Update app.py

app.py

@@ -39,54 +39,54 @@ from streamlit_pdf_viewer import pdf_viewer
 
 
 
-def consume_llm_api(prompt):
-    """
-    Sends a prompt to the LLM API and processes the streamed response.
-    """
-    url = "https://8417-201-238-124-65.ngrok-free.app/api/llm-response"
-    headers = {"Content-Type": "application/json"}
-    payload = {"prompt": prompt}
-
-    try:
-        print("Sending prompt to the LLM API...")
-        with requests.post(url, json=payload, headers=headers, stream=True) as response:
-            response.raise_for_status()
-            print("Response from LLM API:\n")
-            for line in response:
-                yield(line.decode('utf-8'))
-            # print(type(response))
-            # yield(response)
-    except requests.RequestException as e:
-        print(f"Error consuming API: {e}")
-    except Exception as e:
-        print(f"Unexpected error: {e}")
 # def consume_llm_api(prompt):
+#     """
+#     Sends a prompt to the LLM API and processes the streamed response.
+#     """
+#     url = "https://8417-201-238-124-65.ngrok-free.app/api/llm-response"
+#     headers = {"Content-Type": "application/json"}
+#     payload = {"prompt": prompt}
+
+#     try:
+#         print("Sending prompt to the LLM API...")
+#         with requests.post(url, json=payload, headers=headers, stream=True) as response:
+#             response.raise_for_status()
+#             print("Response from LLM API:\n")
+#             for line in response:
+#                 yield(line.decode('utf-8'))
+#             # print(type(response))
+#             # yield(response)
+#     except requests.RequestException as e:
+#         print(f"Error consuming API: {e}")
+#     except Exception as e:
+#         print(f"Unexpected error: {e}")
+def consume_llm_api(prompt):
     
-#     client = Groq(
-#         api_key="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"
-#     )
+    client = Groq(
+        api_key="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"
+    )
 
-#     completion = client.chat.completions.create(
+    completion = client.chat.completions.create(
         
-#         model="llama-3.3-70b-versatile",
-#         messages=[
-
-#             {
-#                 "role": "system",
-#                 "content": prompt
-#             },
-#         ],
-
-#         temperature=1,
-#         # max_completion_tokens=1024,
-#         top_p=1,
-#         stream=True,
-#         stop=None,
-#     )
-
-#     for chunk in completion:
-#         if chunk.choices[0].delta.content:
-#             yield chunk.choices[0].delta.content
+        model="llama-3.3-70b-versatile",
+        messages=[
+
+            {
+                "role": "system",
+                "content": prompt
+            },
+        ],
+
+        temperature=1,
+        # max_completion_tokens=1024,
+        top_p=1,
+        stream=True,
+        stop=None,
+    )
+
+    for chunk in completion:
+        if chunk.choices[0].delta.content:
+            yield chunk.choices[0].delta.content
 @st.cache_resource
 def encoding_model():
     """
@@ -351,7 +351,7 @@ with column2:
                 for index,prompts_ in enumerate(dictionary['every_prompt_with_val'][::-1]):
                     if prompts_[-1]=="@working":
                         if index==0:
-
+                            st.write(prompts_[0].split(send_prompt())[-1].upper() if send_prompt() in prompts_[0] else prompts_[0].upper())
                             data_need=""
                             while(len(data_need)==0):
                                 if len(prompts_)==3: