [Google:{model}] {str(e)}"
 
+    def call_groq(self, model, temp=0.7, given_prompt="Hi"):
+        try:
+            llm = ChatGroq(model=model, temperature=temp)
+            prompt = ChatPromptTemplate.from_messages([
+                ("system", "You are a helpful assistant."),
+                ("human", "{text}")
+            ])
+            chain = prompt | llm | StrOutputParser()
+            return chain.invoke({"text": given_prompt})
+        except Exception as e:
+            return f"⚠️ [Groq:{model}] {str(e)}"
+
     def response(self, model, prompt="Hi", temperature=0.7):
-        # Route to the correct provider and catch errors
         try:
-            if model in self.groq_models:
-                return self.call_groq(model, temp=temperature, given_prompt=prompt)
-            if model in self.hf_models:
-                return self.call_hf(model, temp=temperature, given_prompt=prompt)
-            if model in self.google_models:
+            if model in self.openai_models:
+                return self.call_openai(model, temp=temperature, given_prompt=prompt)
+            elif model in self.anthropic_models:
+                return self.call_anthropic(model, temp=temperature, given_prompt=prompt)
+            elif model in self.google_models:
                 return self.call_google(model, temp=temperature, given_prompt=prompt)
-            return f"❌ Unsupported model: {model}"
+            elif model in self.groq_models:
+                return self.call_groq(model, temp=temperature, given_prompt=prompt)
+            else:
+                return f"❌ Unsupported model: {model}"
         except Exception as e:
             return f"⚠️ Skipping `{model}` due to error: {str(e)}"
 
-
-
-