mirror of
https://github.com/khoj-ai/khoj.git
synced 2024-11-23 15:38:55 +01:00
Merge pull request #587 from khoj-ai/features/search-model-options-custom
Support multiple search models, with ability for custom user config
This commit is contained in:
commit
738f050086
18 changed files with 239 additions and 36 deletions
|
@ -66,7 +66,7 @@ dependencies = [
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"gpt4all >= 2.0.0; platform_system == 'Windows' or platform_system == 'Darwin'",
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"itsdangerous == 2.1.2",
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"httpx == 0.25.0",
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"pgvector == 0.2.3",
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"pgvector == 0.2.4",
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"psycopg2-binary == 2.9.9",
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"google-auth == 2.23.3",
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"python-multipart == 0.0.6",
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|
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@ -25,7 +25,7 @@ from khoj.database.models import KhojUser, Subscription
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from khoj.database.adapters import (
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ConversationAdapters,
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get_all_users,
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get_or_create_search_model,
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get_or_create_search_models,
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aget_user_subscription_state,
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SubscriptionState,
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)
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@ -146,8 +146,14 @@ def configure_server(
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# Initialize Search Models from Config and initialize content
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try:
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state.embeddings_model = EmbeddingsModel(get_or_create_search_model().bi_encoder)
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state.cross_encoder_model = CrossEncoderModel(get_or_create_search_model().cross_encoder)
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search_models = get_or_create_search_models()
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state.embeddings_model = dict()
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state.cross_encoder_model = dict()
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for model in search_models:
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state.embeddings_model.update({model.name: EmbeddingsModel(model.bi_encoder)})
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state.cross_encoder_model.update({model.name: CrossEncoderModel(model.cross_encoder)})
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state.SearchType = configure_search_types()
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state.search_models = configure_search(state.search_models, state.config.search_type)
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initialize_content(regenerate, search_type, init, user)
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@ -32,6 +32,7 @@ from khoj.database.models import (
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SpeechToTextModelOptions,
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Subscription,
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UserConversationConfig,
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UserSearchModelConfig,
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OpenAIProcessorConversationConfig,
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OfflineChatProcessorConversationConfig,
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ReflectiveQuestion,
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@ -250,12 +251,33 @@ async def set_user_github_config(user: KhojUser, pat_token: str, repos: list):
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return config
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def get_or_create_search_model():
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search_model = SearchModelConfig.objects.filter().first()
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if not search_model:
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search_model = SearchModelConfig.objects.create()
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def get_user_search_model_or_default(user=None):
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if user and UserSearchModelConfig.objects.filter(user=user).exists():
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return UserSearchModelConfig.objects.filter(user=user).first().setting
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return search_model
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if SearchModelConfig.objects.filter(name="default").exists():
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return SearchModelConfig.objects.filter(name="default").first()
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else:
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SearchModelConfig.objects.create()
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return SearchModelConfig.objects.first()
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def get_or_create_search_models():
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search_models = SearchModelConfig.objects.all()
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if search_models.count() == 0:
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SearchModelConfig.objects.create()
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search_models = SearchModelConfig.objects.all()
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return search_models
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async def aset_user_search_model(user: KhojUser, search_model_config_id: int):
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config = await SearchModelConfig.objects.filter(id=search_model_config_id).afirst()
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if not config:
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return None
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new_config, _ = await UserSearchModelConfig.objects.aupdate_or_create(user=user, defaults={"setting": config})
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return new_config
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class ConversationAdapters:
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@ -16,6 +16,7 @@ from khoj.database.models import (
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SpeechToTextModelOptions,
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Subscription,
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ReflectiveQuestion,
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UserSearchModelConfig,
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TextToImageModelConfig,
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Conversation,
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)
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@ -29,6 +30,7 @@ admin.site.register(OfflineChatProcessorConversationConfig)
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admin.site.register(SearchModelConfig)
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admin.site.register(Subscription)
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admin.site.register(ReflectiveQuestion)
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admin.site.register(UserSearchModelConfig)
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admin.site.register(TextToImageModelConfig)
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33
src/khoj/database/migrations/0023_usersearchmodelconfig.py
Normal file
33
src/khoj/database/migrations/0023_usersearchmodelconfig.py
Normal file
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@ -0,0 +1,33 @@
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# Generated by Django 4.2.7 on 2023-12-19 15:44
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from django.conf import settings
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from django.db import migrations, models
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import django.db.models.deletion
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class Migration(migrations.Migration):
