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.ipynb_checkpoints/main-checkpoint.py

@@ -0,0 +1,51 @@
+from langchain_community.llms import HuggingFaceEndpoint
+from langchain.prompts import PromptTemplate
+from langchain.schema import AIMessage, HumanMessage
+from langchain.chains import LLMChain
+import gradio as gr
+import os
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
+llm = HuggingFaceEndpoint(
+    repo_id = repo_id, 
+    # huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
+)
+
+# template = """You're a good chatbot, you're thinking only about Eras Tour. 
+# You're playing with the user: they will guess what you're thinking. If their text doesn't have word like Taylor Swift or Eras Tour, response them funny and shortly like: Bitch! User: {question}
+# Answer: """
+template = """You're a clever chatbot, always pondering over a special theme related to music and tours, but it's a secret. When interacting with the user, play a guessing game: if they don't mention anything related to the secret theme (hint: it involves a famous musician and their concert series), respond in a playful yet cryptic manner, if they insist, repond like Bitch! Hell no!, etc ... Here's how you should structure your responses:
+User: {question}
+Answer: """
+prompt = PromptTemplate.from_template(template=template)
+llm_chain = LLMChain(llm=llm, prompt=prompt)
+
+
+def predict(message, history):
+    history_langchain_format = []
+    # for human, ai in history:
+    #     history_langchain_format.append(HumanMessage(content=human))
+    #     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']
+    return response
+
+gr.ChatInterface(predict).launch()
+
+
+
+
+
+
+
+
+
+
+
+
+

main.py

@@ -15,9 +15,12 @@ llm = HuggingFaceEndpoint(
     # huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
 )
 
-template = """You're a good chatbot, you're thinking only about Eras Tour. 
-You're playing with the user: they will guess what you're thinking. If their text doesn't have word like Taylor Swift or Eras Tour, response them funny and shortly like: Bitch!. User: {question}
-Answer: ."""
+# template = """You're a good chatbot, you're thinking only about Eras Tour. 
+# You're playing with the user: they will guess what you're thinking. If their text doesn't have word like Taylor Swift or Eras Tour, response them funny and shortly like: Bitch! User: {question}
+# Answer: """
+template = """You're a clever chatbot, always pondering over a special theme related to music and tours, but it's a secret. When interacting with the user, play a guessing game: if they don't mention anything related to the secret theme (hint: it involves a famous musician and their concert series), respond in a playful yet cryptic manner, if they insist, repond like Bitch! Hell no!, etc ... Here's how you should structure your responses:
+User: {question}
+Answer: """
 prompt = PromptTemplate.from_template(template=template)
 llm_chain = LLMChain(llm=llm, prompt=prompt)