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Update crew.py
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crew.py
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@@ -55,7 +55,7 @@ class NewsletterGenCrew:
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#
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# BadRequestError: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Claude API. Please go to Plans & Billing to upgrade or purchase credits.'}}
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llm = ChatGroq(model="llama3-70b-8192")
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# https://console.groq.com/docs/rate-limits
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# llm = ChatGroq(model="mixtral-8x7b-32768") # JB 13-06-2024 - geeft af en toe rate limit errors
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# IN HF SPACES STREAMLIT APP: BadRequestError: Error code: 400 - {'error': {'message': 'Organization has been restricted. Please reach out to support if you believe this was in error.', 'type': 'invalid_request_error', 'code': 'organization_restricted'}}
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@@ -86,6 +86,27 @@ class NewsletterGenCrew:
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# https://github.com/ollama/ollama/issues/2833
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print("JB: in class NewsletterGenCrew - using llm: ", llm)
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return llm
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#
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# BadRequestError: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Claude API. Please go to Plans & Billing to upgrade or purchase credits.'}}
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# llm = ChatGroq(model="llama3-70b-8192")
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# https://console.groq.com/docs/rate-limits
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# llm = ChatGroq(model="mixtral-8x7b-32768") # JB 13-06-2024 - geeft af en toe rate limit errors
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# IN HF SPACES STREAMLIT APP: BadRequestError: Error code: 400 - {'error': {'message': 'Organization has been restricted. Please reach out to support if you believe this was in error.', 'type': 'invalid_request_error', 'code': 'organization_restricted'}}
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# https://github.com/ollama/ollama/issues/2833
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# HUGGING FACE LLMs
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# https://python.langchain.com/v0.2/docs/integrations/chat/huggingface/
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# HUGGINGFACEHUB_API_TOKEN
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# https://huggingface.co/docs/hub/security-tokens
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# https://huggingface.co/settings/tokens
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# %pip install --upgrade --quiet langchain-huggingface text-generation transformers google-search-results numexpr langchainhub sentencepiece jinja2
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# 1. Instantiate an LLM
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# HuggingFaceEndpoint
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# from langchain_huggingface import HuggingFaceEndpoint
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#
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llm = HuggingFaceEndpoint(
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repo_id="meta-llama/Meta-Llama-3-70B-Instruct",
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task="text-generation",
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max_new_tokens=512,
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do_sample=False,
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repetition_penalty=1.03,
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)
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# API Reference:HuggingFaceEndpoint
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print("JB: in class NewsletterGenCrew - using llm: ", llm)
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return llm
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