Upload app.py

app.py

@@ -0,0 +1,102 @@
+from llama_index.llms.openai import OpenAI
+from llama_index.embeddings.openai import OpenAIEmbedding
+from llama_index.core import Settings
+import os
+import json
+import streamlit as st
+import requests
+
+adminkey = "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"
+os.environ["OPENAI_API_KEY"] = adminkey
+
+Settings.llm = OpenAI(model="gpt-3.5-turbo", temperature=0.4)
+Settings.embed_model = OpenAIEmbedding(model="text-embedding-ada-002")
+
+from opensearchpy import OpenSearch, RequestsHttpConnection
+
+auth = ('admin','klbvrR4AlGNMaQ')
+
+host = '10.11.10.111'
+port = 32000
+
+client = OpenSearch(
+    hosts = [{'host': host, 'port': port}],
+    http_auth = auth,
+    use_ssl = True,
+    verify_certs = False
+)
+
+def generate_opensearch_query(user_input):
+    prompt = f"""
+    You are an assistant trained to translate natural language requests into OpenSearch queries. Based on the user's request, generate an OpenSearch JSON query.
+
+    Examples:
+    User Input: "Get all documents where the status is active."
+    Response:
+    {{
+      "query": {{
+        "match": {{
+          "status": "active"
+        }}
+      }}
+    }}
+
+    User Input: "Find records with priority high created in the last 7 days."
+    Response:
+    {{
+      "query": {{
+        "bool": {{
+          "must": [
+            {{ "match": {{ "priority": "high" }} }},
+            {{ "range": {{ "created_at": {{ "gte": "now-7d/d", "lte": "now" }} }} }}
+          ]
+        }}
+      }}
+    }}
+
+    User Input: "Show documents where age is over 30 and sort by created date."
+    Response:
+    {{
+      "query": {{
+        "range": {{
+          "age": {{ "gt": 30 }}
+        }}
+      }},
+      "sort": [
+        {{ "created_date": {{ "order": "asc" }} }}
+      ]
+    }}
+
+    User Input: "{user_input}"
+    Response:
+    """
+
+    llm_response = Settings.llm.complete(prompt)
+    return llm_response
+
+def implement_query(generated_query):
+    query = json.loads(generated_query.text)
+    response = client.search(body=query)
+    return response
+
+
+st.title("OpenSearch Query Generator")
+st.subheader("Enter your natural language query:")
+
+user_input = st.text_area("Enter a Prompt:", height=150)
+
+if st.button("Generate OpenSearch Query"):
+    if user_input.strip():
+        generated_query = generate_opensearch_query(user_input)
+
+        st.subheader("Generated OpenSearch Query:")
+        st.json(json.loads(generated_query.text))
+
+        try:
+            response = implement_query(generated_query)
+            st.subheader("OpenSearch Response:")
+            st.json(response)
+        except Exception as e:
+            st.error(f"Error executing OpenSearch query: {e}")
+    else:
+        st.warning("Please enter a valid query.")