Create app.py

app.py

@@ -0,0 +1,42 @@
+import gradio as gr
+
+from langchain_community.llms import LlamaCpp
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain_core.callbacks import StreamingStdOutCallbackHandler
+
+
+callbacks = [StreamingStdOutCallbackHandler()]
+print("creating ll started")
+llm = LlamaCpp(
+    model_path="cerebras_Llama3-DocChat-1.0-8B_Base_adapt_basic_model_16bit.gguf",
+    temperature=0.75,
+    max_tokens=30,
+    top_p=4,
+    callback_manager=callbacks,
+    verbose=True,  # Verbose is required to pass to the callback manager
+)
+print("creating ll ended")
+
+template = """You are the Finiantial expert:
+### Instruction:
+{question}
+### Input:
+### Response:
+"""
+
+prompt = PromptTemplate(template=template, input_variables=["question"])
+
+llm_chain_model = LLMChain(prompt=prompt, llm=llm)
+print("creating model created")
+
+
+def greet(question):
+    print(f"question is {question}")
+
+    out_gen = llm_chain_model.run(question)  
+    print(f"out is {out_gen}")
+    return out_gen
+
+demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+demo.launch(debug=True, share=True)