alex
757140ec70
Implement a full chat-based travel agent using LiteLLM for multi-provider LLM support (OpenAI, Anthropic, Gemini, Ollama, Groq, Mistral, etc.). Backend: - New 'chat' Django app with ChatConversation and ChatMessage models - Streaming SSE endpoint via StreamingHttpResponse - 5 agent tools: search_places, list_trips, get_trip_details, add_to_itinerary, get_weather - LiteLLM client wrapper with per-user API key retrieval - System prompt with user preference context injection Frontend: - New /chat route with full-page chat UI (DaisyUI + Tailwind) - Collapsible conversation sidebar with CRUD - SSE streaming response display with tool call visualization - Provider selector dropdown - SSE proxy fix to stream text/event-stream without buffering - Navbar link and i18n keys
26 lines
636 B
Python
26 lines
636 B
Python
from rest_framework import serializers
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from .models import ChatConversation, ChatMessage
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class ChatMessageSerializer(serializers.ModelSerializer):
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class Meta:
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model = ChatMessage
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fields = [
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"id",
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"role",
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"content",
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"tool_calls",
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"tool_call_id",
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"name",
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"created_at",
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]
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class ChatConversationSerializer(serializers.ModelSerializer):
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messages = ChatMessageSerializer(many=True, read_only=True)
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class Meta:
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model = ChatConversation
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fields = ["id", "title", "created_at", "updated_at", "messages"]
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