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refactoring pyproject.toml
Co-Authored-By: Matteo Vedovati <68272450+vedovati-matteo@users.noreply.github.com>
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@ -9,16 +9,11 @@ from scrapegraphai.utils import prettify_exec_info
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graph_config = {
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"llm": {
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"model": "ollama/mistral",
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"temperature": 0,
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"model": "ollama/llama3.1",
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"temperature": 0.5,
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# "model_tokens": 2000, # set context length arbitrarily,
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"base_url": "http://localhost:11434", # set ollama URL arbitrarily
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},
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"embeddings": {
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"model": "ollama/nomic-embed-text",
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"temperature": 0,
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"base_url": "http://localhost:11434", # set ollama URL arbitrarily
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},
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"library": "beautifoulsoup",
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"verbose": True,
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}
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@ -23,6 +23,8 @@ dependencies = [
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"langchain-groq>=0.1.3",
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"langchain-aws>=0.1.3",
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"langchain-anthropic>=0.1.11",
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"langchain-mistralai>=0.1.12",
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"langchain-huggingface>=0.0.3",
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"langchain-nvidia-ai-endpoints>=0.1.6",
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"html2text>=2024.2.26",
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"faiss-cpu>=1.8.0",
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@ -38,11 +40,7 @@ dependencies = [
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"google>=3.0.0",
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"undetected-playwright>=0.3.0",
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"semchunk>=1.0.1",
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"langchain-fireworks>=0.1.3",
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"langchain-community>=0.2.9",
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"langchain-huggingface>=0.0.3",
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"browserbase>=0.3.0",
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"langchain-mistralai>=0.1.12",
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]
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license = "MIT"
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@ -170,12 +170,12 @@ class AbstractGraph(ABC):
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if llm_params["model"].startswith("vertexai"):
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return handle_model(llm_params["model"], "google_vertexai", llm_params["model"])
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if "ollama" in llm_params["model"]:
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model_name = llm_params["model"].split("ollama/")[-1]
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token_key = model_name if "model_tokens" not in llm_params else llm_params["model_tokens"]
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return handle_model(model_name, "ollama", token_key)
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if "hugging_face" in llm_params["model"]:
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model_name = llm_params["model"].split("/")[-1]
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return handle_model(model_name, "hugging_face", model_name)
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@ -90,7 +90,7 @@ class ParseNode(BaseNode):
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chunk_size=self.node_config.get("chunk_size", 4096)-250,
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token_counter=lambda text: len(text.split()),
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memoize=False)
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state.update({self.output[0]: chunks})
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return state
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