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dependencies = [
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("database", "0022_texttoimagemodelconfig"),
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]
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operations = [
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migrations.CreateModel(
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name="UserSearchModelConfig",
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fields=[
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("id", models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name="ID")),
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("created_at", models.DateTimeField(auto_now_add=True)),
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("updated_at", models.DateTimeField(auto_now=True)),
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(
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"setting",
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models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to="database.searchmodelconfig"),
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),
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(
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"user",
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models.OneToOneField(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
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),
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],
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options={
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"abstract": False,
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},
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),
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]
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18
src/khoj/database/migrations/0024_alter_entry_embeddings.py
Normal file
18
src/khoj/database/migrations/0024_alter_entry_embeddings.py
Normal file
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@ -0,0 +1,18 @@
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# Generated by Django 4.2.7 on 2023-12-20 07:27
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from django.db import migrations
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import pgvector.django
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class Migration(migrations.Migration):
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dependencies = [
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("database", "0023_usersearchmodelconfig"),
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]
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operations = [
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migrations.AlterField(
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model_name="entry",
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name="embeddings",
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field=pgvector.django.VectorField(),
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),
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]
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@ -153,6 +153,11 @@ class UserConversationConfig(BaseModel):
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setting = models.ForeignKey(ChatModelOptions, on_delete=models.CASCADE, default=None, null=True, blank=True)
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class UserSearchModelConfig(BaseModel):
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user = models.OneToOneField(KhojUser, on_delete=models.CASCADE)
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setting = models.ForeignKey(SearchModelConfig, on_delete=models.CASCADE)
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class Conversation(BaseModel):
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user = models.ForeignKey(KhojUser, on_delete=models.CASCADE)
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conversation_log = models.JSONField(default=dict)
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@ -180,7 +185,7 @@ class Entry(BaseModel):
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GITHUB = "github"
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user = models.ForeignKey(KhojUser, on_delete=models.CASCADE, default=None, null=True, blank=True)
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embeddings = VectorField(dimensions=384)
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embeddings = VectorField(dimensions=None)
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raw = models.TextField()
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compiled = models.TextField()
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heading = models.CharField(max_length=1000, default=None, null=True, blank=True)
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2
src/khoj/interface/web/assets/icons/web.svg
Normal file
2
src/khoj/interface/web/assets/icons/web.svg
Normal file
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@ -0,0 +1,2 @@
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<?xml version="1.0" encoding="utf-8"?><!-- Uploaded to: SVG Repo, www.svgrepo.com, Generator: SVG Repo Mixer Tools -->
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<svg width="800px" height="800px" viewBox="0 0 64 64" xmlns="http://www.w3.org/2000/svg" stroke-width="3" stroke="#000000" fill="none"><circle cx="34.52" cy="11.43" r="5.82"/><circle cx="53.63" cy="31.6" r="5.82"/><circle cx="34.52" cy="50.57" r="5.82"/><circle cx="15.16" cy="42.03" r="5.82"/><circle cx="15.16" cy="19.27" r="5.82"/><circle cx="34.51" cy="29.27" r="4.7"/><line x1="20.17" y1="16.3" x2="28.9" y2="12.93"/><line x1="38.6" y1="15.59" x2="49.48" y2="27.52"/><line x1="50.07" y1="36.2" x2="38.67" y2="46.49"/><line x1="18.36" y1="24.13" x2="30.91" y2="46.01"/><line x1="20.31" y1="44.74" x2="28.7" y2="48.63"/><line x1="17.34" y1="36.63" x2="31.37" y2="16.32"/><line x1="20.52" y1="21.55" x2="30.34" y2="27.1"/><line x1="39.22" y1="29.8" x2="47.81" y2="30.45"/><line x1="34.51" y1="33.98" x2="34.52" y2="44.74"/></svg>
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After Width: | Height: | Size: 951 B |
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@ -296,6 +296,21 @@
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height: 32px;
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}
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div#notification-banner {
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background-color: var(--primary);
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border: 1px solid var(--primary-hover);
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padding: 8px;
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box-shadow: 0px 1px 3px 0px rgba(0,0,0,0.1),0px 1px 2px -1px rgba(0,0,0,0.8);
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}
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div#notification-banner-parent {
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position: fixed;
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right: 0;
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bottom: 0;
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margin: 20px;
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}
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select#search-models,
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select#chat-models {
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margin-bottom: 0;
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padding: 8px;
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|
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@ -16,6 +16,9 @@ Hi, I am Khoj, your open, personal AI 👋🏽. I can help:
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- 🧠 Answer general knowledge questions
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- 💡 Be a sounding board for your ideas
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- 📜 Chat with your notes & documents
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- 🌄 Generate images based on your messages
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- 🔎 Search the web for answers to your questions
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- 🎙️ Listen to your audio messages
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Get the Khoj [Desktop](https://khoj.dev/downloads), [Obsidian](https://docs.khoj.dev/#/obsidian?id=setup) or [Emacs](https://docs.khoj.dev/#/emacs?id=setup) app to search, chat with your 🖥️ computer docs.
