Update app.py

app.py

@@ -23,7 +23,60 @@ from langchain.llms import HuggingFaceHub
 
 # for the chain and prompt
 from langchain.prompts import PromptTemplate
-from langchain.chains import LLMChain
+from langchain.chains import LLMChain, SimpleSequentialChain 
+
+###################
+
+llm = HuggingFaceHub(
+    
+#    repo_id="google/flan-ul2", 
+    repo_id="google/flan-t5-small", 
+    model_kwargs={"temperature":0.1,
+                  "max_new_tokens":250})
+
+
+    # Chain 1: Generating a rephrased version of the user's question
+    template = """{question}\n\n"""
+    prompt_template = PromptTemplate(input_variables=["question"], template=template)
+    question_chain = LLMChain(llm=llm, prompt=prompt_template)
+
+    # Chain 2: Generating assumptions made in the statement
+    template = """Here is a statement:
+        {statement}
+        Make a bullet point list of the assumptions you made when producing the above statement.\n\n"""
+    prompt_template = PromptTemplate(input_variables=["statement"], template=template)
+    assumptions_chain = LLMChain(llm=llm, prompt=prompt_template)
+    assumptions_chain_seq = SimpleSequentialChain(
+        chains=[question_chain, assumptions_chain], verbose=True
+    )
+
+    # Chain 3: Fact checking the assumptions
+    template = """Here is a bullet point list of assertions:
+    {assertions}
+    For each assertion, determine whether it is true or false. If it is false, explain why.\n\n"""
+    prompt_template = PromptTemplate(input_variables=["assertions"], template=template)
+    fact_checker_chain = LLMChain(llm=llm, prompt=prompt_template)
+    fact_checker_chain_seq = SimpleSequentialChain(
+        chains=[question_chain, assumptions_chain, fact_checker_chain], verbose=True
+    )
+
+    # Final Chain: Generating the final answer to the user's question based on the facts and assumptions
+    template = """In light of the above facts, how would you answer the question '{}'""".format(
+        user_question
+    )
+    template = """{facts}\n""" + template
+    prompt_template = PromptTemplate(input_variables=["facts"], template=template)
+    answer_chain = LLMChain(llm=llm, prompt=prompt_template)
+    overall_chain = SimpleSequentialChain(
+        chains=[question_chain, assumptions_chain, fact_checker_chain, answer_chain],
+        verbose=True,
+    )
+
+print(overall_chain.run("What is the capitol of the usa?"))
+
+##################
+
+
 
 #import model class and tokenizer
 from transformers import BlenderbotTokenizer, BlenderbotForConditionalGeneration