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@@ -8,30 +8,35 @@ chroma_client = chromadb.PersistentClient(path="data/chroma")
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vectordb = chroma_client.get_collection(name="collection")
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vectordb = chroma_client.get_collection(name="collection")
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+def generateStory(question):
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+ query = [question, ]
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+ response = erniebot.Embedding.create(
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+ input=query,
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+ model='ernie-text-embedding',
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+ )
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+ query_embeddings = response.data[0]['embedding']
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+ print(query_embeddings)
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+
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+ results = vectordb.query(
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+ query_embeddings=query_embeddings,
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+ n_results=1 # top_k
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+ )
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+
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+ search_result = {'metadatas': results['metadatas'][0], 'documents': results['documents'][0]}
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+ prompt = f"你是一个擅长给小朋友讲故事的小助手,请根据自己的知识和检索到的内容,对小朋友的疑问进行解答。注意,由于小朋友的年龄较小,问题解答需要用故事的形式。尽量使故事生动、有趣、富有哲理。 \n 用户问题: {question} \n\n 搜索结果:\n {search_result}"
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+ print(prompt)
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+
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+ messages = [
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+ {"role": "user", "content": prompt}
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+ ]
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+ response = erniebot.ChatCompletion.create(
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+ model="ernie-4.0",
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+ messages=messages
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+ )
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+ story = response.get_result()
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+ return story
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+
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+
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+
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question = "什么是克隆羊"
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question = "什么是克隆羊"
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-query = [question,]
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-response = erniebot.Embedding.create(
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- input=query,
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- model='ernie-text-embedding',
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-)
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-query_embeddings = response.data[0]['embedding']
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-print(query_embeddings)
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-
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-results = vectordb.query(
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- query_embeddings = query_embeddings,
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- n_results=1 #top_k
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-)
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-
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-search_result = {'metadatas': results['metadatas'][0], 'documents': results['documents'][0]}
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-prompt = f"你是一个擅长给小朋友讲故事的小助手,请根据自己的知识和检索到的内容,对小朋友的疑问进行解答。注意,由于小朋友的年龄较小,问题解答需要用故事的形式。尽量使故事生动、有趣、富有哲理。 \n 用户问题: {question} \n\n 搜索结果:\n {search_result}"
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-print(prompt)
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-
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-messages = [
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- {"role": "user", "content": prompt}
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-]
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-response = erniebot.ChatCompletion.create(
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- model="ernie-4.0",
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- messages=messages
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-)
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-story = response.get_result()
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-print(story)
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+print(generateStory(question))
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