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@ -107,6 +107,26 @@
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</div>
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</div>
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</div>
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<div class="card">
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<div class="card-title-row">
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<img class="card-icon" src="/static/assets/icons/web.svg" alt="Language">
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<h3 class="card-title">
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Language
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</h3>
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</div>
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<div class="card-description-row">
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<select id="search-models">
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{% for option in search_model_options %}
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<option value="{{ option.id }}" {% if option.id == selected_search_model_config %}selected{% endif %}>{{ option.name }}</option>
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{% endfor %}
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</select>
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</div>
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<div class="card-action-row">
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<button id="save-search-model" class="card-button happy" onclick="updateSearchModel()">
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Save
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</button>
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</div>
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</div>
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</div>
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<div class="general-settings section">
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<div id="status" style="display: none;"></div>
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@ -239,6 +259,10 @@
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</div>
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{% endif %}
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<div class="section"></div>
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</div>
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<div class="section" id="notification-banner-parent">
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<div id="notification-banner"></div>
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</div>
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</div>
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<script>
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@ -266,6 +290,37 @@
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})
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};
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function updateSearchModel() {
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const searchModel = document.getElementById("search-models").value;
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const saveSearchModelButton = document.getElementById("save-search-model");
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saveSearchModelButton.disabled = true;
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saveSearchModelButton.innerHTML = "Saving...";
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fetch('/api/config/data/search/model?id=' + searchModel, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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}
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})
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.then(response => response.json())
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.then(data => {
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if (data.status == "ok") {
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saveSearchModelButton.innerHTML = "Save";
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saveSearchModelButton.disabled = false;
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} else {
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saveSearchModelButton.innerHTML = "Error";
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saveSearchModelButton.disabled = false;
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}
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let notificationBanner = document.getElementById("notification-banner");
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notificationBanner.innerHTML = "When updating the language model, be sure to delete all your saved content and re-initialize.";
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notificationBanner.style.display = "block";
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setTimeout(function() {
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notificationBanner.style.display = "none";
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}, 5000);
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})
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};
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function clearContentType(content_source) {
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fetch('/api/config/data/content-source/' + content_source, {
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method: 'DELETE',
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|
|
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@ -14,7 +14,7 @@ from khoj.utils.helpers import is_none_or_empty, timer, batcher
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from khoj.utils.rawconfig import Entry
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from khoj.search_filter.date_filter import DateFilter
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from khoj.database.models import KhojUser, Entry as DbEntry, EntryDates
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from khoj.database.adapters import EntryAdapters
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from khoj.database.adapters import EntryAdapters, get_user_search_model_or_default
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logger = logging.getLogger(__name__)
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@ -112,7 +112,8 @@ class TextToEntries(ABC):
