Update agent.py
Browse files
agent.py
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@@ -4,7 +4,6 @@ from llama_index.core import VectorStoreIndex, Document
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from llama_index.core.node_parser import SentenceWindowNodeParser, HierarchicalNodeParser
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from llama_index.core.postprocessor import SentenceTransformerRerank
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from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
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from llama_index.core.retrievers import VectorIndexRetriever
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from llama_index.core.query_engine import RetrieverQueryEngine
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from llama_index.readers.file import PDFReader, DocxReader, CSVReader, ImageReader
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@@ -23,9 +22,24 @@ from llama_index.core.callbacks.base import CallbackManager
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from llama_index.core.callbacks.llama_debug import LlamaDebugHandler
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from llama_index.core import Settings
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)
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embed_model = HuggingFaceEmbedding("BAAI/bge-small-en-v1.5")
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from llama_index.core.node_parser import SentenceWindowNodeParser, HierarchicalNodeParser
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from llama_index.core.postprocessor import SentenceTransformerRerank
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from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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from llama_index.core.retrievers import VectorIndexRetriever
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from llama_index.core.query_engine import RetrieverQueryEngine
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from llama_index.readers.file import PDFReader, DocxReader, CSVReader, ImageReader
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from llama_index.core.callbacks.llama_debug import LlamaDebugHandler
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from llama_index.core import Settings
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from llama_index.llms.huggingface import HuggingFaceLLM
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model_id = "mistralai/Pixtral-12B-Base-2409" # or "mistralai/Mistral-7B-Instruct-v0.2"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype="auto", # or torch.float16 for FP16
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device_map="auto" # will use all available GPUs
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)
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proj_llm = HuggingFaceLLM(
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model=model,
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tokenizer=tokenizer,
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context_window=3900, # adjust as needed
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max_new_tokens=512, # adjust as needed
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device_map="auto", # ensures multi-GPU support
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generate_kwargs={"temperature": 0.7, "top_p": 0.95}
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)
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embed_model = HuggingFaceEmbedding("BAAI/bge-small-en-v1.5")
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