app.py

app.py

@@ -1,18 +1,20 @@
 #importing dependencies
 import os
-from keys import apikey, token
+from keys import token
 
 import streamlit as st
-from langchain.llms import OpenAI, HuggingFaceHub
+from transformers import pipeline
+from langchain.llms import HuggingFaceHub
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
 from langchain.tools import WikipediaQueryRun
 from langchain.utilities import WikipediaAPIWrapper
 
+
 wikipedia = WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper())
 
-os.environ["OPENAI_API_KEY"] = apikey
 os.environ["HUGGINGFACEHUB_API_TOKEN"] = token
+repo_id = "tiiuae/falcon-40b"
 
 #app framework
 st.title("🛕Gurubot AI") 
@@ -95,12 +97,16 @@ yoda_grammar = PromptTemplate(
 #llms
 #llm = OpenAI(temperature=0.9)
 #llm_facts = OpenAI(temperature=0)
-llm = HuggingFaceHub
-llm_facts = HuggingFaceHub
-main_chain = LLMChain(llm=llm, prompt=context, verbose=True)
-yoda_grammar_chain = LLMChain(llm=llm_facts, prompt=yoda_grammar)
-keyword_chain = LLMChain(llm=llm_facts, prompt=find_keyword)
-wiki_chain = LLMChain(llm=llm_facts, prompt=context, verbose=True)
+llm = HuggingFaceHub(
+    repo_id=repo_id, model_kwargs={"temperature": 0.9, "max_length": 500}
+)
+llm_facts = HuggingFaceHub(
+    repo_id=repo_id, model_kwargs={"temperature": 0.0, "max_length": 500}
+)
+main_chain = LLMChain(prompt=context, llm=llm)
+yoda_grammar_chain = LLMChain(prompt=yoda_grammar, llm=llm_facts)
+keyword_chain = LLMChain(prompt=find_keyword, llm=llm_facts)
+wiki_chain = LLMChain(prompt=context, llm=llm_facts)
 
 
 #answer on screen if prompt is entered