Update app.py

app.py

@@ -2,6 +2,8 @@ import gradio as gr
 import os
 from langchain_community.document_loaders import JSONLoader
 from langchain_community.vectorstores import Qdrant
+from qdrant_client.http import models as rest
+from qdrant_client import QdrantClient, models
 from langchain_community.embeddings import HuggingFaceEmbeddings, HuggingFaceBgeEmbeddings
 from sentence_transformers.cross_encoder import CrossEncoder
 from groq import Groq
@@ -12,7 +14,7 @@ client = Groq(
 
 # loading data
 json_path = "format_food.json"
-#json_path = "llama70b_food_dump.json"
+json_path = "llama70b_food_dump.json"
 
 def metadata_func(record: dict, metadata: dict) -> dict:
     metadata["title"] = record.get("title")
@@ -37,7 +39,7 @@ loader = JSONLoader(
 )
 
 data = loader.load()
-
+country_list  = list(set([item.metadata['cuisine'] for item in data]))
 # Models
 # model_name = "Snowflake/snowflake-arctic-embed-xs"
 # rerank_model = CrossEncoder("mixedbread-ai/mxbai-rerank-xsmall-v1")
@@ -72,9 +74,25 @@ def format_to_markdown(response_list):
     temp_string = "\n- ".join(response_list)
     return temp_string
 
-def run_query(query: str, groq: bool):
+def run_query(query: str, groq: bool, countries: str = "None"):
     print("Running Query")
-    answer = qdrant.similarity_search(query=query, k=10)
+    if countries != "None":
+        countries_select = models.Filter(
+            must=[
+                models.FieldCondition(
+                    key="metadata.cuisine",  # Adjust key based on your data structure
+                    match=models.MatchValue(value=countries),
+                )
+            ]
+        )
+    else:
+        countries_select = None
+
+    answer = qdrant.similarity_search(
+        query=query, 
+        k=10, 
+        filter=countries_select
+    )
     title_and_description = f"# Best Choice:\nA {answer[0].metadata['title']}: {answer[0].page_content}"
     instructions = format_to_markdown(answer[0].metadata['instructions'])
     recipe = f"# Standard Method\n## Cooking time:\n{answer[0].metadata['time']}\n\n## Recipe:\n{instructions}"
@@ -97,11 +115,12 @@ def run_query(query: str, groq: bool):
 with gr.Blocks() as demo:
     gr.Markdown("Start typing below and then click **Run** to see the output.")
     inp = gr.Textbox(placeholder="What sort of meal are you after?")
+    dropdown = gr.Dropdown(['None'] + country_list, label='Filter on countries', value='None')
     groq_button = gr.Checkbox(value=False, label="Use Llama for a better recipe?")
     title_output = gr.Markdown(label="Title and description")
     instructions_output = gr.Markdown(label="Recipe")
     updated_recipe = gr.Markdown(label="Updated Recipe")
     btn = gr.Button("Run")
-    btn.click(fn=run_query, inputs=[inp, groq_button], outputs=[title_output, instructions_output, updated_recipe])
+    btn.click(fn=run_query, inputs=[inp, groq_button, dropdown], outputs=[title_output, instructions_output, updated_recipe])
 
 demo.launch()