Spaces:
Build error
Build error
heikowagner
commited on
Commit
•
fae55e7
1
Parent(s):
b45426b
addexample
Browse files- .gitignore +0 -1
- app/VectorStore/chroma-collections.parquet +3 -0
- app/VectorStore/index/id_to_uuid_3c194f90-478a-4f8e-a5ac-67776218c783.pkl +3 -0
- app/VectorStore/index/index_3c194f90-478a-4f8e-a5ac-67776218c783.bin +3 -0
- app/VectorStore/index/index_metadata_3c194f90-478a-4f8e-a5ac-67776218c783.pkl +3 -0
- app/VectorStore/index/uuid_to_id_3c194f90-478a-4f8e-a5ac-67776218c783.pkl +3 -0
- app/run.py +1 -1
.gitignore
CHANGED
@@ -8,5 +8,4 @@ root
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.vscode
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/app/mymodels
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/app/.cache
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/app/VectorStore
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*chroma-embeddings.parquet*
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.vscode
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/app/mymodels
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/app/.cache
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*chroma-embeddings.parquet*
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app/VectorStore/chroma-collections.parquet
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:485e9d46361ec332e64d9b50063f7b958cfd7bf015931232033e05d34e3474d2
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size 712
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app/VectorStore/index/id_to_uuid_3c194f90-478a-4f8e-a5ac-67776218c783.pkl
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:30970b5f5b747f17da7471033fc01cda622aeb236966628f64285f507247c30e
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size 7594
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app/VectorStore/index/index_3c194f90-478a-4f8e-a5ac-67776218c783.bin
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:c220ae8125b8343264f932baba1c2abb62767acb593271c3745d43e50094eefb
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size 773296
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app/VectorStore/index/index_metadata_3c194f90-478a-4f8e-a5ac-67776218c783.pkl
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:70331079a9c91229b14c8d52b03b769cc42a7753a3e28272be2dfc41323d1af7
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size 73
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app/VectorStore/index/uuid_to_id_3c194f90-478a-4f8e-a5ac-67776218c783.pkl
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:e0e3ec8fd73d4a0139cfbc5a75be1534a545f7d6885200397eb3397dc792a60e
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size 8896
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app/run.py
CHANGED
@@ -12,6 +12,6 @@ import cloudpickle
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llm= load_model.load_openai_model()
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# %%
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chain = load_model.create_chain(llm, collection="
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result = chain({"query": "What are AXAs green Goals?"})
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print(result)
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llm= load_model.load_openai_model()
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# %%
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chain = load_model.create_chain(llm, collection="heikospaper")
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result = chain({"query": "What are AXAs green Goals?"})
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print(result)
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