Upload usage.py

usage.py

@@ -0,0 +1,38 @@
+from langchain.llms import HuggingFacePipeline
+from langchain.chains import LLMChain
+from langchain.prompts import PromptTemplate
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+
+class NameExtractorChain:
+    def __init__(self, model_name: str = "name-extraction"):
+        self.pipe = pipeline(
+            "text2text-generation",
+            model=model_name,
+            max_new_tokens=10,
+            model_kwargs={"temperature": 0}
+        )
+      
+        self.llm = HuggingFacePipeline(pipeline=self.pipe)
+        
+        self.prompt = PromptTemplate(
+            input_variables=["conversation"],
+            
+       template="""Extract only the name of the person from this conversation. 
+            If there's no name, return 'No name found'.
+            Conversation: {conversation}""")
+        self.chain = LLMChain(llm=self.llm, prompt=self.prompt)
+
+
+    def extract_name(self, text: str):
+        text=text.strip() 
+        if len(text.split())==1:
+              text= "It's " + text
+        try:
+            output = self.chain.run(conversation=text)
+            return output
+        except Exception as e:
+            print(f"Error processing text: {str(e)}")
+
+
+extractor = NameExtractorChain()
+print(extractor.extract_name(sample-text))