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with timer("Generated embeddings for entries to add to database in", logger):
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entries_to_process = [hash_to_current_entries[hashed_val] for hashed_val in hashes_to_process]
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data_to_embed = [getattr(entry, key) for entry in entries_to_process]
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embeddings += self.embeddings_model.embed_documents(data_to_embed)
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model = get_user_search_model_or_default(user)
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embeddings += self.embeddings_model[model.name].embed_documents(data_to_embed)
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added_entries: list[DbEntry] = []
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with timer("Added entries to database in", logger):
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|
|
|
@ -18,7 +18,7 @@ from starlette.authentication import requires
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# Internal Packages
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from khoj.configure import configure_server
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from khoj.database import adapters
|
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from khoj.database.adapters import ConversationAdapters, EntryAdapters
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from khoj.database.adapters import ConversationAdapters, EntryAdapters, get_user_search_model_or_default
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from khoj.database.models import ChatModelOptions, SpeechToTextModelOptions
|
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from khoj.database.models import Entry as DbEntry
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from khoj.database.models import (
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|
@ -332,6 +332,31 @@ async def update_chat_model(
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return {"status": "ok"}
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@api.post("/config/data/search/model", status_code=200)
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@requires(["authenticated"])
|
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async def update_search_model(
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request: Request,
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id: str,
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client: Optional[str] = None,
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):
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user = request.user.object
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|
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new_config = await adapters.aset_user_search_model(user, int(id))
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if new_config is None:
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return {"status": "error", "message": "Model not found"}
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else:
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update_telemetry_state(
|
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request=request,
|
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telemetry_type="api",
|
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api="set_search_model",
|
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client=client,
|
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metadata={"search_model": new_config.setting.name},
|
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)
|
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return {"status": "ok"}
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|
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# Create Routes
|
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@api.get("/config/data/default")
|
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def get_default_config_data():
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|
@ -410,13 +435,10 @@ async def search(
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defiltered_query = filter.defilter(defiltered_query)
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|
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encoded_asymmetric_query = None
|
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if t == SearchType.All or t != SearchType.Image:
|
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text_search_models: List[TextSearchModel] = [
|
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model for model in state.search_models.__dict__.values() if isinstance(model, TextSearchModel)
|
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]
|
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if text_search_models:
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with timer("Encoding query took", logger=logger):
|
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encoded_asymmetric_query = state.embeddings_model.embed_query(defiltered_query)
|
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if t != SearchType.Image:
|
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with timer("Encoding query took", logger=logger):
|
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search_model = await sync_to_async(get_user_search_model_or_default)(user)
|
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encoded_asymmetric_query = state.embeddings_model[search_model.name].embed_query(defiltered_query)
|
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|
||||
with concurrent.futures.ThreadPoolExecutor() as executor:
|
||||
if t in [
|
||||
|
@ -471,10 +493,10 @@ async def search(
|
|||
# Collate results
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||||
results += text_search.collate_results(hits, dedupe=dedupe)
|
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|
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# Sort results across all content types and take top results
|
||||
results = text_search.rerank_and_sort_results(results, query=defiltered_query, rank_results=r)[
|
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:results_count
|
||||
]
|
||||
# Sort results across all content types and take top results
|
||||
results = text_search.rerank_and_sort_results(
|
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results, query=defiltered_query, rank_results=r, search_model_name=search_model.name
