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Configuration error
Configuration error
rlhf with langchain
Browse files- __pycache__/utils.cpython-310.pyc +0 -0
- app.py +15 -10
- data +1 -0
__pycache__/utils.cpython-310.pyc
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Binary file (977 Bytes). View file
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app.py
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@@ -14,6 +14,10 @@ import json
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from utils import force_git_push
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import threading
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# These variables are for storing the mturk HITs in a Hugging Face dataset.
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if Path(".env").is_file():
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load_dotenv(".env")
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@@ -49,7 +53,8 @@ f_stop = threading.Event()
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asynchronous_push(f_stop)
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# Now let's run the app!
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-
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demo = gr.Blocks()
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@@ -76,14 +81,14 @@ with demo:
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# Generate model prediction
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# Default model: distilbert-base-uncased-finetuned-sst-2-english
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def _predict(txt, state):
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conversation_1 = Conversation(past_user_inputs=state["past_user_inputs"].copy(), generated_responses=state["generated_responses"].copy())
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conversation_2 = Conversation(past_user_inputs=state["past_user_inputs"].copy(), generated_responses=state["generated_responses"].copy())
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conversation_1.add_user_input(txt)
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conversation_2.add_user_input(txt)
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conversation_1 = chatbot(
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conversation_2 = chatbot(
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response_1 = conversation_1.
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response_2 = conversation_2.
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state["cnt"] += 1
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@@ -199,4 +204,4 @@ with demo:
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_js=refresh_app_js,
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)
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demo.launch()
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from utils import force_git_push
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import threading
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#langchain imports
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from langchain import HuggingFacePipeline, LLMChain, PromptTemplate
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from langchain.chains.conversation.memory import ConversationalBufferWindowMemory
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# These variables are for storing the mturk HITs in a Hugging Face dataset.
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if Path(".env").is_file():
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load_dotenv(".env")
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asynchronous_push(f_stop)
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# Now let's run the app!
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pipe = pipeline(model="google/flan-t5-xl-qa", tokenizer="google/flan-t5-xl", task="text2text-generation")
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chatbot = HuggingFacePipeline(pipeline=pipe)
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demo = gr.Blocks()
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# Generate model prediction
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# Default model: distilbert-base-uncased-finetuned-sst-2-english
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def _predict(txt, state):
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# conversation_1 = Conversation(past_user_inputs=state["past_user_inputs"].copy(), generated_responses=state["generated_responses"].copy())
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# conversation_2 = Conversation(past_user_inputs=state["past_user_inputs"].copy(), generated_responses=state["generated_responses"].copy())
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# conversation_1.add_user_input(txt)
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# conversation_2.add_user_input(txt)
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conversation_1 = chatbot(txt, do_sample=True, seed=420)
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conversation_2 = chatbot(txt, do_sample=True, seed=69)
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response_1 = conversation_1.generated_text[-1]
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response_2 = conversation_2.generated_text[-1]
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state["cnt"] += 1
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_js=refresh_app_js,
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)
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demo.launch(share=True)
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data
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Subproject commit b539037325ecb230f37bda2d9f8daad6c23db37c
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