Update app.py

app.py

@@ -8,83 +8,38 @@ import requests
 
 openai_api_key = os.getenv('OPENAI_API_KEY')
 
-Settings.llm = OpenAI(model="gpt-3.5-turbo", temperature=0.4)
-Settings.embed_model = OpenAIEmbedding(model="text-embedding-ada-002")
+client = OpenAI(api_key=openai_api_key)
 
-from opensearchpy import OpenSearch, RequestsHttpConnection
+  
 
+job_id = os.getenv('job_id')
+response = client.fine_tuning.jobs.retrieve(job_id)
 
 
-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"
-        }}
-      }}
-    }}
+st.title("AI Assistant - Fine-Tuned Model")
 
-    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:
-    """
+user_input = st.text_input("Enter your question:")
 
-    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
+if st.button("Ask"):
+    if user_input:
+     
+        try: 
+                    completion = client.chat.completions.create(
+                          model="ft:gpt-3.5-turbo-0125:personal::AVdWfIMJ",
+                          messages=[
+                            {"role": "system", "content": "You are an assistant trained to translate natural language requests into OpenSearch queries. Use a step-by-step approach to break down the user's request, identify components like filters, aggregations, and sort criteria, and generate a valid OpenSearch JSON query."},
+                            {"role": "user", "content": user_input}
+                                  ]
+                    )
+     
+                    st.write("Assistant's response:")
+                    st.write(completion.choices[0].message.content)
 
-
-st.title("OpenSearch Query Generator")
-
-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}")
+        except Exception as e:
+            st.write("Error:", e)
     else:
-        st.warning("Please enter a valid query.")
+        st.write("Please enter a question.")