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Like I got two PDF files in different directories. I load them with the following: doc1 = SimpleDirectoryReader('file1').load_data() doc2 = SimpleDirectoryReader('file2.').load_data()
Then I created indexes for each: index1 = GPTTreeIndex.from_documents(doc1) index2 = GPTTreeIndex.from_documents(doc2) index1_summary = "<summary1>" index1_summary = str(summary1)
Hi, @AkshitChugh787! I'm Dosu, and I'm here to help the LlamaIndex team manage their backlog. I wanted to let you know that we are marking this issue as stale.
From what I understand, you opened this issue to inquire about using Llama-index for document classification with multiple indexes. You provided some code snippets and were seeking confirmation if your approach is correct. Asadabbas09 also commented on the issue, asking if a solution has been found.
However, it seems that the issue is still unresolved. Before we close it, we wanted to check with you if it is still relevant to the latest version of the LlamaIndex repository. If it is, please let us know by commenting on the issue. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days.
Thank you for your understanding, and please don't hesitate to reach out if you have any further questions or concerns.
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Oct 5, 2023
Like I got two PDF files in different directories. I load them with the following:
doc1 = SimpleDirectoryReader('file1').load_data()
doc2 = SimpleDirectoryReader('file2.').load_data()
Then I created indexes for each:
index1 = GPTTreeIndex.from_documents(doc1)
index2 = GPTTreeIndex.from_documents(doc2)
index1_summary = "<summary1>"
index1_summary = str(summary1)
all_indices = [index1, index2]
index_summaries = [index1_summary, index2_summary]
graph = ComposableGraph.from_indices(GPTTreeIndex, all_indices, index_summaries=index_summaries)
index = ComposableGraph.load_from_disk("graph.json")
query_configs = [ { "index_struct_type": "simple_dict", "query_mode": "default", "query_kwargs": { "similarity_top_k": 3, "response_mode": "tree_summarize" } }, ]
response = index.query(text, query_configs=query_configs)
is this approach correct or do I have to make changes? Can this classify both the indexes and queries asked related to them?
Thanks!
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