Updated app to aksara v1 dashboard

app.py

@@ -1,66 +1,106 @@
-import os
 import gradio as gr
-import copy
+import sqlite3
+import pandas as pd
 import time
-import llama_cpp
-from llama_cpp import Llama
-from huggingface_hub import hf_hub_download  
-
-llm = Llama(
-    model_path=hf_hub_download(
-        repo_id="praveenpankaj/aksara_1_unsloth_q4",
-        filename="aksara_-unsloth.Q4_K_M.gguf",
-    ),
-    n_ctx=1024,
-) 
-
-history = []
-
-def generate_text(message, history):
-    temp = ""
-    input_prompt = "Ask akṣara anything on Agriculture in the Global South.\n"
-    for interaction in history:
-        input_prompt += "[|Umano|] " + interaction[0] + "\n"
-        input_prompt += "[|Assistente|]" + interaction[1]
+import huggingface_hub
+import shutil
+import os
+import datetime
+from apscheduler.schedulers.background import BackgroundScheduler
+
+from rag_output import rag_response
+
+
+TOKEN = os.environ.get('HFW_TOKEN')
     
-    input_prompt += "[|Umano|] " + message + "\n[|Assistente|]"
-
-    print(input_prompt)
-
-    output = llm(
-        input_prompt,
-        temperature=0.15,
-        top_p=0.1,
-        top_k=40, 
-        repeat_penalty=1.1,
-        max_tokens=1024,
-        stop=[
-            "[|Umano|]",
-            "[|Assistente|]",
-        ],
-        stream=True,
-    )
-    for out in output:
-        stream = copy.deepcopy(out)
-        temp += stream["choices"][0]["text"]
-        yield temp
-
-    history = ["init", input_prompt]
-
-
-demo = gr.ChatInterface(
-    generate_text,
-    title="akṣara running on CPU (quantized Q4_K)",
-    description="This is a quantized version of akṣara running on CPU. It is a quantized version of the original version, that is running on a CPU machine.",
-    examples=[
-        "What are the recommended NPK dosage for maize varieties?",
-        "Heavy rains are predicted next week. Is my rice crop ready for this, or should I harvest early?",
-        "What crops can I grow during the dry season to use water more efficiently?"
-    ],
-    cache_examples=False,
-    retry_btn=None,
-    undo_btn="Delete Previous",
-    clear_btn="Clear",
-)
-demo.queue(concurrency_count=1, max_size=5)
-demo.launch()
+def llm_response(message, history):
+    
+    res = rag_response(message)
+    
+    for i in range(len(res)):
+        time.sleep(0.02)
+        yield res[: i+1]
+    # return res
+
+
+def vote(response: gr.LikeData):
+    if response.liked:
+        add_review(1, response.value)
+    else:
+        add_review(0, response.value)
+        
+
+examples = ["What are the recommended NPK dosage for maize varieties?", 
+            # "What are the recommended chemical treatments to control army worms in wheat crops?", 
+            "Heavy rains are predicted next week. Is my rice crop ready for this, or should I harvest early?", 
+            "What crops can I grow during the dry season to use water more efficiently?", 
+            "How can I improve the health of my soil after a wheat harvest, using natural methods?", 
+            # "Are there crop rotation techniques that can reduce fertilizer needs for barley?"
+           ]
+
+# js_func = """
+# function refresh() {
+#     const url = new URL(window.location);
+
+#     if (url.searchParams.get('__theme') !== 'light') {
+#         url.searchParams.set('__theme', 'light');
+#         window.location.href = url.href;
+#     }
+# }
+# """
+
+
+
+description = "Hi! I am akṣara, an AI agronomist and I am here to help you with agriculture advisories for crops like paddy, wheat, maize, Sorghum, Barley, Cotton, Sugarcane, Soybean and Millets for the Indian subcontinent."
+
+title = "akṣara"
+theme = gr.themes.Soft(primary_hue="sky",)
+
+
+
+chatbot = gr.Chatbot(height="450px", 
+                     show_copy_button=True, 
+                     show_label=False,
+                     avatar_images=("user.webp","cropin.png"))
+
+textbox = gr.Textbox(placeholder="Ask akṣara...",
+                    min_width=300)
+with gr.Blocks(theme=theme, title=title, css="footer {visibility: hidden}") as akshara:
+
+    gr.HTML("""<h1 style='font-family: sans-serif; text-align: center; font-size: 34px'>
+        <i style='color: #04A5D9' >akṣara</i> </h1>""")
+
+    gr.HTML("""<h3 style='font-family: sans-serif; text-align: left'>
+        Welcome! </h3>""")
+
+    # with gr.Column():
+
+    chatbot.like(vote, None, None)
+
+    gr.ChatInterface(fn=llm_response, 
+                     examples=examples, 
+                     cache_examples=False, 
+                     chatbot=chatbot,
+                     description=description, 
+                     retry_btn="Retry", 
+                     undo_btn="Undo", 
+                     clear_btn="Clear",
+                     submit_btn="Ask",
+                     textbox=textbox
+                    )
+
+    gr.HTML("""<h3 style='font-family: sans-serif; text-align: left'>
+        Disclaimer: Beta Test version #1.0 - akṣara is still in the beta testing stage and please verify information with agronomy experts or local extensions officers
+ """)
+
+
+
+def display_ui():
+    akshara.launch()
+
+
+if __name__ == "__main__":
+    display_ui()
+    pass
+
+