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For an example https://github.com/qdrant/examples/blob/06fd19db652bcd9f88e35c8e178a114b5791e8c9/rag-openai-qdrant/rag-openai-qdrant.ipynb still use query_text.
query_text
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) Cell In[9], [line 1](vscode-notebook-cell:?execution_count=9&line=1) ----> [1](vscode-notebook-cell:?execution_count=9&line=1) results = client.search( [2](vscode-notebook-cell:?execution_count=9&line=2) collection_name="knowledge-base", [3](vscode-notebook-cell:?execution_count=9&line=3) query_text=prompt, [4](vscode-notebook-cell:?execution_count=9&line=4) limit=3, [5](vscode-notebook-cell:?execution_count=9&line=5) ) [6](vscode-notebook-cell:?execution_count=9&line=6) results TypeError: QdrantClient.search() missing 1 required positional argument: 'query_vector'
And document just use a random number for query_vector which not reflect real life use.
query_vector
The text was updated successfully, but these errors were encountered:
UPDATE: It seem like I can use client.query instead of client.search maybe this is a way to fix this?
client.query
client.search
results = client.query( collection_name="knowledge-base", query_text=prompt, limit=3, ) results
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For an example https://github.com/qdrant/examples/blob/06fd19db652bcd9f88e35c8e178a114b5791e8c9/rag-openai-qdrant/rag-openai-qdrant.ipynb still use
query_text
.And document just use a random number for
query_vector
which not reflect real life use.The text was updated successfully, but these errors were encountered: