Upload 2 files

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+from langchain import HuggingFaceHub, PromptTemplate, LLMChain
+from langchain.memory import ConversationBufferMemory
+
+repo_id = "tiiuae/falcon-7b-instruct"
+
+template = """You are a chatbot having a conversation with a human.
+
+{chat_history}
+Human: {human_input}
+Chatbot:"""
+prompt = PromptTemplate(template=template, input_variables=["chat_history","human_input"])
+
+def generate_response(question, huggingfacehub_api_token, temperature=0.6, max_new_tokens=500):
+    memory = ConversationBufferMemory(memory_key="chat_history")
+    llm = HuggingFaceHub(huggingfacehub_api_token=huggingfacehub_api_token, 
+                         repo_id=repo_id, 
+                         model_kwargs={"temperature": temperature, 
+                                       "max_new_tokens": max_new_tokens})
+    llm_chain = LLMChain(prompt=prompt, llm=llm, memory=memory)
+    return llm_chain.predict(chat_history="", human_input=question)
+
+inputs = [
+    gr.inputs.Textbox(label="Question"),
+    gr.inputs.Textbox(label="HuggingFace API Token", type="password", default=None),
+    gr.inputs.Slider(minimum=0.1, maximum=2.0, default=0.6, label="Temperature"),
+    gr.inputs.Slider(minimum=100, maximum=1000, default=500, label="Max New Tokens")
+]
+outputs = gr.outputs.Textbox(label="Response")
+
+title = "Chatbot Interface"
+description = "Provide a question and get helpful answers from the AI assistant."
+examples = [["write a poem on Iron Man"], ["What are the benefits of using Python?"]]
+
+iface = gr.Interface(fn=generate_response, 
+                     inputs=inputs,
+                     outputs=outputs, 
+                     title=title, 
+                     description=description,
+                     allow_flagging="never", 
+                     examples=examples)
+
+iface.launch(share=True, debug=True, show_api=True)

requirements.txt

@@ -0,0 +1,3 @@
+langchain 
+huggingface_hub 
+gradio