Create app.py

app.py

@@ -0,0 +1,66 @@
+import os
+import gradio as gr
+import copy
+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]
+    
+    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()