Update main.py
Browse files
main.py
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@@ -22,6 +22,8 @@ from langchain_core.tracers.context import tracing_v2_enabled
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import chainlit as cl
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from chainlit.input_widget import TextInput, Select, Switch, Slider
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from deep_translator import GoogleTranslator
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@@ -45,10 +47,22 @@ def auth_callback(username: str, password: str):
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def LLModel():
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os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HUGGINGFACEHUB_API_TOKEN']
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repo_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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-
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repo_id=repo_id, max_new_tokens=5500, temperature=1.0, task="text2text-generation", streaming=True
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)
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def VectorDatabase(categorie):
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if categorie != "year":
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import chainlit as cl
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from chainlit.input_widget import TextInput, Select, Switch, Slider
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from chainlit.playground.config import add_llm_provider
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from chainlit.playground.providers.langchain import LangchainGenericProvider
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from deep_translator import GoogleTranslator
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def LLModel():
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os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HUGGINGFACEHUB_API_TOKEN']
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repo_id = "mistralai/Mixtral-8x7B-Instruct-v0.1"
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llm = HuggingFaceEndpoint(
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repo_id=repo_id, max_new_tokens=5500, temperature=1.0, task="text2text-generation", streaming=True
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)
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add_llm_provider(
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LangchainGenericProvider(
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# It is important that the id of the provider matches the _llm_type
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id=llm._llm_type,
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# The name is not important. It will be displayed in the UI.
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name="HuggingFaceHub",
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# This should always be a Langchain llm instance (correctly configured)
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llm=llm,
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# If the LLM works with messages, set this to True
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is_chat=True
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)
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)
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return llm
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def VectorDatabase(categorie):
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if categorie != "year":
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