tutorial79

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/ffbbQ6DAI6Q")
+loader=youtube.YoutubeLoader.from_youtube_url("https://youtu.be/GONbsWzP3SY")
 docs=loader.load()
 print(docs)
 with io.open("transcript.txt","w",encoding="utf-8")as f1:

tutorial77/main.py

@@ -1,14 +1,22 @@
 from langchain_openai import OpenAIEmbeddings
 from langchain_chroma import Chroma
 from langchain_community.document_loaders import TextLoader
-from langchain.text_splitter import CharacterTextSplitter
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.document_loaders import PyPDFLoader
+import os
+
+os.environ["OPENAI_API_KEY"] = "sk-proj-wbrNr25jaPp9JvUx73zqT3BlbkFJDsyo7Yc4VKmeagQV6gRR"
+loader = PyPDFLoader(r"C:\Users\welcome\OneDrive\Documents\GitHub\LLMtutorial\tutorial77\abc.pdf")
 
 # loader=TextLoader(r"C:\Users\welcome\OneDrive\Documents\GitHub\LLMtutorial\tutorial77\test.txt")
 # documents=loader.load()
-# text_splitter=CharacterTextSplitter(chunk_size=500,chunk_overlap=0)
+# text_splitter=RecursiveCharacterTextSplitter(chunk_size=500,chunk_overlap=0)
 # docs=text_splitter.split_documents(documents)
-# vs=Chroma.from_documents(documents=docs,embedding=OpenAIEmbeddings(),persist_directory="./db_index")
+# print(len(docs))
+
+# for i in range(100):
+#     vs=Chroma.from_documents(documents=docs,embedding=OpenAIEmbeddings(),persist_directory="./db_index_"+str(i))
 
 vs=Chroma(persist_directory="./db_index",embedding_function=OpenAIEmbeddings())
 info=vs.similarity_search("family of king john",k=3)
-print(info)
+# print(info)

tutorial79/main.py

@@ -0,0 +1,18 @@
+from langchain_openai import OpenAI
+from langchain.chains import APIChain
+
+
+api_docs="""
+base_url:https://api.coincap.io
+end point /v2/assets/{name} uses GET requrest to give information on any crypto token,
+here name is url parameter which is actually the name of the crytop token in lower case
+"""
+llm=OpenAI(temperature=0)
+chain=APIChain.from_llm_and_api_docs(
+    llm,
+    api_docs,
+    verbose=True,
+    limit_to_domains=["https://api.coincap.io"]
+)
+response=chain.invoke("what is the price of ethereum")
+print(response)