pip install -U langchain-imap

pip install "langchain-imap[docling]"

from pathlib import Path
import subprocess
import os

preload_dir = Path(os.getcwd()).parent / "tests" / "fixtures" / "preload"
log_path = Path(os.getcwd()).parent / "tests" / "container.log"

# GreenMail configuration
env_vars = {
    "GREENMAIL_OPTS": " ".join([
        "-Dgreenmail.setup.test.all",
        "-Dgreenmail.users=test:test123@localhost",
        "-Dgreenmail.users.login=local_part",
        "-Dgreenmail.preload.dir=/preload",
        "-Dgreenmail.verbose",
        "-Dgreenmail.hostname=0.0.0.0"
    ])
}

# Start GreenMail container
container_name = "langchain-imap-test"
cmd = [
    "podman", "run", "--rm", "-d",
    "--name", container_name,
    "-e", f"GREENMAIL_OPTS={env_vars['GREENMAIL_OPTS']}",
    "-v", f"{preload_dir}:/preload:ro,Z",
    "-p", "3143:3143",
    "-p", "3993:3993",
    "-p", "8080:8080",
    "--log-driver", "k8s-file",
    "--log-opt", f"path={log_path.absolute()}",
    "docker.io/greenmail/standalone:2.1.5",
]

result = subprocess.run(cmd, capture_output=True, text=True, check=True)

from langchain_imap import ImapConfig, ImapRetriever

config = ImapConfig(
    host="imap.gmail.com",
    port=993,
    user="your-email@gmail.com",
    password="your-app-password",  # Use app password for Gmail
    ssl_mode="ssl",
)

retriever = ImapRetriever(config=config, k=10)

from langchain_imap import ImapRetriever, ImapConfig

config = ImapConfig(
    host="localhost",
    port=3143,
    user="test",
    password="test123",
    ssl_mode="plain",
    verify_cert=False,
)

retriever = ImapRetriever(
    config=config,
    k=50
)

# Search all emails
query = 'ALL'
docs = retriever.invoke(query)

# Search by subject
query = 'SUBJECT "URGENT"'
docs = retriever.invoke(query)

# Search by sender
docs = retriever.invoke('FROM "john@example.com"')

# Search by date
docs = retriever.invoke('SENTSINCE "01-Oct-2024"')

# Combine criteria
docs = retriever.invoke('FROM "boss@company.com" SUBJECT "urgent"')

for doc in docs:
    print(doc.page_content)  # Formatted email content

retriever = ImapRetriever(
    config=config,
    k=10,
    attachment_mode="text_extract"
)

import os
from langchain_openai import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough, RunnableLambda
from langchain_imap import ImapRetriever, ImapConfig

# Setup LLM (example using OpenRouter)
llm = ChatOpenAI(
    model="google/gemini-2.5-flash",
    temperature=0,
    openai_api_key=os.getenv("OPENAI_API_KEY"),
    openai_api_base="https://openrouter.ai/api/v1"
)

# IMAP query generation prompt
query_prompt = ChatPromptTemplate.from_template(
    """Convert the following user question into an IMAP search query.

IMAP query syntax examples:
- 'FROM "john@example.com"' - emails from specific sender
- 'SUBJECT "project update"' - emails with specific subject
- 'SENTSINCE "01-Oct-2024"' - emails since specific date
- 'BODY "meeting"' - emails containing specific word in body
- 'FROM "boss@company.com" SUBJECT "urgent"' - combine criteria

IMPORTANT: Include only VALID imap command in output.
IMPORTANT: Do not include any other text in output.

User Question: {question}

IMAP Query:"""
)

# Answer generation prompt
answer_prompt = ChatPromptTemplate.from_template(
    """Answer the question based only on the context provided from emails.

Context:
{context}

Question: {question}

Answer:"""
)

# IMAP retriever configuration
config = ImapConfig(
    host="localhost",
    port=3993,
    user="test",
    password="test123",
    ssl_mode="ssl",
    auth_method="login",
    verify_cert=False,
)

retriever = ImapRetriever(
    config=config,
    k=5,
    attachment_mode="names_only"
)

def format_docs(docs):
    return "\n\n".join(doc.page_content for doc in docs)

# Create the chain
query_chain = query_prompt | llm | StrOutputParser()

def generate_imap_query(question):
    return query_chain.invoke({"question": question})

def search_emails(query):
    return retriever.invoke(query)

full_chain = (
    {
        "question": lambda x: x,
        "imap_query": lambda x: generate_imap_query(x)
    }
    | RunnablePassthrough.assign(
        context=lambda x: format_docs(search_emails(x["imap_query"]))
    )
    | answer_prompt
    | llm
    | StrOutputParser()
)

# Use the chain
TODO = full_chain.invoke("Please make a TODO based on the e-mails having URGENT in subject")
print(TODO)

cmd = ["podman", "rm", "--force", "langchain-imap-test"]
result = subprocess.run(cmd, capture_output=True, text=True, check=True)