@nekxis/interpret prompt mode (#15)

Co-authored-by: Ignacy Łątka <74246391+LatekVo@users.noreply.github.com>

core/chainables/web.py

@@ -1,5 +1,8 @@
+import datetime
+
 from core.tools.scraper import web_query_google_lookup
 from core.classes.query import WebQuery
+from langchain_core.prompts import ChatPromptTemplate
 
 
 def web_news_lookup(prompt_text: str):
@@ -15,3 +18,67 @@ def web_wiki_lookup(prompt_text: str):
 def web_docs_lookup(prompt_text: str):
     query = WebQuery('docs', prompt_core=prompt_text)
     return web_query_google_lookup(query)
+
+
+def web_docs_lookup_prompt():
+    return ChatPromptTemplate.from_messages([
+        (
+            "system",
+            "You are a search results interpreter."
+            "Your job is to write an detailed instruction based on the provided context. "
+            "Your job is to convert all the search results you were given into a long, comprehensive and clean output. "
+            "Use provided search results data to explain object of user request to the best of your ability. "
+            "You don't have a knowledge cutoff. "
+            "It is currently " + datetime.date.today().strftime("%B %Y"),
+        ),
+        (
+            "user",
+            "Search results data: "
+            "```"
+            "{search_data}"
+            "```"
+            'User request: "Write an article on: {user_request}"',
+        ),
+    ])
+
+
+def web_wiki_lookup_prompt():
+    return ChatPromptTemplate.from_messages([
+        (
+            "system",
+            "You are a search results interpreter. Your job is to write an article based on the provided context. "
+            "Your job is to convert all the search results you were given into a long, comprehensive and clean output. "
+            "Use provided search results data to answer the user request to the best of your ability. "
+            "You don't have a knowledge cutoff. "
+            "It is currently " + datetime.date.today().strftime("%B %Y"),
+        ),
+        (
+            "user",
+            "Search results data: "
+            "```"
+            "{search_data}"
+            "```"
+            'User request: "Write an article on: {user_request}"',
+        ),
+    ])
+
+
+def web_news_lookup_prompt():
+    return ChatPromptTemplate.from_messages([
+        (
+            "system",
+            "You are a search results interpreter. Your job is to write an article based on the provided context. "
+            "Your job is to convert all the search results you were given into a long, comprehensive and clean output. "
+            "Use provided search results data to answer the user request to the best of your ability. "
+            "You don't have a knowledge cutoff. "
+            "It is currently " + datetime.date.today().strftime("%B %Y"),
+        ),
+        (
+            "user",
+            "Search results data: "
+            "```"
+            "{search_data}"
+            "```"
+            'User request: "Write an article on: {user_request}"',
+        ),
+    ])

core/classes/query.py

@@ -15,6 +15,7 @@ class WebQuery:
     prompt_core: str = ''
 
     web_query: str = ''
+
     web_extra_params: Union[dict, None] = None
     web_tbs = 0
 

core/lookup.py

@@ -1,15 +1,19 @@
-import datetime
-
 from langchain_core.output_parsers import StrOutputParser
-from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.runnables import RunnableLambda
 from core.tools.utils import purify_name
 from core.models.configurations import use_configuration
+from langchain_core.prompts import ChatPromptTemplate, BaseChatPromptTemplate
 
 # TODO: replace with puppeteer, this one gets blocked occasionally
 from googlesearch import search
 
-from core.chainables.web import web_docs_lookup, web_wiki_lookup, web_news_lookup
+from core.chainables.web import (
+    web_docs_lookup,
+    web_wiki_lookup,
+    web_news_lookup,
+    web_docs_lookup_prompt,
+    web_news_lookup_prompt,
+    web_wiki_lookup_prompt)
 from core.tools.dbops import get_db_by_name
 from core.tools.model_loader import load_model
 
@@ -29,26 +33,6 @@ def web_chain_function(prompt_dict: dict):
     # TODO: news searches should strictly search for news fresher than 1 month / 1 week
     # TODO: news crawling should be done through only sites like medium, which are much more dense than google
     # TODO: create a different function + prompt for documentation / facts searching, and make this one news focused
-    web_interpret_prompt = ChatPromptTemplate.from_messages(
-        [
-            (
-                "system",
-                "You are a search results interpreter. Your job is to write an article based on the provided context. "
-                "Your job is to convert all the search results you were given into a long, comprehensive and clean output. "
-                "Use provided search results data to answer the user request to the best of your ability. "
-                "You don't have a knowledge cutoff. "
-                "It is currently " + datetime.date.today().strftime("%B %Y"),
-            ),
-            (
-                "user",
-                "Search results data: "
-                "```"
-                "{search_data}"
-                "```"
-                'User request: "Write an article on: {user_request}"',
-            ),
-        ]
-    )
 
     def get_user_prompt(_: dict):
         return prompt_dict["input"]
@@ -63,6 +47,16 @@ def use_selected_mode(user_prompt: str):
         else:
             return web_docs_lookup(user_prompt)
 
+    def interpret_prompt_mode():
+        if prompt_dict["mode"] == "News":
+            return web_news_lookup_prompt()
+        elif prompt_dict["mode"] == "Docs":
+            return web_docs_lookup_prompt()
+        elif prompt_dict["mode"] == "Wiki":
+            return web_wiki_lookup_prompt()
+        else:
+            return web_docs_lookup_prompt()
+    web_interpret_prompt_mode = interpret_prompt_mode()
     # NOTE: a detour has been performed here, more details:
     #       web_chain_function will soon become just a tool playing a part of a larger mechanism.
     #       prompt creation will be taken over by prompt sentiment extractor which will extract all researchable
@@ -76,7 +70,7 @@ def use_selected_mode(user_prompt: str):
             # this has to be a RunnableLambda, it cannot be a string
             "user_request": RunnableLambda(get_user_prompt),
         }
-        | web_interpret_prompt
+        | web_interpret_prompt_mode
         | llm
         | output_parser
     )

core/tools/model_loader.py

@@ -1,10 +1,10 @@
-import torch
 from langchain_community.embeddings import OllamaEmbeddings
 from langchain_community.llms.ollama import Ollama
 from huggingface_hub import hf_hub_download
 from llama_cpp import Llama
 from terminal_gui import USE_HUGGING_FACE
 from core.models.configurations import use_configuration
+
 llm_config, embed_config = use_configuration()