feat: add coze.py

chat.py

@@ -0,0 +1,26 @@
+from openai import OpenAI
+import gradio as gr
+
+api_key = "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"  # Replace with your key
+client = OpenAI(api_key=api_key)
+
+def predict(message, history):
+    history_openai_format = []
+    for human, assistant in history:
+        history_openai_format.append({"role": "user", "content": human })
+        history_openai_format.append({"role": "assistant", "content":assistant})
+    history_openai_format.append({"role": "user", "content": message})
+  
+    response = client.chat.completions.create(model='gpt-3.5-turbo',
+    messages= history_openai_format,
+    temperature=1.0,
+    stream=True)
+
+    partial_message = ""
+    for chunk in response:
+        if chunk.choices[0].delta.content is not None:
+              partial_message = partial_message + chunk.choices[0].delta.content
+              yield partial_message
+
+gr.ChatInterface(predict).launch()
+

app.py → coze.py

@@ -3,6 +3,7 @@ import json
 import aiohttp
 import asyncio
 
+
 API_URL = "https://api.coze.com/v3/chat"
 
 # https://www.coze.com/space/7309440314236747794/bot/7392076134450151432
@@ -18,7 +19,7 @@ TOOLS_CONFIG = {
 }
 
 
-async def run_workflow(parameters, api_name, onmessage):
+async def run_workflow(parameters, api_name):
     config = TOOLS_CONFIG[api_name]
     payload = {
         "bot_id": BOT_ID,
@@ -49,45 +50,43 @@ async def run_workflow(parameters, api_name, onmessage):
         ) as response:
             async for line in response.content:
                 if line:
-                    # print(line)
-                    if callable(onmessage):
-                        try:
-                            if asyncio.iscoroutinefunction(onmessage):
-                                await onmessage(line)
-                            else:
-                                onmessage(line)
-                        except Exception as err:
-                            print(f"Error in onmessage callback: {err}")
-
-
-# 使用示例
-# event:conversation.message.delta
+                    yield line
+
+
 is_message_delta = False
 
 
-async def sample_onmessage(line: str):
+async def process_message(line: str):
     global is_message_delta
     decoded_line = line.decode("utf-8")
 
-    # print(decoded_line, is_message_delta)
-
     if decoded_line.startswith("event:"):
         is_message_delta = decoded_line == "event:conversation.message.delta\n"
-        return
+        return None
 
     if decoded_line.startswith("data:") and is_message_delta:
-        # remove the `data:` prefix and json decode the rest
         message = json.loads(decoded_line[5:])
-        # get role, type, content from the message
-        # if role is assistant and type is anwser, then print the content
         if message.get("role") == "assistant" and message.get("type") == "answer":
-            sys.stdout.write(f"{message.get('content')}")
+            return message.get("content")
+
+    return None
+
+
+async def generate_story(query, history=None):
+    parameters = {"query": query}
+    full_response = ""
+    async for line in run_workflow(parameters, "self:create_full_story"):
+        content = await process_message(line)
+        if content:
+            full_response += content
+            yield full_response  # 使用生成器逐步输出内容
 
 
-# 使用示例
 async def main():
-    parameters = {"query": "冰雪奇缘"}
-    await run_workflow(parameters, "self:create_full_story", onmessage=sample_onmessage)
+    # 调用 generate_story 并传入查询参数
+    query = "冰雪奇缘"
+    async for partial_story in generate_story(query):
+        sys.stdout.write(partial_story)  # 打印生成的故事部分内容
     sys.stdout.write("\n")
 
 

main.py

@@ -0,0 +1,17 @@
+import gradio as gr
+
+from coze import run_workflow, process_message
+
+
+async def create_full_story(query, history=None):
+    parameters = {"query": query}
+    full_response = ""
+    async for line in run_workflow(parameters, "self:create_full_story"):
+        content = await process_message(line)
+        if content:
+            full_response += content
+            yield full_response  # 使用生成器逐步输出内容
+
+
+if __name__ == "__main__":
+    gr.ChatInterface(create_full_story).launch()