preliminary usable features

backend-python/utils/ngrok.py

@@ -3,6 +3,7 @@ import os
 
 def ngrok_connect():
     from pyngrok import ngrok, conf
+
     conf.set_default(conf.PyngrokConfig(ngrok_path="./ngrok"))
     ngrok.set_auth_token(os.environ["ngrok_token"])
     http_tunnel = ngrok.connect(8000)

backend-python/utils/rwkv.py

@@ -1,5 +1,37 @@
 from typing import Dict
 from langchain.llms import RWKV
+from pydantic import BaseModel
+
+
+class ModelConfigBody(BaseModel):
+    max_tokens: int = None
+    temperature: float = None
+    top_p: float = None
+    presence_penalty: float = None
+    frequency_penalty: float = None
+
+
+def set_rwkv_config(model: RWKV, body: ModelConfigBody):
+    if body.max_tokens:
+        model.max_tokens_per_generation = body.max_tokens
+    if body.temperature:
+        model.temperature = body.temperature
+    if body.top_p:
+        model.top_p = body.top_p
+    if body.presence_penalty:
+        model.penalty_alpha_presence = body.presence_penalty
+    if body.frequency_penalty:
+        model.penalty_alpha_frequency = body.frequency_penalty
+
+
+def get_rwkv_config(model: RWKV) -> ModelConfigBody:
+    return ModelConfigBody(
+        max_tokens=model.max_tokens_per_generation,
+        temperature=model.temperature,
+        top_p=model.top_p,
+        presence_penalty=model.penalty_alpha_presence,
+        frequency_penalty=model.penalty_alpha_frequency,
+    )
 
 
 def rwkv_generate(model: RWKV, prompt: str, stop: str = None):

backend-python/utils/torch.py

@@ -11,8 +11,8 @@ def set_torch():
             print("torch already set")
         else:
             print("run:")
-            os.environ['PATH'] = paths + os.pathsep + torch_path + os.pathsep
-            print(f'set Path={paths + os.pathsep + torch_path + os.pathsep}')
+            os.environ["PATH"] = paths + os.pathsep + torch_path + os.pathsep
+            print(f"set Path={paths + os.pathsep + torch_path + os.pathsep}")
     else:
         print("torch not found")