Create app.py

app.py

@@ -0,0 +1,63 @@
+import json
+import subprocess
+import requests
+from llama_cpp import Llama
+import gradio as gr
+
+#url="https://huggingface.co/TheBloke/WizardLM-13B-V1.2-GGUF/resolve/main/wizardlm-13b-v1.2.Q4_0.gguf"
+#url="https://huggingface.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF/resolve/main/mixtral-8x7b-instruct-v0.1.Q4_0.gguf?download=true"
+url="https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GGUF/resolve/main/mistral-7b-instruct-v0.2.Q4_0.gguf?download=true"
+response = requests.get(url)
+with open("./model.gguf", mode="wb") as file:
+  file.write(response.content)
+print("Model downloaded")
+
+command = ["python3", "-m", "llama_cpp.server", "--model", "./model.gguf", "--host", "0.0.0.0", "--port", "2600", "--n_threads", "2"]
+subprocess.Popen(command)
+print("Model ready!")
+
+#llm = Llama(model_path="./model.gguf")
+#def response(input_text, history):
+#    output = llm(f"Q: {input_text} A:", max_tokens=256, stop=["Q:", "\n"], echo=True)
+#    return output['choices'][0]['text']
+
+def response(message, history):
+  #url="https://afischer1985-wizardlm-13b-v1-2-q4-0-gguf.hf.space/v1/completions"
+  url="http://0.0.0.0:2600/v1/completions"  
+  #body={"prompt":"Im Folgenden findest du eine Instruktion, die eine Aufgabe bescheibt. Schreibe eine Antwort, um die Aufgabe zu lösen.\n\n### Instruktion:\n"+message+"\n\n### Antwort:","max_tokens":500, "echo":"False","stream":"True"}
+  #body={"prompt":" chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\n\nUSER:\n"+message+"\n\nASSISTANT:","max_tokens":500, "echo":"False","stream":"True"}    
+  #body={"prompt":system+"### Instruktion:\n"+message+"\n\n### Antwort:","max_tokens":500, "echo":"False","stream":"True"} #e.g. SauerkrautLM
+  body={"prompt":"[INST]"+message+"[/INST]","max_tokens":500, "echo":"False","stream":"True"} #e.g. Mixtral-Instruct
+  response=""
+  buffer=""
+  print("URL: "+url)
+  print("User: "+message+"\nAI: ")
+  for text in requests.post(url, json=body, stream=True):  #-H 'accept: application/json' -H 'Content-Type: application/json'
+    if buffer is None: buffer=""
+    buffer=str("".join(buffer))
+    #print("*** Raw String: "+str(text)+"\n***\n")
+    text=text.decode('utf-8')
+    if((text.startswith(": ping -")==False) & (len(text.strip("\n\r"))>0)): buffer=buffer+str(text)
+    #print("\n*** Buffer: "+str(buffer)+"\n***\n") 
+    buffer=buffer.split('"finish_reason": null}]}')
+    if(len(buffer)==1):
+      buffer="".join(buffer)
+      pass
+    if(len(buffer)==2):
+      part=buffer[0]+'"finish_reason": null}]}'  
+      if(part.lstrip('\n\r').startswith("data: ")): part=part.lstrip('\n\r').replace("data: ", "")
+      try: 
+        part = str(json.loads(part)["choices"][0]["text"])
+        print(part, end="", flush=True)
+        response=response+part
+        buffer="" # reset buffer
+      except Exception as e:
+        print("Exception:"+str(e))
+        pass
+    yield response 
+
+gr.ChatInterface(
+    fn=response,
+    title="Mistral-7B-Instruct-v0.2-GGUF Chatbot",
+    theme='syddharth/gray-minimal'
+).queue().launch(share=True)