tutorial54

tutorial2/single_url.py

@@ -1,7 +1,7 @@
 from langchain.document_loaders import youtube
 import io
 
-loader=youtube.YoutubeLoader.from_youtube_url("https://youtu.be/Jupb5v9Z-vQ")
+loader=youtube.YoutubeLoader.from_youtube_url("https://youtu.be/zeVEPhDvHUQ")
 docs=loader.load()
 print(docs)
 with io.open("transcript.txt","w",encoding="utf-8")as f1:

tutorial53/main.py

@@ -0,0 +1,27 @@
+import  streamlit as st
+import pandas as pd
+from langchain.agents.agent_types import AgentType
+from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent
+from langchain_openai import ChatOpenAI
+
+
+
+llm=ChatOpenAI(model="gpt-4",temperature=0)
+st.title("CSV CHAT APP")
+st.write("upload your csv & and ask anything")
+file=st.file_uploader("select your file",type=["csv"])
+if file is not None:
+    df=pd.read_csv(file)
+    #st.write(df)
+    input=st.text_area("ask your question here")
+    if input is not None:
+        button=st.button("Submit")
+        agent=create_pandas_dataframe_agent(
+        llm,df,verbose=False,agent_type=AgentType.OPENAI_FUNCTIONS
+        )
+        if button:
+            result=agent.invoke(input)
+            st.write(result["output"])
+
+
+

tutorial54/llmload.py

@@ -0,0 +1,15 @@
+from langchain_community.llms import CTransformers
+
+def loadllm():
+    config={
+        "max_new_tokens":1048,
+        "temperature":0.1,
+        "context_length":4096,
+        "gpu_layers":32,
+        "threads":-1
+    }
+    llm=CTransformers(model="/Users/roni/Documents/GitHub/LLMtutorial/tutorial54/mistral-7b-instruct-v0.1.Q5_K_S.gguf",
+                      model_type="mistral",
+                      config=config
+                      )
+    return llm

tutorial54/main.py

@@ -0,0 +1,21 @@
+from llmload import loadllm
+import requests
+from langchain.agents import AgentType,initialize_agent
+from langchain.tools import Tool
+
+def getPrice(input):
+    url="https://api.coincap.io/v2/assets/"+input.lower()
+    response=requests.get(url).json()
+    price=response["data"]["priceUsd"]
+    return price
+
+apicall=Tool(
+    name="getCryptoPrice",
+    func=getPrice,
+    description="use to get the price for any given crypto from user input"
+
+)
+tools=[apicall]
+llm=loadllm()
+agent=initialize_agent(tools,llm,agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,verbose=True)
+print(agent.run("what is the price of shiba-inu"))