|
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)[:results_count]
|
||||
|
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# Cache results
|
||||
if user:
|
||||
|
|
|
@ -143,6 +143,13 @@ async def update(
|
|||
)
|
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return Response(content="Failed", status_code=500)
|
||||
|
||||
indexing_metadata = {
|
||||
"num_org": len(org_files),
|
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"num_markdown": len(markdown_files),
|
||||
"num_pdf": len(pdf_files),
|
||||
"num_plaintext": len(plaintext_files),
|
||||
}
|
||||
|
||||
update_telemetry_state(
|
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request=request,
|
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telemetry_type="api",
|
||||
|
@ -151,6 +158,7 @@ async def update(
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|||
user_agent=user_agent,
|
||||
referer=referer,
|
||||
host=host,
|
||||
metadata=indexing_metadata,
|
||||
)
|
||||
|
||||
logger.info(f"📪 Content index updated via API call by {client} client")
|
||||
|
|
|
@ -155,6 +155,11 @@ def config_page(request: Request):
|
|||
for conversation_option in conversation_options:
|
||||
all_conversation_options.append({"chat_model": conversation_option.chat_model, "id": conversation_option.id})
|
||||
|
||||
search_model_options = adapters.get_or_create_search_models().all()
|
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all_search_model_options = list()
|
||||
for search_model_option in search_model_options:
|
||||
all_search_model_options.append({"name": search_model_option.name, "id": search_model_option.id})
|
||||
|
||||
return templates.TemplateResponse(
|
||||
"config.html",
|
||||
context={
|
||||
|
@ -163,6 +168,7 @@ def config_page(request: Request):
|
|||
"anonymous_mode": state.anonymous_mode,
|
||||
"username": user.username,
|
||||
"conversation_options": all_conversation_options,
|
||||
"search_model_options": all_search_model_options,
|
||||
"selected_conversation_config": selected_conversation_config.id if selected_conversation_config else None,
|
||||
"user_photo": user_picture,
|
||||
"billing_enabled": state.billing_enabled,
|
||||
|
|
|
@ -19,7 +19,7 @@ from khoj.utils.state import SearchType
|
|||
from khoj.utils.rawconfig import SearchResponse, Entry
|
||||
from khoj.utils.jsonl import load_jsonl
|
||||
from khoj.processor.content.text_to_entries import TextToEntries
|
||||
from khoj.database.adapters import EntryAdapters
|
||||
from khoj.database.adapters import EntryAdapters, get_user_search_model_or_default
|
||||
from khoj.database.models import KhojUser, Entry as DbEntry
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
@ -115,7 +115,8 @@ async def query(
|
|||
# Encode the query using the bi-encoder
|
||||
if question_embedding is None:
|
||||
with timer("Query Encode Time", logger, state.device):
|
||||
question_embedding = state.embeddings_model.embed_query(query)
|
||||
search_model = await sync_to_async(get_user_search_model_or_default)(user)
|
||||
question_embedding = state.embeddings_model[search_model.name].embed_query(query)
|
||||
|
||||
# Find relevant entries for the query
|
||||
top_k = 10
|
||||
|
@ -179,13 +180,13 @@ def deduplicated_search_responses(hits: List[SearchResponse]):
|
|||
)
|
||||
|
||||
|
||||
def rerank_and_sort_results(hits, query, rank_results):
|
||||
def rerank_and_sort_results(hits, query, rank_results, search_model_name):
|
||||
# If we have more than one result and reranking is enabled
|
||||
rank_results = rank_results and len(list(hits)) > 1
|
||||
|
||||
# Score all retrieved entries using the cross-encoder
|
||||
if rank_results:
|
||||
hits = cross_encoder_score(query, hits)
|
||||
hits = cross_encoder_score(query, hits, search_model_name)
|
||||
|
||||
# Sort results by cross-encoder score followed by bi-encoder score
|
||||
hits = sort_results(rank_results=rank_results, hits=hits)
|
||||
|
@ -218,10 +219,10 @@ def setup(
|
|||
)
|
||||
|
||||
|
||||
def cross_encoder_score(query: str, hits: List[SearchResponse]) -> List[SearchResponse]:
|
||||
def cross_encoder_score(query: str, hits: List[SearchResponse], search_model_name: str) -> List[SearchResponse]:
|
||||
"""Score all retrieved entries using the cross-encoder"""
|
||||
with timer("Cross-Encoder Predict Time", logger, state.device):
|
||||
cross_scores = state.cross_encoder_model.predict(query, hits)
|
||||
cross_scores = state.cross_encoder_model[search_model_name].predict(query, hits)
|
||||
|
||||
# Convert cross-encoder scores to distances and pass in hits for reranking
|
||||
for idx in range(len(cross_scores)):
|
||||
|
|
|
@ -19,8 +19,8 @@ from khoj.utils.rawconfig import FullConfig
|
|||
# Application Global State
|
||||
config = FullConfig()
|
||||
search_models = SearchModels()
|
||||
embeddings_model: EmbeddingsModel = None
|
||||
cross_encoder_model: CrossEncoderModel = None
|
||||
embeddings_model: Dict[str, EmbeddingsModel] = None
|
||||
cross_encoder_model: Dict[str, CrossEncoderModel] = None
|
||||
content_index = ContentIndex()
|
||||
openai_client: OpenAI = None
|
||||
gpt4all_processor_config: GPT4AllProcessorModel = None
|
||||
|
|
|
@ -45,8 +45,10 @@ def enable_db_access_for_all_tests(db):
|
|||
|
||||
@pytest.fixture(scope="session")
|
||||
def search_config() -> SearchConfig:
|
||||
state.embeddings_model = EmbeddingsModel()
|
||||
state.cross_encoder_model = CrossEncoderModel()
|
||||
state.embeddings_model = dict()
|
||||
state.embeddings_model["default"] = EmbeddingsModel()
|
||||
state.cross_encoder_model = dict()
|
||||
state.cross_encoder_model["default"] = CrossEncoderModel()
|
||||
|
||||
model_dir = resolve_absolute_path("~/.khoj/search")
|
||||
model_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
@ -317,8 +319,10 @@ def client(
|
|||
state.config.content_type = content_config
|
||||
state.config.search_type = search_config
|
||||
state.SearchType = configure_search_types()
|
||||
state.embeddings_model = EmbeddingsModel()
|
||||
state.cross_encoder_model = CrossEncoderModel()
|
||||
state.embeddings_model = dict()
|
||||
state.embeddings_model["default"] = EmbeddingsModel()
|
||||
state.cross_encoder_model = dict()
|
||||
state.cross_encoder_model["default"] = CrossEncoderModel()
|
||||
|
||||
# These lines help us Mock the Search models for these search types
|
||||
state.search_models.image_search = image_search.initialize_model(search_config.image)
|
||||
|
|
Loading…
Reference in a new issue