add newfiles

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+local_qdrant/collection/qa_data/storage.sqlite filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,53 @@
+from langchain.vectorstores import Qdrant
+from langchain.embeddings import HuggingFaceEmbeddings
+from qdrant_client import QdrantClient
+import gradio as gr
+
+def process_text(input_text, top_k):
+    embeddings = HuggingFaceEmbeddings(model_name="intfloat/multilingual-e5-base")
+    client = QdrantClient(
+        path="./local_qdrant", prefer_grpc=True
+    )
+    db = Qdrant(client=client, embeddings=embeddings, collection_name="qa_data")
+
+    query = input_text
+
+    all_answers = []
+    docs = db.similarity_search_with_score(query=query, k=top_k)
+    for i in docs:
+        doc, score = i
+        print({"score": score, "content": doc.page_content, "metadata": doc.metadata} )
+        all_answers.append(doc.metadata["source"])
+
+    return "\n***\\n".join(all_answers)
+
+CSS ="""
+.contain { display: flex; flex-direction: column; }
+.gradio-container { height: 100vh !important; }
+#component-0 { height: 100%; }
+#textbox { flex-grow: 1; overflow: auto; resize: vertical; }
+.secondary {background-color: #6366f1; }
+"""
+#with gr.Blocks() as demo:
+with gr.Blocks(theme=gr.themes.Monochrome(radius_size=gr.themes.sizes.radius_sm)) as demo:
+    with gr.Row():
+        gr.Markdown("# 裁定検索")
+    with gr.Row():
+        output = gr.TextArea(
+            elem_id="検索結果",
+            label="検索結果",
+        )
+    with gr.Row():
+        input = gr.Textbox(
+            label="質問",
+            placeholder="芸魔龍王アメイジンの出た時の効果は、後から出たクリーチャーも影響しますか",
+            lines=3,
+        )
+    with gr.Row():
+        submit = gr.Button(value="検索", variant="secondary").style(full_width=True)
+        top_k = gr.Slider(1, 10, label="表示数", step=1, value=5, interactive=True)
+    
+    submit_click_event = submit.click(fn=process_text, inputs=[input, top_k], outputs=output)
+
+demo.launch()
+# demo.queue(max_size=128, concurrency_count=48).launch(debug=True, server_name="0.0.0.0", server_port=7860)

local_qdrant/.lock

@@ -0,0 +1 @@
+tmp lock file

local_qdrant/collection/qa_data/storage.sqlite

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:59593dd8ca06ee6d0708e9e27e1fe1383e67db9a14145b0000e0ae75ca7a0279
+size 26202112

local_qdrant/meta.json

@@ -0,0 +1 @@
+{"collections": {"qa_data": {"vectors": {"size": 768, "distance": "Cosine", "hnsw_config": null, "quantization_config": null, "on_disk": null}, "shard_number": null, "replication_factor": null, "write_consistency_factor": null, "on_disk_payload": null, "hnsw_config": null, "wal_config": null, "optimizers_config": null, "init_from": null, "quantization_config": null}}, "aliases": {}}

requirements.txt

@@ -0,0 +1,4 @@
+langchain==0.0.312
+qdrant-client==1.6.0
+sentence-transformers==2.2.2
+gradio==3.47.1