Configuration

from langchat import LangChat
from langchat.llm import OpenAI
from langchat.vector_db import Pinecone
from langchat.database import Supabase

# Setup providers
llm = OpenAI(api_key="sk-...", model="gpt-4o-mini", temperature=0.7)
vector_db = Pinecone(api_key="...", index_name="...")
db = Supabase(url="https://...", key="...")

# Create chatbot
ai = LangChat(llm=llm, vector_db=vector_db, db=db)

from langchat.llm import OpenAI

# Basic
llm = OpenAI(api_key="sk-...", model="gpt-4o-mini")

# With options
llm = OpenAI(
    api_key="sk-...",
    model="gpt-4o-mini",
    temperature=0.7,
    max_tokens=1000
)

from langchat.llm import Anthropic, Gemini, Ollama

# Anthropic
llm = Anthropic(api_key="...", model="claude-3-5-sonnet-20241022")

# Gemini
llm = Gemini(api_key="...", model="gemini-1.5-flash")

# Ollama (local)
llm = Ollama(model="llama2", base_url="http://localhost:11434")

from langchat.vector_db import Pinecone

vector_db = Pinecone(
    api_key="pcsk-...",
    index_name="your-index",
    embedding_model="text-embedding-3-large"  # Optional
)

from langchat.database import Supabase

db = Supabase(
    url="https://xxxxx.supabase.co",
    key="eyJhbGc..."
)

custom_prompt = """You are a helpful assistant.
Use this context: {context}
History: {chat_history}
Question: {question}
Answer:"""

ai = LangChat(
    llm=llm,
    vector_db=vector_db,
    db=db,
    prompt_template=custom_prompt
)

from langchat.reranker import Flashrank

reranker = Flashrank(
    model_name="ms-marco-MiniLM-L-12-v2",
    top_n=3
)

ai = LangChat(
    llm=llm,
    vector_db=vector_db,
    db=db,
    reranker=reranker
)

ai = LangChat(
    llm=llm,
    vector_db=vector_db,
    db=db,
    max_chat_history=50  # Keep last 50 messages
)

import os

llm = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
vector_db = Pinecone(
    api_key=os.getenv("PINECONE_API_KEY"),
    index_name=os.getenv("PINECONE_INDEX_NAME")
)

# OpenAI supports multiple keys for rotation
llm = OpenAI(api_keys=["key1", "key2", "key3"])

try:
    ai = LangChat(llm=llm, vector_db=vector_db, db=db)
except ValueError as e:
    print(f"Configuration error: {e}")