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23 lines
943 B
23 lines
943 B
# Example of fetching documents and go though them one by one using Ollama: |
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from arango_class import ArangoDB |
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import ollama |
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# Get the documents where "electric car" is mentioned |
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arango = ArangoDB() |
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db = arango.db |
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q = 'FOR doc IN speeches FILTER doc.translation LIKE "%electric car%" RETURN doc' |
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cursor = db.aql.execute(q) # Modify query |
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documents = list(cursor) |
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# Go though the documents one by one |
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for doc in documents: |
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text = doc['translation'] |
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prompt =f"""Below is a transcript of a speech given in the European Parliament. I'm interested in all arguments related to electric cars. |
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\n{text}\n |
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Please give me a list of all arguments related to electric cars in the text above. One argument per line. |
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Answer ONLY with the arguments. Kepp to the information in the text.""" #TODO Make a better prompt! |
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arguments = ollama.generate(prompt=prompt, model='llama3:8b-instruct-q5_K_M', options={'temperature': 0})
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