push to the space

app.py

@@ -1,44 +1,83 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
 import os
+import requests
+from huggingface_hub import InferenceClient
 
+# -------------------------------
+# 🔐 Hugging Face API setup
+# -------------------------------
 hf_token = os.environ.get("HF_TOKEN")
-client = InferenceClient("Qwen/Qwen1.5-32B-Chat", token=hf_token)
-
-def build_prompt(system_message, history, user_message):
-    prompt = f"<|im_start|>system\n{system_message}<|im_end|>\n"
-    for user, assistant in history:
-        if user:
-            prompt += f"<|im_start|>user\n{user}<|im_end|>\n"
-        if assistant:
-            prompt += f"<|im_start|>assistant\n{assistant}<|im_end|>\n"
-    prompt += f"<|im_start|>user\n{user_message}<|im_end|>\n<|im_start|>assistant\n"
-    return prompt
+client = InferenceClient(model="deepseek-ai/deepseek-v3", token=hf_token)
+
+# -------------------------------
+# 📄 Google Doc Fetching
+# -------------------------------
+def fetch_google_doc_text(doc_id: str) -> str:
+    export_url = f"https://docs.google.com/document/d/{doc_id}/export?format=txt"
+    response = requests.get(export_url)
+    if response.status_code == 200:
+        return response.text.strip()
+    else:
+        return f"⚠️ Unable to fetch document. Status code: {response.status_code}"
+
+# Replace with your actual Google Doc ID
+GOOGLE_DOC_ID = "1s9_2SsGxj5taxNMw_dIq0awSgzQEu-EIW1P0BmZ8zo4"
+doc_context = fetch_google_doc_text(GOOGLE_DOC_ID)
+doc_context = doc_context[:12000]  # Optional: truncate to fit into model context
+#print(doc_context)
 
+# -------------------------------
+# 💬 Chatbot: Use context only
+# -------------------------------
 def respond(message, history, system_message, max_tokens, temperature, top_p):
-    prompt = build_prompt(system_message, history, message)
-    response = ""
-
-    for token in client.text_generation(
-        prompt=prompt,
-        max_new_tokens=max_tokens,
-        temperature=temperature,
-        top_p=top_p,
-        stream=True,
-    ):
-        if token.token:  # some tokens may be empty (e.g., control tokens)
-            response += token.token
-            yield response
+    try:
+        system_prompt = (
+            "You are a helpful assistant. Only answer questions using the context provided. "
+            "If the answer is not in the context, respond with: 'I can't answer this question.'"
+        )
+
+        full_context = f"{system_prompt}\n\nContext:\n{doc_context}"
+        #print(doc_context)
+
+        messages = [
+            {"role": "system", "content": full_context},
+            {"role": "user", "content": message}
+        ]
+
+        response = ""
+        for chunk in client.chat_completion(
+            messages=messages,
+            max_tokens=max_tokens,
+            temperature=temperature,
+            top_p=top_p,
+            stream=True
+        ):
+            token = chunk.choices[0].delta.content
+            if token:
+                response += token
+                yield response
+
+    except Exception as e:
+        yield f"❌ Error: {e}"
 
+# -------------------------------
+# 🎛️ Gradio UI Setup
+# -------------------------------
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a helpful assistant for construction CFOs.", 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.Textbox(value="(ignored in this version)", label="System message"),
+        gr.Slider(minimum=64, maximum=4096, value=1024, step=64, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=1.5, value=0.3, step=0.1, label="Temperature"),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
     ],
+    title="💬 Beiing Human FAQ Chatbot",
+    description="Ask questions based only on the content of the shared Google Doc FAQ. "
+                "If the answer isn't in the document, the bot will say so.",
 )
 
+# -------------------------------
+# 🚀 Launch App
+# -------------------------------
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(debug=True, share=True)

requirements.txt

@@ -1 +1,7 @@
-huggingface_hub==0.25.2
+gradio
+openpyxl
+PyPDF2
+pandas
+pillow  # For PIL (Python Imaging Library)
+pytesseract
+huggingface_hub