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.ipynb_checkpoints/test_gradio-checkpoint.py

@@ -17,8 +17,8 @@ llm = HuggingFaceEndpoint(
 
 
 template = """You're a good chatbot. Answer this request: {question}
-Answer: Lprompt = PromptTemplate.from_template(template=template)
-et's think step by step."""
+Answer: Let's think step by step."""
+prompt = PromptTemplate.from_template(template=template)
 llm_chain = LLMChain(llm=llm, prompt=prompt)
 
 
@@ -29,7 +29,7 @@ def predict(message, history):
     #     history_langchain_format.append(AIMessage(content=ai))
     # history_langchain_format.append(HumanMessage(content=message))
     # gpt_response = llm(history_langchain_format)
-    response = llm_chain.invoke(message)['text']
+    response = llm_chain.invoke(message)
     return response
 
 gr.ChatInterface(predict).launch()

test_gradio.py

@@ -17,8 +17,8 @@ llm = HuggingFaceEndpoint(
 
 
 template = """You're a good chatbot. Answer this request: {question}
-Answer: Lprompt = PromptTemplate.from_template(template=template)
-et's think step by step."""
+Answer: Let's think step by step."""
+prompt = PromptTemplate.from_template(template=template)
 llm_chain = LLMChain(llm=llm, prompt=prompt)
 
 
@@ -29,7 +29,7 @@ def predict(message, history):
     #     history_langchain_format.append(AIMessage(content=ai))
     # history_langchain_format.append(HumanMessage(content=message))
     # gpt_response = llm(history_langchain_format)
-    response = llm_chain.invoke(message)['text']
+    response = llm_chain.invoke(message)
     return response
 
 gr.ChatInterface(predict).launch()