Update app.py

app.py

@@ -1,4 +1,3 @@
-# app.py
 
 from flask import Flask, render_template, request, jsonify
 import faiss
@@ -8,6 +7,7 @@ from sentence_transformers import SentenceTransformer
 from langchain.prompts import PromptTemplate
 from langchain_groq import ChatGroq
 import re
+from langchain_openai import AzureChatOpenAI
 import os
 from dotenv import load_dotenv
 load_dotenv()
@@ -15,11 +15,23 @@ load_dotenv()
 app = Flask(__name__)
 
 # Load Model and FAISS Index
+
+
+# AzureOpenAiEndpoint= os.getenv("AZURE_OPENAI_ENDPOINT")
+# AzureOpenAiKey= os.getenv("AZURE_OPENAI_KEY")
+# OpenaiApiVersion= os.getenv("OPENAI_API_VERSION")
+# DeploymentName= os.getenv("DEPLOYMENT_NAME")
 model = SentenceTransformer('./sentence-transformers_all-MiniLM-L6-v2')
 index = faiss.read_index("faiss_index.bin")
 groq_api_key = os.getenv('GROQ_API_KEY')
 model_name = "llama-3.3-70b-versatile"
 
+# llm = AzureChatOpenAI(
+#     openai_api_version= OpenaiApiVersion,  # Change based on your API version
+#     deployment_name = DeploymentName,  # The model deployment name in Azure
+#     openai_api_key= AzureOpenAiKey,  # Use the environment variable
+#     azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],  # Use the environment variable
+# )
 llm = ChatGroq(
             temperature=0, 
             groq_api_key=groq_api_key, 
@@ -107,7 +119,9 @@ def search_text(query, top_k=2):
 def home():
     return render_template("index.html")
 
+import re
 @app.route("/query", methods=["POST"])
+
 def query_pdf():
     query = request.json.get("query")
 
@@ -134,8 +148,6 @@ def query_pdf():
     if query_type == "rude":
         return jsonify({"text": "I'm here to assist you professionally.", "images": []})
 
-
-
     # Search for relevant PDF content using FAISS
     results = search_text(query, top_k=3)
 
@@ -150,15 +162,16 @@ def query_pdf():
         """
         ### YOU ARE AN EXELSYS EASYHR GUIDE ASSISTANT:
         ### INSTRUCTIONS:
-        - Your job is to provide step-by-step guidance for the following user query based on the provided context.
-        - Base your response **only** on the retrieved context from the PDF.
-        - If no relevant information is found, simply respond with: "Not found."
+        - Identify the most relevant topic based on the user query.
+        - Provide step-by-step guidance for that topic only.
+        - Base your response **only** on the selected topic's content.
+        - Do not use content from other topics.
+        - If no relevant topic is found, respond with: "Not found."
         - If the user greets you (e.g., "Hello", "Hi", "Good morning"), respond politely but keep it brief.
         - If the query is unrelated to Exelsys easyHR, respond with: "I'm here to assist with Exelsys easyHR queries only."
-        - Provide clear and concise answers.
-        - Provide all the links that inside any topic in <a> tag.
+        - Format the response like this:
+        <p>Response text here...</p> \n <a>static/output_images/page_67_img_2.png</a>\n <a>static/output_images/page_45_img_1.jpg</a> 
         
-
         ### USER QUERY:
         {query}
 
@@ -176,20 +189,23 @@ def query_pdf():
     # Convert response to string
     response_text = str(chat_response.content)
 
-    # Determine if images should be included
-    # retrieved_images = []
-    # if "Not found." not in response_text and "I'm here to assist" not in response_text:
-    #     retrieved_images = [img for res in results if "images" in res for img in res["images"]]
+    # Extract multiple image paths from response
+    image_pattern = r"static/output_images/[\w\d_]+\.png"
+    extracted_images = re.findall(image_pattern, response_text)
+
+    # Remove image paths from text
+    cleaned_text = re.sub(image_pattern, "", response_text).strip()
 
     # Final response JSON
     response = {
-        "text": response_text,
-        # "images": retrieved_images
+        "text": cleaned_text,
+        "images": extracted_images  # Store multiple images in a list
     }
     print(response)
 
     return jsonify(response)
 
+
 if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)
+    app.run(debug=True)