krishnadhulipalla commited on
Commit
a1b71de
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1 Parent(s): 22bbe4e

Update app.py

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Files changed (1) hide show
  1. app.py +6 -5
app.py CHANGED
@@ -104,6 +104,7 @@ knowledge_base = KnowledgeBase()
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  # LLMs
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  # repharser_llm = ChatNVIDIA(model="mistralai/mistral-7b-instruct-v0.3") | StrOutputParser()
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  repharser_llm = ChatNVIDIA(model="microsoft/phi-3-mini-4k-instruct") | StrOutputParser()
 
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  instruct_llm = ChatNVIDIA(model="mistralai/mixtral-8x22b-instruct-v0.1") | StrOutputParser()
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  relevance_llm = ChatNVIDIA(model="nvidia/llama-3.1-nemotron-70b-instruct") | StrOutputParser()
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  answer_llm = ChatOpenAI(
@@ -369,7 +370,7 @@ extract_validation_inputs = RunnableLambda(lambda x: {
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  validation_chain = (
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  extract_validation_inputs
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  | relevance_prompt
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- | instruct_llm
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  | RunnableLambda(safe_json_parse)
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  )
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@@ -394,7 +395,7 @@ select_and_prompt = RunnableLambda(lambda x:
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  answer_chain = (
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  prepare_answer_inputs
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  | select_and_prompt
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- | relevance_llm
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  )
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  def RExtract(pydantic_class: Type[BaseModel], llm, prompt):
@@ -422,7 +423,7 @@ def RExtract(pydantic_class: Type[BaseModel], llm, prompt):
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  knowledge_extractor = RExtract(
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  pydantic_class=KnowledgeBase,
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- llm=instruct_llm,
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  prompt=parser_prompt
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  )
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@@ -464,7 +465,7 @@ def chat_interface(message, history):
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  "query": message,
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  "all_queries": [message],
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  "all_texts": all_chunks,
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- "k_per_query": 8,
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  "alpha": 0.5,
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  "vectorstore": vectorstore,
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  "bm25_retriever": bm25_retriever,
@@ -529,7 +530,7 @@ demo = gr.ChatInterface(
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  description="💡 Ask anything about Krishna Vamsi Dhulipalla",
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  examples=[
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  "Give me an overview of Krishna Vamsi Dhulipalla’s work experience across different roles?",
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- "What programming languages and tools does Krishna use for data science?",
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  "Can this chatbot tell me what Krishna's chatbot architecture looks like and how it works?"
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  ],
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  )
 
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  # LLMs
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  # repharser_llm = ChatNVIDIA(model="mistralai/mistral-7b-instruct-v0.3") | StrOutputParser()
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  repharser_llm = ChatNVIDIA(model="microsoft/phi-3-mini-4k-instruct") | StrOutputParser()
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+ validation_llm = ChatNVIDIA(model="microsoft/phi-3-small-8k-instruct") | StrOutputParser()
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  instruct_llm = ChatNVIDIA(model="mistralai/mixtral-8x22b-instruct-v0.1") | StrOutputParser()
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  relevance_llm = ChatNVIDIA(model="nvidia/llama-3.1-nemotron-70b-instruct") | StrOutputParser()
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  answer_llm = ChatOpenAI(
 
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  validation_chain = (
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  extract_validation_inputs
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  | relevance_prompt
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+ | validation_llm
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  | RunnableLambda(safe_json_parse)
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  )
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  answer_chain = (
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  prepare_answer_inputs
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  | select_and_prompt
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+ | answer_llm
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  )
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  def RExtract(pydantic_class: Type[BaseModel], llm, prompt):
 
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  knowledge_extractor = RExtract(
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  pydantic_class=KnowledgeBase,
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+ llm=validation_llm,
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  prompt=parser_prompt
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  )
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  "query": message,
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  "all_queries": [message],
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  "all_texts": all_chunks,
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+ "k_per_query": 7,
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  "alpha": 0.5,
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  "vectorstore": vectorstore,
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  "bm25_retriever": bm25_retriever,
 
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  description="💡 Ask anything about Krishna Vamsi Dhulipalla",
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  examples=[
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  "Give me an overview of Krishna Vamsi Dhulipalla’s work experience across different roles?",
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+ "What programming languages and tools does Krishna use for data science and data engineering?",
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  "Can this chatbot tell me what Krishna's chatbot architecture looks like and how it works?"
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  ],
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  )