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| from langchain_core.prompts import ChatPromptTemplate, PromptTemplate | |
| from langchain_groq import ChatGroq | |
| from langchain_huggingface import ChatHuggingFace | |
| from langchain_huggingface import HuggingFaceEndpoint | |
| from dotenv import load_dotenv | |
| from langchain.schema.output_parser import StrOutputParser | |
| from langchain_huggingface import ChatHuggingFace | |
| from langchain_google_genai import ChatGoogleGenerativeAI | |
| import os | |
| from huggingface_hub import login | |
| load_dotenv() | |
| login(token=os.environ["HUGGING_FACE_API_KEY"]) | |
| os.environ['CURL_CA_BUNDLE'] = '' | |
| load_dotenv() | |
| class Bot(): | |
| def __init__(self): | |
| self.groq_models = ['gemma-7b-it', 'llama3-70b-8192',\ | |
| 'llama3-8b-8192', 'mixtral-8x7b-32768'] | |
| self.hf_models = ["01-ai/Yi-1.5-34B-Chat", "google/gemma-1.1-2b-it",\ | |
| "google/gemma-1.1-7b-it"] | |
| self.google_models = ["gemini-1.0-pro", "gemini-1.5-flash",\ | |
| "gemini-1.5-pro"] | |
| self.models = ["gemini-1.0-pro", "gemini-1.5-flash", "gemini-1.5-pro", "01-ai/Yi-1.5-34B-Chat", "google/gemma-1.1-2b-it",\ | |
| "google/gemma-1.1-7b-it", 'gemma-7b-it', 'llama3-70b-8192', 'llama3-8b-8192', 'mixtral-8x7b-32768'] | |
| def call_groq(self, model, temp = 0.7, given_prompt = "Hi"): | |
| try: | |
| llm = ChatGroq( | |
| temperature=temp, | |
| model= model | |
| ) | |
| system = "You are a helpful assistant." | |
| human = "{text}" | |
| prompt = ChatPromptTemplate.from_messages([("system", system), ("human", human)]) | |
| chain = prompt | llm | StrOutputParser() | |
| return chain.invoke({"text": given_prompt}) | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| def call_hf(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}) | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| def call_google(self,model, temp=0.7, given_prompt = "Hi"): | |
| try: | |
| model = ChatGoogleGenerativeAI(model = model, temprature = temp) | |
| system = "You are a helpful assistant." | |
| human = "{text}" | |
| prompt = ChatPromptTemplate.from_messages([("human", human)]) | |
| chain = prompt | model | StrOutputParser() | |
| return chain.invoke({"text": given_prompt}) | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| def response(self, model, prompt="Hi", temprature = 0.7): | |
| if model in self.groq_models: | |
| res_show = self.call_groq(temp = temprature, given_prompt = prompt, model= model) | |
| elif model in self.hf_models: | |
| res_show = self.call_hf(given_prompt = prompt, temp = temprature, model = model) | |
| elif model in self.google_models: | |
| res_show = self.call_google(given_prompt = prompt, temp = temprature, model = model) | |
| else: | |
| return "Sorry! App not working properly" | |
| return res_show | |