meeh

App/Chat/utils/Summarize.py

@@ -1,17 +1,23 @@
 import aiohttp
-import asyncio,pprint
+import asyncio, pprint
 import google.generativeai as palm
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain import PromptTemplate
 import os
-PALM_API = ''
-API_KEY=os.environ.get("PALM_API",PALM_API)
-palm.configure(api_key=API_KEY)
+from poe_api_wrapper import PoeApi
+import pprint
+client = PoeApi("sXvCnfYy8CHnXNTRlxhmVg==")
+bot = "Assistant"
 
 
+PALM_API = ""
+API_KEY = os.environ.get("PALM_API", PALM_API)
+palm.configure(api_key=API_KEY)
 
 
-text_splitter = RecursiveCharacterTextSplitter(separators=["\n\n", "\n","."], chunk_size=40_000, chunk_overlap=500)
+text_splitter = RecursiveCharacterTextSplitter(
+    separators=["\n\n", "\n", "."], chunk_size=40_000, chunk_overlap=500
+)
 
 
 map_prompt = """
@@ -29,69 +35,72 @@ Return your response in a detailed verbose paragraph which covers the text. Make
 
 SUMMARY:
 """
-def count_tokens(text):
-    return palm.count_message_tokens(prompt=text)['token_count']
-
-
-async def PalmTextModel(text,candidates=1):
-    url = f"https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001:generateText?key={API_KEY}"
-
-    headers = {
-        "Content-Type": "application/json",
-    }
-
-    data = {
-        "prompt": {
-            "text": text
-        },
-        "temperature": 0.95,
-        "top_k": 100,
-        "top_p": 0.95,
-        "candidate_count": candidates,
-        "max_output_tokens": 1024,
-        "stop_sequences": ["</output>"],
-        "safety_settings": [
-            {"category": "HARM_CATEGORY_DEROGATORY", "threshold": 4},
-            {"category": "HARM_CATEGORY_TOXICITY", "threshold": 4},
-            {"category": "HARM_CATEGORY_VIOLENCE", "threshold": 4},
-            {"category": "HARM_CATEGORY_SEXUAL", "threshold": 4},
-            {"category": "HARM_CATEGORY_MEDICAL", "threshold": 4},
-            {"category": "HARM_CATEGORY_DANGEROUS", "threshold": 4},
-        ],
-    }
-
-
-    async with aiohttp.ClientSession() as session:
-        async with session.post(url, json=data, headers=headers) as response:
-            if response.status == 200:
-                result = await response.json()
-                # print(result)
-                if candidates>1:
-                    temp = [candidate["output"] for candidate in result["candidates"]]
-                    return temp                
-                temp = result["candidates"][0]["output"]
-                return temp
-            else:
-                print(f"Error: {response.status}\n{await response.text()}")
 
 
-async def Summarizer(essay):
+def count_tokens(text):
+    return palm.count_message_tokens(prompt=text)["token_count"]
+
+
+# async def PalmTextModel(text, candidates=1):
+#     url = f"https://generativelanguage.googleapis.com/v1beta2/models/text-bison-001:generateText?key={API_KEY}"
+
+#     headers = {
+#         "Content-Type": "application/json",
+#     }
+
+#     data = {
+#         "prompt": {"text": text},
+#         "temperature": 0.95,
+#         "top_k": 100,
+#         "top_p": 0.95,
+#         "candidate_count": candidates,
+#         "max_output_tokens": 1024,
+#         "stop_sequences": ["</output>"],
+#         "safety_settings": [
+#             {"category": "HARM_CATEGORY_DEROGATORY", "threshold": 4},
+#             {"category": "HARM_CATEGORY_TOXICITY", "threshold": 4},
+#             {"category": "HARM_CATEGORY_VIOLENCE", "threshold": 4},
+#             {"category": "HARM_CATEGORY_SEXUAL", "threshold": 4},
+#             {"category": "HARM_CATEGORY_MEDICAL", "threshold": 4},
+#             {"category": "HARM_CATEGORY_DANGEROUS", "threshold": 4},
+#         ],
+#     }
+
+#     async with aiohttp.ClientSession() as session:
+#         async with session.post(url, json=data, headers=headers) as response:
+#             if response.status == 200:
+#                 result = await response.json()
+#                 # print(result)
+#                 if candidates > 1:
+#                     temp = [candidate["output"] for candidate in result["candidates"]]
+#                     return temp
+#                 temp = result["candidates"][0]["output"]
+#                 return temp
+#             else:
+#                 print(f"Error: {response.status}\n{await response.text()}")
+
+
+async def PalmTextModel(message):
+    for chunk in client.send_message(bot, message,chatCode='TWVzc2FnZTozMDY2MzYwNjQ5OQ=='):
+        pass
+    return chunk["text"]
 
+async def Summarizer(essay):
     docs = text_splitter.create_documents([essay])
 
-    #for 1 large document
+    # for 1 large document
     if len(docs) == 1:
-        tasks = [PalmTextModel(combine_prompt.format(text=doc.page_content)) for doc in docs]
+        tasks = [
+            PalmTextModel(combine_prompt.format(text=doc.page_content)) for doc in docs
+        ]
         # Gather and execute the tasks concurrently
         responses = await asyncio.gather(*tasks)
-        ans=" ".join(responses)
-        return ans 
+        ans = " ".join(responses)
+        return ans
 
     tasks = [PalmTextModel(map_prompt.format(text=doc.page_content)) for doc in docs]
     # Gather and execute the tasks concurrently
     responses = await asyncio.gather(*tasks)
-    main=" ".join(responses)
-    ans=await PalmTextModel(combine_prompt.format(text=main),candidates=1)
+    main = " ".join(responses)
+    ans = await PalmTextModel(combine_prompt.format(text=main), candidates=1)
     return ans
-
-