Update app.py

app.py

@@ -1,64 +1,51 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
+import chromadb
+from openai import OpenAI
+from dotenv import load_dotenv
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+load_dotenv()
 
+# setting the environment
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+DATA_PATH = r"data"
+CHROMA_PATH = r"chroma_db"
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+chroma_client = chromadb.PersistentClient(path=CHROMA_PATH)
 
-    messages.append({"role": "user", "content": message})
+collection = chroma_client.get_or_create_collection(name="growing_vegetables")
 
-    response = ""
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+user_query = input("What do you want to know about growing vegetables?\n\n")
 
-        response += token
-        yield response
+results = collection.query(
+    query_texts=[user_query],
+    n_results=1
+)
 
+#print(results['documents'])
+#print(results['metadatas'])
 
+client = OpenAI()
+
+system_prompt = """
+You are a helpful assistant. You answer questions about growing vegetables in Florida. 
+But you only answer based on knowledge I'm providing you. You don't use your internal 
+knowledge and you don't make thins up.
+If you don't know the answer, just say: I don't know
+--------------------
+The data:
+"""+str(results['documents'])+"""
 """
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
+
+#print(system_prompt)
+
+response = client.chat.completions.create(
+    model="gpt-4o",
+    messages = [
+        {"role":"system","content":system_prompt},
+        {"role":"user","content":user_query}    
+    ]
 )
 
+print("\n\n---------------------\n\n")
 
-if __name__ == "__main__":
-    demo.launch()
+print(response.choices[0].message.content)