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54 lines
1.5 KiB
Python
54 lines
1.5 KiB
Python
"""
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Example of Search Graph
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"""
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import os
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from scrapegraphai.graphs import SearchGraph
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from scrapegraphai.utils import convert_to_csv, convert_to_json, prettify_exec_info
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from langchain_community.llms import HuggingFaceEndpoint
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from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
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# ************************************************
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# Define the configuration for the graph
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# ************************************************
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# ************************************************
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HUGGINGFACEHUB_API_TOKEN = os.getenv('HUGGINGFACEHUB_API_TOKEN')
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repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
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llm_model_instance = HuggingFaceEndpoint(
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repo_id=repo_id, max_length=128, temperature=0.5, token=HUGGINGFACEHUB_API_TOKEN
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)
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embedder_model_instance = HuggingFaceInferenceAPIEmbeddings(
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api_key=HUGGINGFACEHUB_API_TOKEN, model_name="sentence-transformers/all-MiniLM-l6-v2"
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)
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graph_config = {
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"llm": {"model_instance": llm_model_instance},
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}
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# ************************************************
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# Create the SearchGraph instance and run it
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# ************************************************
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search_graph = SearchGraph(
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prompt="List me the best escursions near Trento",
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config=graph_config
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)
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result = search_graph.run()
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print(result)
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# ************************************************
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# Get graph execution info
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# ************************************************
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graph_exec_info = search_graph.get_execution_info()
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print(prettify_exec_info(graph_exec_info))
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# Save to json and csv
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convert_to_csv(result, "result")
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convert_to_json(result, "result")
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