use HF token

app.py

@@ -1,8 +1,44 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+import os
+HF_Hub_API_token = os.environ.get('HF_Hub_API_token', None)
+
+llm = HuggingFaceEndpoint(
+    repo_id="mistralai/Mistral-7B-Instruct-v0.2",
+    task="text-generation",
+    max_new_tokens=128,
+    do_sample=False,
+    repetition_penalty=1.03,
+    huggingfacehub_api_token=HF_Hub_API_token
+)
+
+chat_model = ChatHuggingFace(llm=llm)
+
+MAX_LEN = 100
+def gen_prompt1(title):
+    prompt1 = title
+    formatted_str = ''
+    if len(title) > 0:
+        messages = [HumanMessage(content=prompt1),]
+        res = chat_model.invoke(messages)
+        # censure
+        for s in res.content.split('\n'):
+            if len(s) > MAX_LEN:
+                s = s[:MAX_LEN] + " (...)"
+            formatted_str += s + '\n'
 
+        return formatted_str #res.content
+
+example_title = "Mary had a little lamb"
+
+demo = gr.Interface(
+    fn=gen_prompt1,
+    inputs=gr.Textbox(label = "Introduction", show_label=True),
+    outputs=["text"],
+    examples=[example_title]
+)
+
+demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+langchain-core
+langchain-huggingface